From f093a7b332ceb43ca111c9db1a87baf83d6eb7fe Mon Sep 17 00:00:00 2001 From: Xin Pan Date: Wed, 9 May 2018 18:16:36 +0800 Subject: [PATCH 01/31] allow inference test to generate timeline generate timeline file PYTHONPATH=/paddle/dev/my/build2/python/ python /paddle/dev/my/Paddle2/tools/timeline.py --profile_path=train=run_inference_profiler --timeline_path=/tmp/timeline_infer visualize it open url chrome://tracing --- paddle/fluid/inference/tests/test_helper.h | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/paddle/fluid/inference/tests/test_helper.h b/paddle/fluid/inference/tests/test_helper.h index af2a7a5620..2f391dc1e2 100644 --- a/paddle/fluid/inference/tests/test_helper.h +++ b/paddle/fluid/inference/tests/test_helper.h @@ -105,7 +105,7 @@ void TestInference(const std::string& dirname, state = paddle::platform::ProfilerState::kCPU; } else { #ifdef PADDLE_WITH_CUDA - state = paddle::platform::ProfilerState::kCUDA; + state = paddle::platform::ProfilerState::kAll; // The default device_id of paddle::platform::CUDAPlace is 0. // Users can get the device_id using: // int device_id = place.GetDeviceId(); @@ -143,7 +143,7 @@ void TestInference(const std::string& dirname, } // Disable the profiler and print the timing information paddle::platform::DisableProfiler(paddle::platform::EventSortingKey::kDefault, - "load_program_profiler.txt"); + "load_program_profiler"); paddle::platform::ResetProfiler(); // 3. Get the feed_target_names and fetch_target_names @@ -208,7 +208,7 @@ void TestInference(const std::string& dirname, // Disable the profiler and print the timing information paddle::platform::DisableProfiler( paddle::platform::EventSortingKey::kDefault, - "run_inference_profiler.txt"); + "run_inference_profiler"); paddle::platform::ResetProfiler(); } From 94c0a64d6283cc3d9952ffe688a134a279bc6217 Mon Sep 17 00:00:00 2001 From: Xin Pan Date: Mon, 14 May 2018 14:28:58 +0800 Subject: [PATCH 02/31] Fix a profiler race condition In multi-thread condition, EnableProfiler can be called after RecordEvent is constructed. In this case, RecordEvent constructor will not init anything, but RecordEvent destructor will do something since EnableProfiler was called. This PR fixes it. --- paddle/fluid/platform/profiler.cc | 11 +++++++---- paddle/fluid/platform/profiler.h | 2 ++ 2 files changed, 9 insertions(+), 4 deletions(-) diff --git a/paddle/fluid/platform/profiler.cc b/paddle/fluid/platform/profiler.cc index 50bc0aba6a..2fb5c6dc6b 100644 --- a/paddle/fluid/platform/profiler.cc +++ b/paddle/fluid/platform/profiler.cc @@ -173,8 +173,9 @@ void PopEvent(const std::string& name, const DeviceContext* dev_ctx) { } RecordEvent::RecordEvent(const std::string& name, const DeviceContext* dev_ctx) - : start_ns_(PosixInNsec()) { + : is_enabled_(false), start_ns_(PosixInNsec()) { if (g_state == ProfilerState::kDisabled) return; + is_enabled_ = true; dev_ctx_ = dev_ctx; name_ = name; PushEvent(name_, dev_ctx_); @@ -183,7 +184,7 @@ RecordEvent::RecordEvent(const std::string& name, const DeviceContext* dev_ctx) } RecordEvent::~RecordEvent() { - if (g_state == ProfilerState::kDisabled) return; + if (g_state == ProfilerState::kDisabled || !is_enabled_) return; DeviceTracer* tracer = GetDeviceTracer(); if (tracer) { tracer->AddCPURecords(CurAnnotation(), start_ns_, PosixInNsec(), @@ -193,14 +194,16 @@ RecordEvent::~RecordEvent() { PopEvent(name_, dev_ctx_); } -RecordBlock::RecordBlock(int block_id) : start_ns_(PosixInNsec()) { +RecordBlock::RecordBlock(int block_id) + : is_enabled_(false), start_ns_(PosixInNsec()) { if (g_state == ProfilerState::kDisabled) return; + is_enabled_ = true; SetCurBlock(block_id); name_ = string::Sprintf("block_%d", block_id); } RecordBlock::~RecordBlock() { - if (g_state == ProfilerState::kDisabled) return; + if (g_state == ProfilerState::kDisabled || !is_enabled_) return; DeviceTracer* tracer = GetDeviceTracer(); if (tracer) { // We try to put all blocks at the same nested depth in the diff --git a/paddle/fluid/platform/profiler.h b/paddle/fluid/platform/profiler.h index 61b98143e4..643bb6183d 100644 --- a/paddle/fluid/platform/profiler.h +++ b/paddle/fluid/platform/profiler.h @@ -74,6 +74,7 @@ struct RecordEvent { ~RecordEvent(); + bool is_enabled_; uint64_t start_ns_; // The device context is used by Event to get the current cuda stream. const DeviceContext* dev_ctx_; @@ -89,6 +90,7 @@ struct RecordBlock { ~RecordBlock(); private: + bool is_enabled_; std::string name_; uint64_t start_ns_; }; From fe93cce387561a0b997276be5626d23bdea4a270 Mon Sep 17 00:00:00 2001 From: baiyfbupt Date: Wed, 16 May 2018 08:58:04 +0000 Subject: [PATCH 03/31] fix roi_pool op bug --- paddle/fluid/operators/roi_pool_op.cu | 18 ++++++++++++------ 1 file changed, 12 insertions(+), 6 deletions(-) diff --git a/paddle/fluid/operators/roi_pool_op.cu b/paddle/fluid/operators/roi_pool_op.cu index f905d690f9..265dbb3a80 100644 --- a/paddle/fluid/operators/roi_pool_op.cu +++ b/paddle/fluid/operators/roi_pool_op.cu @@ -52,13 +52,19 @@ __global__ void GPUROIPoolForward( int roi_width = max(roi_end_w - roi_start_w + 1, 1); int roi_height = max(roi_end_h - roi_start_h + 1, 1); - T bin_size_h = static_cast(roi_height) / static_cast(pooled_height); - T bin_size_w = static_cast(roi_width) / static_cast(pooled_width); - int hstart = static_cast(floor(static_cast(ph) * bin_size_h)); - int wstart = static_cast(floor(static_cast(pw) * bin_size_w)); - int hend = static_cast(ceil(static_cast(ph + 1) * bin_size_h)); - int wend = static_cast(ceil(static_cast(pw + 1) * bin_size_w)); + int hstart = + static_cast(floor(static_cast(ph) * static_cast(roi_height) / + static_cast(pooled_height))); + int wstart = + static_cast(floor(static_cast(pw) * static_cast(roi_width) / + static_cast(pooled_width))); + int hend = static_cast(ceil(static_cast(ph + 1) * + static_cast(roi_height) / + static_cast(pooled_height))); + int wend = static_cast(ceil(static_cast(pw + 1) * + static_cast(roi_width) / + static_cast(pooled_width))); hstart = min(max(hstart + roi_start_h, 0), height); hend = min(max(hend + roi_start_h, 0), height); From ddd3c15174286b8401049d857aed13517a65eafd Mon Sep 17 00:00:00 2001 From: baiyfbupt Date: Wed, 16 May 2018 17:10:34 +0000 Subject: [PATCH 04/31] bug fix --- paddle/fluid/operators/roi_pool_op.cu | 24 ++++++++++++------------ 1 file changed, 12 insertions(+), 12 deletions(-) diff --git a/paddle/fluid/operators/roi_pool_op.cu b/paddle/fluid/operators/roi_pool_op.cu index 265dbb3a80..a699d21542 100644 --- a/paddle/fluid/operators/roi_pool_op.cu +++ b/paddle/fluid/operators/roi_pool_op.cu @@ -53,18 +53,18 @@ __global__ void GPUROIPoolForward( int roi_width = max(roi_end_w - roi_start_w + 1, 1); int roi_height = max(roi_end_h - roi_start_h + 1, 1); - int hstart = - static_cast(floor(static_cast(ph) * static_cast(roi_height) / - static_cast(pooled_height))); - int wstart = - static_cast(floor(static_cast(pw) * static_cast(roi_width) / - static_cast(pooled_width))); - int hend = static_cast(ceil(static_cast(ph + 1) * - static_cast(roi_height) / - static_cast(pooled_height))); - int wend = static_cast(ceil(static_cast(pw + 1) * - static_cast(roi_width) / - static_cast(pooled_width))); + int hstart = static_cast(floor(static_cast(ph) * + static_cast(roi_height) / + static_cast(pooled_height))); + int wstart = static_cast(floor(static_cast(pw) * + static_cast(roi_width) / + static_cast(pooled_width))); + int hend = static_cast(ceil(static_cast(ph + 1) * + static_cast(roi_height) / + static_cast(pooled_height))); + int wend = static_cast(ceil(static_cast(pw + 1) * + static_cast(roi_width) / + static_cast(pooled_width))); hstart = min(max(hstart + roi_start_h, 0), height); hend = min(max(hend + roi_start_h, 0), height); From 8fd50012235b58f25cb61bb71859e6325e5c3285 Mon Sep 17 00:00:00 2001 From: Luo Tao Date: Thu, 17 May 2018 12:23:40 +0800 Subject: [PATCH 05/31] refine mkldnn cmake with official commit id --- cmake/external/mkldnn.cmake | 4 +- patches/mkldnn.hpp | 4252 ----------------------------------- 2 files changed, 1 insertion(+), 4255 deletions(-) delete mode 100644 patches/mkldnn.hpp diff --git a/cmake/external/mkldnn.cmake b/cmake/external/mkldnn.cmake index 0332e39d14..25c07850dd 100644 --- a/cmake/external/mkldnn.cmake +++ b/cmake/external/mkldnn.cmake @@ -53,11 +53,9 @@ ExternalProject_Add( ${EXTERNAL_PROJECT_LOG_ARGS} DEPENDS ${MKLDNN_DEPENDS} GIT_REPOSITORY "https://github.com/01org/mkl-dnn.git" - GIT_TAG "v0.14" + GIT_TAG "db3424ad44901513c03a1ea31ccaacdf633fbe9f" PREFIX ${MKLDNN_SOURCES_DIR} UPDATE_COMMAND "" - # Patch MKLDNN to compile with gcc 4.8, the related issue is in intel/mkl-dnn#237. - PATCH_COMMAND ${CMAKE_COMMAND} -E copy_if_different ${CMAKE_CURRENT_SOURCE_DIR}/patches/mkldnn.hpp ${MKLDNN_SOURCES_DIR}/src/extern_mkldnn/include/mkldnn.hpp CMAKE_ARGS -DCMAKE_INSTALL_PREFIX=${MKLDNN_INSTALL_DIR} CMAKE_ARGS -DCMAKE_BUILD_TYPE=${CMAKE_BUILD_TYPE} CMAKE_ARGS -DMKLROOT=${MKLML_ROOT} diff --git a/patches/mkldnn.hpp b/patches/mkldnn.hpp deleted file mode 100644 index fe01ad8a10..0000000000 --- a/patches/mkldnn.hpp +++ /dev/null @@ -1,4252 +0,0 @@ -// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. -// -// Licensed under the Apache License, Version 2.0 (the "License"); -// you may not use this file except in compliance with the License. -// You may obtain a copy of the License at -// -// http://www.apache.org/licenses/LICENSE-2.0 -// -// Unless required by applicable law or agreed to in writing, software -// distributed under the License is distributed on an "AS IS" BASIS, -// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -// See the License for the specific language governing permissions and -// limitations under the License. - -/******************************************************************************* -* Copyright 2016-2018 Intel Corporation -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*******************************************************************************/ - -#ifndef MKLDNN_HPP -#define MKLDNN_HPP - -#ifndef DOXYGEN_SHOULD_SKIP_THIS -#include -#include -#include -#include -#include -#include - -#include "mkldnn.h" -#endif - -namespace mkldnn { - -/// @addtogroup cpp_api C++ API -/// @{ - -/// @addtogroup cpp_api_utils Utils -/// @{ - -/// A class that provides the destructor for an Intel(R) MKL-DNN C handle -template -class handle_traits {}; - -/// A class for wrapping an Intel(R) MKL-DNN handle. It is used as the base -/// class for primitive (#mkldnn_primitive_t), engine (#mkldnn_engine_t), and -/// stream (#mkldnn_stream_t) handles. An object of the #mkldnn::handle class -/// can be passed by value. This class enables wrapping: -/// - Newly constructed handles. -/// @n In this case, the constructed handle uses reference counting provided -/// by @p std::shared_ptr with a proper deleter function specified through -/// the @p handle_traits class. -/// - Pre-existing handles returned by the Intel(R) MKL-DNN C API (for -/// example, through #mkldnn_primitive_get_output()). -/// @n In this case, an Intel(R) MKL-DNN C API handle is wrapped without a -/// deleter because it is assumed that the handle wrapper for the original -/// object deletes the handle (this model is similar to @p std::weak_ptr). -template > -class handle { -private: - std::shared_ptr::type> _data; - handle(const handle &&) = delete; - handle &operator=(const handle &&other) = delete; - -protected: - /// Constructs a C handle wrapper. - /// @param t The C handle to wrap. - /// @param weak A flag to specify whether to construct a weak wrapper. - handle(T t = 0, bool weak = false) : _data(0) { reset(t, weak); } - - bool operator==(const T other) const { return other == _data.get(); } - bool operator!=(const T other) const { return !(*this == other); } - -public: - handle(const handle &other) : _data(other._data) {} - handle &operator=(const handle &other) { - _data = other._data; - return *this; - } - /// Resets the value of a C handle. - /// @param t The new value of the C handle. - /// @param weak A flag to specify whether the wrapper should be weak. - void reset(T t, bool weak = false) { - auto dummy_destructor = [](T) { - return decltype(traits::destructor(0))(0); - }; - _data.reset(t, weak ? dummy_destructor : traits::destructor); - } - - /// Returns the value of the underlying C handle. - T get() const { return _data.get(); } - - bool operator==(const handle &other) const { - return other._data.get() == _data.get(); - } - bool operator!=(const handle &other) const { return !(*this == other); } -}; - -#ifndef DOXYGEN_SHOULD_SKIP_THIS -template <> -struct handle_traits { - static constexpr auto destructor = &mkldnn_primitive_desc_destroy; -}; - -template <> -struct handle_traits { - static constexpr auto destructor = &mkldnn_primitive_destroy; -}; -#endif - -/// Base class for all computational primitives. -class primitive : public handle { - friend struct error; - friend struct stream; - friend class primitive_at; - using handle::handle; - -public: - /// A proxy to C primitive kind enum - enum class kind { - undefined_primitive = mkldnn_undefined_primitive, - memory = mkldnn_memory, - view = mkldnn_view, - reorder = mkldnn_reorder, - concat = mkldnn_concat, - concat_inplace = mkldnn_concat_inplace, - sum = mkldnn_sum, - convolution = mkldnn_convolution, - deconvolution = mkldnn_deconvolution, - eltwise = mkldnn_eltwise, - relu = mkldnn_relu, - softmax = mkldnn_softmax, - pooling = mkldnn_pooling, - lrn = mkldnn_lrn, - batch_normalization = mkldnn_batch_normalization, - inner_product = mkldnn_inner_product, - convolution_relu = mkldnn_convolution_relu, - rnn = mkldnn_rnn, - }; - - /// A wrapper structure to specify a particular output of a primitive. - struct at { - /// The underlying C API structure. - mkldnn_primitive_at_t data; - /// Constructs a wrapper specifying @p aprimitive output with index @p - /// at. - /// - /// @param aprimitive The target primitive. - /// @param at The output index. - - at(const primitive &aprimitive, size_t at = 0) - : data(mkldnn_primitive_at(aprimitive.get(), at)) {} - /// Returns the specified output. - inline operator primitive() const; - }; - - /// Returns the descriptor of the underlying C API primitive - inline const_mkldnn_primitive_desc_t get_primitive_desc() const; - // TODO: use the C++ API wrapper structure. -}; - -inline mkldnn_primitive_kind_t convert_to_c(primitive::kind akind) { - return static_cast(akind); -} - -/// Intel(R) MKL-DNN exception class. -/// -/// This class captures the status returned by the failed C API function, error -/// message, and, optionally, handle of the primitive that caused the error. -struct error : public std::exception { - mkldnn_status_t status; - std::string message; - primitive error_primitive; - - /// Constructs an error instance. - /// - /// @param astatus The error status returned by the C API. - /// @param amessage The error message. - /// @param aerror_primitive (optional) A C handle of the primitive that - /// caused the error. - - error(mkldnn_status_t astatus, - std::string amessage, - mkldnn_primitive_t aerror_primitive = 0) - : status(astatus), - message(amessage), - error_primitive(aerror_primitive, true) {} - - /// A convenience function for wrapping calls to the C API. Checks the - /// return status and throws an #error in case of failure. - /// - /// @param status The error status returned by the C API. - /// @param message The error message. - /// @param error_primitive (optional) A C handle of the primitive that - /// caused the error. - - static void wrap_c_api(mkldnn_status_t status, - std::string message, - mkldnn_primitive_t *error_primitive = 0) { - if (status != mkldnn_success) { - if (nullptr != error_primitive) - throw error(status, message, *error_primitive); - else - throw error(status, message, nullptr); - } - } -}; - -inline primitive::at::operator primitive() const { - const_mkldnn_primitive_t output; - error::wrap_c_api( - mkldnn_primitive_get_output(data.primitive, data.output_index, &output), - "could not get an output primitive"); - return primitive(const_cast(output), true); -} - -const_mkldnn_primitive_desc_t primitive::get_primitive_desc() const { - const_mkldnn_primitive_desc_t pd; - error::wrap_c_api(mkldnn_primitive_get_primitive_desc(get(), &pd), - "could not get primitive descriptor by primitive"); - return pd; -} -/// @} - -/// @addtogroup cpp_api_enums Common data types and enumerations -/// @{ - -enum round_mode { - round_nearest = mkldnn_round_nearest, - round_down = mkldnn_round_down, -}; - -inline mkldnn_round_mode_t convert_to_c(round_mode mode) { - return static_cast(mode); -} - -enum padding_kind { zero = mkldnn_padding_zero }; - -inline mkldnn_padding_kind_t convert_to_c(padding_kind kind) { - return static_cast(kind); -} - -enum prop_kind { - forward_training = mkldnn_forward_training, - forward_scoring = mkldnn_forward_scoring, - forward_inference = mkldnn_forward_inference, - forward = mkldnn_forward, - backward = mkldnn_backward, - backward_data = mkldnn_backward_data, - backward_weights = mkldnn_backward_weights, - backward_bias = mkldnn_backward_bias -}; - -inline mkldnn_prop_kind_t convert_to_c(prop_kind kind) { - return static_cast(kind); -} - -enum algorithm { - algorithm_undef = mkldnn_alg_kind_undef, - convolution_direct = mkldnn_convolution_direct, - convolution_winograd = mkldnn_convolution_winograd, - deconvolution_direct = mkldnn_deconvolution_direct, - deconvolution_winograd = mkldnn_deconvolution_winograd, - eltwise_relu = mkldnn_eltwise_relu, - eltwise_tanh = mkldnn_eltwise_tanh, - eltwise_elu = mkldnn_eltwise_elu, - eltwise_square = mkldnn_eltwise_square, - eltwise_abs = mkldnn_eltwise_abs, - eltwise_sqrt = mkldnn_eltwise_sqrt, - eltwise_linear = mkldnn_eltwise_linear, - eltwise_bounded_relu = mkldnn_eltwise_bounded_relu, - eltwise_soft_relu = mkldnn_eltwise_soft_relu, - eltwise_logistic = mkldnn_eltwise_logistic, - lrn_across_channels = mkldnn_lrn_across_channels, - lrn_within_channel = mkldnn_lrn_within_channel, - pooling_max = mkldnn_pooling_max, - pooling_avg = mkldnn_pooling_avg, - pooling_avg_include_padding = mkldnn_pooling_avg_include_padding, - pooling_avg_exclude_padding = mkldnn_pooling_avg_exclude_padding, - vanilla_rnn = mkldnn_vanilla_rnn, - vanilla_lstm = mkldnn_vanilla_lstm, - vanilla_gru = mkldnn_vanilla_gru, -}; - -inline mkldnn_alg_kind_t convert_to_c(algorithm aalgorithm) { - return static_cast(aalgorithm); -} - -enum batch_normalization_flag { - use_global_stats = mkldnn_use_global_stats, - use_scale_shift = mkldnn_use_scaleshift, - omit_stats = mkldnn_omit_stats, - fuse_bn_relu = mkldnn_fuse_bn_relu -}; - -inline mkldnn_batch_normalization_flag_t convert_to_c( - batch_normalization_flag aflag) { - return static_cast(aflag); -} - -enum rnn_direction { - unidirectional_left2right = mkldnn_unidirectional_left2right, - unidirectional_right2left = mkldnn_unidirectional_right2left, - unidirectional = mkldnn_unidirectional, - bidirectional_concat = mkldnn_bidirectional_concat, - bidirectional_sum = mkldnn_bidirectional_sum, -}; - -inline mkldnn_rnn_direction_t convert_to_c(rnn_direction adir) { - return static_cast(adir); -} - -enum query { - undef = mkldnn_query_undef, - - eengine = mkldnn_query_engine, - primitive_kind = mkldnn_query_primitive_kind, - - num_of_inputs_s32 = mkldnn_query_num_of_inputs_s32, - num_of_outputs_s32 = mkldnn_query_num_of_outputs_s32, - - time_estimate_f64 = mkldnn_query_time_estimate_f64, - memory_consumption_s64 = mkldnn_query_memory_consumption_s64, - - impl_info_str = mkldnn_query_impl_info_str, - - memory_d = mkldnn_query_memory_d, - convolution_d = mkldnn_query_convolution_d, - deconvolution_d = mkldnn_query_deconvolution_d, - eltwise_d = mkldnn_query_eltwise_d, - relu_d = mkldnn_query_relu_d, - softmax_d = mkldnn_query_softmax_d, - pooling_d = mkldnn_query_pooling_d, - lrn_d = mkldnn_query_lrn_d, - batch_normalization_d = mkldnn_query_batch_normalization_d, - inner_product_d = mkldnn_query_inner_product_d, - convolution_relu_d = mkldnn_query_convolution_relu_d, - rnn_d = mkldnn_query_rnn_d, - - input_pd = mkldnn_query_input_pd, - output_pd = mkldnn_query_output_pd, - src_pd = mkldnn_query_src_pd, - diff_src_pd = mkldnn_query_diff_src_pd, - weights_pd = mkldnn_query_weights_pd, - diff_weights_pd = mkldnn_query_diff_weights_pd, - dst_pd = mkldnn_query_dst_pd, - diff_dst_pd = mkldnn_query_diff_dst_pd, - workspace_pd = mkldnn_query_workspace_pd, -}; - -inline mkldnn_query_t convert_to_c(query aquery) { - return static_cast(aquery); -} - -/// @} - -/// @addtogroup cpp_api_attr Attributes -/// @{ - -#ifndef DOXYGEN_SHOULD_SKIP_THIS -template <> -struct handle_traits { - static constexpr auto destructor = &mkldnn_post_ops_destroy; -}; -#endif - -struct post_ops : public handle { - post_ops() { - mkldnn_post_ops_t result; - error::wrap_c_api(mkldnn_post_ops_create(&result), - "could not create post operation sequence"); - reset(result); - } - - int len() const { return mkldnn_post_ops_len(get()); } - - primitive::kind kind(int index) const { - error::wrap_c_api(index < len() ? mkldnn_success : mkldnn_invalid_arguments, - "post_ops index is out of range"); - return static_cast(mkldnn_post_ops_get_kind(get(), index)); - } - - void append_sum(float scale = 1.) { - error::wrap_c_api(mkldnn_post_ops_append_sum(get(), scale), - "could not append sum"); - } - - void get_params_sum(int index, float &scale) const { - error::wrap_c_api(mkldnn_post_ops_get_params_sum(get(), index, &scale), - "could not get sum params"); - } - - void append_eltwise(float scale, algorithm alg, float alpha, float beta) { - error::wrap_c_api(mkldnn_post_ops_append_eltwise( - get(), scale, convert_to_c(alg), alpha, beta), - "could not append eltwise"); - } - - void get_params_eltwise(int index, - float &scale, - algorithm &alg, - float &alpha, - float &beta) const { - mkldnn_alg_kind_t c_alg; - error::wrap_c_api(mkldnn_post_ops_get_params_eltwise( - get(), index, &scale, &c_alg, &alpha, &beta), - "could not get eltwise params"); - alg = static_cast(c_alg); - } -}; - -#ifndef DOXYGEN_SHOULD_SKIP_THIS -template <> -struct handle_traits { - static constexpr auto destructor = &mkldnn_primitive_attr_destroy; -}; -#endif - -struct primitive_attr : public handle { - primitive_attr() { - mkldnn_primitive_attr_t result; - error::wrap_c_api(mkldnn_primitive_attr_create(&result), - "could not create a primitive attr"); - reset(result); - } - - round_mode get_int_output_round_mode() const { - mkldnn_round_mode_t result; - error::wrap_c_api( - mkldnn_primitive_attr_get_int_output_round_mode(get(), &result), - "could not get int output round mode"); - return round_mode(result); - } - - void set_int_output_round_mode(round_mode mode) { - error::wrap_c_api(mkldnn_primitive_attr_set_int_output_round_mode( - get(), mkldnn::convert_to_c(mode)), - "could not set int output round mode"); - } - - void get_output_scales(int &mask, std::vector &scales) const { - int count, c_mask; - const float *c_scales; - error::wrap_c_api(mkldnn_primitive_attr_get_output_scales( - get(), &count, &c_mask, &c_scales), - "could not get int output scales"); - scales.resize(count); - - mask = c_mask; - for (int c = 0; c < count; ++c) scales[c] = c_scales[c]; - } - - void set_output_scales(int mask, const std::vector &scales) { - error::wrap_c_api(mkldnn_primitive_attr_set_output_scales( - get(), (int)scales.size(), mask, &scales[0]), - "could not set int output scales"); - } - - const post_ops get_post_ops() const { - post_ops result; - const_mkldnn_post_ops_t c_result; - error::wrap_c_api(mkldnn_primitive_attr_get_post_ops(get(), &c_result), - "could not get post operation sequence"); - result.reset(const_cast(c_result), true); - return result; - } - - void set_post_ops(post_ops ops) { - error::wrap_c_api(mkldnn_primitive_attr_set_post_ops(get(), ops.get()), - "could not set post operation sequence"); - } -}; - -/// @} - -/// @addtogroup cpp_api_engine Engine -/// @{ - -#ifndef DOXYGEN_SHOULD_SKIP_THIS -template <> -struct handle_traits { - static constexpr auto destructor = &mkldnn_engine_destroy; -}; -#endif - -/// An execution engine. -struct engine : public handle { - friend class primitive; - // gcc bug??? using handle::handle; - - /// Kinds of engines - enum kind { - /// An unspecified engine - any = mkldnn_any_engine, - /// CPU engine - cpu = mkldnn_cpu, - }; - - /// Returns the number of engines of a certain kind. - /// - /// @param akind The kind of engines to count. - - static size_t get_count(kind akind) { - return mkldnn_engine_get_count(convert_to_c(akind)); - } - - /// Constructs an engine. - /// - /// @param akind The kind of engine to construct. - /// @param index The index of the engine. Must be less than the value - /// returned by #get_count() for this particular kind of engine. - - engine(kind akind, size_t index) { - mkldnn_engine_t aengine; - error::wrap_c_api( - mkldnn_engine_create(&aengine, convert_to_c(akind), index), - "could not create an engine"); - reset(aengine); - } - - explicit engine(const mkldnn_engine_t &aengine) : handle(aengine, true) {} - - engine(const handle &pd) { - mkldnn_engine_t engine_q; - error::wrap_c_api( - mkldnn_primitive_desc_query( - pd.get(), mkldnn::convert_to_c(eengine), 0, &engine_q), - "could not get engine from primitive_desc"); - reset(engine_q, true); - } - - template - static engine query(const primitive_desc &pd) { - mkldnn_engine_t engine_q; - error::wrap_c_api( - mkldnn_primitive_desc_query( - pd.get(), mkldnn::convert_to_c(eengine), 0, &engine_q), - "could not get engine from primitive_desc"); - - return engine(engine_q); - } - -private: - static mkldnn_engine_kind_t convert_to_c(kind akind) { - return static_cast(akind); - } -}; - -/// @} - -/// @addtogroup cpp_api_primitives Primitives -/// @{ - -/// @addtogroup cpp_api_memory Memory -/// @{ - -/// Memory primitive that describes the data. -struct memory : public primitive { -private: - std::shared_ptr _handle; - -public: - typedef std::vector::type> dims; - - template - static void validate_dims(std::vector v) { - if (v.size() > TENSOR_MAX_DIMS) - throw error(mkldnn_invalid_arguments, "invalid dimensions"); - } - - /// Data type specification. See #mkldnn_data_type_t for a detailed - /// description. - enum data_type { - data_undef = mkldnn_data_type_undef, - f32 = mkldnn_f32, - s32 = mkldnn_s32, - s16 = mkldnn_s16, - s8 = mkldnn_s8, - u8 = mkldnn_u8, - }; - - /// Memory format specification. See #mkldnn_memory_format_t - /// for a detailed description. - enum format { - format_undef = mkldnn_format_undef, - any = mkldnn_any, - blocked = mkldnn_blocked, - x = mkldnn_x, - nc = mkldnn_nc, - nchw = mkldnn_nchw, - nhwc = mkldnn_nhwc, - chwn = mkldnn_chwn, - nChw8c = mkldnn_nChw8c, - nChw16c = mkldnn_nChw16c, - ncdhw = mkldnn_ncdhw, - ndhwc = mkldnn_ndhwc, - nCdhw16c = mkldnn_nCdhw16c, - oi = mkldnn_oi, - io = mkldnn_io, - oihw = mkldnn_oihw, - ihwo = mkldnn_ihwo, - hwio = mkldnn_hwio, - oidhw = mkldnn_oidhw, - OIdhw16i16o = mkldnn_OIdhw16i16o, - OIdhw16o16i = mkldnn_OIdhw16o16i, - Oidhw16o = mkldnn_Oidhw16o, - Odhwi16o = mkldnn_Odhwi16o, - oIhw8i = mkldnn_oIhw8i, - oIhw16i = mkldnn_oIhw16i, - OIhw8i8o = mkldnn_OIhw8i8o, - OIhw16i16o = mkldnn_OIhw16i16o, - OIhw8o8i = mkldnn_OIhw8o8i, - OIhw16o16i = mkldnn_OIhw16o16i, - IOhw16o16i = mkldnn_IOhw16o16i, - OIhw8i16o2i = mkldnn_OIhw8i16o2i, - OIhw8o16i2o = mkldnn_OIhw8o16i2o, - OIhw4i16o4i = mkldnn_OIhw4i16o4i, - Oihw8o = mkldnn_Oihw8o, - Oihw16o = mkldnn_Oihw16o, - Ohwi8o = mkldnn_Ohwi8o, - Ohwi16o = mkldnn_Ohwi16o, - OhIw16o4i = mkldnn_OhIw16o4i, - goihw = mkldnn_goihw, - hwigo = mkldnn_hwigo, - gOIhw8i8o = mkldnn_gOIhw8i8o, - gOIhw16i16o = mkldnn_gOIhw16i16o, - gOIhw8i16o2i = mkldnn_gOIhw8i16o2i, - gOIhw8o16i2o = mkldnn_gOIhw8o16i2o, - gOIhw4i16o4i = mkldnn_gOIhw4i16o4i, - gOihw8o = mkldnn_gOihw8o, - gOihw16o = mkldnn_gOihw16o, - gOhwi8o = mkldnn_gOhwi8o, - gOhwi16o = mkldnn_gOhwi16o, - Goihw8g = mkldnn_Goihw8g, - Goihw16g = mkldnn_Goihw16g, - gOIhw8o8i = mkldnn_gOIhw8o8i, - gOIhw16o16i = mkldnn_gOIhw16o16i, - gIOhw16o16i = mkldnn_gIOhw16o16i, - gOhIw16o4i = mkldnn_gOhIw16o4i, - goidhw = mkldnn_goidhw, - gOIdhw16i16o = mkldnn_gOIdhw16i16o, - gOIdhw16o16i = mkldnn_gOIdhw16o16i, - gOidhw16o = mkldnn_gOidhw16o, - gOdhwi16o = mkldnn_gOdhwi16o, - ntc = mkldnn_ntc, - tnc = mkldnn_tnc, - ldsnc = mkldnn_ldsnc, - ldigo = mkldnn_ldigo, - ldigo_p = mkldnn_ldigo_p, - ldgoi = mkldnn_ldgoi, - ldgoi_p = mkldnn_ldgoi_p, - ldgo = mkldnn_ldgo, - wino_fmt = mkldnn_wino_fmt, - format_last = mkldnn_format_last, - }; - - /// A memory descriptor. - struct desc { - friend struct memory; - /// The underlying C API data structure. - mkldnn_memory_desc_t data; - - /// Constructs a memory descriptor. - /// - /// @param adims Data dimensions - /// @param adata_type Data precision/type. - /// @param aformat Data layout format. - desc(dims adims, data_type adata_type, format aformat) { - validate_dims(adims); - error::wrap_c_api( - mkldnn_memory_desc_init(&data, - (int)adims.size(), - adims.size() == 0 ? nullptr : &adims[0], - convert_to_c(adata_type), - convert_to_c(aformat)), - "could not initialize a memory descriptor"); - } - - /// Constructs a memory descriptor from a C API data structure. - /// - /// @param adata A C API #mkldnn_memory_desc_t structure. - desc(const mkldnn_memory_desc_t &adata) : data(adata) {} - }; - - /// A memory primitive descriptor. - struct primitive_desc : public handle { - friend struct memory; - - // TODO: make private - primitive_desc() {} - - /// Constructs a memory primitive descriptor. - primitive_desc(const desc &adesc, const engine &aengine) { - mkldnn_primitive_desc_t result; - error::wrap_c_api(mkldnn_memory_primitive_desc_create( - &result, &adesc.data, aengine.get()), - "could not initialize a memory primitive descriptor"); - reset(result); - } - - /// Returns the memory primitive descriptor. - memory::desc desc() { - auto memory_d = mkldnn_primitive_desc_query_memory_d(get()); - return memory::desc(*memory_d); - } - - /// Returns the number of bytes required to allocate the memory described - /// including the padding area. - size_t get_size() const { - return mkldnn_memory_primitive_desc_get_size(get()); - } - - bool operator==(const primitive_desc &other) const { - return mkldnn_memory_primitive_desc_equal(get(), other.get()); - } - - bool operator!=(const primitive_desc &other) const { - return !operator==(other); - } - - engine get_engine() { return engine::query(*this); } - }; - - /// Constructs a memory primitive from a generic primitive. - /// - /// @param aprimitive The primitive to treat as memory. - memory(const primitive &aprimitive) : primitive(aprimitive) {} - /// Constructs a memory primitive. - /// - /// @param adesc Memory primitive descriptor. - memory(const primitive_desc &adesc) { - mkldnn_primitive_t result; - error::wrap_c_api( - mkldnn_primitive_create(&result, adesc.get(), nullptr, nullptr), - "could not create a memory primitive"); - reset(result); - auto _malloc = [](size_t size, int alignment) { - void *ptr; -#ifdef _WIN32 - ptr = _aligned_malloc(size, alignment); - int rc = ((ptr) ? 0 : errno); -#else - int rc = ::posix_memalign(&ptr, alignment, size); -#endif /* _WIN32 */ - return (rc == 0) ? (char *)ptr : nullptr; - }; - auto _free = [](char *p) { -#ifdef _WIN32 - _aligned_free((void *)p); -#else - ::free((void *)p); -#endif /* _WIN32 */ - }; - _handle.reset(_malloc(adesc.get_size(), 4096), _free); - set_data_handle(_handle.get()); - } - - memory(const primitive_desc &adesc, void *ahandle) { - mkldnn_primitive_t result; - error::wrap_c_api( - mkldnn_primitive_create(&result, adesc.get(), nullptr, nullptr), - "could not create a memory primitive"); - reset(result); - set_data_handle(ahandle); - } - - /// Returns the descriptor of the memory primitive. - primitive_desc get_primitive_desc() const { - primitive_desc adesc; - const_mkldnn_primitive_desc_t cdesc; - error::wrap_c_api( - mkldnn_primitive_get_primitive_desc(get(), &cdesc), - "could not get primitive descriptor from a memory primitive"); - /* FIXME: no const_cast should be here */ - adesc.reset(const_cast(cdesc), true); - return adesc; - } - - /// Returns a handle of the data contained in the memory primitive. On - /// the CPU engine, this is a pointer to the allocated memory. - inline void *get_data_handle() const { - void *handle; - error::wrap_c_api(mkldnn_memory_get_data_handle(get(), &handle), - "could not get native handle"); - return handle; - } - - inline void set_data_handle(void *handle) const { - error::wrap_c_api(mkldnn_memory_set_data_handle(get(), handle), - "could not set native handle"); - } - - // Must go away or be private: - static mkldnn_data_type_t convert_to_c(data_type adata_type) { - return static_cast(adata_type); - } - static mkldnn_memory_format_t convert_to_c(format aformat) { - return static_cast(aformat); - } -}; - -inline memory::desc zero_md() { - mkldnn_memory_desc_t zero; - zero.primitive_kind = mkldnn_memory; - return memory::desc(zero); -} - -inline memory null_memory(engine eng) { - mkldnn::memory::desc zero = zero_md(); - return memory({zero, eng}, nullptr); -} - -inline bool is_null_memory(const const_mkldnn_primitive_t &aprimitive) { - const_mkldnn_primitive_desc_t aprimitive_pd; - mkldnn_primitive_get_primitive_desc(aprimitive, &aprimitive_pd); - const mkldnn_memory_desc_t *aprimitive_md = - mkldnn_primitive_desc_query_memory_d(aprimitive_pd); - - return ((aprimitive_md != nullptr) && (aprimitive_md->ndims == 0)); -} - -inline bool operator==(mkldnn_data_type_t a, memory::data_type b) { - return a == memory::convert_to_c(b); -} -inline bool operator!=(mkldnn_data_type_t a, memory::data_type b) { - return !(a == b); -} -inline bool operator==(memory::data_type a, mkldnn_data_type_t b) { - return b == a; -} -inline bool operator!=(memory::data_type a, mkldnn_data_type_t b) { - return !(a == b); -} - -inline bool operator==(mkldnn_memory_format_t a, memory::format b) { - return a == memory::convert_to_c(b); -} -inline bool operator!=(mkldnn_memory_format_t a, memory::format b) { - return !(a == b); -} -inline bool operator==(memory::format a, mkldnn_memory_format_t b) { - return b == a; -} -inline bool operator!=(memory::format a, mkldnn_memory_format_t b) { - return !(a == b); -} - -/// @} - -/// @addtogroup cpp_api_reorder Reorder -/// @{ - -struct reorder : public primitive { - struct primitive_desc : public handle { - primitive_desc(const memory::primitive_desc &input, - const memory::primitive_desc &output) { - mkldnn_primitive_desc_t result; - error::wrap_c_api(mkldnn_reorder_primitive_desc_create( - &result, input.get(), output.get()), - "could not create a reorder primitive descriptor"); - reset(result); - } - - primitive_desc(const memory::primitive_desc &input, - const memory::primitive_desc &output, - const primitive_attr &aattr) { - mkldnn_primitive_desc_t result; - error::wrap_c_api(mkldnn_reorder_primitive_desc_create_v2( - &result, input.get(), output.get(), aattr.get()), - "could not create a reorder primitive descriptor"); - reset(result); - } - - engine get_engine() { return engine::query(*this); } - }; - - reorder(const primitive_desc &aprimitive_desc, - const primitive::at &input, - const memory &output) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {input.data}; - const_mkldnn_primitive_t outputs[] = {output.get()}; - error::wrap_c_api(mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a reorder primitive"); - reset(result); - } - - reorder(const primitive::at &input, const memory &output) { - auto input_mpd = memory(input).get_primitive_desc(); - auto output_mpd = output.get_primitive_desc(); - - auto reorder_d = primitive_desc(input_mpd, output_mpd); - - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {input.data}; - const_mkldnn_primitive_t outputs[] = {output.get()}; - error::wrap_c_api( - mkldnn_primitive_create(&result, reorder_d.get(), inputs, outputs), - "could not create a reorder primitive"); - reset(result); - } -}; - -/// @} - -/// @addtogroup cpp_api_view View -/// @{ - -struct view : public primitive { - struct primitive_desc : public handle { - primitive_desc(const memory::primitive_desc &input, - memory::dims dims, - memory::dims offsets) { - mkldnn_primitive_desc_t result; - - error::wrap_c_api(mkldnn_view_primitive_desc_create( - &result, input.get(), &dims[0], &offsets[0]), - "could not create a view primitive descriptor"); - reset(result); - } - - memory::primitive_desc dst_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(dst_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a dst primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - engine get_engine() { return engine::query(*this); } - }; - - view(const primitive_desc &view_pd, primitive::at input) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {input.data}; - error::wrap_c_api( - mkldnn_primitive_create(&result, view_pd.get(), inputs, nullptr), - "could not create a view primitive"); - reset(result); - } - - view(memory input, memory::dims dims, memory::dims offsets) { - mkldnn_primitive_t result; - primitive_desc view_pd(input.get_primitive_desc(), dims, offsets); - mkldnn_primitive_at_t inputs[] = {primitive::at(input).data}; - error::wrap_c_api( - mkldnn_primitive_create(&result, view_pd.get(), inputs, nullptr), - "could not create a view primitive"); - reset(result); - } -}; - -/// @} - -/// @addtogroup cpp_api_concat Concat -/// @{ - -struct concat : public primitive { - struct primitive_desc : public handle { - std::vector cpp_to_c( - std::vector inputs) { - std::vector c_api_inputs; - c_api_inputs.reserve(inputs.size()); - auto convert_to_c = [](memory::primitive_desc d) { return d.get(); }; - std::transform(inputs.begin(), - inputs.end(), - std::back_inserter(c_api_inputs), - convert_to_c); - return c_api_inputs; - } - - primitive_desc(const memory::desc &output, - int concat_dimension, - std::vector inputs) { - mkldnn_primitive_desc_t result; - - auto c_api_inputs = cpp_to_c(inputs); - - error::wrap_c_api( - mkldnn_concat_primitive_desc_create(&result, - &output.data, - (int)c_api_inputs.size(), - concat_dimension, - &c_api_inputs[0]), - "could not create a concat primitive descriptor"); - reset(result); - } - - primitive_desc(int concat_dimension, - std::vector inputs) { - mkldnn_primitive_desc_t result; - - auto c_api_inputs = cpp_to_c(inputs); - - error::wrap_c_api( - mkldnn_concat_primitive_desc_create(&result, - nullptr, - (int)c_api_inputs.size(), - concat_dimension, - &c_api_inputs[0]), - "could not create a concat primitive descriptor"); - reset(result); - } - - memory::primitive_desc dst_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(dst_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a dst primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - engine get_engine() { return engine::query(*this); } - }; - - concat(const primitive_desc &concat_pd, - std::vector &inputs, - const memory &output) { - mkldnn_primitive_t result; - - std::vector p_inputs; - for (size_t i = 0; i < inputs.size(); i++) - p_inputs.push_back(inputs[i].data); - const_mkldnn_primitive_t outputs[] = {output.get()}; - - error::wrap_c_api(mkldnn_primitive_create( - &result, concat_pd.get(), &p_inputs[0], outputs), - "could not create a concat primitive"); - reset(result); - } -}; - -/// @} - -/// @addtogroup cpp_api_sum Sum -/// @{ - -struct sum : public primitive { - struct primitive_desc : public handle { - std::vector cpp_to_c( - std::vector inputs) { - std::vector c_api_inputs; - c_api_inputs.reserve(inputs.size()); - auto convert_to_c = [](memory::primitive_desc d) { return d.get(); }; - std::transform(inputs.begin(), - inputs.end(), - std::back_inserter(c_api_inputs), - convert_to_c); - return c_api_inputs; - } - - primitive_desc(const memory::desc &output, - const std::vector &scales, - std::vector inputs) { - mkldnn_primitive_desc_t result; - - auto c_api_inputs = cpp_to_c(inputs); - - error::wrap_c_api( - mkldnn_sum_primitive_desc_create(&result, - &output.data, - (int)c_api_inputs.size(), - &scales[0], - &c_api_inputs[0]), - "could not create a sum primitive descriptor"); - reset(result); - } - - primitive_desc(const std::vector &scales, - std::vector inputs) { - mkldnn_primitive_desc_t result; - - auto c_api_inputs = cpp_to_c(inputs); - - error::wrap_c_api( - mkldnn_sum_primitive_desc_create(&result, - nullptr, - (int)c_api_inputs.size(), - &scales[0], - &c_api_inputs[0]), - "could not create a sum primitive descriptor"); - reset(result); - } - - /** @deprecated: api backwards compatibility for double scales type */ - MKLDNN_DEPRECATED - primitive_desc(const memory::desc &output, - std::vector scale, - std::vector inputs) { - mkldnn_primitive_desc_t result; - - auto c_api_inputs = cpp_to_c(inputs); - auto scale_f = scale_to_float(scale); - - error::wrap_c_api( - mkldnn_sum_primitive_desc_create(&result, - &output.data, - (int)c_api_inputs.size(), - &scale_f[0], - &c_api_inputs[0]), - "could not create a sum primitive descriptor"); - reset(result); - } - - /** @deprecated: api backwards compatibility for double scales type */ - MKLDNN_DEPRECATED - primitive_desc(std::vector scale, - std::vector inputs) { - mkldnn_primitive_desc_t result; - - auto c_api_inputs = cpp_to_c(inputs); - auto scale_f = scale_to_float(scale); - - error::wrap_c_api( - mkldnn_sum_primitive_desc_create(&result, - nullptr, - (int)c_api_inputs.size(), - &scale_f[0], - &c_api_inputs[0]), - "could not create a sum primitive descriptor"); - reset(result); - } - - memory::primitive_desc dst_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(dst_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a dst primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - engine get_engine() { return engine::query(*this); } - }; - - sum(const primitive_desc &sum_pd, - std::vector &inputs, - const memory &output) { - mkldnn_primitive_t result; - - std::vector p_inputs; - for (size_t i = 0; i < inputs.size(); i++) - p_inputs.push_back(inputs[i].data); - const_mkldnn_primitive_t outputs[] = {output.get()}; - - error::wrap_c_api( - mkldnn_primitive_create(&result, sum_pd.get(), &p_inputs[0], outputs), - "could not create a sum primitive"); - reset(result); - } - -private: - static std::vector scale_to_float(const std::vector &vd) { - std::vector vf(vd.size()); - std::transform( - vd.begin(), vd.end(), vf.begin(), [=](double x) { return (float)x; }); - return vf; - } -}; - -/// @} - -/// @addtogroup cpp_api_convolution Convolution -/// @{ - -struct convolution_forward : public primitive { - struct desc { - mkldnn_convolution_desc_t data; - desc(prop_kind aprop_kind, - algorithm aalgorithm, - const memory::desc &src_desc, - const memory::desc &weights_desc, - const memory::desc &bias_desc, - const memory::desc &dst_desc, - const memory::dims strides, - const memory::dims padding_l, - const memory::dims padding_r, - const padding_kind apadding_kind) { - memory::validate_dims(strides); - memory::validate_dims(padding_l); - memory::validate_dims(padding_r); - error::wrap_c_api(mkldnn_convolution_forward_desc_init( - &data, - mkldnn::convert_to_c(aprop_kind), - convert_to_c(aalgorithm), - &src_desc.data, - &weights_desc.data, - &bias_desc.data, - &dst_desc.data, - &strides[0], - &padding_l[0], - &padding_r[0], - mkldnn::convert_to_c(apadding_kind)), - "could not create a convolution forward descriptor"); - } - desc(prop_kind aprop_kind, - algorithm aalgorithm, - const memory::desc &src_desc, - const memory::desc &weights_desc, - const memory::desc &dst_desc, - const memory::dims strides, - const memory::dims padding_l, - const memory::dims padding_r, - const padding_kind apadding_kind) { - memory::validate_dims(strides); - memory::validate_dims(padding_l); - memory::validate_dims(padding_r); - error::wrap_c_api(mkldnn_convolution_forward_desc_init( - &data, - mkldnn::convert_to_c(aprop_kind), - convert_to_c(aalgorithm), - &src_desc.data, - &weights_desc.data, - nullptr, - &dst_desc.data, - &strides[0], - &padding_l[0], - &padding_r[0], - mkldnn::convert_to_c(apadding_kind)), - "could not create a convolution forward descriptor"); - } - desc(prop_kind aprop_kind, - algorithm aalgorithm, - const memory::desc &src_desc, - const memory::desc &weights_desc, - const memory::desc &bias_desc, - const memory::desc &dst_desc, - const memory::dims strides, - const memory::dims dilates, - const memory::dims padding_l, - const memory::dims padding_r, - const padding_kind apadding_kind) { - memory::validate_dims(strides); - memory::validate_dims(dilates); - memory::validate_dims(padding_l); - memory::validate_dims(padding_r); - error::wrap_c_api( - mkldnn_dilated_convolution_forward_desc_init( - &data, - mkldnn::convert_to_c(aprop_kind), - convert_to_c(aalgorithm), - &src_desc.data, - &weights_desc.data, - &bias_desc.data, - &dst_desc.data, - &strides[0], - &dilates[0], - &padding_l[0], - &padding_r[0], - mkldnn::convert_to_c(apadding_kind)), - "could not create a dilated convolution forward descriptor"); - } - desc(prop_kind aprop_kind, - algorithm aalgorithm, - const memory::desc &src_desc, - const memory::desc &weights_desc, - const memory::desc &dst_desc, - const memory::dims strides, - const memory::dims dilates, - const memory::dims padding_l, - const memory::dims padding_r, - const padding_kind apadding_kind) { - memory::validate_dims(strides); - memory::validate_dims(dilates); - memory::validate_dims(padding_l); - memory::validate_dims(padding_r); - error::wrap_c_api( - mkldnn_dilated_convolution_forward_desc_init( - &data, - mkldnn::convert_to_c(aprop_kind), - convert_to_c(aalgorithm), - &src_desc.data, - &weights_desc.data, - nullptr, - &dst_desc.data, - &strides[0], - &dilates[0], - &padding_l[0], - &padding_r[0], - mkldnn::convert_to_c(apadding_kind)), - "could not create a dilated convolution forward descriptor"); - } - }; - struct primitive_desc : public handle { - primitive_desc(const desc &adesc, const engine &aengine) { - mkldnn_primitive_desc_t result; - error::wrap_c_api( - mkldnn_primitive_desc_create( - &result, &adesc.data, aengine.get(), nullptr), - "could not create a convolution forward primitive descriptor"); - reset(result); - } - - primitive_desc(const desc &adesc, - const primitive_attr &aattr, - const engine &aengine) { - mkldnn_primitive_desc_t result; - error::wrap_c_api( - mkldnn_primitive_desc_create_v2( - &result, &adesc.data, aattr.get(), aengine.get(), nullptr), - "could not create a convolution forward primitive descriptor"); - reset(result); - } - - memory::primitive_desc src_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(src_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a src primititve descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc weights_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(weights_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a weights primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc bias_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(weights_pd), 1); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a bias primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc dst_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(dst_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a dst primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - engine get_engine() { return engine::query(*this); } - }; - - convolution_forward(const primitive_desc &aprimitive_desc, - const primitive::at &src, - const primitive::at &weights, - const primitive::at &bias, - const memory &dst) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {src.data, weights.data, bias.data}; - const_mkldnn_primitive_t outputs[] = {dst.get()}; - error::wrap_c_api(mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a convolution forward bias primitive"); - reset(result); - } - - convolution_forward(const primitive_desc &aprimitive_desc, - const primitive::at &src, - const primitive::at &weights, - const memory &dst) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {src.data, weights.data}; - const_mkldnn_primitive_t outputs[] = {dst.get()}; - error::wrap_c_api(mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a convolution forward primitive"); - reset(result); - } -}; - -struct convolution_backward_data : public primitive { - struct desc { - mkldnn_convolution_desc_t data; - desc(algorithm aalgorithm, - const memory::desc &diff_src_desc, - const memory::desc &weights_desc, - const memory::desc &diff_dst_desc, - const memory::dims strides, - const memory::dims padding_l, - const memory::dims padding_r, - const padding_kind apadding_kind) { - memory::validate_dims(strides); - memory::validate_dims(padding_l); - memory::validate_dims(padding_r); - error::wrap_c_api( - mkldnn_convolution_backward_data_desc_init( - &data, - convert_to_c(aalgorithm), - &diff_src_desc.data, - &weights_desc.data, - &diff_dst_desc.data, - &strides[0], - &padding_l[0], - &padding_r[0], - mkldnn::convert_to_c(apadding_kind)), - "could not create a convolution backward data descriptor"); - } - desc(algorithm aalgorithm, - const memory::desc &diff_src_desc, - const memory::desc &weights_desc, - const memory::desc &diff_dst_desc, - const memory::dims strides, - const memory::dims dilates, - const memory::dims padding_l, - const memory::dims padding_r, - const padding_kind apadding_kind) { - memory::validate_dims(strides); - memory::validate_dims(dilates); - memory::validate_dims(padding_l); - memory::validate_dims(padding_r); - error::wrap_c_api( - mkldnn_dilated_convolution_backward_data_desc_init( - &data, - convert_to_c(aalgorithm), - &diff_src_desc.data, - &weights_desc.data, - &diff_dst_desc.data, - &strides[0], - &dilates[0], - &padding_l[0], - &padding_r[0], - mkldnn::convert_to_c(apadding_kind)), - "could not create a convolution backward data descriptor"); - } - }; - struct primitive_desc : public handle { - primitive_desc( - const desc &adesc, - const engine &aengine, - const convolution_forward::primitive_desc &hint_fwd_primitive_desc) { - mkldnn_primitive_desc_t result; - error::wrap_c_api( - mkldnn_primitive_desc_create(&result, - &adesc.data, - aengine.get(), - hint_fwd_primitive_desc.get()), - "could not create a convolution backward data primitive descriptor"); - reset(result); - } - memory::primitive_desc diff_src_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(diff_src_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a diff_src primititve descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc weights_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(weights_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a weights primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc diff_dst_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(diff_dst_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a diff_dst primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - engine get_engine() { return engine::query(*this); } - }; - - convolution_backward_data(const primitive_desc &aprimitive_desc, - const primitive::at &diff_dst, - const primitive::at &weights, - const memory &diff_src) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {diff_dst.data, weights.data}; - const_mkldnn_primitive_t outputs[] = {diff_src.get()}; - error::wrap_c_api(mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a convolution backward data primitive"); - reset(result); - } -}; - -struct convolution_backward_weights : public primitive { - struct desc { - mkldnn_convolution_desc_t data; - desc(algorithm aalgorithm, - const memory::desc &src_desc, - const memory::desc &diff_weights_desc, - const memory::desc &diff_bias_desc, - const memory::desc &diff_dst_desc, - const memory::dims strides, - const memory::dims padding_l, - const memory::dims padding_r, - const padding_kind apadding_kind) { - memory::validate_dims(strides); - memory::validate_dims(padding_l); - memory::validate_dims(padding_r); - error::wrap_c_api( - mkldnn_convolution_backward_weights_desc_init( - &data, - convert_to_c(aalgorithm), - &src_desc.data, - &diff_weights_desc.data, - &diff_bias_desc.data, - &diff_dst_desc.data, - &strides[0], - &padding_l[0], - &padding_r[0], - mkldnn::convert_to_c(apadding_kind)), - "could not create a convolution backward weights descriptor"); - } - desc(algorithm aalgorithm, - const memory::desc &src_desc, - const memory::desc &diff_weights_desc, - const memory::desc &diff_dst_desc, - const memory::dims strides, - const memory::dims padding_l, - const memory::dims padding_r, - const padding_kind apadding_kind) { - memory::validate_dims(strides); - memory::validate_dims(padding_l); - memory::validate_dims(padding_r); - error::wrap_c_api( - mkldnn_convolution_backward_weights_desc_init( - &data, - convert_to_c(aalgorithm), - &src_desc.data, - &diff_weights_desc.data, - nullptr, - &diff_dst_desc.data, - &strides[0], - &padding_l[0], - &padding_r[0], - mkldnn::convert_to_c(apadding_kind)), - "could not create a convolution backward weights descriptor"); - } - desc(algorithm aalgorithm, - const memory::desc &src_desc, - const memory::desc &diff_weights_desc, - const memory::desc &diff_bias_desc, - const memory::desc &diff_dst_desc, - const memory::dims strides, - const memory::dims dilates, - const memory::dims padding_l, - const memory::dims padding_r, - const padding_kind apadding_kind) { - memory::validate_dims(strides); - memory::validate_dims(dilates); - memory::validate_dims(padding_l); - memory::validate_dims(padding_r); - error::wrap_c_api( - mkldnn_dilated_convolution_backward_weights_desc_init( - &data, - convert_to_c(aalgorithm), - &src_desc.data, - &diff_weights_desc.data, - &diff_bias_desc.data, - &diff_dst_desc.data, - &strides[0], - &dilates[0], - &padding_l[0], - &padding_r[0], - mkldnn::convert_to_c(apadding_kind)), - "could not create a convolution backward weights descriptor"); - } - desc(algorithm aalgorithm, - const memory::desc &src_desc, - const memory::desc &diff_weights_desc, - const memory::desc &diff_dst_desc, - const memory::dims strides, - const memory::dims dilates, - const memory::dims padding_l, - const memory::dims padding_r, - const padding_kind apadding_kind) { - memory::validate_dims(strides); - memory::validate_dims(dilates); - memory::validate_dims(padding_l); - memory::validate_dims(padding_r); - error::wrap_c_api( - mkldnn_dilated_convolution_backward_weights_desc_init( - &data, - convert_to_c(aalgorithm), - &src_desc.data, - &diff_weights_desc.data, - nullptr, - &diff_dst_desc.data, - &strides[0], - &dilates[0], - &padding_l[0], - &padding_r[0], - mkldnn::convert_to_c(apadding_kind)), - "could not create a convolution backward weights descriptor"); - } - }; - - struct primitive_desc : public handle { - primitive_desc( - const desc &adesc, - const engine &aengine, - const convolution_forward::primitive_desc &hint_fwd_primitive_desc) { - mkldnn_primitive_desc_t result; - error::wrap_c_api( - mkldnn_primitive_desc_create(&result, - &adesc.data, - aengine.get(), - hint_fwd_primitive_desc.get()), - "could not create a convolution backward weights primitive " - "descriptor"); - reset(result); - } - memory::primitive_desc src_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(src_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a src primititve descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc diff_weights_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(diff_weights_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a diff_weights primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc diff_bias_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(diff_weights_pd), 1); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a diff_bias primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc diff_dst_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(diff_dst_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a diff_dst primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - engine get_engine() { return engine::query(*this); } - }; - - convolution_backward_weights(const primitive_desc &aprimitive_desc, - const primitive::at &src, - const primitive::at &diff_dst, - const memory &diff_weights, - const memory &diff_bias) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data}; - const_mkldnn_primitive_t outputs[] = {diff_weights.get(), diff_bias.get()}; - error::wrap_c_api( - mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a convolution backward weights primitive"); - reset(result); - } - convolution_backward_weights(const primitive_desc &aprimitive_desc, - const primitive::at &src, - const primitive::at &diff_dst, - const memory &diff_weights) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data}; - const_mkldnn_primitive_t outputs[] = {diff_weights.get()}; - error::wrap_c_api( - mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a convolution backward weights primitive"); - reset(result); - } -}; - -struct convolution_relu_forward : public primitive { - struct desc { - mkldnn_convolution_relu_desc_t data; - desc(const convolution_forward::desc conv_desc, - const float negative_slope) { - error::wrap_c_api( - mkldnn_convolution_relu_desc_init( - &data, &conv_desc.data, negative_slope), - "could not create a convolution_relu_forward descriptor"); - } - }; - - struct primitive_desc : public handle { - primitive_desc(const desc &adesc, const engine &aengine) { - mkldnn_primitive_desc_t result; - error::wrap_c_api( - mkldnn_primitive_desc_create( - &result, &adesc.data, aengine.get(), nullptr), - "could not create a convolution relu forward descriptor"); - reset(result); - } - - engine get_engine() { return engine::query(*this); } - }; - - convolution_relu_forward(const primitive_desc &aprimitive_desc, - const primitive::at &src, - const primitive::at &weights, - const primitive::at &bias, - const memory &dst) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {src.data, weights.data, bias.data}; - const_mkldnn_primitive_t outputs[] = {dst.get()}; - error::wrap_c_api(mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a convolution relu forward primitive"); - reset(result); - } - - convolution_relu_forward(const primitive_desc &aprimitive_desc, - const primitive::at &src, - const primitive::at &weights, - const memory &dst) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {src.data, weights.data}; - const_mkldnn_primitive_t outputs[] = {dst.get()}; - error::wrap_c_api(mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a convolution relu forward primitive"); - reset(result); - } -}; - -/// @} -// -/// @addtogroup cpp_api_deconvolution Deconvolution -/// @{ - -struct deconvolution_forward : public primitive { - struct desc { - mkldnn_deconvolution_desc_t data; - desc(prop_kind aprop_kind, - algorithm aalgorithm, - const memory::desc &src_desc, - const memory::desc &weights_desc, - const memory::desc &bias_desc, - const memory::desc &dst_desc, - const memory::dims strides, - const memory::dims padding_l, - const memory::dims padding_r, - const padding_kind apadding_kind) { - memory::validate_dims(strides); - memory::validate_dims(padding_l); - memory::validate_dims(padding_r); - error::wrap_c_api(mkldnn_deconvolution_forward_desc_init( - &data, - mkldnn::convert_to_c(aprop_kind), - convert_to_c(aalgorithm), - &src_desc.data, - &weights_desc.data, - &bias_desc.data, - &dst_desc.data, - &strides[0], - &padding_l[0], - &padding_r[0], - mkldnn::convert_to_c(apadding_kind)), - "could not create a deconvolution forward descriptor"); - } - desc(prop_kind aprop_kind, - algorithm aalgorithm, - const memory::desc &src_desc, - const memory::desc &weights_desc, - const memory::desc &dst_desc, - const memory::dims strides, - const memory::dims padding_l, - const memory::dims padding_r, - const padding_kind apadding_kind) { - memory::validate_dims(strides); - memory::validate_dims(padding_l); - memory::validate_dims(padding_r); - error::wrap_c_api(mkldnn_deconvolution_forward_desc_init( - &data, - mkldnn::convert_to_c(aprop_kind), - convert_to_c(aalgorithm), - &src_desc.data, - &weights_desc.data, - nullptr, - &dst_desc.data, - &strides[0], - &padding_l[0], - &padding_r[0], - mkldnn::convert_to_c(apadding_kind)), - "could not create a deconvolution forward descriptor"); - } - }; - struct primitive_desc : public handle { - primitive_desc(const desc &adesc, const engine &aengine) { - mkldnn_primitive_desc_t result; - error::wrap_c_api( - mkldnn_primitive_desc_create( - &result, &adesc.data, aengine.get(), nullptr), - "could not create a deconvolution forward primitive descriptor"); - reset(result); - } - - primitive_desc(const desc &adesc, - const primitive_attr &aattr, - const engine &aengine) { - mkldnn_primitive_desc_t result; - error::wrap_c_api( - mkldnn_primitive_desc_create_v2( - &result, &adesc.data, aattr.get(), aengine.get(), nullptr), - "could not create a deconvolution forward primitive descriptor"); - reset(result); - } - - memory::primitive_desc src_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(src_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a src primititve descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc weights_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(weights_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a weights primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc bias_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(weights_pd), 1); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a bias primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc dst_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(dst_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a dst primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - engine get_engine() { return engine::query(*this); } - }; - - deconvolution_forward(const primitive_desc &aprimitive_desc, - const primitive::at &src, - const primitive::at &weights, - const primitive::at &bias, - const memory &dst) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {src.data, weights.data, bias.data}; - const_mkldnn_primitive_t outputs[] = {dst.get()}; - error::wrap_c_api( - mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a deconvolution forward bias primitive"); - reset(result); - } - - deconvolution_forward(const primitive_desc &aprimitive_desc, - const primitive::at &src, - const primitive::at &weights, - const memory &dst) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {src.data, weights.data}; - const_mkldnn_primitive_t outputs[] = {dst.get()}; - error::wrap_c_api(mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a deconvolution forward primitive"); - reset(result); - } -}; - -struct deconvolution_backward_data : public primitive { - struct desc { - mkldnn_deconvolution_desc_t data; - desc(algorithm aalgorithm, - const memory::desc &diff_src_desc, - const memory::desc &weights_desc, - const memory::desc &diff_dst_desc, - const memory::dims strides, - const memory::dims padding_l, - const memory::dims padding_r, - const padding_kind apadding_kind) { - memory::validate_dims(strides); - memory::validate_dims(padding_l); - memory::validate_dims(padding_r); - error::wrap_c_api( - mkldnn_deconvolution_backward_data_desc_init( - &data, - convert_to_c(aalgorithm), - &diff_src_desc.data, - &weights_desc.data, - &diff_dst_desc.data, - &strides[0], - &padding_l[0], - &padding_r[0], - mkldnn::convert_to_c(apadding_kind)), - "could not create a deconvolution backward data descriptor"); - } - }; - struct primitive_desc : public handle { - primitive_desc( - const desc &adesc, - const engine &aengine, - const deconvolution_forward::primitive_desc &hint_fwd_primitive_desc) { - mkldnn_primitive_desc_t result; - error::wrap_c_api( - mkldnn_primitive_desc_create(&result, - &adesc.data, - aengine.get(), - hint_fwd_primitive_desc.get()), - "could not create a deconvolution backward data primitive " - "descriptor"); - reset(result); - } - memory::primitive_desc diff_src_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(diff_src_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a diff_src primititve descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc weights_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(weights_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a weights primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc diff_dst_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(diff_dst_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a diff_dst primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - engine get_engine() { return engine::query(*this); } - }; - - deconvolution_backward_data(const primitive_desc &aprimitive_desc, - const primitive::at &diff_dst, - const primitive::at &weights, - const memory &diff_src) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {diff_dst.data, weights.data}; - const_mkldnn_primitive_t outputs[] = {diff_src.get()}; - error::wrap_c_api( - mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a deconvolution backward data primitive"); - reset(result); - } -}; - -struct deconvolution_backward_weights : public primitive { - struct desc { - mkldnn_deconvolution_desc_t data; - desc(algorithm aalgorithm, - const memory::desc &src_desc, - const memory::desc &diff_weights_desc, - const memory::desc &diff_bias_desc, - const memory::desc &diff_dst_desc, - const memory::dims strides, - const memory::dims padding_l, - const memory::dims padding_r, - const padding_kind apadding_kind) { - memory::validate_dims(strides); - memory::validate_dims(padding_l); - memory::validate_dims(padding_r); - error::wrap_c_api( - mkldnn_deconvolution_backward_weights_desc_init( - &data, - convert_to_c(aalgorithm), - &src_desc.data, - &diff_weights_desc.data, - &diff_bias_desc.data, - &diff_dst_desc.data, - &strides[0], - &padding_l[0], - &padding_r[0], - mkldnn::convert_to_c(apadding_kind)), - "could not create a deconvolution backward weights descriptor"); - } - desc(algorithm aalgorithm, - const memory::desc &src_desc, - const memory::desc &diff_weights_desc, - const memory::desc &diff_dst_desc, - const memory::dims strides, - const memory::dims padding_l, - const memory::dims padding_r, - const padding_kind apadding_kind) { - memory::validate_dims(strides); - memory::validate_dims(padding_l); - memory::validate_dims(padding_r); - error::wrap_c_api( - mkldnn_deconvolution_backward_weights_desc_init( - &data, - convert_to_c(aalgorithm), - &src_desc.data, - &diff_weights_desc.data, - nullptr, - &diff_dst_desc.data, - &strides[0], - &padding_l[0], - &padding_r[0], - mkldnn::convert_to_c(apadding_kind)), - "could not create a deconvolution backward weights descriptor"); - } - }; - - struct primitive_desc : public handle { - primitive_desc( - const desc &adesc, - const engine &aengine, - const deconvolution_forward::primitive_desc &hint_fwd_primitive_desc) { - mkldnn_primitive_desc_t result; - error::wrap_c_api( - mkldnn_primitive_desc_create(&result, - &adesc.data, - aengine.get(), - hint_fwd_primitive_desc.get()), - "could not create a deconvolution backward weights primitive " - "descriptor"); - reset(result); - } - memory::primitive_desc src_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(src_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a src primititve descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc diff_weights_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(diff_weights_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a diff_weights primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc diff_bias_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(diff_weights_pd), 1); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a diff_bias primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc diff_dst_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(diff_dst_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a diff_dst primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - engine get_engine() { return engine::query(*this); } - }; - - deconvolution_backward_weights(const primitive_desc &aprimitive_desc, - const primitive::at &src, - const primitive::at &diff_dst, - const memory &diff_weights, - const memory &diff_bias) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data}; - const_mkldnn_primitive_t outputs[] = {diff_weights.get(), diff_bias.get()}; - error::wrap_c_api( - mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a deconvolution backward weights primitive"); - reset(result); - } - deconvolution_backward_weights(const primitive_desc &aprimitive_desc, - const primitive::at &src, - const primitive::at &diff_dst, - const memory &diff_weights) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data}; - const_mkldnn_primitive_t outputs[] = {diff_weights.get()}; - error::wrap_c_api( - mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a deconvolution backward weights primitive"); - reset(result); - } -}; - -/// @} - -/// @addtogroup cpp_api_lrn LRN -/// @{ - -struct lrn_forward : public primitive { - struct desc { - mkldnn_lrn_desc_t data; - desc(prop_kind aprop_kind, - algorithm aalgorithm, - const memory::desc &src_desc, - int local_size, - float alpha, - float beta, - float k) { - error::wrap_c_api( - mkldnn_lrn_forward_desc_init(&data, - mkldnn::convert_to_c(aprop_kind), - convert_to_c(aalgorithm), - &src_desc.data, - local_size, - alpha, - beta, - k), - "could not create a lrn forward descriptor"); - } - desc(prop_kind aprop_kind, - algorithm aalgorithm, - const memory::desc &src_desc, - int local_size, - float alpha, - float beta) { - error::wrap_c_api( - mkldnn_lrn_forward_desc_init(&data, - mkldnn::convert_to_c(aprop_kind), - convert_to_c(aalgorithm), - &src_desc.data, - local_size, - alpha, - beta, - float(1.0)), - "could not create a lrn forward descriptor"); - } - }; - - struct primitive_desc : public handle { - primitive_desc(const desc &adesc, const engine &aengine) { - mkldnn_primitive_desc_t result; - error::wrap_c_api(mkldnn_primitive_desc_create( - &result, &adesc.data, aengine.get(), nullptr), - "could not create a lrn forward primitive descriptor"); - reset(result); - } - - memory::primitive_desc src_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(src_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a src primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc workspace_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t ldesc; - const_mkldnn_primitive_desc_t const_ldesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(workspace_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&ldesc, const_ldesc), - "could not clone a workspace primitive descriptor"); - adesc.reset(ldesc); - return adesc; - } - - memory::primitive_desc dst_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(dst_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a dst primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - engine get_engine() { return engine::query(*this); } - }; - - lrn_forward(const primitive_desc &aprimitive_desc, - const primitive::at &src, - const memory &workspace, - const memory &dst) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {src.data}; - const_mkldnn_primitive_t outputs[] = {dst.get(), workspace.get()}; - error::wrap_c_api(mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a lrn forward primitive"); - reset(result); - } - - lrn_forward(const primitive_desc &aprimitive_desc, - const primitive::at &src, - const memory &dst) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {src.data}; - const_mkldnn_primitive_t outputs[] = {dst.get()}; - error::wrap_c_api(mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a lrn forward primitive"); - reset(result); - } -}; - -struct lrn_backward : public primitive { - struct desc { - mkldnn_lrn_desc_t data; - desc(algorithm aalgorithm, - const memory::desc &data_desc, - const memory::desc &diff_data_desc, - int local_size, - float alpha, - float beta, - float k) { - error::wrap_c_api(mkldnn_lrn_backward_desc_init(&data, - convert_to_c(aalgorithm), - &diff_data_desc.data, - &data_desc.data, - local_size, - alpha, - beta, - k), - "could not create a lrn backward descriptor"); - } - desc(algorithm aalgorithm, - const memory::desc &data_desc, - const memory::desc &diff_data_desc, - int local_size, - float alpha, - float beta) { - error::wrap_c_api(mkldnn_lrn_backward_desc_init(&data, - convert_to_c(aalgorithm), - &diff_data_desc.data, - &data_desc.data, - local_size, - alpha, - beta, - float(1.0)), - "could not create a lrn backward descriptor"); - } - }; - - struct primitive_desc : public handle { - primitive_desc(const desc &adesc, - const engine &aengine, - const lrn_forward::primitive_desc &hint_fwd_primitive_desc) { - mkldnn_primitive_desc_t result; - error::wrap_c_api( - mkldnn_primitive_desc_create(&result, - &adesc.data, - aengine.get(), - hint_fwd_primitive_desc.get()), - "could not create a backward lrn primitive descriptor"); - reset(result); - } - - memory::primitive_desc diff_src_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(diff_src_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a diff_src primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc workspace_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t ldesc; - const_mkldnn_primitive_desc_t const_ldesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(workspace_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&ldesc, const_ldesc), - "could not clone a workspace primitive descriptor"); - adesc.reset(ldesc); - return adesc; - } - - memory::primitive_desc diff_dst_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(diff_dst_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a diff_dst primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - engine get_engine() { return engine::query(*this); } - }; - - lrn_backward(const primitive_desc &aprimitive_desc, - const primitive::at &src, - const primitive::at &diff_dst, - const primitive::at &workspace, - const memory &diff_src) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data, workspace.data}; - const_mkldnn_primitive_t outputs[] = {diff_src.get()}; - error::wrap_c_api(mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a lrn backward primitive"); - reset(result); - } - - lrn_backward(const primitive_desc &aprimitive_desc, - const primitive::at &src, - const primitive::at &diff_dst, - const memory &diff_src) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data}; - const_mkldnn_primitive_t outputs[] = {diff_src.get()}; - error::wrap_c_api(mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a lrn backward primitive"); - reset(result); - } -}; - -/// @} - -/// @addtogroup cpp_api_pooling Pooling -/// @{ - -struct pooling_forward : public primitive { - struct desc { - mkldnn_pooling_desc_t data; - desc(prop_kind aprop_kind, - algorithm aalgorithm, - const memory::desc &src_desc, - const memory::desc &dst_desc, - const memory::dims strides, - const memory::dims kernel, - const memory::dims padding_l, - const memory::dims padding_r, - const padding_kind apadding_kind) { - memory::validate_dims(strides); - memory::validate_dims(kernel); - memory::validate_dims(padding_l); - memory::validate_dims(padding_r); - error::wrap_c_api( - mkldnn_pooling_forward_desc_init(&data, - mkldnn::convert_to_c(aprop_kind), - convert_to_c(aalgorithm), - &src_desc.data, - &dst_desc.data, - &strides[0], - &kernel[0], - &padding_l[0], - &padding_r[0], - mkldnn::convert_to_c(apadding_kind)), - "could not init a forward pooling descriptor"); - } - }; - - struct primitive_desc : public handle { - primitive_desc(const desc &adesc, const engine &aengine) { - mkldnn_primitive_desc_t result; - error::wrap_c_api( - mkldnn_primitive_desc_create( - &result, &adesc.data, aengine.get(), nullptr), - "could not create a forward pooling primitive descriptor"); - reset(result); - } - - memory::primitive_desc workspace_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(workspace_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a workspace primititve descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc dst_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(dst_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a dst primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - engine get_engine() { return engine::query(*this); } - }; - - pooling_forward(const primitive_desc &aprimitive_desc, - const primitive::at &src, - const memory &dst) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {src.data}; - const_mkldnn_primitive_t outputs[] = {dst.get(), nullptr}; - error::wrap_c_api(mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a pooling forward primitive"); - reset(result); - } - - pooling_forward(const primitive_desc &aprimitive_desc, - const primitive::at &src, - const memory &dst, - const memory &workspace) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {src.data}; - const_mkldnn_primitive_t outputs[] = {dst.get(), workspace.get()}; - error::wrap_c_api(mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a pooling forward primitive"); - reset(result); - } -}; - -struct pooling_backward : public primitive { - struct desc { - mkldnn_pooling_desc_t data; - desc(algorithm aalgorithm, - const memory::desc &diff_src_desc, - const memory::desc &diff_dst_desc, - const memory::dims &strides, - const memory::dims &kernel, - const memory::dims &padding_l, - const memory::dims &padding_r, - const padding_kind apadding_kind) { - memory::validate_dims(strides); - memory::validate_dims(kernel); - memory::validate_dims(padding_l); - memory::validate_dims(padding_r); - error::wrap_c_api(mkldnn_pooling_backward_desc_init( - &data, - convert_to_c(aalgorithm), - &diff_src_desc.data, - &diff_dst_desc.data, - &strides[0], - &kernel[0], - &padding_l[0], - &padding_r[0], - mkldnn::convert_to_c(apadding_kind)), - "could not init a backward pooling descriptor"); - } - }; - - struct primitive_desc : public handle { - primitive_desc( - const desc &adesc, - const engine &aengine, - const pooling_forward::primitive_desc &hint_fwd_primitive_desc) { - mkldnn_primitive_desc_t result; - error::wrap_c_api( - mkldnn_primitive_desc_create(&result, - &adesc.data, - aengine.get(), - hint_fwd_primitive_desc.get()), - "could not create a backward pooling primitive descriptor"); - reset(result); - } - - memory::primitive_desc diff_src_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(diff_src_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a diff src primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - engine get_engine() { return engine::query(*this); } - }; - - pooling_backward(const primitive_desc &aprimitive_desc, - const primitive::at &diff_dst, - const memory &diff_src) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {diff_dst.data}; - const_mkldnn_primitive_t outputs[] = {diff_src.get()}; - error::wrap_c_api(mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a pooling backward primitive"); - reset(result); - } - - pooling_backward(const primitive_desc &aprimitive_desc, - const primitive::at &diff_dst, - const primitive::at &workspace, - const memory &diff_src) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {diff_dst.data, workspace.data}; - const_mkldnn_primitive_t outputs[] = {diff_src.get()}; - error::wrap_c_api(mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a pooling backward primitive"); - reset(result); - } -}; - -/// @} - -/// @addtogroup cpp_api_eltwise Eltwise -/// @{ - -struct eltwise_forward : public primitive { - struct desc { - mkldnn_eltwise_desc_t data; - template - desc(prop_kind aprop_kind, - algorithm alg_kind, - const memory::desc &src_desc, - T alpha = 0, - T beta = 0) { - error::wrap_c_api( - mkldnn_eltwise_forward_desc_init(&data, - mkldnn::convert_to_c(aprop_kind), - mkldnn::convert_to_c(alg_kind), - &src_desc.data, - static_cast(alpha), - static_cast(beta)), - "could not create a eltwise forward descriptor"); - } - - /** @deprecated: api backward compatibility for relu */ - template - MKLDNN_DEPRECATED desc(prop_kind aprop_kind, - const memory::desc &src_desc, - T negative_slope) - : desc(aprop_kind, eltwise_relu, src_desc, negative_slope) {} - }; - - struct primitive_desc : public handle { - primitive_desc(const desc &adesc, const engine &aengine) { - mkldnn_primitive_desc_t result; - error::wrap_c_api( - mkldnn_primitive_desc_create( - &result, &adesc.data, aengine.get(), nullptr), - "could not create a eltwise forward primitive descriptor"); - reset(result); - } - - memory::primitive_desc dst_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(dst_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a dst primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - engine get_engine() { return engine::query(*this); } - }; - - eltwise_forward(const primitive_desc &aprimitive_desc, - const primitive::at &src, - const memory &dst) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {src.data}; - const_mkldnn_primitive_t outputs[] = {dst.get()}; - error::wrap_c_api(mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a eltwise forward primitive"); - reset(result); - } -}; - -typedef eltwise_forward relu_forward; - -struct eltwise_backward : public primitive { - struct desc { - mkldnn_eltwise_desc_t data; - - template - desc(algorithm alg_kind, - const memory::desc &diff_data_desc, - const memory::desc &data_desc, - T alpha = 0, - T beta = 0) { - error::wrap_c_api( - mkldnn_eltwise_backward_desc_init(&data, - mkldnn::convert_to_c(alg_kind), - &diff_data_desc.data, - &data_desc.data, - static_cast(alpha), - static_cast(beta)), - "could not create a eltwise backward descriptor"); - } - - /** @deprecated: api backward compatibility for relu */ - template - MKLDNN_DEPRECATED desc(const memory::desc &diff_data_desc, - const memory::desc &data_desc, - T negative_slope) - : desc(eltwise_relu, diff_data_desc, data_desc, negative_slope) {} - }; - - struct primitive_desc : public handle { - primitive_desc( - const desc &adesc, - const engine &aengine, - const eltwise_forward::primitive_desc &hint_fwd_primitive_desc) { - mkldnn_primitive_desc_t result; - error::wrap_c_api( - mkldnn_primitive_desc_create(&result, - &adesc.data, - aengine.get(), - hint_fwd_primitive_desc.get()), - "could not create a eltwise backward primitive descriptor"); - reset(result); - } - - memory::primitive_desc diff_src_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(diff_src_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a diff src primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - engine get_engine() { return engine::query(*this); } - }; - - eltwise_backward(const primitive_desc &aprimitive_desc, - const primitive::at &src, - const primitive::at &diff_dst, - const memory &diff_src) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data}; - const_mkldnn_primitive_t outputs[] = {diff_src.get()}; - error::wrap_c_api(mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a eltwise backward primitive"); - reset(result); - } -}; - -typedef eltwise_backward relu_backward; - -/// @} - -/// @addtogroup cpp_api_softmax Softmax -/// @{ - -struct softmax_forward : public primitive { - struct desc { - mkldnn_softmax_desc_t data; - desc(prop_kind aprop_kind, - const memory::desc &data_desc, - int softmax_axis) { - error::wrap_c_api( - mkldnn_softmax_forward_desc_init(&data, - mkldnn::convert_to_c(aprop_kind), - &data_desc.data, - softmax_axis), - "could not create a softmax forward descriptor"); - } - }; - - struct primitive_desc : public handle { - primitive_desc(const desc &adesc, const engine &aengine) { - mkldnn_primitive_desc_t result; - error::wrap_c_api( - mkldnn_primitive_desc_create( - &result, &adesc.data, aengine.get(), nullptr), - "could not create a softmax forward primitive descriptor"); - reset(result); - } - - engine get_engine() { return engine::query(*this); } - }; - - softmax_forward(const primitive_desc &aprimitive_desc, - const primitive::at &src, - const memory &dst) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {src.data}; - const_mkldnn_primitive_t outputs[] = {dst.get()}; - error::wrap_c_api(mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a softmax forward primitive"); - reset(result); - } -}; - -/// @} - -/// @addtogroup cpp_api_batch_norm Batch normalization -/// @{ - -struct batch_normalization_forward : public primitive { - struct desc { - mkldnn_batch_normalization_desc_t data; - template - desc(prop_kind aprop_kind, - const memory::desc &src_desc, - T epsilon, - unsigned flags) { - error::wrap_c_api( - mkldnn_batch_normalization_forward_desc_init( - &data, - mkldnn::convert_to_c(aprop_kind), - &src_desc.data, - static_cast(epsilon), - flags), - "could not create a batch normalization forward descriptor"); - } - }; - - struct primitive_desc : public handle { - primitive_desc(const desc &adesc, const engine &aengine) { - mkldnn_primitive_desc_t result; - error::wrap_c_api(mkldnn_primitive_desc_create( - &result, &adesc.data, aengine.get(), nullptr), - "could not create a batch normalization forward " - "primitive descriptor"); - reset(result); - } - - primitive_desc(const desc &adesc, - const primitive_attr &aattr, - const engine &aengine) { - mkldnn_primitive_desc_t result; - error::wrap_c_api( - mkldnn_primitive_desc_create_v2( - &result, &adesc.data, aattr.get(), aengine.get(), nullptr), - "could not create a batch normalization forward " - "primitive descriptor"); - reset(result); - } - - memory::primitive_desc weights_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t bndesc; - const_mkldnn_primitive_desc_t const_bndesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(weights_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&bndesc, const_bndesc), - "could not clone a weights primitive descriptor"); - adesc.reset(bndesc); - return adesc; - } - - memory::primitive_desc mean_primitive_desc() const { - memory::primitive_desc aprimitive_desc; - mkldnn_primitive_desc_t bndesc; - mkldnn_batch_normalization_desc_t *p; - error::wrap_c_api( - mkldnn_primitive_desc_query( - get(), mkldnn::convert_to_c(batch_normalization_d), 0, &p), - "could not get a batch-normalization descriptor"); - const_mkldnn_primitive_desc_t const_bndesc = - (p->flags & use_global_stats) - ? mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(src_pd), 1) - : mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(dst_pd), 1); - error::wrap_c_api(mkldnn_primitive_desc_clone(&bndesc, const_bndesc), - "could not clone a mean primitive descriptor"); - aprimitive_desc.reset(bndesc); - return aprimitive_desc; - } - - memory::primitive_desc variance_primitive_desc() const { - memory::primitive_desc aprimitive_desc; - mkldnn_primitive_desc_t bndesc; - mkldnn_batch_normalization_desc_t *p; - error::wrap_c_api( - mkldnn_primitive_desc_query( - get(), mkldnn::convert_to_c(batch_normalization_d), 0, &p), - "could not get a batch-normalization descriptor"); - const_mkldnn_primitive_desc_t const_bndesc = - (p->flags & use_global_stats) - ? mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(src_pd), 2) - : mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(dst_pd), 2); - error::wrap_c_api(mkldnn_primitive_desc_clone(&bndesc, const_bndesc), - "could not clone a variance primitive descriptor"); - aprimitive_desc.reset(bndesc); - return aprimitive_desc; - } - - memory::primitive_desc workspace_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(workspace_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a workspace primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc dst_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(dst_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a dst primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - engine get_engine() { return engine::query(*this); } - }; - - batch_normalization_forward(const primitive_desc &aprimitive_desc, - const primitive::at &src, - const primitive::at &mean, - const primitive::at &variance, - const primitive::at &weights, - const memory &dst) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = { - src.data, mean.data, variance.data, weights.data}; - const_mkldnn_primitive_t outputs[] = {dst.get()}; - error::wrap_c_api( - mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a batch normalization forward primitive"); - reset(result); - } - - batch_normalization_forward(const primitive_desc &aprimitive_desc, - const primitive::at &src, - const primitive::at &mean, - const primitive::at &variance, - const memory &dst) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {src.data, mean.data, variance.data}; - const_mkldnn_primitive_t outputs[] = {dst.get()}; - error::wrap_c_api( - mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a batch normalization forward primitive"); - reset(result); - } - - /// @warning batch_normalization_forward has 2 constructors with very - /// similar signatures: - /// - (pd, src, weights, dst, mean, variance) // 2 in, 3 out - /// - (pd, src, dst, mean, variance, workspace) // 1 in, 4 out - /// The only way to distinguish between those is to explicitly - /// cast all input parameters to their type, i.e. to - /// const primitive:at &. - batch_normalization_forward(const primitive_desc &aprimitive_desc, - const primitive::at &src, - const primitive::at &weights, - const memory &dst, - const memory &mean, - const memory &variance) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {src.data, weights.data}; - const_mkldnn_primitive_t outputs[] = { - dst.get(), mean.get(), variance.get()}; - error::wrap_c_api( - mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a batch normalization forward primitive"); - reset(result); - } - - batch_normalization_forward(const primitive_desc &aprimitive_desc, - const primitive::at &src, - const primitive::at &weights, - const memory &dst, - const memory &mean, - const memory &variance, - const memory &workspace) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {src.data, weights.data}; - const_mkldnn_primitive_t outputs[] = { - dst.get(), mean.get(), variance.get(), workspace.get()}; - error::wrap_c_api( - mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a batch normalization forward primitive"); - reset(result); - } - - batch_normalization_forward(const primitive_desc &aprimitive_desc, - const primitive::at &src, - const memory &dst, - const memory &mean, - const memory &variance) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {src.data}; - const_mkldnn_primitive_t outputs[] = { - dst.get(), mean.get(), variance.get()}; - error::wrap_c_api( - mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a batch normalization forward primitive"); - reset(result); - } - - /// @warning batch_normalization_forward has 2 constructors with very - /// similar signatures: - /// - (pd, src, weights, dst, mean, variance) // 2 in, 3 out - /// - (pd, src, dst, mean, variance, workspace) // 1 in, 4 out - /// The only way to distinguish between those is to explicitly - /// cast all input parameters to their type, i.e. to - /// const primitive:at &. - /// @note to make users' experience a little bit better this constructor - /// checks if whether parameters match corresponding primitive - /// descriptor, and if they are not -- call the other (proper) - /// constructor. Yeah, this is still very ugly... - batch_normalization_forward(const primitive_desc &aprimitive_desc, - const primitive::at &src, - const memory &dst, - const memory &mean, - const memory &variance, - const memory &workspace) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[2] = {src.data}; - const_mkldnn_primitive_t outputs[4] = { - dst.get(), mean.get(), variance.get(), workspace.get()}; - - if (1) { // check whether this is the `wrong` constructor - const int n_inputs_expected = mkldnn_primitive_desc_query_s32( - aprimitive_desc.get(), mkldnn_query_num_of_inputs_s32, 0); - const int n_outputs_expected = mkldnn_primitive_desc_query_s32( - aprimitive_desc.get(), mkldnn_query_num_of_outputs_s32, 0); - if (n_inputs_expected == 2 && n_outputs_expected == 3) { - // shift parameters, get rid of workspace, and add weights... - auto _weights = dst; - inputs[1] = {_weights.get(), 0}; - - auto _dst = mean, _mean = variance, _variance = workspace; - outputs[0] = _dst.get(); - outputs[1] = _mean.get(); - outputs[2] = _variance.get(); - outputs[3] = nullptr; - } - } - error::wrap_c_api( - mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a batch normalization forward primitive"); - reset(result); - } - - batch_normalization_forward(const primitive_desc &aprimitive_desc, - const primitive::at &src, - const primitive::at &weights, - const memory &dst) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {src.data, weights.data}; - const_mkldnn_primitive_t outputs[] = {dst.get()}; - error::wrap_c_api( - mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a batch normalization forward primitive"); - reset(result); - } - - batch_normalization_forward(const primitive_desc &aprimitive_desc, - const primitive::at &src, - const memory &dst) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {src.data}; - const_mkldnn_primitive_t outputs[] = {dst.get()}; - error::wrap_c_api( - mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a batch normalization forward primitive"); - reset(result); - } -}; - -struct batch_normalization_backward : public primitive { - struct desc { - mkldnn_batch_normalization_desc_t data; - template - desc(prop_kind aprop_kind, - const memory::desc &diff_data_desc, - const memory::desc &data_desc, - T epsilon, - unsigned flags) { - error::wrap_c_api( - mkldnn_batch_normalization_backward_desc_init( - &data, - mkldnn::convert_to_c(aprop_kind), - &diff_data_desc.data, - &data_desc.data, - static_cast(epsilon), - flags), - "could not create a batch normalization backward descriptor"); - } - }; - - struct primitive_desc : public handle { - primitive_desc(const desc &adesc, - const engine &aengine, - const batch_normalization_forward::primitive_desc - &hint_fwd_primitive_desc) { - mkldnn_primitive_desc_t result; - error::wrap_c_api( - mkldnn_primitive_desc_create(&result, - &adesc.data, - aengine.get(), - hint_fwd_primitive_desc.get()), - "could not create a batch normalization backward primitive " - "descriptor"); - reset(result); - } - - memory::primitive_desc weights_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t bndesc; - const_mkldnn_primitive_desc_t const_bndesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(weights_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&bndesc, const_bndesc), - "could not clone a weights primitive descriptor"); - adesc.reset(bndesc); - return adesc; - } - - memory::primitive_desc diff_weights_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t bndesc; - const_mkldnn_primitive_desc_t const_bndesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(diff_weights_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&bndesc, const_bndesc), - "could not clone a diff_weights primitive descriptor"); - adesc.reset(bndesc); - return adesc; - } - - memory::primitive_desc mean_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t bndesc; - const_mkldnn_primitive_desc_t const_bndesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(src_pd), 1); - error::wrap_c_api(mkldnn_primitive_desc_clone(&bndesc, const_bndesc), - "could not clone a mean primitive descriptor"); - adesc.reset(bndesc); - return adesc; - } - - memory::primitive_desc variance_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t bndesc; - const_mkldnn_primitive_desc_t const_bndesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(src_pd), 2); - error::wrap_c_api(mkldnn_primitive_desc_clone(&bndesc, const_bndesc), - "could not clone a variance primitive descriptor"); - adesc.reset(bndesc); - return adesc; - } - - memory::primitive_desc workspace_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(workspace_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a workspace primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc dst_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(dst_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a dst primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - engine get_engine() { return engine::query(*this); } - }; - - // Prop_kind == backward - batch_normalization_backward(const primitive_desc &aprimitive_desc, - const primitive::at &src, - const primitive::at &mean, - const primitive::at &variance, - const primitive::at &diff_dst, - const primitive::at &weights, - const memory &diff_src, - const memory &diff_weights) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = { - src.data, mean.data, variance.data, diff_dst.data, weights.data}; - const_mkldnn_primitive_t outputs[] = {diff_src.get(), diff_weights.get()}; - error::wrap_c_api( - mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a batch normalization backward primitive"); - reset(result); - } - - // Prop_kind == backward (+ws) - batch_normalization_backward(const primitive_desc &aprimitive_desc, - const primitive::at &src, - const primitive::at &mean, - const primitive::at &variance, - const primitive::at &diff_dst, - const primitive::at &weights, - const primitive::at &workspace, - const memory &diff_src, - const memory &diff_weights) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {src.data, - mean.data, - variance.data, - diff_dst.data, - weights.data, - workspace.data}; - const_mkldnn_primitive_t outputs[] = {diff_src.get(), diff_weights.get()}; - error::wrap_c_api( - mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a batch normalization backward primitive"); - reset(result); - } - - // Prop_kind == backward_data (+ws or +weights) - /// @warning This constructor works for backward_data propagation - /// - w/ weights but w/o workspace, or - /// - w/ workspace but w/o weights - batch_normalization_backward(const primitive_desc &aprimitive_desc, - const primitive::at &src, - const primitive::at &mean, - const primitive::at &variance, - const primitive::at &diff_dst, - const primitive::at &weights_or_workspace, - const memory &diff_src) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {src.data, - mean.data, - variance.data, - diff_dst.data, - weights_or_workspace.data}; - const_mkldnn_primitive_t outputs[] = {diff_src.get()}; - error::wrap_c_api( - mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a batch normalization backward primitive"); - reset(result); - } - - // Prop_kind == backward_data - batch_normalization_backward(const primitive_desc &aprimitive_desc, - const primitive::at &src, - const primitive::at &mean, - const primitive::at &variance, - const primitive::at &diff_dst, - const memory &diff_src) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = { - src.data, mean.data, variance.data, diff_dst.data}; - const_mkldnn_primitive_t outputs[] = {diff_src.get()}; - error::wrap_c_api( - mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a batch normalization backward primitive"); - reset(result); - } -}; - -/// @} - -/// @addtogroup cpp_api_inner_product Inner Product -/// @{ - -struct inner_product_forward : public primitive { - struct desc { - mkldnn_inner_product_desc_t data; - desc(prop_kind aprop_kind, - const memory::desc &src_desc, - const memory::desc &weights_desc, - const memory::desc &bias_desc, - const memory::desc &dst_desc) { - error::wrap_c_api(mkldnn_inner_product_forward_desc_init( - &data, - mkldnn::convert_to_c(aprop_kind), - &src_desc.data, - &weights_desc.data, - &bias_desc.data, - &dst_desc.data), - "could not create a inner product forward descriptor"); - } - - desc(prop_kind aprop_kind, - const memory::desc &src_desc, - const memory::desc &weights_desc, - const memory::desc &dst_desc) { - error::wrap_c_api(mkldnn_inner_product_forward_desc_init( - &data, - mkldnn::convert_to_c(aprop_kind), - &src_desc.data, - &weights_desc.data, - nullptr, - &dst_desc.data), - "could not create a inner product forward descriptor"); - } - }; - - struct primitive_desc : public handle { - primitive_desc(const desc &adesc, const engine &aengine) { - mkldnn_primitive_desc_t result; - error::wrap_c_api( - mkldnn_primitive_desc_create( - &result, &adesc.data, aengine.get(), nullptr), - "could not create a inner product forward primitive descriptor"); - reset(result); - } - - primitive_desc(const desc &adesc, - const primitive_attr &aattr, - const engine &aengine) { - mkldnn_primitive_desc_t result; - error::wrap_c_api( - mkldnn_primitive_desc_create_v2( - &result, &adesc.data, aattr.get(), aengine.get(), nullptr), - "could not create a inner product " - "forward primitive descriptor"); - reset(result); - } - - memory::primitive_desc src_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(src_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a src primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc weights_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(weights_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a weights primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc bias_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(weights_pd), 1); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a bias primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc dst_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(dst_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a dst primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - engine get_engine() { return engine::query(*this); } - }; - - inner_product_forward(const primitive_desc &aprimitive_desc, - const primitive::at &src, - const primitive::at weights, - const primitive::at &bias, - const memory &dst) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {src.data, weights.data, bias.data}; - const_mkldnn_primitive_t outputs[] = {dst.get()}; - error::wrap_c_api(mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a inner product forward primitive"); - reset(result); - } - - inner_product_forward(const primitive_desc &aprimitive_desc, - const primitive::at &src, - const primitive::at weights, - const memory &dst) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {src.data, weights.data}; - const_mkldnn_primitive_t outputs[] = {dst.get()}; - error::wrap_c_api(mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a inner product forward primitive"); - reset(result); - } -}; - -struct inner_product_backward_data : public primitive { - struct desc { - mkldnn_inner_product_desc_t data; - desc(const memory::desc &diff_src_desc, - const memory::desc &weights_desc, - const memory::desc &diff_dst_desc) { - error::wrap_c_api( - mkldnn_inner_product_backward_data_desc_init(&data, - &diff_src_desc.data, - &weights_desc.data, - &diff_dst_desc.data), - "could not create a inner product backward data descriptor"); - } - }; - - struct primitive_desc : public handle { - primitive_desc( - const desc &adesc, - const engine &aengine, - const inner_product_forward::primitive_desc &hint_fwd_primitive_desc) { - mkldnn_primitive_desc_t result; - error::wrap_c_api( - mkldnn_primitive_desc_create(&result, - &adesc.data, - aengine.get(), - hint_fwd_primitive_desc.get()), - "could not create a inner product backward data primitive " - "descriptor"); - reset(result); - } - - memory::primitive_desc diff_dst_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(diff_dst_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a diff dst primititve descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc weights_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(weights_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a weights primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc diff_src_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(diff_src_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a diff src primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - engine get_engine() { return engine::query(*this); } - }; - - inner_product_backward_data(const primitive_desc &aprimitive_desc, - const primitive::at &diff_dst, - const primitive::at weights, - const memory &diff_src) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {diff_dst.data, weights.data}; - const_mkldnn_primitive_t outputs[] = {diff_src.get()}; - error::wrap_c_api( - mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a inner product backward data primitive"); - reset(result); - } -}; - -struct inner_product_backward_weights : public primitive { - struct desc { - mkldnn_inner_product_desc_t data; - desc(const memory::desc &src_desc, - const memory::desc &diff_weights_desc, - const memory::desc &diff_bias_desc, - const memory::desc &diff_dst_desc) { - error::wrap_c_api( - mkldnn_inner_product_backward_weights_desc_init( - &data, - &src_desc.data, - &diff_weights_desc.data, - &diff_bias_desc.data, - &diff_dst_desc.data), - "could not create a inner product backward weights descriptor"); - } - desc(const memory::desc &src_desc, - const memory::desc &diff_weights_desc, - const memory::desc &diff_dst_desc) { - error::wrap_c_api( - mkldnn_inner_product_backward_weights_desc_init( - &data, - &src_desc.data, - &diff_weights_desc.data, - nullptr, - &diff_dst_desc.data), - "could not create a inner product backward weights descriptor"); - } - }; - - struct primitive_desc : public handle { - primitive_desc( - const desc &adesc, - const engine &aengine, - const inner_product_forward::primitive_desc &hint_fwd_primitive_desc) { - mkldnn_primitive_desc_t result; - error::wrap_c_api( - mkldnn_primitive_desc_create(&result, - &adesc.data, - aengine.get(), - hint_fwd_primitive_desc.get()), - "could not create a inner product backward weights primitive " - "descriptor"); - reset(result); - } - - memory::primitive_desc diff_dst_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(diff_dst_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a diff dst primititve descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc diff_weights_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(diff_weights_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a diff weights primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc diff_bias_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(diff_weights_pd), 1); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a diff bias primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc src_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(src_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a src primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - engine get_engine() { return engine::query(*this); } - }; - - inner_product_backward_weights(const primitive_desc &aprimitive_desc, - const primitive::at &src, - const primitive::at diff_dst, - const memory &diff_weights) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data}; - const_mkldnn_primitive_t outputs[] = {diff_weights.get()}; - error::wrap_c_api( - mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a inner product backward weights primitive"); - reset(result); - } - - inner_product_backward_weights(const primitive_desc &aprimitive_desc, - const primitive::at &src, - const primitive::at diff_dst, - const memory &diff_weights, - const memory &diff_bias) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data}; - const_mkldnn_primitive_t outputs[] = {diff_weights.get(), diff_bias.get()}; - error::wrap_c_api( - mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create a inner product backward weights primitive"); - reset(result); - } -}; - -/// @} - -/// @addtogroup cpp_api_rnn RNN -/// @{ - -struct rnn_cell { - struct desc { - mkldnn_rnn_cell_desc_t c_rnn_cell_; - - desc(algorithm kind, algorithm activation_f) { - error::wrap_c_api( - mkldnn_rnn_cell_desc_init(&c_rnn_cell_, - mkldnn::convert_to_c(kind), - mkldnn::convert_to_c(activation_f), - 0U, - 0, - 0), - "could not init an rnn cell descriptor"); - } - desc(algorithm kind) : desc(kind, algorithm::algorithm_undef) {} - - operator const mkldnn_rnn_cell_desc_t *() const { return &c_rnn_cell_; } - - algorithm get_cell_kind() const { return algorithm(c_rnn_cell_.cell_kind); } - algorithm get_activation() const { - return algorithm(c_rnn_cell_.activation_kind); - } - - float get_alpha() const { return c_rnn_cell_.alpha; } - void set_alpha(float alpha) { - c_rnn_cell_.flags |= mkldnn_rnn_cell_with_relu; - c_rnn_cell_.alpha = alpha; - } - - float get_clipping() const { return c_rnn_cell_.clipping; } - void set_clipping(float clipping) { - c_rnn_cell_.flags |= mkldnn_rnn_cell_with_clipping; - c_rnn_cell_.clipping = clipping; - } - - int get_gates_count() const { - return mkldnn_rnn_cell_get_gates_count(&c_rnn_cell_); - } - int get_state_count() const { - return mkldnn_rnn_cell_get_states_count(&c_rnn_cell_); - } - }; -}; - -struct rnn_forward : public primitive { - struct desc { - mkldnn_rnn_desc_t data; - desc(prop_kind aprop_kind, - rnn_cell::desc cell, - const rnn_direction direction, - const memory::desc &src_layer_desc, - const memory::desc &src_iter_desc, - const memory::desc &weights_layer_desc, - const memory::desc &weights_iter_desc, - const memory::desc &bias_desc, - const memory::desc &dst_layer_desc, - const memory::desc &dst_iter_desc) { - error::wrap_c_api( - mkldnn_rnn_forward_desc_init(&data, - mkldnn::convert_to_c(aprop_kind), - cell, - mkldnn::convert_to_c(direction), - &src_layer_desc.data, - &src_iter_desc.data, - &weights_layer_desc.data, - &weights_iter_desc.data, - &bias_desc.data, - &dst_layer_desc.data, - &dst_iter_desc.data), - "could not create an RNN forward descriptor"); - } - }; - struct primitive_desc : public handle { - primitive_desc(const desc &adesc, const engine &aengine) { - mkldnn_primitive_desc_t result; - error::wrap_c_api(mkldnn_primitive_desc_create( - &result, &adesc.data, aengine.get(), nullptr), - "could not create an RNN forward primitive descriptor"); - reset(result); - } - - memory::primitive_desc src_layer_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(src_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone an src layer primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc src_iter_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(src_pd), 1); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a src iter primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc weights_layer_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(weights_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a weights primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc weights_src_iter_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(weights_pd), 1); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a weights primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc bias_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(weights_pd), 2); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a bias primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc workspace_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t ldesc; - const_mkldnn_primitive_desc_t const_ldesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(workspace_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&ldesc, const_ldesc), - "could not clone a workspace primitive descriptor"); - adesc.reset(ldesc); - return adesc; - } - - memory::primitive_desc dst_layer_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(dst_pd), 0); - error::wrap_c_api( - mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a dst last layer primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc dst_iter_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(dst_pd), 1); - error::wrap_c_api( - mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a dst last iteration primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - engine get_engine() { return engine::query(*this); } - }; - - rnn_forward(const primitive_desc &aprimitive_desc, - const primitive::at &src_layer, - const primitive::at &src_iter, - const primitive::at &weights_layer, - const primitive::at &weights_iter, - const primitive::at &bias, - const memory &dst_layer, - const memory &dst_iter, - const memory &workspace) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[5]; - const_mkldnn_primitive_t outputs[3]; - int idx = 0; - inputs[idx++] = src_layer.data; - if (!is_null_memory(src_iter.data.primitive)) inputs[idx++] = src_iter.data; - inputs[idx++] = weights_layer.data; - inputs[idx++] = weights_iter.data; - if (!is_null_memory(bias.data.primitive)) inputs[idx++] = bias.data; - - idx = 0; - outputs[idx++] = dst_layer.get(); - if (!is_null_memory(dst_iter.get())) outputs[idx++] = dst_iter.get(); - if (!is_null_memory(workspace.get())) outputs[idx++] = workspace.get(); - - error::wrap_c_api(mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create an RNN forward primitive"); - reset(result); - } -}; - -struct rnn_backward : public primitive { - struct desc { - mkldnn_rnn_desc_t data; - desc(prop_kind aprop_kind, - rnn_cell::desc cell, - const rnn_direction direction, - const memory::desc &src_layer_desc, - const memory::desc &src_iter_desc, - const memory::desc &weights_layer_desc, - const memory::desc &weights_iter_desc, - const memory::desc &bias_desc, - const memory::desc &dst_layer_desc, - const memory::desc &dst_iter_desc, - const memory::desc &diff_src_layer_desc, - const memory::desc &diff_src_iter_desc, - const memory::desc &diff_weights_layer_desc, - const memory::desc &diff_weights_iter_desc, - const memory::desc &diff_bias_desc, - const memory::desc &diff_dst_layer_desc, - const memory::desc &diff_dst_iter_desc) { - error::wrap_c_api( - mkldnn_rnn_backward_desc_init(&data, - mkldnn::convert_to_c(aprop_kind), - cell, - mkldnn::convert_to_c(direction), - &src_layer_desc.data, - &src_iter_desc.data, - &weights_layer_desc.data, - &weights_iter_desc.data, - &bias_desc.data, - &dst_layer_desc.data, - &dst_iter_desc.data, - &diff_src_layer_desc.data, - &diff_src_iter_desc.data, - &diff_weights_layer_desc.data, - &diff_weights_iter_desc.data, - &diff_bias_desc.data, - &diff_dst_layer_desc.data, - &diff_dst_iter_desc.data), - "could not create an RNN backward descriptor"); - } - }; - struct primitive_desc : public handle { - primitive_desc(const desc &adesc, const engine &aengine) { - mkldnn_primitive_desc_t result; - error::wrap_c_api( - mkldnn_primitive_desc_create( - &result, &adesc.data, aengine.get(), nullptr), - "could not create an RNN backward primitive descriptor"); - reset(result); - } - - memory::primitive_desc src_layer_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(src_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone an src layer primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc src_iter_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(src_pd), 1); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a src iter primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc weights_layer_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(weights_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a weights primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc weights_iter_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(weights_pd), 1); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a weights primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc bias_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(weights_pd), 2); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a bias primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc dst_layer_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(dst_pd), 0); - error::wrap_c_api( - mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a dst last layer primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc dst_iter_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(dst_pd), 1); - error::wrap_c_api( - mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a dst last iteration primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc diff_src_layer_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(diff_src_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone an src_layer primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc diff_src_iter_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(diff_src_pd), 1); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a src iter primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc diff_weights_layer_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(diff_weights_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a weights primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc diff_weights_iter_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(diff_weights_pd), 1); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a weights primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc diff_bias_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(diff_weights_pd), 2); - error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a bias primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc diff_dst_layer_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(diff_dst_pd), 0); - error::wrap_c_api( - mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a dst last layer primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc diff_dst_iter_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t cdesc; - const_mkldnn_primitive_desc_t const_cdesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(diff_dst_pd), 1); - error::wrap_c_api( - mkldnn_primitive_desc_clone(&cdesc, const_cdesc), - "could not clone a dst last iteration primitive descriptor"); - adesc.reset(cdesc); - return adesc; - } - - memory::primitive_desc workspace_primitive_desc() const { - memory::primitive_desc adesc; - mkldnn_primitive_desc_t ldesc; - const_mkldnn_primitive_desc_t const_ldesc = - mkldnn_primitive_desc_query_pd( - get(), mkldnn::convert_to_c(workspace_pd), 0); - error::wrap_c_api(mkldnn_primitive_desc_clone(&ldesc, const_ldesc), - "could not clone a workspace primitive descriptor"); - adesc.reset(ldesc); - return adesc; - } - - engine get_engine() { return engine::query(*this); } - }; - // With last iteration (with and without input src_iter) - rnn_backward(const primitive_desc &aprimitive_desc, - const primitive::at &src_layer, - const primitive::at &src_iter, - const primitive::at &weights_layer, - const primitive::at &weights_iter, - const primitive::at &bias, - const primitive::at &dst_layer, - const primitive::at &dst_iter, - const memory &diff_src_layer, - const memory &diff_src_iter, - const memory &diff_weights_layer, - const memory &diff_weights_iter, - const memory &diff_bias, - const primitive::at &diff_dst_layer, - const primitive::at &diff_dst_iter, - const primitive::at &workspace) { - mkldnn_primitive_t result; - mkldnn_primitive_at_t inputs[10]; - const_mkldnn_primitive_t outputs[5]; - int idx = 0; - inputs[idx] = src_layer.data; - if (!is_null_memory(src_iter.data.primitive)) inputs[idx++] = src_iter.data; - inputs[idx++] = weights_layer.data; - inputs[idx++] = weights_iter.data; - if (!is_null_memory(bias.data.primitive)) inputs[idx++] = bias.data; - inputs[idx] = dst_layer.data; - if (!is_null_memory(dst_iter.data.primitive)) inputs[idx++] = dst_iter.data; - inputs[idx] = diff_dst_layer.data; - if (!is_null_memory(diff_dst_iter.data.primitive)) - inputs[idx++] = diff_dst_iter.data; - inputs[idx] = workspace.data; - - idx = 0; - outputs[idx] = diff_src_layer.get(); - if (!is_null_memory(diff_src_iter.get())) - outputs[idx++] = diff_src_iter.get(); - outputs[idx] = diff_weights_layer.get(); - outputs[idx] = diff_weights_iter.get(); - if (!is_null_memory(diff_bias.get())) outputs[idx] = diff_bias.get(); - error::wrap_c_api(mkldnn_primitive_create( - &result, aprimitive_desc.get(), inputs, outputs), - "could not create an RNN backward primitive"); - reset(result); - } -}; - -/// @} -/// @} Primitives - -/// @addtogroup cpp_api_stream Stream -/// @{ - -#ifndef DOXYGEN_SHOULD_SKIP_THIS -template <> -struct handle_traits { - static constexpr auto destructor = &mkldnn_stream_destroy; -}; -#endif - -struct stream : public handle { - using handle::handle; - - enum kind { - any = mkldnn_stream_kind_t::mkldnn_any_stream, - eager = mkldnn_stream_kind_t::mkldnn_eager, - lazy = mkldnn_stream_kind_t::mkldnn_lazy - }; - - static mkldnn_stream_kind_t convert_to_c(kind akind) { - return static_cast(akind); - } - /// Constructs a stream. - stream(kind akind) { - mkldnn_stream_t astream; - error::wrap_c_api(mkldnn_stream_create(&astream, convert_to_c(akind)), - "could not create a stream"); - reset(astream); - } - - /// Submits a vector of primitives to a stream for computations. - /// - /// @param primitives The vector of primitives to submit. - /// @returns The stream. - stream &submit(std::vector primitives) { - // TODO: find a proper way to convert vector to - // vector - if (primitives.size() == 0) return *this; - std::vector c_api_primitives; - c_api_primitives.reserve(primitives.size()); - auto convert_to_c = [](primitive p) { return p.get(); }; - std::transform(primitives.begin(), - primitives.end(), - std::back_inserter(c_api_primitives), - convert_to_c); - - mkldnn_primitive_t c_api_error_primitive; - error::wrap_c_api(mkldnn_stream_submit(get(), - c_api_primitives.size(), - &c_api_primitives[0], - &c_api_error_primitive), - "could not submit primitives to a stream", - &c_api_error_primitive); - - return *this; - } - - /// Waits for all computations submitted to the stream to complete. - /// - /// @param block Specifies whether the operation should wait indefinitely or - /// return - /// immediately. - /// @returns @c true if all computations completed. - /// @returns @c false if not all computations completed. - bool wait(bool block = true) { - mkldnn_primitive_t c_api_error_primitive; - mkldnn_status_t status = - mkldnn_stream_wait(get(), block, &c_api_error_primitive); - if (status != mkldnn_success && status != mkldnn_try_again) - error::wrap_c_api( - status, "could not wait on a stream", &c_api_error_primitive); - return (status == mkldnn_success); - } - - stream &rerun() { - mkldnn_primitive_t c_api_error_primitive; - error::wrap_c_api(mkldnn_stream_rerun(get(), &c_api_error_primitive), - "could not rerun a stream", - &c_api_error_primitive); - return *this; - } -}; - -/// @} - -/// @} C++ API - -} // namespace mkldnn - -#endif From 3d1953d855787f56e88406b69f6d6e90eb2bc533 Mon Sep 17 00:00:00 2001 From: chengduoZH Date: Thu, 17 May 2018 13:43:13 +0800 Subject: [PATCH 06/31] fix timeline --- tools/timeline.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tools/timeline.py b/tools/timeline.py index 8cd6353d46..b413bb6fe0 100644 --- a/tools/timeline.py +++ b/tools/timeline.py @@ -171,7 +171,7 @@ if args.timeline_path: profile_paths = profile_path.split(',') profile_dict = dict() -if len(profile_path) == 1: +if len(profile_paths) == 1: with open(profile_path, 'r') as f: profile_s = f.read() profile_pb = profiler_pb2.Profile() From e8d24aa144b1f68436e98f4b343aa9d975e67717 Mon Sep 17 00:00:00 2001 From: qiaolongfei Date: Thu, 17 May 2018 15:13:17 +0800 Subject: [PATCH 07/31] Inferencer support parallel_executor --- python/paddle/fluid/inferencer.py | 12 ++++++++++-- python/paddle/fluid/trainer.py | 12 ++++++------ 2 files changed, 16 insertions(+), 8 deletions(-) diff --git a/python/paddle/fluid/inferencer.py b/python/paddle/fluid/inferencer.py index 56c008d1af..8c6dbd3b5a 100644 --- a/python/paddle/fluid/inferencer.py +++ b/python/paddle/fluid/inferencer.py @@ -17,6 +17,7 @@ import core import executor import framework import io +import parallel_executor import unique_name from trainer import check_and_get_place @@ -24,7 +25,7 @@ __all__ = ['Inferencer', ] class Inferencer(object): - def __init__(self, infer_func, param_path, place=None): + def __init__(self, infer_func, param_path, place=None, parallel=False): """ :param infer_func: a function that will return predict Variable :param param_path: the path where the inference model is saved by fluid.io.save_params @@ -32,13 +33,20 @@ class Inferencer(object): """ self.param_path = param_path self.scope = core.Scope() + self.parallel = parallel + self.place = check_and_get_place(place) self.inference_program = framework.Program() with framework.program_guard(self.inference_program): with unique_name.guard(): self.predict_var = infer_func() - self.exe = executor.Executor(check_and_get_place(place)) + if parallel: + self.exe = parallel_executor.ParallelExecutor( + use_cuda=isinstance(self.place, core.CUDAPlace), + loss_name=self.predict_var.name) + else: + self.exe = executor.Executor(self.place) with executor.scope_guard(self.scope): # load params from param_path into scope io.load_params(self.exe, param_path, self.inference_program) diff --git a/python/paddle/fluid/trainer.py b/python/paddle/fluid/trainer.py index d158d58632..f4292208c9 100644 --- a/python/paddle/fluid/trainer.py +++ b/python/paddle/fluid/trainer.py @@ -12,18 +12,18 @@ # See the License for the specific language governing permissions and # limitations under the License. +import contextlib import os + import core -import framework -import executor + import data_feeder -import contextlib +import executor +import framework import io -import unique_name -import parallel_executor - # optimizer is same as the parameter of Trainer.__init__. Rename it to opt_module import optimizer as opt_module +import parallel_executor from transpiler import distribute_transpiler __all__ = [ From 57734901d91532248e1c1f87e1d4585c9719cbc7 Mon Sep 17 00:00:00 2001 From: Yancey1989 Date: Thu, 17 May 2018 16:48:54 +0800 Subject: [PATCH 08/31] use cdn to speed up thirdparty package download --- cmake/external/boost.cmake | 2 +- cmake/external/mklml.cmake | 2 +- paddle/scripts/paddle_build.sh | 1 - 3 files changed, 2 insertions(+), 3 deletions(-) diff --git a/cmake/external/boost.cmake b/cmake/external/boost.cmake index 10662fc967..499682f644 100644 --- a/cmake/external/boost.cmake +++ b/cmake/external/boost.cmake @@ -24,7 +24,7 @@ set(BOOST_PROJECT "extern_boost") # So we use 1.41.0 here. set(BOOST_VER "1.41.0") set(BOOST_TAR "boost_1_41_0") -set(BOOST_URL "http://paddlepaddledeps.bj.bcebos.com/${BOOST_TAR}.tar.gz") +set(BOOST_URL "http://paddlepaddledeps.cdn.bcebos.com/${BOOST_TAR}.tar.gz") set(BOOST_SOURCES_DIR ${THIRD_PARTY_PATH}/boost) set(BOOST_DOWNLOAD_DIR "${BOOST_SOURCES_DIR}/src/${BOOST_PROJECT}") set(BOOST_INCLUDE_DIR "${BOOST_DOWNLOAD_DIR}/${BOOST_TAR}" CACHE PATH "boost include directory." FORCE) diff --git a/cmake/external/mklml.cmake b/cmake/external/mklml.cmake index cebde27504..e9a37b52e6 100644 --- a/cmake/external/mklml.cmake +++ b/cmake/external/mklml.cmake @@ -28,7 +28,7 @@ INCLUDE(ExternalProject) SET(MKLML_PROJECT "extern_mklml") SET(MKLML_VER "mklml_lnx_2018.0.3.20180406") -SET(MKLML_URL "http://paddlepaddledeps.bj.bcebos.com/${MKLML_VER}.tgz") +SET(MKLML_URL "http://paddlepaddledeps.cdn.bcebos.com/${MKLML_VER}.tgz") SET(MKLML_SOURCE_DIR "${THIRD_PARTY_PATH}/mklml") SET(MKLML_DOWNLOAD_DIR "${MKLML_SOURCE_DIR}/src/${MKLML_PROJECT}") SET(MKLML_DST_DIR "mklml") diff --git a/paddle/scripts/paddle_build.sh b/paddle/scripts/paddle_build.sh index 58a30ab3e5..e5af42ed57 100755 --- a/paddle/scripts/paddle_build.sh +++ b/paddle/scripts/paddle_build.sh @@ -95,7 +95,6 @@ function cmake_gen() { -DWITH_AVX=${WITH_AVX:-OFF} -DWITH_GOLANG=${WITH_GOLANG:-OFF} -DCUDA_ARCH_NAME=${CUDA_ARCH_NAME:-All} - -DWITH_SWIG_PY=ON -DWITH_C_API=${WITH_C_API:-OFF} -DWITH_PYTHON=${WITH_PYTHON:-ON} -DWITH_SWIG_PY=${WITH_SWIG_PY:-ON} From 5f1333058cad70fb242eb32c115c540f4480ea4b Mon Sep 17 00:00:00 2001 From: Jacek Czaja Date: Mon, 14 May 2018 16:57:33 +0200 Subject: [PATCH 09/31] - Draft of reuse of pooling mkldnn operator - Finished draft of pooling reusing of operators - Using gethash in PoolGrad added - Removed diagnostic - Added pool mkldnn grad reusing of primitives - Added diagnostic - Removed diagnostic - added dependency to mkldnn data type for pooling mkldnn - Added mkldnn memory data type determining based on template type of op - Compilation warning fix - codying style fixes --- paddle/fluid/operators/pool_mkldnn_op.cc | 229 +++++++++++++++-------- paddle/fluid/platform/mkldnn_helper.h | 10 + 2 files changed, 163 insertions(+), 76 deletions(-) diff --git a/paddle/fluid/operators/pool_mkldnn_op.cc b/paddle/fluid/operators/pool_mkldnn_op.cc index 63eaaedcd5..60e936298d 100644 --- a/paddle/fluid/operators/pool_mkldnn_op.cc +++ b/paddle/fluid/operators/pool_mkldnn_op.cc @@ -18,6 +18,26 @@ limitations under the License. */ namespace paddle { namespace operators { +using mkldnn::memory; // Note: paddle has also "memory" namespace +using mkldnn::pooling_forward; +using mkldnn::pooling_backward; + +// Generate keys for storing/retriving primitives for this operator +// TODO(jczaja): Make hashing function more optimial +static std::string gethash(memory::dims& input_dims, std::string& pooling_type, + std::vector& ksize, std::vector& strides, + std::vector& paddings, std::string suffix) { + auto dims2str = [](memory::dims& operand_dims) { + std::string dstr = ""; + for (size_t i = 0; i < operand_dims.size(); ++i) { + dstr += std::to_string(operand_dims[i]) + "-"; + } + return dstr; + }; + return dims2str(input_dims) + dims2str(ksize) + dims2str(strides) + + dims2str(paddings) + pooling_type + suffix; +} + template class PoolMKLDNNOpKernel : public paddle::framework::OpKernel { public: @@ -34,10 +54,6 @@ class PoolMKLDNNOpKernel : public paddle::framework::OpKernel { // Get an unique name from "argument" name of "Out" variable // This name will be used as key when saving info into device context - const std::string key = ctx.op().Output("Out"); - const std::string key_pool_pd = key + "@pool_pd"; - const std::string key_pool_workspace_memory = - key + "@pool_workspace_memory"; std::string pooling_type = ctx.Attr("pooling_type"); std::vector ksize = ctx.Attr>("ksize"); @@ -63,37 +79,71 @@ class PoolMKLDNNOpKernel : public paddle::framework::OpKernel { std::vector src_tz = paddle::framework::vectorize2int(input->dims()); std::vector dst_tz = paddle::framework::vectorize2int(output->dims()); - // TODO(pzelazko-intel): support more formats - auto src_md = platform::MKLDNNMemDesc(src_tz, mkldnn::memory::f32, - mkldnn::memory::format::nchw); - auto dst_md = platform::MKLDNNMemDesc(dst_tz, mkldnn::memory::f32, - mkldnn::memory::format::nchw); - - std::shared_ptr pool_pd = - CreatePrimitiveDesc(src_md, dst_md, strides, paddings, ksize, - pooling_type, mkldnn_engine); - - // save pool_pd into global device context to be referred in backward path - dev_ctx.SetBlob(key_pool_pd, pool_pd); - - std::shared_ptr workspace_memory = - CreateWorkspaceMemory(pool_pd, pooling_type, mkldnn_engine); - - // save pool_workspace_memory to be referred in backward path - dev_ctx.SetBlob(key_pool_workspace_memory, workspace_memory); - - auto src_memory = - mkldnn::memory({src_md, mkldnn_engine}, - static_cast(const_cast(input_data))); - auto dst_memory = - mkldnn::memory({dst_md, mkldnn_engine}, - static_cast(const_cast(output_data))); + const std::string key = gethash(src_tz, pooling_type, ksize, strides, + paddings, ctx.op().Output("Out")); + const std::string key_pool_p = key + "@pool_p"; + const std::string key_pool_pd = key + "@pool_pd"; + const std::string key_pool_src_mem_p = key + "@pool_src_mem_p"; + const std::string key_pool_dst_mem_p = key + "@pool_dst_mem_p"; + const std::string key_pool_workspace_memory = + key + "@pool_workspace_memory"; - auto pool_prim = mkldnn::pooling_forward(*pool_pd, src_memory, dst_memory, - *workspace_memory); + auto pool_p = + std::static_pointer_cast(dev_ctx.GetBlob(key_pool_p)); + if (pool_p == nullptr) { + // TODO(pzelazko-intel): support more formats + + auto src_md = + platform::MKLDNNMemDesc(src_tz, platform::MKLDNNGetDataType(), + mkldnn::memory::format::nchw); + auto dst_md = + platform::MKLDNNMemDesc(dst_tz, platform::MKLDNNGetDataType(), + mkldnn::memory::format::nchw); + + std::shared_ptr pool_pd = + CreatePrimitiveDesc(src_md, dst_md, strides, paddings, ksize, + pooling_type, mkldnn_engine); + + // save pool_pd into global device context to be referred in backward path + dev_ctx.SetBlob(key_pool_pd, pool_pd); + + std::shared_ptr workspace_memory = + CreateWorkspaceMemory(pool_pd, pooling_type, mkldnn_engine); + + // save pool_workspace_memory to be referred in backward path + dev_ctx.SetBlob(key_pool_workspace_memory, workspace_memory); + + auto pool_src_memory_p = std::make_shared( + memory::primitive_desc{src_md, mkldnn_engine}, + static_cast(const_cast(input_data))); + dev_ctx.SetBlob(key_pool_src_mem_p, pool_src_memory_p); + + auto pool_dst_memory_p = std::make_shared( + memory::primitive_desc{dst_md, mkldnn_engine}, + static_cast(output_data)); + dev_ctx.SetBlob(key_pool_dst_mem_p, pool_dst_memory_p); + + pool_p = std::make_shared( + *pool_pd, *(pool_src_memory_p.get()), *(pool_dst_memory_p.get()), + *workspace_memory); + dev_ctx.SetBlob(key_pool_p, pool_p); + } else { + // Primitives already exist + auto pool_src_memory_p = + std::static_pointer_cast(dev_ctx.GetBlob(key_pool_src_mem_p)); + PADDLE_ENFORCE(pool_src_memory_p != nullptr, + "Fail to find pooling src mem_p in device context"); + auto pool_dst_memory_p = + std::static_pointer_cast(dev_ctx.GetBlob(key_pool_dst_mem_p)); + PADDLE_ENFORCE(pool_dst_memory_p != nullptr, + "Fail to find pooling dst mem_p in device context"); + pool_src_memory_p->set_data_handle( + reinterpret_cast(const_cast(input_data))); + pool_dst_memory_p->set_data_handle(output_data); + } // push primitive to stream and wait until it's executed - std::vector pipeline{pool_prim}; + std::vector pipeline{*(pool_p.get())}; mkldnn::stream(mkldnn::stream::kind::eager).submit(pipeline).wait(); } @@ -120,9 +170,10 @@ class PoolMKLDNNOpKernel : public paddle::framework::OpKernel { mkldnn::memory::primitive_desc workspace_md = pooling_type == "max" ? pool_pd->workspace_primitive_desc() - : mkldnn::memory::primitive_desc( - {{}, mkldnn::memory::f32, mkldnn::memory::format::nchw}, - engine); + : mkldnn::memory::primitive_desc({{}, + platform::MKLDNNGetDataType(), + mkldnn::memory::format::nchw}, + engine); auto p_workspace_memory = new mkldnn::memory(workspace_md); return std::unique_ptr(p_workspace_memory); @@ -140,13 +191,6 @@ class PoolMKLDNNGradOpKernel : public paddle::framework::OpKernel { const Tensor* out_grad = ctx.Input(framework::GradVarName("Out")); Tensor* in_x_grad = ctx.Output(framework::GradVarName("X")); - // Get an unique name from "argument" name of "Out" variable - // This name will be used as key when referring info from device context - const std::string key = ctx.op().Input("Out"); - const std::string key_pool_pd = key + "@pool_pd"; - const std::string key_pool_workspace_memory = - key + "@pool_workspace_memory"; - std::string pooling_type = ctx.Attr("pooling_type"); std::vector ksize = ctx.Attr>("ksize"); std::vector strides = ctx.Attr>("strides"); @@ -171,43 +215,76 @@ class PoolMKLDNNGradOpKernel : public paddle::framework::OpKernel { std::vector diff_dst_tz = paddle::framework::vectorize2int(out_grad->dims()); - auto diff_src_md = platform::MKLDNNMemDesc(diff_src_tz, mkldnn::memory::f32, - mkldnn::memory::format::nchw); - auto diff_dst_md = platform::MKLDNNMemDesc(diff_dst_tz, mkldnn::memory::f32, - mkldnn::memory::format::nchw); - - // Retrieve pool_pd/pool_workspace_memory from device context - auto pool_pd = - std::static_pointer_cast( - dev_ctx.GetBlob(key_pool_pd)); - PADDLE_ENFORCE(pool_pd != nullptr, - "Fail to find pool_pd in device context"); - - auto workspace_memory = std::static_pointer_cast( - dev_ctx.GetBlob(key_pool_workspace_memory)); - PADDLE_ENFORCE(workspace_memory != nullptr, - "Fail to find workspace_memory in device context"); - - auto pool_bwd_desc = mkldnn::pooling_backward::desc( - pooling_type == "max" ? mkldnn::algorithm::pooling_max - : mkldnn::algorithm::pooling_avg, - diff_src_md, diff_dst_md, strides, ksize, paddings, paddings, - mkldnn::padding_kind::zero); - auto pool_bwd_pd = mkldnn::pooling_backward::primitive_desc( - pool_bwd_desc, mkldnn_engine, *pool_pd); - - auto diff_src_memory = - mkldnn::memory({diff_src_md, mkldnn_engine}, - static_cast(const_cast(in_x_grad_data))); - auto diff_dst_memory = - mkldnn::memory({diff_dst_md, mkldnn_engine}, - static_cast(const_cast(out_grad_data))); + // Get an unique name from "argument" name of "Out" variable + // This name will be used as key when referring info from device context + const std::string key = gethash(diff_src_tz, pooling_type, ksize, strides, + paddings, ctx.op().Input("Out")); + const std::string key_pool_bwd_p = key + "@pool_bwd_p"; + const std::string key_pool_diff_src_mem_p = key + "@pool_diff_src_mem_p"; + const std::string key_pool_diff_dst_mem_p = key + "@pool_diff_dst_mem_p"; + const std::string key_pool_pd = key + "@pool_pd"; + const std::string key_pool_workspace_memory = + key + "@pool_workspace_memory"; - auto bwd_prim = mkldnn::pooling_backward( - pool_bwd_pd, diff_dst_memory, *workspace_memory, diff_src_memory); + auto pool_bwd_p = std::static_pointer_cast( + dev_ctx.GetBlob(key_pool_bwd_p)); + if (pool_bwd_p == nullptr) { + auto diff_src_md = + platform::MKLDNNMemDesc(diff_src_tz, platform::MKLDNNGetDataType(), + mkldnn::memory::format::nchw); + auto diff_dst_md = + platform::MKLDNNMemDesc(diff_dst_tz, platform::MKLDNNGetDataType(), + mkldnn::memory::format::nchw); + // Retrieve pool_pd/pool_workspace_memory from device context + auto pool_pd = + std::static_pointer_cast( + dev_ctx.GetBlob(key_pool_pd)); + PADDLE_ENFORCE(pool_pd != nullptr, + "Fail to find pool_pd in device context"); + + auto workspace_memory = std::static_pointer_cast( + dev_ctx.GetBlob(key_pool_workspace_memory)); + PADDLE_ENFORCE(workspace_memory != nullptr, + "Fail to find workspace_memory in device context"); + + auto pool_diff_src_memory_p = std::make_shared(memory( + {diff_src_md, mkldnn_engine}, static_cast(in_x_grad_data))); + dev_ctx.SetBlob(key_pool_diff_src_mem_p, pool_diff_src_memory_p); + + auto pool_diff_dst_memory_p = std::make_shared( + memory({diff_dst_md, mkldnn_engine}, + static_cast(const_cast(out_grad_data)))); + dev_ctx.SetBlob(key_pool_diff_dst_mem_p, pool_diff_dst_memory_p); + + auto pool_bwd_desc = mkldnn::pooling_backward::desc( + pooling_type == "max" ? mkldnn::algorithm::pooling_max + : mkldnn::algorithm::pooling_avg, + diff_src_md, diff_dst_md, strides, ksize, paddings, paddings, + mkldnn::padding_kind::zero); + auto pool_bwd_pd = mkldnn::pooling_backward::primitive_desc( + pool_bwd_desc, mkldnn_engine, *pool_pd); + + pool_bwd_p = std::make_shared( + pool_bwd_pd, *(pool_diff_dst_memory_p.get()), *workspace_memory, + *(pool_diff_src_memory_p)); + dev_ctx.SetBlob(key_pool_bwd_p, pool_bwd_p); + } else { + // Primitives already exist + auto pool_diff_src_memory_p = std::static_pointer_cast( + dev_ctx.GetBlob(key_pool_diff_src_mem_p)); + PADDLE_ENFORCE(pool_diff_src_memory_p != nullptr, + "Fail to find pooling src mem_p in device context"); + auto pool_diff_dst_memory_p = std::static_pointer_cast( + dev_ctx.GetBlob(key_pool_diff_dst_mem_p)); + PADDLE_ENFORCE(pool_diff_dst_memory_p != nullptr, + "Fail to find pooling dst mem_p in device context"); + pool_diff_src_memory_p->set_data_handle( + reinterpret_cast(in_x_grad_data)); + pool_diff_dst_memory_p->set_data_handle(const_cast(out_grad_data)); + } // push primitive to stream and wait until it's executed - std::vector pipeline{bwd_prim}; + std::vector pipeline{*(pool_bwd_p.get())}; mkldnn::stream(mkldnn::stream::kind::eager).submit(pipeline).wait(); } // Compute() }; diff --git a/paddle/fluid/platform/mkldnn_helper.h b/paddle/fluid/platform/mkldnn_helper.h index 23f1d615da..56ed5912a1 100644 --- a/paddle/fluid/platform/mkldnn_helper.h +++ b/paddle/fluid/platform/mkldnn_helper.h @@ -71,5 +71,15 @@ inline bool CanMKLDNNBeUsed(const framework::ExecutionContext& ctx) { return use_mkldnn && platform::is_cpu_place(ctx.GetPlace()); } +template +mkldnn::memory::data_type MKLDNNGetDataType() { + return mkldnn::memory::data_undef; +} + +template <> +inline mkldnn::memory::data_type MKLDNNGetDataType() { + return mkldnn::memory::f32; +} + } // namespace platform } // namespace paddle From feed94e20f614373986bd749da536caff38fdb5d Mon Sep 17 00:00:00 2001 From: qiaolongfei Date: Thu, 17 May 2018 19:50:51 +0800 Subject: [PATCH 10/31] should load parameter before create parallel_executor --- python/paddle/fluid/inferencer.py | 33 +++++++++++-------- .../fit_a_line/test_fit_a_line.py | 2 +- .../test_recognize_digits_conv.py | 2 +- .../test_recognize_digits_mlp.py | 2 +- .../word2vec/no_test_word2vec_new_api.py | 14 ++++---- 5 files changed, 29 insertions(+), 24 deletions(-) diff --git a/python/paddle/fluid/inferencer.py b/python/paddle/fluid/inferencer.py index 8c6dbd3b5a..0c2620d692 100644 --- a/python/paddle/fluid/inferencer.py +++ b/python/paddle/fluid/inferencer.py @@ -12,6 +12,8 @@ # See the License for the specific language governing permissions and # limitations under the License. +import contextlib + import core import executor @@ -41,31 +43,36 @@ class Inferencer(object): with unique_name.guard(): self.predict_var = infer_func() + with self._prog_and_scope_guard(): + # load params from param_path into scope + io.load_params(executor.Executor(self.place), param_path) + if parallel: - self.exe = parallel_executor.ParallelExecutor( - use_cuda=isinstance(self.place, core.CUDAPlace), - loss_name=self.predict_var.name) + with self._prog_and_scope_guard(): + self.exe = parallel_executor.ParallelExecutor( + use_cuda=isinstance(self.place, core.CUDAPlace), + loss_name=self.predict_var.name) else: self.exe = executor.Executor(self.place) - with executor.scope_guard(self.scope): - # load params from param_path into scope - io.load_params(self.exe, param_path, self.inference_program) - def infer(self, inputs, return_numpy=True): + def infer(self, inputs): """ :param inputs: a map of {"input_name": input_var} that will be feed into the inference program to get the predict value - :param return_numpy: if return numpy value for row tensor :return: the predict value of the inference model """ if not isinstance(inputs, dict): raise ValueError( "inputs should be a map of {'input_name': input_var}") - with executor.scope_guard(self.scope): - results = self.exe.run(self.inference_program, - feed=inputs, - fetch_list=[self.predict_var], - return_numpy=return_numpy) + with self._prog_and_scope_guard(): + results = self.exe.run(feed=inputs, + fetch_list=[self.predict_var.name]) return results + + @contextlib.contextmanager + def _prog_and_scope_guard(self): + with framework.program_guard(main_program=self.inference_program): + with executor.scope_guard(self.scope): + yield diff --git a/python/paddle/fluid/tests/book/high-level-api/fit_a_line/test_fit_a_line.py b/python/paddle/fluid/tests/book/high-level-api/fit_a_line/test_fit_a_line.py index fbcf2a282f..973142ccdf 100644 --- a/python/paddle/fluid/tests/book/high-level-api/fit_a_line/test_fit_a_line.py +++ b/python/paddle/fluid/tests/book/high-level-api/fit_a_line/test_fit_a_line.py @@ -94,7 +94,7 @@ def infer(use_cuda, inference_program, save_dirname=None): tensor_x = numpy.random.uniform(0, 10, [batch_size, 13]).astype("float32") results = inferencer.infer({'x': tensor_x}) - print("infer results: ", results[0]) + print("infer results: ", numpy.array(results[0])) def main(use_cuda): diff --git a/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py index f252a7e2b9..c1bae77ec4 100644 --- a/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py +++ b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py @@ -118,7 +118,7 @@ def infer(use_cuda, inference_program, save_dirname=None): results = inferencer.infer({'img': tensor_img}) - print("infer results: ", results[0]) + print("infer results: ", numpy.array(results[0])) def main(use_cuda): diff --git a/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_mlp.py b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_mlp.py index 9427a772f5..ae915b8458 100644 --- a/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_mlp.py +++ b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_mlp.py @@ -99,7 +99,7 @@ def infer(use_cuda, inference_program, save_dirname=None): results = inferencer.infer({'img': tensor_img}) - print("infer results: ", results[0]) + print("infer results: ", numpy.array(results[0])) def main(use_cuda): diff --git a/python/paddle/fluid/tests/book/high-level-api/word2vec/no_test_word2vec_new_api.py b/python/paddle/fluid/tests/book/high-level-api/word2vec/no_test_word2vec_new_api.py index 4f861e5aae..6d7495e4dd 100644 --- a/python/paddle/fluid/tests/book/high-level-api/word2vec/no_test_word2vec_new_api.py +++ b/python/paddle/fluid/tests/book/high-level-api/word2vec/no_test_word2vec_new_api.py @@ -127,14 +127,12 @@ def infer(use_cuda, inference_program, save_path): third_word = create_random_lodtensor(lod, place, low=0, high=dict_size - 1) fourth_word = create_random_lodtensor(lod, place, low=0, high=dict_size - 1) - result = inferencer.infer( - { - 'firstw': first_word, - 'secondw': second_word, - 'thirdw': third_word, - 'forthw': fourth_word - }, - return_numpy=False) + result = inferencer.infer({ + 'firstw': first_word, + 'secondw': second_word, + 'thirdw': third_word, + 'forthw': fourth_word + }) print(np.array(result[0])) From 8023bc766b8d1c39f280295abaeac7a374face72 Mon Sep 17 00:00:00 2001 From: baiyfbupt Date: Thu, 17 May 2018 14:58:44 +0000 Subject: [PATCH 11/31] fix index --- paddle/fluid/operators/roi_pool_op.cu | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/paddle/fluid/operators/roi_pool_op.cu b/paddle/fluid/operators/roi_pool_op.cu index a699d21542..972dc36c11 100644 --- a/paddle/fluid/operators/roi_pool_op.cu +++ b/paddle/fluid/operators/roi_pool_op.cu @@ -38,10 +38,10 @@ __global__ void GPUROIPoolForward( int index = blockIdx.x * blockDim.x + threadIdx.x; int offset = blockDim.x * gridDim.x; for (size_t i = index; i < nthreads; i += offset) { - int pw = index % pooled_width; - int ph = (index / pooled_width) % pooled_height; - int c = (index / pooled_width / pooled_height) % channels; - int n = index / pooled_width / pooled_height / channels; + int pw = i % pooled_width; + int ph = (i / pooled_width) % pooled_height; + int c = (i / pooled_width / pooled_height) % channels; + int n = i / pooled_width / pooled_height / channels; const int64_t* offset_input_rois = input_rois + n * kROISize; int roi_batch_ind = roi_batch_id_data[n]; @@ -65,7 +65,6 @@ __global__ void GPUROIPoolForward( int wend = static_cast(ceil(static_cast(pw + 1) * static_cast(roi_width) / static_cast(pooled_width))); - hstart = min(max(hstart + roi_start_h, 0), height); hend = min(max(hend + roi_start_h, 0), height); wstart = min(max(wstart + roi_start_w, 0), width); @@ -85,9 +84,9 @@ __global__ void GPUROIPoolForward( } } } - output_data[index] = maxval; + output_data[i] = maxval; if (argmax_data) { - argmax_data[index] = maxidx; + argmax_data[i] = maxidx; } } } @@ -144,6 +143,7 @@ class GPUROIPoolOpKernel : public framework::OpKernel { int width = in_dims[3]; int rois_num = rois->dims()[0]; + if (rois_num == 0) return; int output_size = out->numel(); From 93c470034a96b4963b3b0740105ef5f92ac70f96 Mon Sep 17 00:00:00 2001 From: chengduo Date: Fri, 18 May 2018 02:46:38 +0800 Subject: [PATCH 12/31] fix DataTransFunc (#10752) --- paddle/fluid/framework/data_device_transform.cc | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/paddle/fluid/framework/data_device_transform.cc b/paddle/fluid/framework/data_device_transform.cc index 85dbb39e6f..a876725ac0 100644 --- a/paddle/fluid/framework/data_device_transform.cc +++ b/paddle/fluid/framework/data_device_transform.cc @@ -36,9 +36,11 @@ void TransDataDevice(const Tensor& in, const platform::Place& dst_place, VLOG(3) << "DeviceTransform in, src_place " << in.place() << " dst_place: " << dst_place; auto* dev_ctx = GetDeviceContext(in.place(), dst_place); - dev_ctx->Wait(); + TensorCopy(in, dst_place, *dev_ctx, out); - dev_ctx->Wait(); + if (platform::is_gpu_place(in.place()) && platform::is_cpu_place(dst_place)) { + dev_ctx->Wait(); + } } } // namespace framework From 868bdc97713169f3525a014f71a4dd3e52e85008 Mon Sep 17 00:00:00 2001 From: Lei Wang Date: Thu, 17 May 2018 16:46:53 -0700 Subject: [PATCH 13/31] Build: fix build error when WITH_FLUID_ONLY and WITH_GPU both set as OFF. (#10756) --- paddle/fluid/operators/CMakeLists.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/paddle/fluid/operators/CMakeLists.txt b/paddle/fluid/operators/CMakeLists.txt index eb559114e9..ac1f3f44ae 100644 --- a/paddle/fluid/operators/CMakeLists.txt +++ b/paddle/fluid/operators/CMakeLists.txt @@ -203,8 +203,8 @@ if(WITH_DISTRIBUTE) set_source_files_properties(send_barrier_op.cc PROPERTIES COMPILE_FLAGS ${DISTRIBUTE_COMPILE_FLAGS}) set_source_files_properties(send_recv_op_test.cc PROPERTIES COMPILE_FLAGS ${DISTRIBUTE_COMPILE_FLAGS}) cc_test(test_send_recv SRCS send_recv_op_test.cc DEPS prefetch_op send_op listen_and_serv_op sum_op executor) - cc_test(test_send_nccl_id SRCS test_send_nccl_id.cc DEPS send_op listen_and_serv_op executor) if(WITH_GPU) + cc_test(test_send_nccl_id SRCS test_send_nccl_id.cc DEPS send_op listen_and_serv_op executor) op_library(gen_nccl_id_op DEPS nccl_common sendrecvop_grpc) set_source_files_properties(gen_nccl_id_op.cc PROPERTIES COMPILE_FLAGS ${DISTRIBUTE_COMPILE_FLAGS}) else() From d2d671e34107e1193fa4e30314178bb73a6a8c3e Mon Sep 17 00:00:00 2001 From: qiaolongfei Date: Fri, 18 May 2018 09:48:46 +0800 Subject: [PATCH 14/31] add comment --- python/paddle/fluid/inferencer.py | 1 + 1 file changed, 1 insertion(+) diff --git a/python/paddle/fluid/inferencer.py b/python/paddle/fluid/inferencer.py index 0c2620d692..894f6dbfad 100644 --- a/python/paddle/fluid/inferencer.py +++ b/python/paddle/fluid/inferencer.py @@ -32,6 +32,7 @@ class Inferencer(object): :param infer_func: a function that will return predict Variable :param param_path: the path where the inference model is saved by fluid.io.save_params :param place: place to do the inference + :param parallel: use parallel_executor to run the inference, it will use multi CPU/GPU. """ self.param_path = param_path self.scope = core.Scope() From 1d7f91e867b598bc4cde7dd5f0ef0410ca569bd5 Mon Sep 17 00:00:00 2001 From: baiyfbupt Date: Fri, 18 May 2018 02:14:09 +0000 Subject: [PATCH 15/31] fix roi_pool gpu_backward kernel --- paddle/fluid/operators/roi_pool_op.cu | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/paddle/fluid/operators/roi_pool_op.cu b/paddle/fluid/operators/roi_pool_op.cu index 972dc36c11..50450b62f7 100644 --- a/paddle/fluid/operators/roi_pool_op.cu +++ b/paddle/fluid/operators/roi_pool_op.cu @@ -101,10 +101,10 @@ __global__ void GPUROIPoolBackward( int index = blockIdx.x * blockDim.x + threadIdx.x; int offset = blockDim.x * gridDim.x; for (int i = index; i < nthreads; i += offset) { - int pw = index % pooled_width; - int ph = (index / pooled_width) % pooled_height; - int c = (index / pooled_width / pooled_height) % channels; - int n = index / pooled_width / pooled_height / channels; + int pw = i % pooled_width; + int ph = (i / pooled_width) % pooled_height; + int c = (i / pooled_width / pooled_height) % channels; + int n = i / pooled_width / pooled_height / channels; int roi_batch_ind = roi_batch_id_data[n]; int input_offset = (roi_batch_ind * channels + c) * height * width; From ebc7303990a74ca8de91af4d68543614825d25f2 Mon Sep 17 00:00:00 2001 From: Wu Yi Date: Fri, 18 May 2018 10:21:30 +0800 Subject: [PATCH 16/31] listen_and_serv use local scope (#10663) * listen_and_serv use localscope * fix ut --- paddle/fluid/framework/executor.cc | 15 +++++++++------ paddle/fluid/framework/executor.h | 3 ++- paddle/fluid/inference/tests/test_helper.h | 4 ++-- paddle/fluid/operators/detail/grpc_server.cc | 2 +- paddle/fluid/operators/listen_and_serv_op.cc | 7 +++---- paddle/fluid/operators/send_recv_op_test.cc | 9 +++++++-- .../fluid/tests/unittests/test_dist_train.py | 9 ++++++--- 7 files changed, 30 insertions(+), 19 deletions(-) diff --git a/paddle/fluid/framework/executor.cc b/paddle/fluid/framework/executor.cc index ce91d7a826..4e431561f8 100644 --- a/paddle/fluid/framework/executor.cc +++ b/paddle/fluid/framework/executor.cc @@ -228,7 +228,8 @@ static bool has_fetch_operators( void Executor::Run(const ProgramDesc& program, Scope* scope, std::map* feed_targets, std::map* fetch_targets, - bool create_vars, const std::string& feed_holder_name, + bool create_local_scope, bool create_vars, + const std::string& feed_holder_name, const std::string& fetch_holder_name) { platform::RecordBlock b(kProgramId); bool has_feed_ops = @@ -290,8 +291,9 @@ void Executor::Run(const ProgramDesc& program, Scope* scope, } auto ctx = Prepare(*copy_program, 0); - RunPreparedContext(ctx.get(), scope, feed_targets, fetch_targets, create_vars, - feed_holder_name, fetch_holder_name); + RunPreparedContext(ctx.get(), scope, feed_targets, fetch_targets, + create_local_scope, create_vars, feed_holder_name, + fetch_holder_name); } std::unique_ptr Executor::Prepare( @@ -366,8 +368,9 @@ void Executor::RunPreparedContext(ExecutorPrepareContext* ctx, Scope* scope, void Executor::RunPreparedContext( ExecutorPrepareContext* ctx, Scope* scope, std::map* feed_targets, - std::map* fetch_targets, bool create_vars, - const std::string& feed_holder_name, const std::string& fetch_holder_name) { + std::map* fetch_targets, bool create_local_scope, + bool create_vars, const std::string& feed_holder_name, + const std::string& fetch_holder_name) { auto& global_block = ctx->prog_.Block(ctx->block_id_); PADDLE_ENFORCE( @@ -387,7 +390,7 @@ void Executor::RunPreparedContext( } } - RunPreparedContext(ctx, scope, create_vars, create_vars); + RunPreparedContext(ctx, scope, create_local_scope, create_vars); // obtain the data of fetch_targets from fetch_holder for (auto* op : global_block.AllOps()) { diff --git a/paddle/fluid/framework/executor.h b/paddle/fluid/framework/executor.h index 4a3d637e2d..0c3c23611d 100644 --- a/paddle/fluid/framework/executor.h +++ b/paddle/fluid/framework/executor.h @@ -57,7 +57,7 @@ class Executor { void Run(const ProgramDesc& program, Scope* scope, std::map* feed_targets, std::map* fetch_targets, - bool create_vars = true, + bool create_local_scope = true, bool create_vars = true, const std::string& feed_holder_name = "feed", const std::string& fetch_holder_name = "fetch"); @@ -76,6 +76,7 @@ class Executor { void RunPreparedContext(ExecutorPrepareContext* ctx, Scope* scope, std::map* feed_targets, std::map* fetch_targets, + bool create_local_scope = true, bool create_vars = true, const std::string& feed_holder_name = "feed", const std::string& fetch_holder_name = "fetch"); diff --git a/paddle/fluid/inference/tests/test_helper.h b/paddle/fluid/inference/tests/test_helper.h index b02e5c99f0..e33eb7f170 100644 --- a/paddle/fluid/inference/tests/test_helper.h +++ b/paddle/fluid/inference/tests/test_helper.h @@ -208,10 +208,10 @@ void TestInference(const std::string& dirname, if (PrepareContext) { ctx = executor.Prepare(*inference_program, 0); executor.RunPreparedContext(ctx.get(), scope, &feed_targets, - &fetch_targets, CreateVars); + &fetch_targets, true, CreateVars); } else { executor.Run(*inference_program, scope, &feed_targets, &fetch_targets, - CreateVars); + true, CreateVars); } // Enable the profiler diff --git a/paddle/fluid/operators/detail/grpc_server.cc b/paddle/fluid/operators/detail/grpc_server.cc index d09f8479b7..eb114a47d9 100644 --- a/paddle/fluid/operators/detail/grpc_server.cc +++ b/paddle/fluid/operators/detail/grpc_server.cc @@ -184,7 +184,7 @@ class RequestPrefetch final : public RequestBase { framework::Scope* local_scope = &scope_->NewScope(); auto* var = local_scope->FindVar(var_name); InitializeVariable(var, var_desc->GetType()); - executor_->RunPreparedContext(prefetch_ctx_, scope_, false, false); + executor_->RunPreparedContext(prefetch_ctx_, scope_); SerializeToByteBuffer(var_name, var, *dev_ctx_, &reply); diff --git a/paddle/fluid/operators/listen_and_serv_op.cc b/paddle/fluid/operators/listen_and_serv_op.cc index abc88d3eb1..57eb5d9a0e 100644 --- a/paddle/fluid/operators/listen_and_serv_op.cc +++ b/paddle/fluid/operators/listen_and_serv_op.cc @@ -57,8 +57,7 @@ static void ParallelExecuteBlocks( framework::Async([&executor, &prepared, &program, &scope, idx]() { int run_block = idx; // thread local try { - executor->RunPreparedContext(prepared[run_block].get(), scope, - false, false); + executor->RunPreparedContext(prepared[run_block].get(), scope); } catch (std::exception &e) { LOG(ERROR) << "run sub program error " << e.what(); } @@ -211,8 +210,8 @@ static void AsyncUpdateThread( } auto fs = framework::Async([var_name, &executor, &v, prepared] { try { - executor->RunPreparedContext(prepared, v.second->GetMutableLocalScope(), - false, false); + executor->RunPreparedContext(prepared, + v.second->GetMutableLocalScope()); } catch (std::exception &e) { LOG(ERROR) << "run sub program error " << e.what(); } diff --git a/paddle/fluid/operators/send_recv_op_test.cc b/paddle/fluid/operators/send_recv_op_test.cc index eb51f301bf..d5303eaf50 100644 --- a/paddle/fluid/operators/send_recv_op_test.cc +++ b/paddle/fluid/operators/send_recv_op_test.cc @@ -92,12 +92,16 @@ void InitSelectedRowsInScope(const p::CPUPlace &place, f::Scope *scope) { void AddOp(const std::string &type, const f::VariableNameMap &inputs, const f::VariableNameMap &outputs, f::AttributeMap attrs, - f::BlockDesc *block) { + f::BlockDesc *block, bool is_sparse) { // insert output for (auto kv : outputs) { for (auto v : kv.second) { auto var = block->Var(v); var->SetDataType(f::proto::VarType::FP32); + var->SetPersistable(true); + if (is_sparse) { + var->SetType(f::proto::VarType::SELECTED_ROWS); + } } } @@ -128,7 +132,8 @@ void StartServerNet(bool is_sparse, std::atomic *initialized) { auto *optimize_block = program.AppendBlock(root_block); auto *prefetch_block = program.AppendBlock(root_block); // X for server side tensors, RX for received tensors, must be of same shape. - AddOp("sum", {{"X", {"x0", "x1"}}}, {{"Out", {"Out"}}}, {}, optimize_block); + AddOp("sum", {{"X", {"x0", "x1"}}}, {{"Out", {"Out"}}}, {}, optimize_block, + is_sparse); f::AttributeMap attrs; attrs.insert({"endpoint", std::string("127.0.0.1:0")}); attrs.insert({"Fanin", 1}); diff --git a/python/paddle/fluid/tests/unittests/test_dist_train.py b/python/paddle/fluid/tests/unittests/test_dist_train.py index 77e9a8f7e7..c2393a288c 100644 --- a/python/paddle/fluid/tests/unittests/test_dist_train.py +++ b/python/paddle/fluid/tests/unittests/test_dist_train.py @@ -52,15 +52,18 @@ class TestSendOp(unittest.TestCase): serv = layers.ListenAndServ( "127.0.0.1:0", ["X"], optimizer_mode=False) with serv.do(): + out_var = main.global_block().create_var( + name="scale_0.tmp_0", + psersistable=True, + dtype="float32", + shape=[32, 32]) x = layers.data( shape=[32, 32], dtype='float32', name="X", append_batch_size=False) fluid.initializer.Constant(value=1.0)(x, main.global_block()) - o = layers.scale(x=x, scale=10.0) - main.global_block().create_var( - name=o.name, psersistable=False, dtype=o.dtype, shape=o.shape) + layers.scale(x=x, scale=10.0, out=out_var) self.server_exe = fluid.Executor(place) self.server_exe.run(main) From eb7d87545e14112fea1ef82d4d0eb60d3faa4a10 Mon Sep 17 00:00:00 2001 From: Qiao Longfei Date: Fri, 18 May 2018 13:06:34 +0800 Subject: [PATCH 17/31] add trainer.stop and fix a bug for train_by_parallel_executor (#10762) --- .../fit_a_line/test_fit_a_line.py | 26 +++++++++---------- python/paddle/fluid/trainer.py | 13 +++++++--- 2 files changed, 22 insertions(+), 17 deletions(-) diff --git a/python/paddle/fluid/tests/book/high-level-api/fit_a_line/test_fit_a_line.py b/python/paddle/fluid/tests/book/high-level-api/fit_a_line/test_fit_a_line.py index 973142ccdf..4c8505acf3 100644 --- a/python/paddle/fluid/tests/book/high-level-api/fit_a_line/test_fit_a_line.py +++ b/python/paddle/fluid/tests/book/high-level-api/fit_a_line/test_fit_a_line.py @@ -57,22 +57,20 @@ def train(use_cuda, train_program, save_dirname): optimizer=fluid.optimizer.SGD(learning_rate=0.001)) def event_handler(event): - if isinstance(event, fluid.EndEpochEvent): - test_metrics = trainer.test( - reader=test_reader, feed_order=['x', 'y']) - print test_metrics - ''' - - ... - ['25.768919467926025'] - ['15.343549569447836'] - ... - - ''' - if float(test_metrics[0]) < 20.0: + if isinstance(event, fluid.EndStepEvent): + if event.step == 10: + test_metrics = trainer.test( + reader=test_reader, feed_order=['x', 'y']) + print test_metrics + ''' + ... + ['25.768919467926025'] + ['15.343549569447836'] + ... + ''' if save_dirname is not None: trainer.save_params(save_dirname) - return + trainer.stop() trainer.train( reader=train_reader, diff --git a/python/paddle/fluid/trainer.py b/python/paddle/fluid/trainer.py index f4292208c9..7da123dd92 100644 --- a/python/paddle/fluid/trainer.py +++ b/python/paddle/fluid/trainer.py @@ -100,6 +100,7 @@ class Trainer(object): param_path=None, place=None, parallel=False): + self.__stop = False self.parallel = parallel # 1. we need to generate a framework.Program by calling # program_func. Reference: fluid.program_guard in @@ -210,6 +211,12 @@ class Trainer(object): 'TRAINING_ROLE environment variable must be either TRAINER or PSERVER' ) + def stop(self): + """ + stop training + """ + self.__stop = True + def train(self, num_epochs, event_handler, reader=None, feed_order=None): """ Train the model. @@ -289,6 +296,8 @@ class Trainer(object): for epoch_id in range(num_epochs): event_handler(BeginEpochEvent(epoch_id)) for step_id, data in enumerate(reader()): + if self.__stop: + return begin_event = BeginStepEvent(epoch_id, step_id) event_handler(begin_event) if begin_event.fetch_metrics: @@ -327,9 +336,7 @@ class Trainer(object): feeder = data_feeder.DataFeeder( feed_list=feed_var_list, place=self.place) reader = feeder.decorate_reader(reader, multi_devices=True) - for epoch_id in range(num_epochs): - self._train_by_any_executor(event_handler, pe, num_epochs, - reader) + self._train_by_any_executor(event_handler, pe, num_epochs, reader) def _get_parallel_executor(self): return getattr(self, 'parallel_executor', None) From 871bc43064421a2b1c92f1638cef6792c25aa663 Mon Sep 17 00:00:00 2001 From: Xin Pan Date: Fri, 18 May 2018 17:16:07 +0800 Subject: [PATCH 18/31] Fix a compile error --- paddle/fluid/operators/CMakeLists.txt | 1 + 1 file changed, 1 insertion(+) diff --git a/paddle/fluid/operators/CMakeLists.txt b/paddle/fluid/operators/CMakeLists.txt index ac1f3f44ae..7fce138e3f 100644 --- a/paddle/fluid/operators/CMakeLists.txt +++ b/paddle/fluid/operators/CMakeLists.txt @@ -204,6 +204,7 @@ if(WITH_DISTRIBUTE) set_source_files_properties(send_recv_op_test.cc PROPERTIES COMPILE_FLAGS ${DISTRIBUTE_COMPILE_FLAGS}) cc_test(test_send_recv SRCS send_recv_op_test.cc DEPS prefetch_op send_op listen_and_serv_op sum_op executor) if(WITH_GPU) + set_source_files_properties(test_send_nccl_id.cc PROPERTIES COMPILE_FLAGS ${DISTRIBUTE_COMPILE_FLAGS}) cc_test(test_send_nccl_id SRCS test_send_nccl_id.cc DEPS send_op listen_and_serv_op executor) op_library(gen_nccl_id_op DEPS nccl_common sendrecvop_grpc) set_source_files_properties(gen_nccl_id_op.cc PROPERTIES COMPILE_FLAGS ${DISTRIBUTE_COMPILE_FLAGS}) From 17f503726b3829476431d18fc11209a95d3f5909 Mon Sep 17 00:00:00 2001 From: Yancey Date: Fri, 18 May 2018 17:32:25 +0800 Subject: [PATCH 19/31] use latest pip version in dev and production Docker image (#10760) * use latest pip version * fix ci * update by comment --- Dockerfile | 2 +- paddle/scripts/docker/build.sh | 2 +- paddle/scripts/paddle_build.sh | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/Dockerfile b/Dockerfile index 164fe84904..ea39efd00b 100644 --- a/Dockerfile +++ b/Dockerfile @@ -70,7 +70,7 @@ RUN localedef -i en_US -f UTF-8 en_US.UTF-8 # specify sphinx version as 1.5.6 and remove -U option for [pip install -U # sphinx-rtd-theme] since -U option will cause sphinx being updated to newest # version(1.7.1 for now), which causes building documentation failed. -RUN pip install --upgrade pip==9.0.3 && \ +RUN easy_install -U pip && \ pip install -U wheel && \ pip install -U docopt PyYAML sphinx==1.5.6 && \ pip install sphinx-rtd-theme==0.1.9 recommonmark diff --git a/paddle/scripts/docker/build.sh b/paddle/scripts/docker/build.sh index 7e00bd3848..92b8b90880 100755 --- a/paddle/scripts/docker/build.sh +++ b/paddle/scripts/docker/build.sh @@ -198,7 +198,7 @@ EOF # run paddle version to install python packages first RUN apt-get update &&\ ${NCCL_DEPS}\ - apt-get install -y wget python-pip dmidecode python-tk && pip install -U pip==9.0.3 && \ + apt-get install -y wget python-pip dmidecode python-tk && easy_install -U pip && \ pip install /*.whl; apt-get install -f -y && \ apt-get clean -y && \ rm -f /*.whl && \ diff --git a/paddle/scripts/paddle_build.sh b/paddle/scripts/paddle_build.sh index e5af42ed57..3efca04a5c 100755 --- a/paddle/scripts/paddle_build.sh +++ b/paddle/scripts/paddle_build.sh @@ -449,7 +449,7 @@ EOF # run paddle version to install python packages first RUN apt-get update &&\ ${NCCL_DEPS}\ - apt-get install -y wget python-pip dmidecode python-tk && pip install -U pip==9.0.3 && \ + apt-get install -y wget python-pip dmidecode python-tk && easy_install -U pip && \ pip install /*.whl; apt-get install -f -y && \ apt-get clean -y && \ rm -f /*.whl && \ From 8282d3e0120b22a7c2d5ec4427595322626a13ac Mon Sep 17 00:00:00 2001 From: Xin Pan Date: Fri, 18 May 2018 04:05:04 -0700 Subject: [PATCH 20/31] fix cpp lint --- paddle/fluid/inference/tests/test_helper.h | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/paddle/fluid/inference/tests/test_helper.h b/paddle/fluid/inference/tests/test_helper.h index 1adbf57d0b..cc1589514a 100644 --- a/paddle/fluid/inference/tests/test_helper.h +++ b/paddle/fluid/inference/tests/test_helper.h @@ -236,8 +236,7 @@ void TestInference(const std::string& dirname, // Disable the profiler and print the timing information paddle::platform::DisableProfiler( - paddle::platform::EventSortingKey::kDefault, - "run_inference_profiler"); + paddle::platform::EventSortingKey::kDefault, "run_inference_profiler"); paddle::platform::ResetProfiler(); } From 11b6473c2693e1b965bf4abcdf16a576ef65523b Mon Sep 17 00:00:00 2001 From: daminglu Date: Fri, 18 May 2018 12:02:57 -0700 Subject: [PATCH 21/31] Image classification & word2vec (#10738) --- .../tests/book/high-level-api/CMakeLists.txt | 1 + .../image_classification/CMakeLists.txt | 7 ++ .../cifar10_small_test_set.py | 82 +++++++++++++++++++ ...py => test_image_classification_resnet.py} | 51 +++++++----- ...gg.py => test_image_classification_vgg.py} | 53 +++++++----- 5 files changed, 152 insertions(+), 42 deletions(-) create mode 100644 python/paddle/fluid/tests/book/high-level-api/image_classification/CMakeLists.txt create mode 100644 python/paddle/fluid/tests/book/high-level-api/image_classification/cifar10_small_test_set.py rename python/paddle/fluid/tests/book/high-level-api/image_classification/{notest_image_classification_resnet.py => test_image_classification_resnet.py} (77%) rename python/paddle/fluid/tests/book/high-level-api/image_classification/{notest_image_classification_vgg.py => test_image_classification_vgg.py} (72%) diff --git a/python/paddle/fluid/tests/book/high-level-api/CMakeLists.txt b/python/paddle/fluid/tests/book/high-level-api/CMakeLists.txt index c2a15bdb3b..da76747f82 100644 --- a/python/paddle/fluid/tests/book/high-level-api/CMakeLists.txt +++ b/python/paddle/fluid/tests/book/high-level-api/CMakeLists.txt @@ -8,3 +8,4 @@ endforeach() add_subdirectory(fit_a_line) add_subdirectory(recognize_digits) +add_subdirectory(image_classification) diff --git a/python/paddle/fluid/tests/book/high-level-api/image_classification/CMakeLists.txt b/python/paddle/fluid/tests/book/high-level-api/image_classification/CMakeLists.txt new file mode 100644 index 0000000000..673c965b66 --- /dev/null +++ b/python/paddle/fluid/tests/book/high-level-api/image_classification/CMakeLists.txt @@ -0,0 +1,7 @@ +file(GLOB TEST_OPS RELATIVE "${CMAKE_CURRENT_SOURCE_DIR}" "test_*.py") +string(REPLACE ".py" "" TEST_OPS "${TEST_OPS}") + +# default test +foreach(src ${TEST_OPS}) + py_test(${src} SRCS ${src}.py) +endforeach() diff --git a/python/paddle/fluid/tests/book/high-level-api/image_classification/cifar10_small_test_set.py b/python/paddle/fluid/tests/book/high-level-api/image_classification/cifar10_small_test_set.py new file mode 100644 index 0000000000..7fed6d914f --- /dev/null +++ b/python/paddle/fluid/tests/book/high-level-api/image_classification/cifar10_small_test_set.py @@ -0,0 +1,82 @@ +# Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +""" +CIFAR dataset. + +This module will download dataset from +https://www.cs.toronto.edu/~kriz/cifar.html and parse train/test set into +paddle reader creators. + +The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, +with 6000 images per class. There are 50000 training images and 10000 test +images. + +The CIFAR-100 dataset is just like the CIFAR-10, except it has 100 classes +containing 600 images each. There are 500 training images and 100 testing +images per class. + +""" + +import cPickle +import itertools +import numpy +import paddle.v2.dataset.common +import tarfile + +__all__ = ['train10'] + +URL_PREFIX = 'https://www.cs.toronto.edu/~kriz/' +CIFAR10_URL = URL_PREFIX + 'cifar-10-python.tar.gz' +CIFAR10_MD5 = 'c58f30108f718f92721af3b95e74349a' + + +def reader_creator(filename, sub_name, batch_size=None): + def read_batch(batch): + data = batch['data'] + labels = batch.get('labels', batch.get('fine_labels', None)) + assert labels is not None + for sample, label in itertools.izip(data, labels): + yield (sample / 255.0).astype(numpy.float32), int(label) + + def reader(): + with tarfile.open(filename, mode='r') as f: + names = (each_item.name for each_item in f + if sub_name in each_item.name) + + batch_count = 0 + for name in names: + batch = cPickle.load(f.extractfile(name)) + for item in read_batch(batch): + if isinstance(batch_size, int) and batch_count > batch_size: + break + batch_count += 1 + yield item + + return reader + + +def train10(batch_size=None): + """ + CIFAR-10 training set creator. + + It returns a reader creator, each sample in the reader is image pixels in + [0, 1] and label in [0, 9]. + + :return: Training reader creator + :rtype: callable + """ + return reader_creator( + paddle.v2.dataset.common.download(CIFAR10_URL, 'cifar', CIFAR10_MD5), + 'data_batch', + batch_size=batch_size) diff --git a/python/paddle/fluid/tests/book/high-level-api/image_classification/notest_image_classification_resnet.py b/python/paddle/fluid/tests/book/high-level-api/image_classification/test_image_classification_resnet.py similarity index 77% rename from python/paddle/fluid/tests/book/high-level-api/image_classification/notest_image_classification_resnet.py rename to python/paddle/fluid/tests/book/high-level-api/image_classification/test_image_classification_resnet.py index 17db38797c..1160e500db 100644 --- a/python/paddle/fluid/tests/book/high-level-api/image_classification/notest_image_classification_resnet.py +++ b/python/paddle/fluid/tests/book/high-level-api/image_classification/test_image_classification_resnet.py @@ -17,6 +17,7 @@ from __future__ import print_function import paddle import paddle.fluid as fluid import numpy +import cifar10_small_test_set def resnet_cifar10(input, depth=32): @@ -81,46 +82,50 @@ def train_network(): cost = fluid.layers.cross_entropy(input=predict, label=label) avg_cost = fluid.layers.mean(cost) accuracy = fluid.layers.accuracy(input=predict, label=label) - return avg_cost, accuracy + return [avg_cost, accuracy] -def train(use_cuda, save_path): +def train(use_cuda, train_program, save_dirname): BATCH_SIZE = 128 EPOCH_NUM = 1 train_reader = paddle.batch( paddle.reader.shuffle( - paddle.dataset.cifar.train10(), buf_size=128 * 10), + cifar10_small_test_set.train10(batch_size=10), buf_size=128 * 10), batch_size=BATCH_SIZE) test_reader = paddle.batch( paddle.dataset.cifar.test10(), batch_size=BATCH_SIZE) def event_handler(event): - if isinstance(event, fluid.EndIteration): - if (event.batch_id % 10) == 0: - avg_cost, accuracy = trainer.test(reader=test_reader) + if isinstance(event, fluid.EndStepEvent): + avg_cost, accuracy = trainer.test( + reader=test_reader, feed_order=['pixel', 'label']) - print('BatchID {1:04}, Loss {2:2.2}, Acc {3:2.2}'.format( - event.batch_id + 1, avg_cost, accuracy)) + print('Loss {0:2.2}, Acc {1:2.2}'.format(avg_cost, accuracy)) - if accuracy > 0.01: # Low threshold for speeding up CI - trainer.params.save(save_path) - return + if accuracy > 0.01: # Low threshold for speeding up CI + if save_dirname is not None: + trainer.save_params(save_dirname) + return place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace() trainer = fluid.Trainer( - train_network, + train_func=train_program, optimizer=fluid.optimizer.Adam(learning_rate=0.001), - place=place, - event_handler=event_handler) - trainer.train(train_reader, EPOCH_NUM, event_handler=event_handler) + place=place) + trainer.train( + reader=train_reader, + num_epochs=EPOCH_NUM, + event_handler=event_handler, + feed_order=['pixel', 'label']) -def infer(use_cuda, save_path): - params = fluid.Params(save_path) + +def infer(use_cuda, inference_program, save_dirname=None): place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace() - inferencer = fluid.Inferencer(inference_network, params, place=place) + inferencer = fluid.Inferencer( + infer_func=inference_program, param_path=save_dirname, place=place) # The input's dimension of conv should be 4-D or 5-D. # Use normilized image pixels as input data, which should be in the range @@ -135,8 +140,14 @@ def main(use_cuda): if use_cuda and not fluid.core.is_compiled_with_cuda(): return save_path = "image_classification_resnet.inference.model" - train(use_cuda, save_path) - infer(use_cuda, save_path) + + train( + use_cuda=use_cuda, train_program=train_network, save_dirname=save_path) + + infer( + use_cuda=use_cuda, + inference_program=inference_network, + save_dirname=save_path) if __name__ == '__main__': diff --git a/python/paddle/fluid/tests/book/high-level-api/image_classification/notest_image_classification_vgg.py b/python/paddle/fluid/tests/book/high-level-api/image_classification/test_image_classification_vgg.py similarity index 72% rename from python/paddle/fluid/tests/book/high-level-api/image_classification/notest_image_classification_vgg.py rename to python/paddle/fluid/tests/book/high-level-api/image_classification/test_image_classification_vgg.py index e83afeed2f..1e3e955ba0 100644 --- a/python/paddle/fluid/tests/book/high-level-api/image_classification/notest_image_classification_vgg.py +++ b/python/paddle/fluid/tests/book/high-level-api/image_classification/test_image_classification_vgg.py @@ -17,6 +17,7 @@ from __future__ import print_function import paddle import paddle.fluid as fluid import numpy +import cifar10_small_test_set def vgg16_bn_drop(input): @@ -60,46 +61,48 @@ def train_network(): cost = fluid.layers.cross_entropy(input=predict, label=label) avg_cost = fluid.layers.mean(cost) accuracy = fluid.layers.accuracy(input=predict, label=label) - return avg_cost, accuracy + return [avg_cost, accuracy] -def train(use_cuda, save_path): +def train(use_cuda, train_program, save_dirname): BATCH_SIZE = 128 - EPOCH_NUM = 1 - train_reader = paddle.batch( paddle.reader.shuffle( - paddle.dataset.cifar.train10(), buf_size=128 * 10), + cifar10_small_test_set.train10(batch_size=10), buf_size=128 * 10), batch_size=BATCH_SIZE) test_reader = paddle.batch( paddle.dataset.cifar.test10(), batch_size=BATCH_SIZE) def event_handler(event): - if isinstance(event, fluid.EndIteration): - if (event.batch_id % 10) == 0: - avg_cost, accuracy = trainer.test(reader=test_reader) + if isinstance(event, fluid.EndStepEvent): + avg_cost, accuracy = trainer.test( + reader=test_reader, feed_order=['pixel', 'label']) - print('BatchID {1:04}, Loss {2:2.2}, Acc {3:2.2}'.format( - event.batch_id + 1, avg_cost, accuracy)) + print('Loss {0:2.2}, Acc {1:2.2}'.format(avg_cost, accuracy)) - if accuracy > 0.01: # Low threshold for speeding up CI - trainer.params.save(save_path) - return + if accuracy > 0.01: # Low threshold for speeding up CI + if save_dirname is not None: + trainer.save_params(save_dirname) + return place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace() trainer = fluid.Trainer( - train_network, - optimizer=fluid.optimizer.Adam(learning_rate=0.001), + train_func=train_program, place=place, - event_handler=event_handler) - trainer.train(train_reader, EPOCH_NUM, event_handler=event_handler) + optimizer=fluid.optimizer.Adam(learning_rate=0.001)) + + trainer.train( + reader=train_reader, + num_epochs=1, + event_handler=event_handler, + feed_order=['pixel', 'label']) -def infer(use_cuda, save_path): - params = fluid.Params(save_path) +def infer(use_cuda, inference_program, save_dirname=None): place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace() - inferencer = fluid.Inferencer(inference_network, params, place=place) + inferencer = fluid.Inferencer( + infer_func=inference_program, param_path=save_dirname, place=place) # The input's dimension of conv should be 4-D or 5-D. # Use normilized image pixels as input data, which should be in the range @@ -114,8 +117,14 @@ def main(use_cuda): if use_cuda and not fluid.core.is_compiled_with_cuda(): return save_path = "image_classification_vgg.inference.model" - train(use_cuda, save_path) - infer(use_cuda, save_path) + + train( + use_cuda=use_cuda, train_program=train_network, save_dirname=save_path) + + infer( + use_cuda=use_cuda, + inference_program=inference_network, + save_dirname=save_path) if __name__ == '__main__': From ae1990731d78c46cde120e42f939ba30ce22630a Mon Sep 17 00:00:00 2001 From: daminglu Date: Fri, 18 May 2018 18:33:48 -0700 Subject: [PATCH 22/31] Test word2vec (#10779) --- paddle/fluid/inference/tests/test_helper.h | 3 +- ...ec_new_api.py => test_word2vec_new_api.py} | 57 ++++++++++++------- 2 files changed, 39 insertions(+), 21 deletions(-) rename python/paddle/fluid/tests/book/high-level-api/word2vec/{no_test_word2vec_new_api.py => test_word2vec_new_api.py} (77%) diff --git a/paddle/fluid/inference/tests/test_helper.h b/paddle/fluid/inference/tests/test_helper.h index 1adbf57d0b..cc1589514a 100644 --- a/paddle/fluid/inference/tests/test_helper.h +++ b/paddle/fluid/inference/tests/test_helper.h @@ -236,8 +236,7 @@ void TestInference(const std::string& dirname, // Disable the profiler and print the timing information paddle::platform::DisableProfiler( - paddle::platform::EventSortingKey::kDefault, - "run_inference_profiler"); + paddle::platform::EventSortingKey::kDefault, "run_inference_profiler"); paddle::platform::ResetProfiler(); } diff --git a/python/paddle/fluid/tests/book/high-level-api/word2vec/no_test_word2vec_new_api.py b/python/paddle/fluid/tests/book/high-level-api/word2vec/test_word2vec_new_api.py similarity index 77% rename from python/paddle/fluid/tests/book/high-level-api/word2vec/no_test_word2vec_new_api.py rename to python/paddle/fluid/tests/book/high-level-api/word2vec/test_word2vec_new_api.py index 6d7495e4dd..bf86cd9acf 100644 --- a/python/paddle/fluid/tests/book/high-level-api/word2vec/no_test_word2vec_new_api.py +++ b/python/paddle/fluid/tests/book/high-level-api/word2vec/test_word2vec_new_api.py @@ -90,7 +90,7 @@ def train_program(is_sparse): return avg_cost -def train(use_cuda, train_program, save_path): +def train(use_cuda, train_program, save_dirname): train_reader = paddle.batch( paddle.dataset.imikolov.train(word_dict, N), BATCH_SIZE) test_reader = paddle.batch( @@ -99,27 +99,36 @@ def train(use_cuda, train_program, save_path): place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace() def event_handler(event): - if isinstance(event, fluid.EndEpochEvent): - outs = trainer.test(reader=test_reader) + if isinstance(event, fluid.EndStepEvent): + outs = trainer.test( + reader=test_reader, + feed_order=['firstw', 'secondw', 'thirdw', 'forthw', 'nextw']) avg_cost = outs[0] print("loss= ", avg_cost) - if avg_cost < 5.0: - trainer.save_params(save_path) - return + if avg_cost < 10.0: + trainer.save_params(save_dirname) + trainer.stop() + if math.isnan(avg_cost): sys.exit("got NaN loss, training failed.") trainer = fluid.Trainer( - train_program, fluid.optimizer.SGD(learning_rate=0.001), place=place) + train_func=train_program, + optimizer=fluid.optimizer.SGD(learning_rate=0.001), + place=place) + trainer.train( - reader=train_reader, num_epochs=1, event_handler=event_handler) + reader=train_reader, + num_epochs=1, + event_handler=event_handler, + feed_order=['firstw', 'secondw', 'thirdw', 'forthw', 'nextw']) -def infer(use_cuda, inference_program, save_path): +def infer(use_cuda, inference_program, save_dirname=None): place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace() inferencer = fluid.Inferencer( - infer_func=inference_program, param_path=save_path, place=place) + infer_func=inference_program, param_path=save_dirname, place=place) lod = [0, 1] first_word = create_random_lodtensor(lod, place, low=0, high=dict_size - 1) @@ -127,12 +136,14 @@ def infer(use_cuda, inference_program, save_path): third_word = create_random_lodtensor(lod, place, low=0, high=dict_size - 1) fourth_word = create_random_lodtensor(lod, place, low=0, high=dict_size - 1) - result = inferencer.infer({ - 'firstw': first_word, - 'secondw': second_word, - 'thirdw': third_word, - 'forthw': fourth_word - }) + result = inferencer.infer( + { + 'firstw': first_word, + 'secondw': second_word, + 'thirdw': third_word, + 'forthw': fourth_word + }, + return_numpy=False) print(np.array(result[0])) @@ -140,9 +151,17 @@ def main(use_cuda, is_sparse): if use_cuda and not fluid.core.is_compiled_with_cuda(): return - save_path = "word2vec.params" - train(use_cuda, partial(train_program, is_sparse), save_path) - infer(use_cuda, partial(inference_program, is_sparse), save_path) + save_path = "word2vec.inference.model" + + train( + use_cuda=use_cuda, + train_program=partial(train_program, is_sparse), + save_dirname=save_path) + + infer( + use_cuda=use_cuda, + inference_program=partial(inference_program, is_sparse), + save_dirname=save_path) if __name__ == '__main__': From 0ad9212d78d26a82e5d9722aad7807b3fede47d1 Mon Sep 17 00:00:00 2001 From: Lei Wang Date: Fri, 18 May 2018 19:04:13 -0700 Subject: [PATCH 23/31] Dockerfile: unify dev and product docker environment. (#10778) * Dockerfile: unify dev and product docker environment. * Fix check style error. * Use envrioment valuable to get version info. --- paddle/scripts/paddle_build.sh | 10 ++++++---- 1 file changed, 6 insertions(+), 4 deletions(-) diff --git a/paddle/scripts/paddle_build.sh b/paddle/scripts/paddle_build.sh index 3efca04a5c..fbe219a1c9 100755 --- a/paddle/scripts/paddle_build.sh +++ b/paddle/scripts/paddle_build.sh @@ -405,17 +405,19 @@ EOF function gen_dockerfile() { # Set BASE_IMAGE according to env variables + CUDA_MAJOR="$(echo $CUDA_VERSION | cut -d '.' -f 1).$(echo $CUDA_VERSION | cut -d '.' -f 2)" + CUDNN_MAJOR=$(echo $CUDNN_VERSION | cut -d '.' -f 1) if [[ ${WITH_GPU} == "ON" ]]; then - BASE_IMAGE="nvidia/cuda:8.0-cudnn5-runtime-ubuntu16.04" + BASE_IMAGE="nvidia/cuda:${CUDA_MAJOR}-cudnn${CUDNN_MAJOR}-runtime-ubuntu16.04" else - BASE_IMAGE="ubuntu:16.04" + BASE_IMAGE="ubuntu:16.04" fi DOCKERFILE_GPU_ENV="" DOCKERFILE_CUDNN_DSO="" if [[ ${WITH_GPU:-OFF} == 'ON' ]]; then DOCKERFILE_GPU_ENV="ENV LD_LIBRARY_PATH /usr/lib/x86_64-linux-gnu:\${LD_LIBRARY_PATH}" - DOCKERFILE_CUDNN_DSO="RUN ln -s /usr/lib/x86_64-linux-gnu/libcudnn.so.5 /usr/lib/x86_64-linux-gnu/libcudnn.so" + DOCKERFILE_CUDNN_DSO="RUN ln -s /usr/lib/x86_64-linux-gnu/libcudnn.so.${CUDNN_MAJOR} /usr/lib/x86_64-linux-gnu/libcudnn.so" fi cat < Date: Sun, 20 May 2018 18:34:03 +0800 Subject: [PATCH 24/31] Expose prior_box op into detection.py (#10773) * package prior_box op * add doc * add unittest * add unittest * fix CI fails --- python/paddle/fluid/layers/detection.py | 141 +++++++++++++------- python/paddle/fluid/tests/test_detection.py | 18 +++ 2 files changed, 114 insertions(+), 45 deletions(-) diff --git a/python/paddle/fluid/layers/detection.py b/python/paddle/fluid/layers/detection.py index a5938fe494..b33adf55cf 100644 --- a/python/paddle/fluid/layers/detection.py +++ b/python/paddle/fluid/layers/detection.py @@ -23,6 +23,7 @@ import nn import math __all__ = [ + 'prior_box', 'multi_box_head', 'bipartite_match', 'target_assign', @@ -564,6 +565,98 @@ def ssd_loss(location, return loss +def prior_box(input, + image, + min_sizes, + max_sizes=None, + aspect_ratios=None, + variance=[0.1, 0.1, 0.2, 0.2], + flip=False, + clip=False, + steps=[0.0, 0.0], + offset=0.5, + name=None): + """ + **Prior box operator** + + Generate prior boxes for SSD(Single Shot MultiBox Detector) algorithm. + Each position of the input produce N prior boxes, N is determined by + the count of min_sizes, max_sizes and aspect_ratios, The size of the + box is in range(min_size, max_size) interval, which is generated in + sequence according to the aspect_ratios. + + Args: + input(Variable): The Input Variables, the format is NCHW. + image(Variable): The input image data of PriorBoxOp, + the layout is NCHW. + min_sizes(list|tuple): min sizes of generated prior boxes. + max_sizes(list|tuple|None): max sizes of generated prior boxes. + Default: None. + aspect_ratios(list|tuple): the aspect ratios of generated prior + boxes. Default: None. + variance(list|tuple): the variances to be encoded in prior boxes. + Default:[0.1, 0.1, 0.2, 0.2]. + flip(bool): Whether to flip aspect ratios. Default:False. + clip(bool): Whether to clip out-of-boundary boxes. Default: False. + step(list|turple): Prior boxes step across weight and height, If + step[0] == 0.0/step[1] == 0.0, the prior boxes step across + height/weight of the input will be automatically calculated. + Default: [0.0] + offset(float): Prior boxes center offset. Default: 0.5 + name(str): Name of the prior box op. Default: None. + + Returns: + boxes(Variable): the output prior boxes of PriorBox. + The layout is [H, W, num_priors, 4]. + H is the height of input, W is the width of input, + num_priors is the total + box count of each position of input. + Variances(Variable): the expanded variances of PriorBox. + The layout is [H, W, num_priors, 4]. + H is the height of input, W is the width of input + num_priors is the total + box count of each position of input + + + Examples: + .. code-block:: python + box, var = prior_box( + input=conv1, + image=images, + min_sizes=[100.], + flip=True, + clip=True) + """ + helper = LayerHelper("prior_box", **locals()) + dtype = helper.input_dtype() + + attrs = { + 'min_sizes': min_sizes, + 'aspect_ratios': aspect_ratios, + 'variances': variance, + 'flip': flip, + 'clip': clip, + 'step_w': steps[0], + 'step_h': steps[1], + 'offset': offset + } + if max_sizes is not None and len(max_sizes) > 0 and max_sizes[0] > 0: + attrs['max_sizes'] = max_sizes + + box = helper.create_tmp_variable(dtype) + var = helper.create_tmp_variable(dtype) + helper.append_op( + type="prior_box", + inputs={"Input": input, + "Image": image}, + outputs={"Boxes": box, + "Variances": var}, + attrs=attrs, ) + box.stop_gradient = True + var.stop_gradient = True + return box, var + + def multi_box_head(inputs, image, base_size, @@ -660,47 +753,6 @@ def multi_box_head(inputs, clip=True) """ - def _prior_box_(input, - image, - min_sizes, - max_sizes, - aspect_ratios, - variance, - flip=False, - clip=False, - step_w=0.0, - step_h=0.0, - offset=0.5, - name=None): - helper = LayerHelper("prior_box", **locals()) - dtype = helper.input_dtype() - - attrs = { - 'min_sizes': min_sizes, - 'aspect_ratios': aspect_ratios, - 'variances': variance, - 'flip': flip, - 'clip': clip, - 'step_w': step_w, - 'step_h': step_h, - 'offset': offset - } - if len(max_sizes) > 0 and max_sizes[0] > 0: - attrs['max_sizes'] = max_sizes - - box = helper.create_tmp_variable(dtype) - var = helper.create_tmp_variable(dtype) - helper.append_op( - type="prior_box", - inputs={"Input": input, - "Image": image}, - outputs={"Boxes": box, - "Variances": var}, - attrs=attrs, ) - box.stop_gradient = True - var.stop_gradient = True - return box, var - def _reshape_with_axis_(input, axis=1): if not (axis > 0 and axis < len(input.shape)): raise ValueError("The axis should be smaller than " @@ -777,11 +829,10 @@ def multi_box_head(inputs, aspect_ratio = aspect_ratios[i] if not _is_list_or_tuple_(aspect_ratio): aspect_ratio = [aspect_ratio] + step = [step_w[i] if step_w else 0.0, step_h[i] if step_w else 0.0] - box, var = _prior_box_(input, image, min_size, max_size, aspect_ratio, - variance, flip, clip, step_w[i] - if step_w else 0.0, step_h[i] - if step_w else 0.0, offset) + box, var = prior_box(input, image, min_size, max_size, aspect_ratio, + variance, flip, clip, step, offset) box_results.append(box) var_results.append(var) diff --git a/python/paddle/fluid/tests/test_detection.py b/python/paddle/fluid/tests/test_detection.py index 921260ef3f..8569d838bd 100644 --- a/python/paddle/fluid/tests/test_detection.py +++ b/python/paddle/fluid/tests/test_detection.py @@ -109,6 +109,24 @@ class TestDetection(unittest.TestCase): print(str(program)) +class TestPriorBox(unittest.TestCase): + def test_prior_box(self): + data_shape = [3, 224, 224] + images = fluid.layers.data( + name='pixel', shape=data_shape, dtype='float32') + conv1 = fluid.layers.conv2d(images, 3, 3, 2) + box, var = layers.prior_box( + input=conv1, + image=images, + min_sizes=[100.0], + aspect_ratios=[1.], + flip=True, + clip=True) + assert len(box.shape) == 4 + assert box.shape == var.shape + assert box.shape[3] == 4 + + class TestMultiBoxHead(unittest.TestCase): def test_multi_box_head(self): data_shape = [3, 224, 224] From 0e4467eee40a0b31bacec57e2dd46623af40143d Mon Sep 17 00:00:00 2001 From: dzhwinter Date: Mon, 21 May 2018 10:18:58 +0800 Subject: [PATCH 25/31] "fix compile" (#10657) --- paddle/fluid/operators/beam_search_op.h | 4 ---- paddle/fluid/platform/CMakeLists.txt | 2 +- 2 files changed, 1 insertion(+), 5 deletions(-) diff --git a/paddle/fluid/operators/beam_search_op.h b/paddle/fluid/operators/beam_search_op.h index 9b51db8a45..46bc4f6f93 100644 --- a/paddle/fluid/operators/beam_search_op.h +++ b/paddle/fluid/operators/beam_search_op.h @@ -14,10 +14,6 @@ limitations under the License. */ #pragma once -#ifdef PADDLE_WITH_TESTING -#include "gtest/gtest.h" -#endif - #include #include #include "paddle/fluid/framework/lod_tensor.h" diff --git a/paddle/fluid/platform/CMakeLists.txt b/paddle/fluid/platform/CMakeLists.txt index 79e3c26fef..b29035bafd 100644 --- a/paddle/fluid/platform/CMakeLists.txt +++ b/paddle/fluid/platform/CMakeLists.txt @@ -49,7 +49,7 @@ nv_test(device_context_test SRCS device_context_test.cu DEPS device_context gpu_ nv_test(cudnn_helper_test SRCS cudnn_helper_test.cc DEPS dynload_cuda) nv_test(transform_test SRCS transform_test.cu DEPS memory place device_context) -cc_library(device_tracer SRCS device_tracer.cc DEPS boost profiler_proto ${GPU_CTX_DEPS}) +cc_library(device_tracer SRCS device_tracer.cc DEPS boost profiler_proto framework_proto ${GPU_CTX_DEPS}) cc_library(profiler SRCS profiler.cc DEPS device_context device_tracer) cc_test(profiler_test SRCS profiler_test.cc DEPS profiler) From 7ae03ec08b1d2699fa6520bedd7b20dd4fc02f54 Mon Sep 17 00:00:00 2001 From: Yancey Date: Mon, 21 May 2018 10:33:03 +0800 Subject: [PATCH 26/31] fix lack split_byref op in parallel executor (#10770) --- paddle/fluid/framework/details/multi_devices_graph_builder.cc | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/paddle/fluid/framework/details/multi_devices_graph_builder.cc b/paddle/fluid/framework/details/multi_devices_graph_builder.cc index 45bad58145..6b0c0a6b9f 100644 --- a/paddle/fluid/framework/details/multi_devices_graph_builder.cc +++ b/paddle/fluid/framework/details/multi_devices_graph_builder.cc @@ -98,7 +98,7 @@ bool MultiDevSSAGraphBuilder::IsDistTrainOp(const OpDesc &op, return false; }; - if (op.Type() == "split") { + if (op.Type() == "split" || op.Type() == "split_byref") { return checker(op.OutputArgumentNames(), send_op->InputArgumentNames()); } else if (op.Type() == "concat") { return checker(op.InputArgumentNames(), send_op->OutputArgumentNames()); From 1bd0197b5ae4e46f91f19b25d4c90d3924387916 Mon Sep 17 00:00:00 2001 From: Shan Yi <35982308+shanyi15@users.noreply.github.com> Date: Mon, 21 May 2018 10:59:17 +0800 Subject: [PATCH 27/31] Update cpu_profiling_cn.md --- doc/fluid/howto/optimization/cpu_profiling_cn.md | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/doc/fluid/howto/optimization/cpu_profiling_cn.md b/doc/fluid/howto/optimization/cpu_profiling_cn.md index 8266dec3c6..198a05a79e 100644 --- a/doc/fluid/howto/optimization/cpu_profiling_cn.md +++ b/doc/fluid/howto/optimization/cpu_profiling_cn.md @@ -1,3 +1,5 @@ +# CPU性能调优 + 此教程会介绍如何使用Python的cProfile包、Python库yep、Google perftools来进行性能分析 (profiling) 与调优（performance tuning）。 Profling 指发现性能瓶颈。系统中的瓶颈可能和程序员开发过程中想象的瓶颈相去甚远。Tuning 指消除瓶颈。性能优化的过程通常是不断重复地 profiling 和 tuning。 @@ -8,7 +10,7 @@ PaddlePaddle 用户一般通过调用 Python API 编写深度学习程序。大 * Python 与 C++ 混合代码的性能分析 -# Python代码的性能分析 +## Python代码的性能分析 ### 生成性能分析文件 From 60f4b73aaa2be72df5f4e8082b3a9e1e295b1b84 Mon Sep 17 00:00:00 2001 From: Shan Yi <35982308+shanyi15@users.noreply.github.com> Date: Mon, 21 May 2018 11:02:59 +0800 Subject: [PATCH 28/31] Update cpu_profiling_en.md --- doc/fluid/howto/optimization/cpu_profiling_en.md | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/doc/fluid/howto/optimization/cpu_profiling_en.md b/doc/fluid/howto/optimization/cpu_profiling_en.md index e95556dd60..216694965b 100644 --- a/doc/fluid/howto/optimization/cpu_profiling_en.md +++ b/doc/fluid/howto/optimization/cpu_profiling_en.md @@ -1,3 +1,5 @@ +# Tune CPU performance + This tutorial introduces techniques we use to profile and tune the CPU performance of PaddlePaddle. We will use Python packages `cProfile` and `yep`, and Google's `perftools`. @@ -14,7 +16,7 @@ the profiling and tuning of 1. the Python code and 1. the mixture of Python and C++ code. -# Profiling the Python Code +## Profiling the Python Code ### Generate the Performance Profiling File From 5828101c239fa51f85eb34caeb942e2df92467e6 Mon Sep 17 00:00:00 2001 From: dzhwinter Date: Mon, 21 May 2018 15:11:17 +0800 Subject: [PATCH 29/31] make uint8 support in data_type transform and memory optimize (#10715) * "a piece of job." * "fix typeo" * "fix ci" --- paddle/fluid/framework/data_type_transform.cc | 6 ++++++ paddle/fluid/pybind/protobuf.cc | 1 + python/paddle/fluid/framework.py | 2 ++ .../fluid/transpiler/memory_optimization_transpiler.py | 3 ++- 4 files changed, 11 insertions(+), 1 deletion(-) diff --git a/paddle/fluid/framework/data_type_transform.cc b/paddle/fluid/framework/data_type_transform.cc index c0523f3c79..5a57ec2058 100644 --- a/paddle/fluid/framework/data_type_transform.cc +++ b/paddle/fluid/framework/data_type_transform.cc @@ -91,6 +91,12 @@ void TransDataType(const OpKernelType& kernel_type_for_var, case proto::VarType::BOOL: framework::VisitDataType(dst_type, CastDataType(in, out, ctx)); break; + case proto::VarType::INT16: + framework::VisitDataType(dst_type, CastDataType(in, out, ctx)); + break; + case proto::VarType::UINT8: + framework::VisitDataType(dst_type, CastDataType(in, out, ctx)); + break; default: PADDLE_THROW("Not support type %d", src_type); } diff --git a/paddle/fluid/pybind/protobuf.cc b/paddle/fluid/pybind/protobuf.cc index 6471eb3ab7..bcf6d4dd30 100644 --- a/paddle/fluid/pybind/protobuf.cc +++ b/paddle/fluid/pybind/protobuf.cc @@ -238,6 +238,7 @@ void BindVarDsec(pybind11::module *m) { pybind11::enum_(var_desc, "VarType", "") .value("BOOL", pd::proto::VarType::BOOL) + .value("UINT8", pd::proto::VarType::UINT8) .value("INT16", pd::proto::VarType::INT16) .value("INT32", pd::proto::VarType::INT32) .value("INT64", pd::proto::VarType::INT64) diff --git a/python/paddle/fluid/framework.py b/python/paddle/fluid/framework.py index 38c765938f..161ea55586 100644 --- a/python/paddle/fluid/framework.py +++ b/python/paddle/fluid/framework.py @@ -72,6 +72,8 @@ def convert_np_dtype_to_dtype_(np_dtype): return core.VarDesc.VarType.INT64 elif dtype == np.bool: return core.VarDesc.VarType.BOOL + elif dtype == np.uint8: + return core.VarDesc.VarType.UINT8 else: raise ValueError("Not supported numpy dtype " + str(dtype)) diff --git a/python/paddle/fluid/transpiler/memory_optimization_transpiler.py b/python/paddle/fluid/transpiler/memory_optimization_transpiler.py index 49034b47b2..80a8f7c09c 100644 --- a/python/paddle/fluid/transpiler/memory_optimization_transpiler.py +++ b/python/paddle/fluid/transpiler/memory_optimization_transpiler.py @@ -24,7 +24,8 @@ dtype_to_size = { core.VarDesc.VarType.INT16: 2, core.VarDesc.VarType.INT32: 4, core.VarDesc.VarType.INT64: 8, - core.VarDesc.VarType.BOOL: 1 + core.VarDesc.VarType.BOOL: 1, + core.VarDesc.VarType.UINT8: 1, } SUB_BLOCK_OPS = [ From 9ff6715f8a51af81e1aaaea3388c406900b25f37 Mon Sep 17 00:00:00 2001 From: Qingsheng Li Date: Mon, 21 May 2018 15:27:17 +0800 Subject: [PATCH 30/31] Enhanced is_empty_op for our seq2seq model (#10704) * Added kernel to is_empty_op * Added python API * Updated code as required * Updated unittests --- paddle/fluid/operators/is_empty_op.cc | 57 ++++++++++--------- paddle/fluid/operators/is_empty_op.h | 37 ++++++++++++ python/paddle/fluid/layers/control_flow.py | 38 +++++++++++++ .../fluid/tests/unittests/test_is_empty_op.py | 42 ++++---------- 4 files changed, 117 insertions(+), 57 deletions(-) create mode 100644 paddle/fluid/operators/is_empty_op.h diff --git a/paddle/fluid/operators/is_empty_op.cc b/paddle/fluid/operators/is_empty_op.cc index d3f3ad9244..29b73951bb 100644 --- a/paddle/fluid/operators/is_empty_op.cc +++ b/paddle/fluid/operators/is_empty_op.cc @@ -12,45 +12,41 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. */ +#include "paddle/fluid/operators/is_empty_op.h" #include "paddle/fluid/framework/op_registry.h" #include "paddle/fluid/framework/operator.h" namespace paddle { namespace operators { -constexpr char kInput[] = "X"; -constexpr char kOutput[] = "Out"; - -class IsEmptyOp : public framework::OperatorBase { +class IsEmptyOp : public framework::OperatorWithKernel { public: - IsEmptyOp(const std::string &type, const framework::VariableNameMap &inputs, - const framework::VariableNameMap &outputs, - const framework::AttributeMap &attrs) - : OperatorBase(type, inputs, outputs, attrs) {} + using framework::OperatorWithKernel::OperatorWithKernel; - private: - void RunImpl(const framework::Scope &scope, - const platform::Place &place) const override { - // get input - auto *var = scope.FindVar(Input(kInput)); - PADDLE_ENFORCE_NOT_NULL(var); - auto &tensor = var->Get(); - // get output - auto *out = scope.FindVar(Output(kOutput)); - PADDLE_ENFORCE_NOT_NULL(out); - auto *out_tensor = out->GetMutable(); + protected: + void InferShape(framework::InferShapeContext *ctx) const override { + PADDLE_ENFORCE(ctx->HasInput("X"), + "Input(X) of IsEmptyOp should not be null."); + PADDLE_ENFORCE(ctx->HasOutput("Out"), + "Output(Out) of IsEmptyOp should not be null."); + ctx->SetOutputDim("Out", {1}); + } - out_tensor->Resize({1}); - out_tensor->mutable_data(platform::CPUPlace())[0] = - framework::product(tensor.dims()) == 0; + framework::OpKernelType GetExpectedKernelType( + const framework::ExecutionContext &ctx) const override { + framework::OpKernelType kt = framework::OpKernelType( + framework::ToDataType(ctx.Input("X")->type()), + platform::CPUPlace()); + return kt; } }; -class IsEmptyOpProtoMaker : public framework::OpProtoAndCheckerMaker { +class IsEmptyOpMaker : public framework::OpProtoAndCheckerMaker { public: void Make() override { - AddInput(kInput, "(Tensor) Tensor which is to be checked."); - AddOutput(kOutput, "(Tensor) a boolean Tensor that indicate empty or not."); + AddInput("X", "(LoDTensor) Tensor which is to be checked."); + AddOutput("Out", + "(LoDTensor) a boolean Tensor that indicate empty or not."); AddComment(R"DOC( IsEmpty Operator which checks whether a tensor is empty. @@ -62,5 +58,12 @@ It will just return product(tensor.ddims()) > 0; } // namespace operators } // namespace paddle -REGISTER_OP_WITHOUT_GRADIENT(is_empty, paddle::operators::IsEmptyOp, - paddle::operators::IsEmptyOpProtoMaker); +namespace ops = paddle::operators; + +REGISTER_OPERATOR(is_empty, ops::IsEmptyOp, ops::IsEmptyOpMaker, + paddle::framework::EmptyGradOpMaker); +REGISTER_OP_CPU_KERNEL( + is_empty, ops::IsEmptyOpKernel, + ops::IsEmptyOpKernel, + ops::IsEmptyOpKernel, + ops::IsEmptyOpKernel); diff --git a/paddle/fluid/operators/is_empty_op.h b/paddle/fluid/operators/is_empty_op.h new file mode 100644 index 0000000000..3e3af22fa8 --- /dev/null +++ b/paddle/fluid/operators/is_empty_op.h @@ -0,0 +1,37 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ + +#pragma once +#include "paddle/fluid/framework/op_registry.h" +#include "paddle/fluid/framework/operator.h" + +namespace paddle { +namespace operators { + +template +class IsEmptyOpKernel : public framework::OpKernel { + public: + void Compute(const framework::ExecutionContext& context) const override { + // get input + auto* input_tensor = context.Input("X"); + // get output + auto* output_tensor = context.Output("Out"); + + output_tensor->mutable_data(platform::CPUPlace())[0] = + framework::product(input_tensor->dims()) == 0; + } +}; + +} // namespace operators +} // namespace paddle diff --git a/python/paddle/fluid/layers/control_flow.py b/python/paddle/fluid/layers/control_flow.py index 4b707973e2..dee4144808 100644 --- a/python/paddle/fluid/layers/control_flow.py +++ b/python/paddle/fluid/layers/control_flow.py @@ -49,6 +49,7 @@ __all__ = [ 'reorder_lod_tensor_by_rank', 'ParallelDo', 'Print', + 'is_empty', ] @@ -1562,3 +1563,40 @@ def reorder_lod_tensor_by_rank(x, rank_table): 'RankTable': [rank_table]}, outputs={'Out': [out]}) return out + + +def is_empty(x, cond=None, **ignored): + """ + **Is Empty** + + This layer returns the truth value of whether the variable is empty. + + Args: + x(Variable): Operand of *is_empty* + cond(Variable|None): Optional output variable to store the result + of *is_empty* + + Returns: + Variable: The tensor variable storing the output of *is_empty*. + + Raises: + TypeError: If input cond is not a variable, or cond's dtype is + not bool + + Examples: + .. code-block:: python + + less = fluid.layers.is_empty(x=input) + """ + helper = LayerHelper("is_empty", **locals()) + if cond is None: + cond = helper.create_tmp_variable(dtype='bool') + cond.stop_gradient = True + elif not isinstance(cond, Variable): + raise TypeError("cond takes a variable") + elif cond.dtype != 'bool': + raise TypeError("The data type of cond must be bool") + + helper.append_op( + type='is_empty', inputs={'X': [x]}, outputs={'Out': [cond]}) + return cond diff --git a/python/paddle/fluid/tests/unittests/test_is_empty_op.py b/python/paddle/fluid/tests/unittests/test_is_empty_op.py index 4d11cf226b..11121d9b65 100644 --- a/python/paddle/fluid/tests/unittests/test_is_empty_op.py +++ b/python/paddle/fluid/tests/unittests/test_is_empty_op.py @@ -14,42 +14,24 @@ import unittest import numpy as np -from paddle.fluid.op import Operator -import paddle.fluid.core as core +from op_test import OpTest -def create_tensor(scope, name, np_data): - tensor = scope.var(name).get_tensor() - tensor.set_dims(np_data.shape) - tensor.set(np_data, core.CPUPlace()) - return tensor - - -class TestIsEmptyOp(unittest.TestCase): +class TestEmpty(OpTest): def setUp(self): - self.scope = core.Scope() - # create input variables - np_data0 = np.array([0, 1, 2]) - create_tensor(self.scope, "X0", np_data0) - - np_data1 = np.array([1]) - t = create_tensor(self.scope, "X1", np_data1) - t.set_dims([0]) + self.op_type = "is_empty" + self.inputs = {'X': np.array([1, 2, 3])} + self.outputs = {'Out': np.array([False])} - # create output variables - self.scope.var("out") + def test_check_output(self): + self.check_output() - def test_no_empty(self): - self.one_case("X0", False) - def test_empty(self): - self.one_case("X1", True) - - def one_case(self, input, target): - op = Operator(type="is_empty", X=input, Out="out") - op.run(self.scope, core.CPUPlace()) - out = self.scope.var("out").get_tensor() - self.assertEqual(np.array(out)[0], target) +class TestNotEmpty(TestEmpty): + def setUp(self): + self.op_type = "is_empty" + self.inputs = {'X': np.array([])} + self.outputs = {'Out': np.array([True])} if __name__ == "__main__": From 35e5563695ac9a227a1d78965b417ee45202b457 Mon Sep 17 00:00:00 2001 From: Yancey Date: Mon, 21 May 2018 15:37:43 +0800 Subject: [PATCH 31/31] fix wheel package name (#10697) * fix wheel package name * delete cuda7.5 cudnn5 --- doc/v2/build_and_install/pip_install_cn.rst | 11 +++++------ doc/v2/build_and_install/pip_install_en.rst | 11 +++++------ 2 files changed, 10 insertions(+), 12 deletions(-) diff --git a/doc/v2/build_and_install/pip_install_cn.rst b/doc/v2/build_and_install/pip_install_cn.rst index b3d8827437..aa1dc6ee2c 100644 --- a/doc/v2/build_and_install/pip_install_cn.rst +++ b/doc/v2/build_and_install/pip_install_cn.rst @@ -37,12 +37,11 @@ PaddlePaddle可以使用常用的Python包管理工具 :header: "版本说明", "cp27-cp27mu", "cp27-cp27m" :widths: 1, 3, 3 - "cpu_avx_mkl", "`paddlepaddle-0.11.0-cp27-cp27mu-linux_x86_64.whl `_", "`paddlepaddle-0.11.0-cp27-cp27m-linux_x86_64.whl `_" - "cpu_avx_openblas", "`paddlepaddle-0.11.0-cp27-cp27mu-linux_x86_64.whl `_", "`paddlepaddle-0.11.0-cp27-cp27m-linux_x86_64.whl `_" - "cpu_noavx_openblas", "`paddlepaddle-0.11.0-cp27-cp27mu-linux_x86_64.whl `_", "`paddlepaddle-0.11.0-cp27-cp27m-linux_x86_64.whl `_" - "cuda7.5_cudnn5_avx_mkl", "`paddlepaddle_gpu-0.11.0-cp27-cp27mu-linux_x86_64.whl `_", "`paddlepaddle_gpu-0.11.0-cp27-cp27m-linux_x86_64.whl `_" - "cuda8.0_cudnn5_avx_mkl", "`paddlepaddle_gpu-0.11.0-cp27-cp27mu-linux_x86_64.whl `_", "`paddlepaddle_gpu-0.11.0-cp27-cp27m-linux_x86_64.whl `_" - "cuda8.0_cudnn7_avx_mkl", "`paddlepaddle_gpu-0.11.0-cp27-cp27mu-linux_x86_64.whl `_", "`paddlepaddle_gpu-0.11.0-cp27-cp27m-linux_x86_64.whl `_" + "cpu_avx_mkl", "`paddlepaddle-latest-cp27-cp27mu-linux_x86_64.whl `_", "`paddlepaddle-latest-cp27-cp27m-linux_x86_64.whl `_" + "cpu_avx_openblas", "`paddlepaddle-latest-cp27-cp27mu-linux_x86_64.whl `_", "`paddlepaddle-latest-cp27-cp27m-linux_x86_64.whl `_" + "cpu_noavx_openblas", "`paddlepaddle-latest-cp27-cp27mu-linux_x86_64.whl `_", "`paddlepaddle-latest-cp27-cp27m-linux_x86_64.whl `_" + "cuda8.0_cudnn5_avx_mkl", "`paddlepaddle_gpu-latest-cp27-cp27mu-linux_x86_64.whl `_", "`paddlepaddle_gpu-latest-cp27-cp27m-linux_x86_64.whl `_" + "cuda8.0_cudnn7_avx_mkl", "`paddlepaddle_gpu-latest-cp27-cp27mu-linux_x86_64.whl `_", "`paddlepaddle_gpu-latest-cp27-cp27m-linux_x86_64.whl `_" .. _pip_dependency: diff --git a/doc/v2/build_and_install/pip_install_en.rst b/doc/v2/build_and_install/pip_install_en.rst index 1e409d86b9..a70821eb48 100644 --- a/doc/v2/build_and_install/pip_install_en.rst +++ b/doc/v2/build_and_install/pip_install_en.rst @@ -40,12 +40,11 @@ If the links below shows up the login form, just click "Log in as guest" to star :header: "version", "cp27-cp27mu", "cp27-cp27m" :widths: 1, 3, 3 - "cpu_avx_mkl", "`paddlepaddle-0.11.0-cp27-cp27mu-linux_x86_64.whl `_", "`paddlepaddle-0.11.0-cp27-cp27m-linux_x86_64.whl `_" - "cpu_avx_openblas", "`paddlepaddle-0.11.0-cp27-cp27mu-linux_x86_64.whl `_", "`paddlepaddle-0.11.0-cp27-cp27m-linux_x86_64.whl `_" - "cpu_noavx_openblas", "`paddlepaddle-0.11.0-cp27-cp27mu-linux_x86_64.whl `_", "`paddlepaddle-0.11.0-cp27-cp27m-linux_x86_64.whl `_" - "cuda7.5_cudnn5_avx_mkl", "`paddlepaddle_gpu-0.11.0-cp27-cp27mu-linux_x86_64.whl `_", "`paddlepaddle_gpu-0.11.0-cp27-cp27m-linux_x86_64.whl `_" - "cuda8.0_cudnn5_avx_mkl", "`paddlepaddle_gpu-0.11.0-cp27-cp27mu-linux_x86_64.whl `_", "`paddlepaddle_gpu-0.11.0-cp27-cp27m-linux_x86_64.whl `_" - "cuda8.0_cudnn7_avx_mkl", "`paddlepaddle_gpu-0.11.0-cp27-cp27mu-linux_x86_64.whl `_", "`paddlepaddle_gpu-0.11.0-cp27-cp27m-linux_x86_64.whl `_" + "cpu_avx_mkl", "`paddlepaddle-latest-cp27-cp27mu-linux_x86_64.whl `_", "`paddlepaddle-latest-cp27-cp27m-linux_x86_64.whl `_" + "cpu_avx_openblas", "`paddlepaddle-latest-cp27-cp27mu-linux_x86_64.whl `_", "`paddlepaddle-latest-cp27-cp27m-linux_x86_64.whl `_" + "cpu_noavx_openblas", "`paddlepaddle-latest-cp27-cp27mu-linux_x86_64.whl `_", "`paddlepaddle-latest-cp27-cp27m-linux_x86_64.whl `_" + "cuda8.0_cudnn5_avx_mkl", "`paddlepaddle_gpu-latest-cp27-cp27mu-linux_x86_64.whl `_", "`paddlepaddle_gpu-latest-cp27-cp27m-linux_x86_64.whl `_" + "cuda8.0_cudnn7_avx_mkl", "`paddlepaddle_gpu-latest-cp27-cp27mu-linux_x86_64.whl `_", "`paddlepaddle_gpu-latest-cp27-cp27m-linux_x86_64.whl `_" .. _pip_dependency: