!5928 [MS][LITE]optimize interface and data structure
Merge pull request !5928 from zhaizhiqiang/masterpull/5928/MERGE
mindspore-ci-bot
5 years ago
committed by
Gitee
commit
c621f6f751
@ -0,0 +1,31 @@
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cmake_minimum_required(VERSION 3.14)
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project (Lite_Internal)
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set(TOP_DIR ${CMAKE_CURRENT_SOURCE_DIR}/../)
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include_directories(${TOP_DIR})
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file(GLOB_RECURSE C_SRC ${CMAKE_CURRENT_SOURCE_DIR}/*.cc)
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file(GLOB KERNEL_SRC
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${CMAKE_CURRENT_SOURCE_DIR}/../nnacl/*.c
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${CMAKE_CURRENT_SOURCE_DIR}/../nnacl/fp32/*.c
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${CMAKE_CURRENT_SOURCE_DIR}/../nnacl/int8/*.c
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${CMAKE_CURRENT_SOURCE_DIR}/../nnacl/quantization/*.c
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)
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list(REMOVE_ITEM KERNEL_SRC ${CMAKE_CURRENT_SOURCE_DIR}/../nnacl/opt_op_handler.c)
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set(CCSRC
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${TOP_DIR}/src/common/log_adapter.cc
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${TOP_DIR}/src/runtime/allocator.cc
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${CMAKE_CURRENT_SOURCE_DIR}/../../core/gvar/logging_level.cc
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)
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if (PLATFORM_ARM64)
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# assembly
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file(GLOB ASSEMBLY_SRC ${CMAKE_CURRENT_SOURCE_DIR}/../nnacl/assembly/arm64/*.s
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${CMAKE_CURRENT_SOURCE_DIR}/../nnacl/assembly/arm64/*.S)
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set_property(SOURCE ${ASSEMBLY_SRC} PROPERTY LANGUAGE C)
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set(KERNEL_SRC ${KERNEL_SRC} ${ASSEMBLY_SRC})
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add_library(mslite_internal SHARED ${C_SRC} ${CCSRC} ${KERNEL_SRC})
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target_link_libraries(mslite_internal log)
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endif()
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@ -0,0 +1,40 @@
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/**
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* Copyright 2020 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#ifndef MINDSPORE_LITE_INTERNAL_INCLUDE_CONTEXT_H_
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#define MINDSPORE_LITE_INTERNAL_INCLUDE_CONTEXT_H_
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/// \brief CpuBindMode defined for holding bind cpu strategy argument.
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typedef enum {
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MID_CPU = -1, /**< bind middle cpu first */
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HIGHER_CPU = 1, /**< bind higher cpu first */
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NO_BIND = 0 /**< no bind */
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} CpuBindMode;
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/// \brief DeviceType defined for holding user's preferred backend.
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typedef enum {
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DT_CPU, /**< CPU device type */
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DT_GPU, /**< GPU device type */
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DT_NPU /**< NPU device type, not supported yet */
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} DeviceType;
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/// \brief Context defined for holding environment variables during runtime.
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typedef struct {
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bool float16_priority = false; /**< prior enable float16 inference */
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DeviceType device_type_ = DT_CPU;
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int thread_num_ = 2; /**< thread number config for thread pool */
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} Context;
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#endif // MINDSPORE_LITE_INCLUDE_CONTEXT_H_
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@ -0,0 +1,55 @@
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/**
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* Copyright 2020 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#ifndef MINDSPORE_LITE_INTERNAL_INCLUDE_ERRORCODE_H_
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#define MINDSPORE_LITE_INTERNAL_INCLUDE_ERRORCODE_H_
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/// \brief STATUS defined for holding error code in MindSpore Lite.
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using STATUS = int;
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/* Success */
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constexpr int RET_OK = 0; /**< No error occurs. */
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/* Common error code, range: [-1, -100]*/
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constexpr int RET_ERROR = -1; /**< Common error code. */
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constexpr int RET_NULL_PTR = -2; /**< NULL pointer returned.*/
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constexpr int RET_PARAM_INVALID = -3; /**< Invalid parameter.*/
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constexpr int RET_NO_CHANGE = -4; /**< No change. */
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constexpr int RET_SUCCESS_EXIT = -5; /**< No error but exit. */
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constexpr int RET_MEMORY_FAILED = -6; /**< Fail to create memory. */
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/* Executor error code, range: [-101,-200] */
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constexpr int RET_OUT_OF_TENSOR_RANGE = -101; /**< Failed to check range. */
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constexpr int RET_INPUT_TENSOR_ERROR = -102; /**< Failed to check input tensor. */
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constexpr int RET_REENTRANT_ERROR = -103; /**< Exist executor running. */
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/* Graph error code, range: [-201,-300] */
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constexpr int RET_GRAPH_FILE_ERR = -201; /**< Failed to verify graph file. */
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/* Node error code, range: [-301,-400] */
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constexpr int RET_NOT_FIND_OP = -301; /**< Failed to find operator. */
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constexpr int RET_INVALID_OP_NAME = -302; /**< Invalid operator name. */
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constexpr int RET_INVALID_OP_ATTR = -303; /**< Invalid operator attr. */
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constexpr int RET_OP_EXECUTE_FAILURE = -304; /**< Failed to execution operator. */
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/* Tensor error code, range: [-401,-500] */
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constexpr int RET_FORMAT_ERR = -401; /**< Failed to checking tensor format. */
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/* InferShape error code, range: [-501,-600] */
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constexpr int RET_INFER_ERR = -501; /**< Failed to infer shape. */
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constexpr int RET_INFER_INVALID = -502; /**< Invalid infer shape before runtime. */
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#endif // MINDSPORE_LITE_INCLUDE_ERRORCODE_H_
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@ -0,0 +1,90 @@
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/**
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* Copyright 2020 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#ifndef MINDSPORE_LITE_INTERNAL_INCLUDE_LITE_SESSION_H
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#define MINDSPORE_LITE_INTERNAL_INCLUDE_LITE_SESSION_H
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#include "internal/include/ms_tensor.h"
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#include "internal/include/model.h"
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#include "internal/include/context.h"
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#include "internal/include/lite_utils.h"
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/// \brief LiteSession defined session in MindSpore Lite for compiling Model and forwarding model.
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typedef struct LiteSession {
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/// \brief Static method to create a LiteSession pointer.
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///
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/// \param[in] context Define the context of session to be created.
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///
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/// \return Pointer of MindSpore Lite LiteSession.
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static LiteSession *CreateSession(Context *context);
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/// \brief Compile MindSpore Lite model.
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///
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/// \note CompileGraph should be called before RunGraph.
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///
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/// \param[in] model Define the model to be compiled.
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///
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/// \return STATUS as an error code of compiling graph, STATUS is defined in errorcode.h.
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int CompileGraph(Model *model);
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/// \brief Get input MindSpore Lite MSTensors of model.
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///
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/// \return The vector of MindSpore Lite MSTensor.
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TensorPtrVector GetInputs() const;
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/// \brief Get input MindSpore Lite MSTensors of model by node name.
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///
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/// \param[in] node_name Define node name.
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///
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/// \return The vector of MindSpore Lite MSTensor.
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TensorPtrVector GetInputsByName(const String &node_name) const;
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/// \brief Get output MindSpore Lite MSTensors of model by node name.
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///
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/// \param[in] node_name Define node name.
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///
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/// \return The vector of MindSpore Lite MSTensor.
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TensorPtrVector GetOutputsByNodeName(const String &node_name) const;
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/// \brief Get output MindSpore Lite MSTensors of model mapped by tensor name.
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///
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/// \return The map of output tensor name and MindSpore Lite MSTensor.
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TensorPtrVector GetOutputs() const;
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/// \brief Get name of output tensors of model compiled by this session.
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///
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/// \return The vector of string as output tensor names in order.
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StringVector GetOutputTensorNames() const;
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/// \brief Get output MindSpore Lite MSTensors of model by tensor name.
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///
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/// \param[in] tensor_name Define tensor name.
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///
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/// \return Pointer of MindSpore Lite MSTensor.
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MSTensor *GetOutputByTensorName(const String &tensor_name) const;
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/// \note RunGraph should be called after CompileGraph.
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int RunGraph();
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/// \brief Resize inputs shape.
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///
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/// \param[in] inputs Define the new inputs shape.
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///
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/// \return STATUS as an error code of resize inputs, STATUS is defined in errorcode.h.
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int Resize(const TensorPtrVector &inputs);
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} LiteSession;
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#endif // MINDSPORE_LITE_INCLUDE_LITE_SESSION_H
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@ -0,0 +1,59 @@
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/**
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* Copyright 2020 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#ifndef MINDSPORE_LITE_INTERNAL_INCLUDE_MODEL_H
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#define MINDSPORE_LITE_INTERNAL_INCLUDE_MODEL_H
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#include "internal/include/lite_utils.h"
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#include "nnacl/op_base.h"
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using PrimitiveC = OpParameter;
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enum NodeType {
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NodeType_ValueNode = 0,
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NodeType_Parameter = 1,
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NodeType_CNode = 2,
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NodeType_MIN = NodeType_ValueNode,
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NodeType_MAX = NodeType_CNode
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};
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typedef struct Node {
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String name_;
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NodeType node_type_;
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PrimitiveC *primitive_;
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Uint32Vector input_indices_;
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Uint32Vector output_indices_;
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} Node;
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typedef struct Model {
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String name_;
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String version_;
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TensorPtrVector all_tensors_;
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Uint32Vector input_indices_;
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Uint32Vector output_indices_;
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NodePtrVector nodes_;
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char *buf;
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/// \brief Static method to create a Model pointer.
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///
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/// \param[in] model_buf Define the buffer read from a model file.
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/// \param[in] size Define bytes number of model buffer.
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///
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/// \return Pointer of MindSpore Lite Model.
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static Model *Import(const char *model_buf, size_t size);
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/// \brief Free all the temporary buffer
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void Free();
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} Model;
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#endif // MINDSPORE_LITE_INTERNAL_INCLUDE_MODEL_H
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@ -0,0 +1,142 @@
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/**
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* Copyright 2020 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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||||
* 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
|
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*
|
||||
* 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.
|
||||
*/
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#ifndef MINDSPORE_LITE_INTERNAL_INCLUDE_MS_TENSOR_H_
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#define MINDSPORE_LITE_INTERNAL_INCLUDE_MS_TENSOR_H_
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#include "internal/include/lite_utils.h"
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enum TypeId : int {
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kTypeUnknown = 0,
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kMetaTypeBegin = kTypeUnknown,
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kMetaTypeType, // Type
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kMetaTypeAnything,
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kMetaTypeObject,
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kMetaTypeTypeType, // TypeType
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kMetaTypeProblem,
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kMetaTypeExternal,
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kMetaTypeNone,
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kMetaTypeNull,
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kMetaTypeEllipsis,
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kMetaTypeEnd,
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//
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// Object types
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//
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kObjectTypeBegin = kMetaTypeEnd,
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kObjectTypeNumber,
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kObjectTypeString,
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kObjectTypeList,
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kObjectTypeTuple,
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kObjectTypeSlice,
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kObjectTypeKeyword,
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kObjectTypeTensorType,
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kObjectTypeRowTensorType,
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kObjectTypeSparseTensorType,
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kObjectTypeUndeterminedType,
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kObjectTypeClass,
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kObjectTypeDictionary,
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kObjectTypeFunction,
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kObjectTypeJTagged,
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kObjectTypeSymbolicKeyType,
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kObjectTypeEnvType,
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kObjectTypeRefKey,
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kObjectTypeRef,
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kObjectTypeEnd,
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//
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// Number Types
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//
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kNumberTypeBegin = kObjectTypeEnd,
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kNumberTypeBool,
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kNumberTypeInt,
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kNumberTypeInt8,
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kNumberTypeInt16,
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kNumberTypeInt32,
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kNumberTypeInt64,
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kNumberTypeUInt,
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kNumberTypeUInt8,
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kNumberTypeUInt16,
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kNumberTypeUInt32,
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kNumberTypeUInt64,
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kNumberTypeFloat,
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kNumberTypeFloat16,
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kNumberTypeFloat32,
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kNumberTypeFloat64,
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kNumberTypeEnd
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||||
};
|
||||
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enum Format {
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Format_NCHW = 0,
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Format_NHWC = 1,
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Format_NHWC4 = 2,
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Format_HWKC = 3,
|
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Format_HWCK = 4,
|
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Format_KCHW = 5,
|
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Format_CKHW = 6,
|
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Format_KHWC = 7,
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Format_CHWK = 8,
|
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Format_HW = 9,
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Format_HW4 = 10,
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Format_NC = 11,
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Format_NC4 = 12,
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Format_NC4HW4 = 100,
|
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Format_NUM_OF_FORMAT = 101,
|
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Format_MIN = Format_NCHW,
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Format_MAX = Format_NUM_OF_FORMAT
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};
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typedef struct MSTensor {
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enum Category {
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CONST, // weight tensor
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VAR // activation tensor
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};
|
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void *data_ = NULL;
|
||||
void *device_data_ = NULL;
|
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TypeId data_type_;
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||||
Format format_ = Format_NHWC;
|
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Category category_ = VAR;
|
||||
ShapeVector shape_ = {};
|
||||
size_t refCount = 0;
|
||||
|
||||
int32_t Batch() const;
|
||||
|
||||
int32_t Channel() const;
|
||||
|
||||
int32_t Height() const;
|
||||
|
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int32_t Width() const;
|
||||
|
||||
/// \brief Get size of the dimension of the MindSpore Lite MSTensor index by the parameter index.
|
||||
///
|
||||
/// \param[in] index Define index of dimension returned.
|
||||
///
|
||||
/// \return Size of dimension of the MindSpore Lite MSTensor.
|
||||
int DimensionSize(size_t index) const;
|
||||
|
||||
/// \brief Get number of element in MSTensor.
|
||||
///
|
||||
/// \return Number of element in MSTensor.
|
||||
int ElementsNum() const;
|
||||
|
||||
int ElementsC4Num() const;
|
||||
|
||||
/// \brief Get byte size of data in MSTensor.
|
||||
///
|
||||
/// \return Byte size of data in MSTensor.
|
||||
size_t Size() const;
|
||||
} MSTensor;
|
||||
|
||||
MSTensor *CreateTensor(TypeId data_type, const ShapeVector &shape);
|
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#endif // MINDSPORE_LITE_INCLUDE_MS_TENSOR_H_
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||||
@ -0,0 +1,68 @@
|
||||
/**
|
||||
* Copyright 2020 Huawei Technologies Co., Ltd
|
||||
*
|
||||
* 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.
|
||||
*/
|
||||
#include "internal/include/lite_session.h"
|
||||
#include "internal/include/model.h"
|
||||
#include "internal/include/ms_tensor.h"
|
||||
#include "src/runtime/allocator.h"
|
||||
|
||||
static Context *g_Ctx;
|
||||
static Model *g_Model;
|
||||
static LiteSession g_Session;
|
||||
static mindspore::lite::DefaultAllocator allocator;
|
||||
|
||||
LiteSession *LiteSession::CreateSession(Context *context) {
|
||||
g_Ctx = context;
|
||||
return &g_Session;
|
||||
}
|
||||
|
||||
int LiteSession::CompileGraph(Model *model) {
|
||||
g_Model = model;
|
||||
for (auto in : g_Model->input_indices_) {
|
||||
g_Model->all_tensors_[in]->data_ = allocator.Malloc(g_Model->all_tensors_[in]->Size());
|
||||
}
|
||||
return 0;
|
||||
}
|
||||
|
||||
TensorPtrVector LiteSession::GetInputs() const {
|
||||
TensorPtrVector in(g_Model->input_indices_.size());
|
||||
// for(auto index : g_Model->input_indices_){
|
||||
// in.emplace_back(g_Model->all_tensors_[index]);
|
||||
// }
|
||||
return in;
|
||||
}
|
||||
|
||||
TensorPtrVector LiteSession::GetInputsByName(const String &node_name) const { return TensorPtrVector(); }
|
||||
|
||||
TensorPtrVector LiteSession::GetOutputsByNodeName(const String &node_name) const { return TensorPtrVector(); }
|
||||
|
||||
TensorPtrVector LiteSession::GetOutputs() const {
|
||||
TensorPtrVector out(g_Model->output_indices_.size());
|
||||
// for(auto index : g_Model->output_indices_){
|
||||
// out.emplace_back(g_Model->all_tensors_[index]);
|
||||
// }
|
||||
return out;
|
||||
}
|
||||
|
||||
int LiteSession::RunGraph() {
|
||||
// invoke nnacl kernel
|
||||
return 0;
|
||||
}
|
||||
|
||||
StringVector LiteSession::GetOutputTensorNames() const { return StringVector(); }
|
||||
|
||||
MSTensor *LiteSession::GetOutputByTensorName(const String &tensor_name) const { return NULL; }
|
||||
|
||||
int LiteSession::Resize(const TensorPtrVector &inputs) { return 0; }
|
||||
@ -0,0 +1,194 @@
|
||||
/**
|
||||
* Copyright 2020 Huawei Technologies Co., Ltd
|
||||
*
|
||||
* 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.
|
||||
*/
|
||||
#include <iostream>
|
||||
#include <vector>
|
||||
#include <numeric>
|
||||
#include <string>
|
||||
#include <functional>
|
||||
#include "internal/include/ms_tensor.h"
|
||||
MSTensor *CreateTensor(TypeId data_type, const ShapeVector &shape) {
|
||||
MSTensor *tensor = new MSTensor();
|
||||
tensor->shape_ = shape;
|
||||
tensor->data_type_ = data_type;
|
||||
return tensor;
|
||||
}
|
||||
int MSTensor::ElementsNum() const { return std::accumulate(shape_.begin(), shape_.end(), 1LL, std::multiplies<int>()); }
|
||||
|
||||
size_t MSTensor::Size() const {
|
||||
size_t size = 0;
|
||||
switch (this->data_type_) {
|
||||
case kNumberTypeFloat64:
|
||||
size = sizeof(double);
|
||||
break;
|
||||
case kNumberTypeFloat:
|
||||
case kNumberTypeFloat32:
|
||||
size = sizeof(float);
|
||||
break;
|
||||
case kNumberTypeInt8:
|
||||
size = sizeof(int8_t);
|
||||
break;
|
||||
case kNumberTypeUInt8:
|
||||
size = sizeof(uint8_t);
|
||||
break;
|
||||
case kNumberTypeFloat16:
|
||||
size = sizeof(int16_t);
|
||||
break;
|
||||
case kNumberTypeInt16:
|
||||
size = sizeof(int16_t);
|
||||
break;
|
||||
case kNumberTypeInt32:
|
||||
size = sizeof(int32_t);
|
||||
break;
|
||||
case kNumberTypeInt64:
|
||||
size = sizeof(int64_t);
|
||||
break;
|
||||
case kNumberTypeUInt16:
|
||||
size = sizeof(uint16_t);
|
||||
break;
|
||||
case kNumberTypeUInt32:
|
||||
size = sizeof(uint32_t);
|
||||
break;
|
||||
case kNumberTypeUInt64:
|
||||
size = sizeof(uint64_t);
|
||||
break;
|
||||
case kNumberTypeBool:
|
||||
size = sizeof(bool);
|
||||
break;
|
||||
default:
|
||||
std::cout << "Not support the type: " << this->data_type_;
|
||||
return 0;
|
||||
}
|
||||
size *= (format_ == Format::Format_NC4HW4 || format_ == Format::Format_NHWC4) ? ElementsC4Num() : ElementsNum();
|
||||
|
||||
return size;
|
||||
}
|
||||
int32_t MSTensor::Batch() const {
|
||||
if (this->shape_.size() != 4 && this->shape_.size() != 2) {
|
||||
std::cout << "Unsupported tensor shape: " << this->shape_.size();
|
||||
return -1;
|
||||
}
|
||||
switch (this->format_) {
|
||||
case Format::Format_NHWC:
|
||||
case Format::Format_NHWC4:
|
||||
case Format::Format_NCHW:
|
||||
case Format::Format_NC4HW4:
|
||||
case Format::Format_KCHW:
|
||||
case Format::Format_KHWC:
|
||||
case Format::Format_NC:
|
||||
case Format::Format_NC4:
|
||||
return this->shape_[0];
|
||||
case Format::Format_HWCK:
|
||||
case Format::Format_CHWK:
|
||||
return this->shape_[3];
|
||||
case Format::Format_HWKC:
|
||||
return this->shape_[2];
|
||||
case Format::Format_CKHW:
|
||||
return this->shape_[1];
|
||||
default:
|
||||
// std::cout << "Unsupported format: " << EnumNameFormat(this->format_);
|
||||
return -1;
|
||||
}
|
||||
}
|
||||
|
||||
int32_t MSTensor::Channel() const {
|
||||
if (this->shape_.size() != 4 && this->shape_.size() != 2) {
|
||||
std::cout << "Unsupported tensor shape: " << this->shape_.size();
|
||||
return -1;
|
||||
}
|
||||
switch (this->format_) {
|
||||
case Format::Format_NCHW:
|
||||
case Format::Format_KCHW:
|
||||
case Format::Format_NC:
|
||||
case Format::Format_NC4:
|
||||
return this->shape_[1];
|
||||
case Format::Format_HWCK:
|
||||
return this->shape_[2];
|
||||
case Format::Format_HWKC:
|
||||
case Format::Format_NHWC:
|
||||
case Format::Format_NHWC4:
|
||||
case Format::Format_NC4HW4:
|
||||
case Format::Format_KHWC:
|
||||
return this->shape_[3];
|
||||
case Format::Format_CKHW:
|
||||
case Format::Format_CHWK:
|
||||
return this->shape_[0];
|
||||
default:
|
||||
return -1;
|
||||
}
|
||||
}
|
||||
|
||||
int32_t MSTensor::Height() const {
|
||||
if (this->shape_.size() != 4 && this->shape_.size() != 2) {
|
||||
std::cout << "Unsupported tensor shape: " << this->shape_.size();
|
||||
return -1;
|
||||
}
|
||||
switch (this->format_) {
|
||||
case Format::Format_NCHW:
|
||||
case Format::Format_KCHW:
|
||||
case Format::Format_CKHW:
|
||||
return this->shape_[2];
|
||||
case Format::Format_NHWC:
|
||||
case Format::Format_NHWC4:
|
||||
case Format::Format_NC4HW4:
|
||||
case Format::Format_KHWC:
|
||||
case Format::Format_CHWK:
|
||||
return this->shape_[1];
|
||||
case Format::Format_HWCK:
|
||||
case Format::Format_HWKC:
|
||||
case Format::Format_HW:
|
||||
case Format::Format_HW4:
|
||||
return this->shape_[0];
|
||||
default:
|
||||
// std::cout << "Unsupported format: " << EnumNameFormat(this->format_);
|
||||
return -1;
|
||||
}
|
||||
}
|
||||
|
||||
int32_t MSTensor::Width() const {
|
||||
if (this->shape_.size() != 4 && this->shape_.size() != 2) {
|
||||
std::cout << "Unsupported tensor shape: " << this->shape_.size();
|
||||
return -1;
|
||||
}
|
||||
switch (this->format_) {
|
||||
case Format::Format_NCHW:
|
||||
case Format::Format_KCHW:
|
||||
case Format::Format_CKHW:
|
||||
return this->shape_[3];
|
||||
case Format::Format_KHWC:
|
||||
case Format::Format_NHWC:
|
||||
case Format::Format_NHWC4:
|
||||
case Format::Format_NC4HW4:
|
||||
case Format::Format_CHWK:
|
||||
return this->shape_[2];
|
||||
case Format::Format_HWCK:
|
||||
case Format::Format_HWKC:
|
||||
case Format::Format_HW:
|
||||
case Format::Format_HW4:
|
||||
return this->shape_[1];
|
||||
default:
|
||||
return -1;
|
||||
}
|
||||
}
|
||||
|
||||
int MSTensor::ElementsC4Num() const {
|
||||
int result = 0;
|
||||
if (this->shape_.size() == 4) {
|
||||
result = Batch() * Height() * Width() * ((Channel() + 3) / 4 * 4);
|
||||
} else if (this->shape_.size() == 2) {
|
||||
result = this->shape_[0] * ((this->shape_[1] + 3) / 4 * 4);
|
||||
}
|
||||
return result;
|
||||
}
|
||||
Some files were not shown because too many files have changed in this diff Show More
Loading…
Reference in new issue