dzhwinter
6 years ago
commit
3932cd6714
@ -1,5 +1,5 @@
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if(WITH_PYTHON)
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cc_library(layer SRCS layer.cc DEPS proto_desc operator device_context blas)
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cc_library(tracer SRCS tracer.cc DEPS proto_desc device_context)
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cc_library(layer SRCS layer.cc DEPS proto_desc operator device_context blas pybind)
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cc_library(tracer SRCS tracer.cc DEPS proto_desc device_context pybind)
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cc_library(engine SRCS engine.cc)
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endif()
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@ -0,0 +1,65 @@
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/*Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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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#pragma once
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#include <string>
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#include <vector>
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#include "ngraph/ngraph.hpp"
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#include "paddle/fluid/platform/ngraph_helper.h"
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namespace paddle {
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namespace operators {
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namespace ngraphs {
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void BuildAccuracyNode(
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const std::shared_ptr<framework::OperatorBase>& op,
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std::shared_ptr<
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std::unordered_map<std::string, std::shared_ptr<ngraph::Node>>>
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ngb_node_map) {
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auto indices = platform::GetInputNode(op, "Indices", ngb_node_map);
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auto label = platform::GetInputNode(op, "Label", ngb_node_map);
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auto inference = platform::GetInputNode(op, "Out", ngb_node_map);
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auto inference_shape = inference->get_shape();
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size_t num_samples = inference_shape.at(0);
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size_t k = inference_shape.at(1);
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std::shared_ptr<ngraph::Node> label_k = label;
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if (k > 1) {
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auto label_1d = std::make_shared<ngraph::op::Reshape>(
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label, ngraph::AxisVector{0, 1}, ngraph::Shape{num_samples});
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label_k = std::make_shared<ngraph::op::Broadcast>(label_1d, inference_shape,
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ngraph::AxisSet{1});
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}
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auto node_equal = std::make_shared<ngraph::op::Equal>(indices, label_k);
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auto node_eq_int =
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std::make_shared<ngraph::op::Convert>(node_equal, ngraph::element::i64);
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auto num_correct_0d =
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std::make_shared<ngraph::op::Sum>(node_eq_int, ngraph::AxisSet{0, 1});
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std::shared_ptr<ngraph::Node> num_correct =
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platform::NgReshaper(num_correct_0d, ngraph::Shape{1});
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std::shared_ptr<ngraph::Node> n_samples = ngraph::op::Constant::create(
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ngraph::element::i64, ngraph::Shape{1}, {num_samples});
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std::shared_ptr<ngraph::Node> accuracy = std::make_shared<ngraph::op::Divide>(
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std::make_shared<ngraph::op::Convert>(num_correct, ngraph::element::f32),
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std::make_shared<ngraph::op::Convert>(n_samples, ngraph::element::f32));
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platform::SetOutputNode(op, "Accuracy", accuracy, ngb_node_map);
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platform::SetOutputNode(op, "Correct", num_correct, ngb_node_map);
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platform::SetOutputNode(op, "Total", n_samples, ngb_node_map);
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}
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} // namespace ngraphs
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} // namespace operators
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} // namespace paddle
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