wehub-resource-sync
103 lines
3.5 KiB
C++
103 lines
3.5 KiB
C++
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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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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#include "paddle/phi/kernels/accuracy_kernel.h"
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#include <algorithm>
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#include "paddle/phi/backends/cpu/cpu_context.h"
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#include "paddle/phi/core/kernel_registry.h"
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namespace phi {
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template <typename T, typename Context>
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void AccuracyKernel(const Context& dev_ctx,
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const DenseTensor& inference,
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const DenseTensor& indices,
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const DenseTensor& label,
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DenseTensor* accuracy,
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DenseTensor* correct,
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DenseTensor* total) {
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int* correct_data = dev_ctx.template Alloc<int>(correct);
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int* total_data = dev_ctx.template Alloc<int>(total);
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float* accuracy_data = dev_ctx.template Alloc<float>(accuracy);
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const int64_t* indices_data = indices.data<int64_t>();
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const int64_t* label_data = label.data<int64_t>();
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PADDLE_ENFORCE_EQ(
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inference.dims().size(),
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2,
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common::errors::InvalidArgument(
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"Rank(Input) of AccuracyOp must be 2, with shape "
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"[sample_number, class_dim], But received rank(Input) is %d",
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inference.dims().size()));
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size_t num_samples = inference.dims()[0];
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size_t class_dim = inference.dims()[1];
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*accuracy_data = 0.0f;
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PADDLE_ENFORCE_GT(label.dims().size(),
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0,
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common::errors::InvalidArgument(
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"Rank(Label) of AccuracyOp must greater than 0, "
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"But received rank(Label) is %d",
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label.dims().size()));
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PADDLE_ENFORCE_GE(label.dims()[0],
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inference.dims()[0],
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common::errors::InvalidArgument(
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"num_samples(%d) of Label should less than "
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"or equal to num_samples(%d) of Input",
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label.dims()[0],
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num_samples));
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if (num_samples == 0) {
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return;
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}
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int num_correct = 0;
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// assume inference is already the topk of the output
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for (size_t i = 0; i < num_samples; ++i) {
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PADDLE_ENFORCE_GE(
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label_data[i],
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0,
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common::errors::InvalidArgument(
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"label of AccuracyOp must >= 0, But received label[%d] is %d",
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i,
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label_data[i]));
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for (size_t j = 0; j < class_dim; ++j) {
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if (indices_data[i * class_dim + j] == label_data[i]) {
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++num_correct;
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break;
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}
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}
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}
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*correct_data = num_correct;
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*total_data = static_cast<int>(num_samples);
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*accuracy_data =
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static_cast<float>(num_correct) / static_cast<float>(num_samples);
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}
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} // namespace phi
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// TODO(add supported dtype.)
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PD_REGISTER_KERNEL(
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accuracy, CPU, ALL_LAYOUT, phi::AccuracyKernel, float, double) {
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kernel->InputAt(1).SetDataType(phi::DataType::INT64);
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kernel->InputAt(2).SetDataType(phi::DataType::INT64);
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kernel->OutputAt(0).SetDataType(phi::DataType::FLOAT32);
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kernel->OutputAt(1).SetDataType(phi::DataType::INT32);
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kernel->OutputAt(2).SetDataType(phi::DataType::INT32);
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}
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