wehub-resource-sync
131 lines
4.0 KiB
C++
131 lines
4.0 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/embedding_kernel.h"
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#include "paddle/phi/backends/cpu/cpu_context.h"
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#include "paddle/phi/common/data_type.h"
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#include "paddle/phi/core/dense_tensor.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/kernels/funcs/embedding_util.h"
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#include "paddle/phi/kernels/p_norm_kernel.h"
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namespace phi {
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template <typename T, typename Context>
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struct EmbeddingCPUFunctor {
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EmbeddingCPUFunctor(const Context& dev_ctx,
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const DenseTensor& input,
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const DenseTensor& weight,
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int64_t padding_idx,
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DenseTensor* out)
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: dev_ctx_(dev_ctx),
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input_(input),
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weight_(weight),
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out_(out),
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padding_idx_(padding_idx) {}
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template <typename IdT>
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void apply() {
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auto ids = CopyIdsToVector<IdT, int64_t>(input_);
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auto ids_numel = static_cast<int64_t>(ids.size());
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int64_t row_number = weight_.dims()[0];
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int64_t row_width = weight_.dims()[1];
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auto* table = weight_.data<T>();
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dev_ctx_.template Alloc<T>(out_);
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auto* output = out_->data<T>();
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for (int64_t i = 0; i < ids_numel; ++i) {
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if (padding_idx_ == kNoPadding && ids[i] != padding_idx_) {
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PADDLE_ENFORCE_LT(
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ids[i],
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row_number,
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common::errors::InvalidArgument(
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"Variable value (input) of OP(embedding) "
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"expected >= 0 and < %ld, but got %ld. Please check input "
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"value.",
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row_number,
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ids[i]));
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PADDLE_ENFORCE_GE(
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ids[i],
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0,
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common::errors::InvalidArgument(
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"Variable value (input) of OP(embedding) "
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"expected >= 0 and < %ld, but got %ld. Please check input "
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"value.",
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row_number,
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ids[i]));
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}
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}
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#if defined(_OPENMP) && !defined(PADDLE_WITH_CUDA)
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#pragma omp parallel for
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#endif
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for (int64_t i = 0; i < ids_numel; ++i) {
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if (padding_idx_ != kNoPadding && ids[i] == padding_idx_) {
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memset(output + i * row_width, 0, row_width * sizeof(T));
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} else {
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memcpy(output + i * row_width,
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table + ids[i] * row_width,
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row_width * sizeof(T));
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}
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}
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}
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private:
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const Context& dev_ctx_;
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const DenseTensor& input_;
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const DenseTensor& weight_;
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DenseTensor* out_;
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int64_t padding_idx_;
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};
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template <typename T, typename Context>
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void EmbeddingKernel(const Context& dev_ctx,
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const DenseTensor& input,
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const DenseTensor& weight,
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int64_t padding_idx,
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DenseTensor* out) {
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EmbeddingCPUFunctor<T, Context> functor(
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dev_ctx, input, weight, padding_idx, out);
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if (input.dtype() == DataType::INT32) {
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functor.template apply<int>();
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} else if (input.dtype() == DataType::INT64) {
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functor.template apply<int64_t>();
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} else {
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PADDLE_THROW(common::errors::Unimplemented(
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"embedding input only support int32 and int64, but get %s",
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input.dtype()));
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}
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}
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} // namespace phi
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PD_REGISTER_KERNEL(embedding,
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CPU,
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ALL_LAYOUT,
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phi::EmbeddingKernel,
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float,
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double,
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int8_t,
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phi::float16,
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phi::bfloat16,
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phi::complex64,
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phi::complex128) {}
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