// Copyright (c) 2022 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. #include "paddle/phi/kernels/embedding_kernel.h" #include "paddle/phi/kernels/funcs/embedding_util.h" #include "paddle/fluid/framework/convert_utils.h" #include "paddle/fluid/framework/data_type.h" #include "paddle/phi/backends/cpu/cpu_context.h" #include "paddle/phi/core/kernel_registry.h" namespace phi { template struct LookupTableV2CPUFunctor { LookupTableV2CPUFunctor(const Context& dev_ctx, const DenseTensor& input, const DenseTensor& weight, int64_t padding_idx, DenseTensor* out) : dev_ctx_(dev_ctx), input_(input), weight_(weight), out_(out), padding_idx_(padding_idx) {} template void apply() { auto ids = CopyIdsToVector(input_); auto ids_numel = static_cast(ids.size()); int64_t row_number = weight_.dims()[0]; int64_t row_width = weight_.dims()[1]; auto* table = weight_.data(); dev_ctx_.template Alloc(out_); auto* output = out_->data(); for (int64_t i = 0; i < ids_numel; ++i) { if (padding_idx_ != kNoPadding && ids[i] == padding_idx_) { memset(output + i * row_width, 0, row_width * sizeof(T)); } else { PADDLE_ENFORCE_LT( ids[i], row_number, phi::errors::InvalidArgument( "Variable value (input) of OP(fluid.layers.embedding) " "expected >= 0 and < %ld, but got %ld. Please check input " "value.", row_number, ids[i])); PADDLE_ENFORCE_GE( ids[i], 0, phi::errors::InvalidArgument( "Variable value (input) of OP(fluid.layers.embedding) " "expected >= 0 and < %ld, but got %ld. Please check input " "value.", row_number, ids[i])); memcpy(output + i * row_width, table + ids[i] * row_width, row_width * sizeof(T)); } } } private: const Context& dev_ctx_; const DenseTensor& input_; const DenseTensor& weight_; DenseTensor* out_; int64_t padding_idx_; }; template void EmbeddingKernel(const Context& ctx, const DenseTensor& input, const DenseTensor& weight, int64_t padding_idx, DenseTensor* out) { LookupTableV2CPUFunctor functor( ctx, input, weight, padding_idx, out); paddle::framework::VisitIntDataType( paddle::framework::TransToProtoVarType(input.dtype()), functor); } } // namespace phi PT_REGISTER_KERNEL(embedding, CPU, ALL_LAYOUT, phi::EmbeddingKernel, float, double, phi::dtype::float16) {}