wehub-resource-sync
132 lines
4.9 KiB
C++
132 lines
4.9 KiB
C++
// Copyright (c) 2024 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 <string>
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#include <vector>
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#include "paddle/phi/core/dense_tensor.h"
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#include "paddle/phi/core/enforce.h"
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#include "paddle/phi/kernels/funcs/blas/blas.h"
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#include "paddle/phi/kernels/funcs/eigen/common.h"
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#include "paddle/phi/kernels/funcs/selected_rows_functor.h"
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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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namespace sr {
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constexpr int64_t kNoPadding = -1;
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template <typename T, typename Context>
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void LookupTableKernel(const Context &dev_ctx,
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const SelectedRows &w,
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const DenseTensor &ids_in,
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bool is_sparse,
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bool is_distributed UNUSED,
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int64_t padding_idx,
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bool remote_prefetch UNUSED,
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const std::string &entry_config UNUSED,
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bool is_test,
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const std::string &entry UNUSED,
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const std::string &table_class UNUSED,
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const std::vector<std::string> &table_names UNUSED,
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int trainer_id UNUSED,
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bool grad_inplace UNUSED,
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const std::vector<std::string> &epmap UNUSED,
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const std::vector<int64_t> &height_sections UNUSED,
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SelectedRows *out) {
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auto *ids_t = &ids_in; // int tensor
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auto *output_t = out; // float tensor
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int64_t *ids = const_cast<int64_t *>(ids_t->data<int64_t>());
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int64_t ids_numel = ids_t->numel();
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const auto &table_t = w;
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int64_t row_width = table_t.value().dims()[1];
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const auto *table = table_t.value().data<T>();
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auto *output = dev_ctx.template Alloc<T>(output_t);
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auto input_data_type = table_t.value().dtype();
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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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PADDLE_ENFORCE_GE(ids[i],
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0,
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common::errors::InvalidArgument(
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"Variable value (input) of OP(lookup_table) "
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"expected >= 0. But received %ld",
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ids[i]));
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if (is_test) {
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auto id_index = table_t.GetIndexFromId(ids[i]);
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if (id_index != -1) {
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if (input_data_type == phi::DataType::INT8 ||
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input_data_type == phi::DataType::INT16 ||
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input_data_type == phi::DataType::BFLOAT16) {
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memcpy(output + i * row_width,
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table + id_index * row_width,
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row_width * sizeof(T));
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} else {
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auto blas = funcs::GetBlas<CPUContext, T>(dev_ctx);
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blas.VCOPY(row_width,
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table + id_index * row_width,
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output + i * row_width);
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}
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} else {
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memset(output + i * row_width, 0, row_width * sizeof(T));
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}
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} else {
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auto id_index = table_t.Index(ids[i]);
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PADDLE_ENFORCE_GE(ids[i],
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0,
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common::errors::InvalidArgument(
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"Variable value (input) of OP(lookup_table) "
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"expected >= 0. But received %ld",
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ids[i]));
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PADDLE_ENFORCE_GE(
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id_index,
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0,
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common::errors::InvalidArgument(
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"the input key should be exists. But received %d.", id_index));
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if (input_data_type == phi::DataType::INT8 ||
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input_data_type == phi::DataType::INT16 ||
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input_data_type == phi::DataType::BFLOAT16) {
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memcpy(output + i * row_width,
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table + id_index * row_width,
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row_width * sizeof(T));
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} else {
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auto blas = funcs::GetBlas<CPUContext, T>(dev_ctx);
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blas.VCOPY(
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row_width, table + id_index * row_width, output + i * row_width);
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}
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}
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}
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}
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}
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} // namespace sr
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} // namespace phi
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PD_REGISTER_KERNEL(lookup_table_sr,
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CPU,
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ALL_LAYOUT,
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phi::sr::LookupTableKernel,
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float,
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double,
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int8_t,
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int16_t,
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phi::bfloat16) {}
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