wehub-resource-sync
135 lines
4.6 KiB
Plaintext
135 lines
4.6 KiB
Plaintext
// 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 "paddle/phi/backends/gpu/gpu_primitives.h"
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#include "paddle/phi/common/memory_utils.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/core/selected_rows.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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namespace phi {
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namespace sr {
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template <typename T,
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int BlockDimX,
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int BlockDimY,
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int GridDimX,
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bool PaddingFlag>
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__global__ void LookupTable(T *output,
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const T *table,
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const int64_t *ids,
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const int64_t N,
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const int64_t K,
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const int64_t D,
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const int64_t padding_idx) {
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int idx = threadIdx.x;
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int64_t idy = static_cast<int64_t>(blockIdx.x) +
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static_cast<int64_t>(threadIdx.y) * GridDimX;
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while (idy < K) {
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int64_t id = ids[idy];
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PADDLE_ENFORCE(
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id >= 0,
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"Variable value (input) of OP(lookup_table) "
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"expected >= 0 and < %ld, but got %ld. Please check input value.",
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N,
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id);
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PADDLE_ENFORCE(
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id < N,
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"Variable value (input) of OP(lookup_table) "
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"expected >= 0 and < %ld, but got %ld. Please check input value.",
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N,
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id);
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T *out = output + idy * D;
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const T *tab = table + id * D;
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for (int i = idx; i < D; i += BlockDimX) {
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if (PaddingFlag) {
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if (id == padding_idx)
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out[i] = static_cast<T>(0);
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else
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out[i] = tab[i];
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} else {
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out[i] = tab[i];
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}
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}
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idy += BlockDimY * GridDimX;
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}
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}
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template <typename T, typename Context>
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void LookupTableCUDAKernel(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 *table_t = &w;
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auto *ids_t = &ids_in;
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auto *output_t = out;
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size_t N = table_t->dims()[0];
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size_t D = table_t->dims()[1];
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size_t K = ids_t->numel();
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auto *ids = ids_t->data<int64_t>();
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auto *table = table_t->value().data<T>();
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auto *output = dev_ctx.template Alloc<T>(output_t);
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#ifdef PADDLE_WITH_HIP
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dim3 threads(64, 4);
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#else
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dim3 threads(128, 8);
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#endif // PADDLE_WITH_HIP
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dim3 grids(8, 1);
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#ifdef PADDLE_WITH_HIP
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if (padding_idx == -1)
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LookupTable<T, 64, 4, 8, false><<<grids, threads, 0, dev_ctx.stream()>>>(
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output, table, ids, N, K, D, padding_idx);
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else
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LookupTable<T, 64, 4, 8, true><<<grids, threads, 0, dev_ctx.stream()>>>(
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output, table, ids, N, K, D, padding_idx);
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#else
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if (padding_idx == -1)
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LookupTable<T, 128, 8, 8, false><<<grids, threads, 0, dev_ctx.stream()>>>(
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output, table, ids, N, K, D, padding_idx);
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else
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LookupTable<T, 128, 8, 8, true><<<grids, threads, 0, dev_ctx.stream()>>>(
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output, table, ids, N, K, D, padding_idx);
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#endif // PADDLE_WITH_HIP
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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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GPU,
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ALL_LAYOUT,
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phi::sr::LookupTableCUDAKernel,
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float,
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double,
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phi::float16,
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int8_t,
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int16_t) {}
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