wehub-resource-sync
116 lines
3.7 KiB
C++
116 lines
3.7 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/xpu/enforce_xpu.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 EmbeddingKernel(const Context &dev_ctx,
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const DenseTensor &inputx,
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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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using XPUType = typename XPUTypeTrait<T>::Type;
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auto *ids_t = &inputx; // int
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auto *output_t = out; // float
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PADDLE_ENFORCE_EQ(
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(std::is_same<Context, XPUContext>::value),
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true,
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common::errors::PreconditionNotMet("Unsupported place! only support "
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"xpu place , please check your "
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"place."));
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int64_t ids_numel = ids_t->numel();
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auto *table_t = &weight;
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auto *table = table_t->data<T>();
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auto *output = dev_ctx.template Alloc<T>(output_t);
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if (ids_numel == 0) return;
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int64_t ym = ids_numel;
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int64_t xm = table_t->dims()[0];
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int64_t n = table_t->dims()[1];
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int r;
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xpu::ctx_guard RAII_GUARD(dev_ctx.x_context());
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if (ids_t->dtype() == DataType::INT64) {
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#ifndef PADDLE_WITH_XPU_PLUGIN
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r = xpu::paddle_embedding<XPUType, int64_t>(
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dev_ctx.x_context(),
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reinterpret_cast<const XPUType *>(table),
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ids_t->data<int64_t>(),
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reinterpret_cast<XPUType *>(output),
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xm,
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n,
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ym,
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padding_idx);
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#else
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r = xpu::plugin::fast_embedding<XPUType, int64_t>(
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dev_ctx.x_context(),
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reinterpret_cast<const XPUType *>(table),
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ids_t->data<int64_t>(),
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reinterpret_cast<XPUType *>(output),
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xm,
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n,
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ym,
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padding_idx);
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#endif
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} else {
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#ifndef PADDLE_WITH_XPU_PLUGIN
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int64_t *ids_tt = RAII_GUARD.alloc_l3_or_gm<int64_t>(ids_t->numel());
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r = xpu::cast<int32_t, int64_t>(
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dev_ctx.x_context(), ids_t->data<int>(), ids_tt, ids_t->numel());
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PADDLE_ENFORCE_XDNN_SUCCESS(r, "cast");
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const int64_t *ids = reinterpret_cast<const int64_t *>(ids_tt);
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r = xpu::paddle_embedding<XPUType>(dev_ctx.x_context(),
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reinterpret_cast<const XPUType *>(table),
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ids,
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reinterpret_cast<XPUType *>(output),
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xm,
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n,
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ym,
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padding_idx);
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#else
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r = xpu::plugin::fast_embedding<XPUType, int>(
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dev_ctx.x_context(),
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reinterpret_cast<const XPUType *>(table),
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ids_t->data<int>(),
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reinterpret_cast<XPUType *>(output),
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xm,
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n,
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ym,
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padding_idx);
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#endif
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}
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PADDLE_ENFORCE_XDNN_SUCCESS(r, "paddle_embedding");
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}
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} // namespace phi
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PD_REGISTER_KERNEL(embedding,
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XPU,
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ALL_LAYOUT,
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phi::EmbeddingKernel,
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float,
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phi::float16,
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phi::bfloat16) {}
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