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83 lines
3.1 KiB
83 lines
3.1 KiB
/* Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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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#ifdef PADDLE_WITH_ASCEND_CL
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#include <iostream>
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#include <memory>
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#include <string>
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#include "paddle/fluid/framework/op_registry.h"
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#include "paddle/fluid/operators/expand_op.h"
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#include "paddle/fluid/operators/npu_op_runner.h"
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namespace paddle {
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namespace operators {
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template <typename DeviceContext, typename T>
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class ExpandNPUKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& context) const override {
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auto rank = context.Input<Tensor>("X")->dims().size();
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PADDLE_ENFORCE_GE(
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rank, 1,
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platform::errors::InvalidArgument(
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"The number of dimensions of the input 'x' for Op(expand) "
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"must be greater than or equal to 1, but the value received is %d.",
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rank));
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PADDLE_ENFORCE_LE(
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rank, MAX_RANK_SUPPORTED,
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platform::errors::InvalidArgument(
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"The number of dimensions of the input 'x' for Op(expand) "
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"must be less than or equal to %d, but the value received is %d.",
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MAX_RANK_SUPPORTED, rank));
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switch (rank) { REP_EXPAND_TEMPLATE(MAX_RANK_SUPPORTED) }
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}
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protected:
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template <int Rank>
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void Expand(const framework::ExecutionContext& context) const {
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auto* in0 = context.Input<framework::LoDTensor>("X");
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auto in_dims = in0->dims();
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auto expand_times = get_expand_times(context);
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PADDLE_ENFORCE_EQ(
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static_cast<size_t>(in_dims.size()), expand_times.size(),
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platform::errors::InvalidArgument(
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"The number of elements (%d) of 'expand_times' for "
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"Op(expand) must be equal to the number "
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"of dimensions (%d) of the input.",
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expand_times.size(), static_cast<size_t>(in_dims.size())));
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auto* out0 = context.Output<framework::LoDTensor>("Out");
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framework::DDim out_dims(in_dims);
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for (size_t i = 0; i < expand_times.size(); ++i) {
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out_dims[i] *= expand_times[i];
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}
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out0->Resize(out_dims);
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out0->mutable_data<T>(context.device_context().GetPlace());
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auto runner = NpuOpRunner("TileD", {*in0}, {*out0}, {{"multiples", expand_times}});
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auto stream =
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context.template device_context<paddle::platform::NPUDeviceContext>()
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.stream();
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runner.Run(stream);
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}
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};
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} // namespace operators
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} // namespace paddle
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namespace ops = paddle::operators;
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REGISTER_OP_NPU_KERNEL(
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expand, ops::ExpandNPUKernel<paddle::platform::NPUDeviceContext, float>,
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ops::ExpandNPUKernel<paddle::platform::NPUDeviceContext,
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paddle::platform::float16>);
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#endif
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