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90 lines
3.1 KiB
90 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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#include <memory>
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#include <string>
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#include "paddle/fluid/operators/top_k_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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void gen_assist_seq(framework::Tensor* assit_tensor,
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int64_t dim, const framework::ExecutionContext& ctx) {
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const int64_t dimx2 = dim;
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std::vector<paddle::platform::float16> assit;
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assit.resize(2 * dimx2);
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for (int64_t i = 0; i < dimx2; i++) {
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// for i in range [0, dim]
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assit[i] = static_cast<paddle::platform::float16>(i);
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// for i in range [dim, dimx2]
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int64_t idx = static_cast<int64_t>(
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static_cast<paddle::platform::float16>(i));
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int64_t gap = i - idx;
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assit[i + dim] = static_cast<paddle::platform::float16>(gap);
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}
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framework::TensorFromVector(assit, ctx.device_context(), assit_tensor);
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}
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template <typename DeviceContext, typename T>
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class TopkNPUKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& ctx) const override {
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// read input
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auto* input = ctx.Input<framework::LoDTensor>("X");
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auto* output = ctx.Output<framework::LoDTensor>("Out");
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auto* indices = ctx.Output<framework::LoDTensor>("Indices");
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size_t k = static_cast<int>(ctx.Attr<int>("k"));
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output->mutable_data<T>(ctx.GetPlace());
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indices->mutable_data<int>(ctx.GetPlace());
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// prepare assit
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auto dim = input->dims().size();
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framework::Tensor assist_seq_tensor;
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assist_seq_tensor.Resize({2 * dim});
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assist_seq_tensor.mutable_data<T>(ctx.GetPlace());
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gen_assist_seq(&assist_seq_tensor, dim, ctx);
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framework::NPUAttributeMap attr_input = {{"sorted", "true"},
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{"k", static_cast<int>(k)},
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{"dim", -1},
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{"largest", true}};
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// run ascend
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auto runner = NpuOpRunner("TopKD",
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{*input, assist_seq_tensor},
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{*output, *indices},
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attr_input);
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auto stream =
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ctx.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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// Ascend Op TopKD only support input float 16 dtype
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REGISTER_OP_NPU_KERNEL(
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top_k,
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ops::TopkNPUKernel<paddle::platform::NPUDeviceContext,
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paddle::platform::float16>);
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