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93 lines
3.4 KiB
93 lines
3.4 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 <memory>
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#include <string>
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#include "paddle/fluid/operators/cast_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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static std::map<framework::proto::VarType::Type, aclDataType>
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DTYPE_2_ACL_DTYPE = {
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{framework::proto::VarType::BOOL, ACL_BOOL},
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{framework::proto::VarType::INT16, ACL_INT16},
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{framework::proto::VarType::INT32, ACL_INT32},
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{framework::proto::VarType::INT64, ACL_INT64},
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{framework::proto::VarType::FP16, ACL_FLOAT16},
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{framework::proto::VarType::FP32, ACL_FLOAT},
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{framework::proto::VarType::FP64, ACL_DOUBLE},
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};
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using Tensor = framework::Tensor;
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template <typename DeviceContext, typename T>
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class CastNPUKernel : 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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auto* x = ctx.Input<Tensor>("X");
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int dtype = ctx.Attr<int>("out_dtype");
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auto* out = ctx.Output<Tensor>("Out");
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auto place = ctx.GetPlace();
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auto iter = DTYPE_2_ACL_DTYPE.find(static_cast<framework::proto::VarType::Type>(dtype));
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int aclDtype = iter->second;
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if (dtype == framework::proto::VarType::FP32) {
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out->mutable_data<float>(place);
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} else if (dtype == framework::proto::VarType::FP16) {
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out->mutable_data<paddle::platform::float16>(place);
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} else if (dtype == framework::proto::VarType::INT16) {
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out->mutable_data<int16_t>(place);
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} else if (dtype == framework::proto::VarType::INT32) {
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out->mutable_data<int32_t>(place);
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} else if (dtype == framework::proto::VarType::INT64) {
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out->mutable_data<int64_t>(place);
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} else if (dtype == framework::proto::VarType::FP64) {
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out->mutable_data<double>(place);
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} else if (dtype == framework::proto::VarType::BOOL) {
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out->mutable_data<bool>(place);
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}
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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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auto runner = NpuOpRunner("Cast", {*x}, {*out}, {{"dst_type", static_cast<int32_t>(aclDtype)}});
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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 paddleaclDtype
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namespace ops = paddle::operators;
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REGISTER_OP_NPU_KERNEL(
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cast,
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ops::CastNPUKernel<paddle::platform::NPUDeviceContext, int16_t>,
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ops::CastNPUKernel<paddle::platform::NPUDeviceContext, int32_t>,
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ops::CastNPUKernel<paddle::platform::NPUDeviceContext, int64_t>,
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ops::CastNPUKernel<paddle::platform::NPUDeviceContext, int>,
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ops::CastNPUKernel<paddle::platform::NPUDeviceContext, bool>,
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ops::CastNPUKernel<paddle::platform::NPUDeviceContext, double>,
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ops::CastNPUKernel<paddle::platform::NPUDeviceContext, float>,
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ops::CastNPUKernel<paddle::platform::NPUDeviceContext,
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paddle::platform::float16>);
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#endif
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