wehub-resource-sync
80 lines
2.6 KiB
C++
80 lines
2.6 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/npu_identity_kernel.h"
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#include "glog/logging.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/kernels/empty_kernel.h"
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namespace phi {
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template <typename T, typename Context>
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void NPUIdentityKernel(const Context& dev_ctx UNUSED,
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const DenseTensor& x,
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const int format UNUSED,
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DenseTensor* out) {
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VLOG(4) << "npu_identity op is only for NPU, please avoid using this kernel!";
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out->ShareDataWith(x);
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}
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} // namespace phi
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/** [ Why need npu_identity op? ]
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*
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* 1. Ascend CANN use internal storage format for high performance
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* computing, for example if run BatchNorm2D op with CANN internal
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* storage format ACL_FORMAT_NC1HWC0, time costs in transdata will
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* be removed, and at will gain 2x performance improvement.
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*
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* 2.The internal storage format will use storage_properties_ in
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* DenseTensor, and will change the size and layout of denser, and
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* finally it should be called when change tensor to numpy and restore
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* original size and format by calling CANN Identity OP.
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*
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* TODO(qili93): remove this op after custom op and custom device
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* integrated and then move this op along with its code to plugin.
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*/
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PD_REGISTER_KERNEL(npu_identity,
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CPU,
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ALL_LAYOUT,
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phi::NPUIdentityKernel,
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float,
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double,
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int8_t,
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uint8_t,
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int16_t,
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int,
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int64_t,
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bool,
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phi::float16) {}
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#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
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PD_REGISTER_KERNEL(npu_identity,
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GPU,
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ALL_LAYOUT,
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phi::NPUIdentityKernel,
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float,
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double,
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int8_t,
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uint8_t,
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int16_t,
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int,
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int64_t,
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bool,
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phi::float16) {}
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#endif
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