78 lines
3.5 KiB
C++
78 lines
3.5 KiB
C++
/****************************************************************************
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*
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* Copyright (c) 2020-2023 Vivante Corporation
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*
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* Permission is hereby granted, free of charge, to any person obtaining a
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* copy of this software and associated documentation files (the "Software"),
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* to deal in the Software without restriction, including without limitation
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* the rights to use, copy, modify, merge, publish, distribute, sublicense,
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* and/or sell copies of the Software, and to permit persons to whom the
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* Software is furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in
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* all copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
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* FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
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* DEALINGS IN THE SOFTWARE.
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*
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*****************************************************************************/
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#ifndef TIM_LAYOUT_INFER_SIMMPLE_OPS_LAYOUT_INFERENCE_H_
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#define TIM_LAYOUT_INFER_SIMMPLE_OPS_LAYOUT_INFERENCE_H_
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#include "tim/vx/ops/simple_operations.h"
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#include "ops/op_layout_inference.h"
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#include "permute_vector.h"
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#include "builtin_op_impl.h"
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namespace tim {
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namespace transform {
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template <typename OpType>
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class SimpleOpsLayoutInfer : public OpLayoutInfer {
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public:
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SimpleOpsLayoutInfer(
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const std::shared_ptr<vx::Operation> op,
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std::shared_ptr<layout_inference_impl::LayoutInferContext>& context)
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: OpLayoutInfer(op, context) {}
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void OnInputs(
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std::vector<std::shared_ptr<vx::Tensor>>& next_tensors) override {
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// Transmit input pv to out pv directly for simple ops
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assert(op_->impl()->InputsTensor().size() == 1);
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auto i_src = op_->impl()->InputsTensor()[0];
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auto input_pv = context_->GetPermuteVector(i_src);
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auto out_infer = CreateOutputsTensor(input_pv);
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auto simple_op = context_->infer_graph_->CreateOperation<OpType>();
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(*simple_op)
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.BindInput(context_->GetMappedTensor(i_src))
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.BindOutput(out_infer[0]);
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context_->SetPermuteVector(op_->impl()->OutputsTensor()[0], input_pv);
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next_tensors.push_back(op_->impl()->OutputsTensor()[0]);
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}
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};
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using DataConvertLayoutInfer = SimpleOpsLayoutInfer<vx::ops::DataConvert>;
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using NegLayoutInfer = SimpleOpsLayoutInfer<vx::ops::Neg>;
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using AbsLayoutInfer = SimpleOpsLayoutInfer<vx::ops::Abs>;
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using SinLayoutInfer = SimpleOpsLayoutInfer<vx::ops::Sin>;
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using CosLayoutInfer = SimpleOpsLayoutInfer<vx::ops::Cos>;
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using TanLayoutInfer = SimpleOpsLayoutInfer<vx::ops::Tan>;
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using ATanLayoutInfer = SimpleOpsLayoutInfer<vx::ops::ATan>;
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using ATanhLayoutInfer = SimpleOpsLayoutInfer<vx::ops::ATanh>;
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using ACoshLayoutInfer = SimpleOpsLayoutInfer<vx::ops::ACosh>;
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using ExpLayoutInfer = SimpleOpsLayoutInfer<vx::ops::Exp>;
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using LogLayoutInfer = SimpleOpsLayoutInfer<vx::ops::Log>;
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using SqrtLayoutInfer = SimpleOpsLayoutInfer<vx::ops::Sqrt>;
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using RsqrtLayoutInfer = SimpleOpsLayoutInfer<vx::ops::Rsqrt>;
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using SquareLayoutInfer = SimpleOpsLayoutInfer<vx::ops::Square>;
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using LogicalNotLayoutInfer = SimpleOpsLayoutInfer<vx::ops::LogicalNot>;
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} // namespace transform
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} // namespace tim
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#endif |