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66 lines
2.4 KiB
C++
66 lines
2.4 KiB
C++
/*
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* The MIT License (MIT)
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*
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* Copyright (c) 2015-2022 Advanced Micro Devices, Inc. All rights reserved.
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*
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* Permission is hereby granted, free of charge, to any person obtaining a copy
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* of this software and associated documentation files (the "Software"), to deal
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* in the Software without restriction, including without limitation the rights
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* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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* copies of the Software, and to permit persons to whom the Software is
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* 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 FROM,
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* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
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* THE SOFTWARE.
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*/
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#include <migraphx/config.hpp>
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#include <migraphx/cpu/dnnl.hpp>
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namespace migraphx {
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inline namespace MIGRAPHX_INLINE_NS {
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namespace cpu {
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struct dnnl_layernorm : dnnl_op<dnnl_layernorm, dnnl::layer_normalization_forward>
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{
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float epsilon = 1e-12f;
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template <class Self, class F>
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static auto reflect(Self& self, F f)
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{
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return pack(f(self.epsilon, "epsilon"));
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}
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std::string name() const { return "dnnl::layernorm"; }
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shape compute_shape(std::vector<shape> inputs) const
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{
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// Compensate for allocation
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inputs.pop_back();
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check_shapes{this->trim_post_op_inputs(inputs), *this}.has(1);
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auto s = inputs.at(0);
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// Call to get_primitive to make sure an algo is available
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this->get_primitive(this->to_memory_desc(s, inputs));
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return s;
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}
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dnnl::layer_normalization_forward::desc
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get_desc(const std::unordered_map<int, dnnl::memory::desc>& m) const
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{
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return {dnnl::prop_kind::forward_inference,
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m.at(MIGRAPHX_DNNL_PREFIX(ARG_SRC)),
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1e-12f,
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dnnl::normalization_flags::none};
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}
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};
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} // namespace cpu
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} // namespace MIGRAPHX_INLINE_NS
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} // namespace migraphx
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