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413 lines
18 KiB
C++
413 lines
18 KiB
C++
/*******************************************************************************
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*
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* MIT License
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*
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* Copyright (c) 2022-2025 Advanced Micro Devices, Inc.
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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 all
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* 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 THE
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* SOFTWARE.
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*
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*******************************************************************************/
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#include "test.hpp"
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#include <array>
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#include <iostream>
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#include <iterator>
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#include <limits>
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#include <memory>
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#include <miopen/activ.hpp>
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#include <miopen/miopen.h>
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#include <miopen/stringutils.hpp>
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#include <miopen/tensor.hpp>
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#include <utility>
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#include <fusionHost.hpp>
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#include "verify.hpp"
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#include "gtest/gtest.h"
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#include <half/half.hpp>
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struct ActivationConfig
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{
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size_t N;
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size_t C;
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size_t H;
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size_t W;
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friend std::ostream& operator<<(std::ostream& outStream, const ActivationConfig& activConfig)
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{
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return outStream << "N:" << activConfig.N << " C:" << activConfig.C
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<< " H:" << activConfig.H << " W:" << activConfig.W;
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}
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};
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template <typename T>
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struct GPU_TestActivationBase
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: public ::testing::TestWithParam<std::tuple<miopenActivationMode_t, ActivationConfig>>
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{
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protected:
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void SetUp() override
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{
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std::tie(activ_mode, activ_config) = GetParam();
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double alpha = 0.95;
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double beta = 2.3;
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double gamma = 3.4;
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input = tensor<T>{activ_config.N, activ_config.C, activ_config.H, activ_config.W};
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input.generate(tensor_elem_gen_integer{17});
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dinput_cpu = input;
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dinput_gpu = input;
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miopenCreateActivationDescriptor(&activ_desc);
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miopenSetActivationDescriptor(activ_desc, activ_mode, alpha, beta, gamma);
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std::size_t n, c, h, w;
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auto&& handle = get_handle();
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std::tie(n, c, h, w) = miopen::tien<4>(input.desc.GetLengths());
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size_t total_mem =
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4 * input.desc.GetNumBytes(); // estimate based on both forward and backward passes
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size_t device_mem = handle.GetGlobalMemorySize();
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ASSERT_LT(total_mem, device_mem) << "Tensor exceeds system memory size";
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output_gpu =
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tensor<T>{static_cast<size_t>(n), // n from miopenGetConvolutionForwardOutputDim ?
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static_cast<size_t>(c),
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static_cast<size_t>(h),
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static_cast<size_t>(w)};
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output_cpu_ref =
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tensor<T>{static_cast<size_t>(n), // n from miopenGetConvolutionForwardOutputDim ?
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static_cast<size_t>(c),
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static_cast<size_t>(h),
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static_cast<size_t>(w)};
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std::fill(output_gpu.begin(), output_gpu.end(), std::numeric_limits<T>::quiet_NaN());
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std::fill(
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output_cpu_ref.begin(), output_cpu_ref.end(), std::numeric_limits<T>::quiet_NaN());
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// Infer on CPU, forward
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activationHostInfer(activ_mode,
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gamma, // 0.0f?
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beta, // 0.0f?
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alpha, // 0.0f?
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input.data, // Input
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output_cpu_ref.data); // Output
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// Infer on CPU, backward
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doutput = output_cpu_ref;
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doutput.generate([&](int n1, int c1, int h1, int w1) {
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float x = output_cpu_ref(n1, c1, h1, w1);
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double y =
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(877 * n1 + 547 * c1 + 701 * h1 + 1049 * w1 + static_cast<int>(769 * x)) % 2503;
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return ((x * y) / 1301.0);
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});
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activationHostBwd(activ_mode,
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gamma,
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beta,
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alpha,
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doutput.data, // dy
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input.data, // x
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output_cpu_ref.data, // y
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dinput_cpu.data); // dx
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in_dev = handle.Write(input.data);
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out_dev = handle.Write(output_gpu.data);
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din_dev = handle.Write(dinput_gpu.data);
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dout_dev = handle.Write(doutput.data);
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}
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void TearDown() override
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{
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auto&& handle = get_handle();
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// Read data from GPU
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output_gpu.data = handle.Read<T>(out_dev, output_gpu.data.size());
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CompareTensors(output_cpu_ref, output_gpu);
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if(isBwdActivation)
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{
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dinput_gpu.data = handle.Read<T>(din_dev, dinput_gpu.data.size());
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CompareTensors(dinput_cpu, dinput_gpu);
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}
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miopenDestroyActivationDescriptor(activ_desc);
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}
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template <class T1, class T2>
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void CompareTensors(T1&& t1, T2&& t2)
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{
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double tolerance = 80;
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EXPECT_FALSE(miopen::range_zero(t1)) << "CPU data is all zeros. Config: " << activ_config;
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EXPECT_FALSE(miopen::range_zero(t2)) << "GPU data is all zeros. Config: " << activ_config;
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EXPECT_EQ(miopen::range_distance(t1), miopen::range_distance(t2))
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<< "range distance b/w CPU and GPU not equal. Config:" << activ_config;
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using value_type = miopen::range_value<decltype(t2)>;
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double threshold = std::numeric_limits<value_type>::epsilon() * tolerance;
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std::vector<double> error{miopen::rms_range(t1, t2)};
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EXPECT_FALSE(error.front() > threshold) << "Config:" << activ_config;
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return;
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}
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bool isBwdActivation;
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tensor<T> input; // x
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tensor<T> output_gpu; // share
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tensor<T> output_cpu_ref; // y share
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tensor<T> dinput_cpu; // dx
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tensor<T> dinput_gpu;
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tensor<T> doutput;
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ActivationConfig activ_config;
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miopenActivationMode_t activ_mode;
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miopenActivationDescriptor_t activ_desc;
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miopen::Allocator::ManageDataPtr in_dev; // x
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miopen::Allocator::ManageDataPtr out_dev; // y
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miopen::Allocator::ManageDataPtr din_dev; // dx
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miopen::Allocator::ManageDataPtr dout_dev; // dy
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};
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struct GPU_TestActivation_FP32 : public GPU_TestActivationBase<float>
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{
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};
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struct GPU_TestActivation_FP16 : public GPU_TestActivationBase<half_float::half>
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{
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};
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miopenStatus_t RunFwdActivation(const miopen::Handle& handle,
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miopenActivationDescriptor_t activationDesc,
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const void* alpha,
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const miopen::TensorDescriptor& xDesc,
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ConstData_t x,
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const void* beta,
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const miopen::TensorDescriptor& yDesc,
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Data_t y)
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{
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if(alpha == nullptr || beta == nullptr)
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MIOPEN_THROW(miopenStatusBadParm, "alpha or beta is NULL");
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miopen::ActivationDescriptor desc = miopen::deref(activationDesc);
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miopenStatus_t status = desc.Forward(handle,
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alpha,
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xDesc, // input.desc
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x, // in_dev.get()
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beta,
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yDesc, // output_gpu.desc
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y); // out_dev.get()
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return status;
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}
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miopenStatus_t RunFwdBwdActivation(const miopen::Handle& handle,
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miopenActivationDescriptor_t activationDesc,
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const void* alpha,
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const miopen::TensorDescriptor& xDesc,
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ConstData_t x,
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const void* beta,
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const miopen::TensorDescriptor& yDesc,
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Data_t y,
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const miopen::TensorDescriptor& dyDesc,
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ConstData_t dy,
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const miopen::TensorDescriptor& dxDesc,
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Data_t dx)
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{
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if(alpha == nullptr || beta == nullptr)
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MIOPEN_THROW(miopenStatusBadParm, "alpha or beta is NULL");
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miopen::ActivationDescriptor desc = miopen::deref(activationDesc);
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miopenStatus_t fwdStatus = desc.Forward(handle,
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alpha,
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xDesc, // input.desc
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x, // in_dev.get()
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beta,
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yDesc, // output_gpu.desc
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y); // out_dev.get()
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miopenStatus_t bwdStatus = desc.Backward(handle,
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alpha,
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yDesc, // out.desc
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y, // out_dev.get()
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dyDesc,
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dy,
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xDesc, // input.desc
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x,
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beta,
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dxDesc,
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dx);
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if(fwdStatus == miopenStatusSuccess && bwdStatus == miopenStatusSuccess)
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return miopenStatusSuccess;
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else if(fwdStatus != miopenStatusSuccess)
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return fwdStatus;
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else
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return bwdStatus;
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}
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TEST_P(GPU_TestActivation_FP32, ActivationFwdTest)
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{
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const float alpha = 1.0f, beta = 0;
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isBwdActivation = false;
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miopenStatus_t status = RunFwdActivation(get_handle(),
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activ_desc,
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&alpha,
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input.desc, // x
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in_dev.get(),
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&beta,
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output_gpu.desc, // y
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out_dev.get());
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EXPECT_EQ(status, miopenStatusSuccess) << "Forward activation failed. Config: " << activ_config;
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}
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TEST_P(GPU_TestActivation_FP16, ActivationFwdTest)
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{
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const float alpha = 1.0f, beta = 0;
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isBwdActivation = false;
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miopenStatus_t status = RunFwdActivation(get_handle(),
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activ_desc,
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&alpha,
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input.desc, // x
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in_dev.get(),
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&beta,
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output_gpu.desc, // y
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out_dev.get());
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EXPECT_EQ(status, miopenStatusSuccess) << "Forward activation failed. Config: " << activ_config;
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}
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TEST_P(GPU_TestActivation_FP32, ActivationBwdTest)
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{
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const float alpha = 1.0f, beta = 0;
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isBwdActivation = true;
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miopenStatus_t status = RunFwdBwdActivation(get_handle(),
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activ_desc,
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&alpha,
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input.desc, // x
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in_dev.get(),
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&beta,
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output_gpu.desc, // y
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out_dev.get(),
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doutput.desc, // dy
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dout_dev.get(),
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dinput_gpu.desc, // dx
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din_dev.get());
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EXPECT_EQ(status, miopenStatusSuccess)
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<< "Backward activation failed. Config: " << activ_config;
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}
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TEST_P(GPU_TestActivation_FP16, ActivationBwdTest)
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{
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const float alpha = 1.0f, beta = 0;
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isBwdActivation = true;
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miopenStatus_t status = RunFwdBwdActivation(get_handle(),
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activ_desc,
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&alpha,
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input.desc, // x
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in_dev.get(),
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&beta,
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output_gpu.desc, // y
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out_dev.get(),
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doutput.desc, // dy
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dout_dev.get(),
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dinput_gpu.desc, // dx
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din_dev.get());
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EXPECT_EQ(status, miopenStatusSuccess)
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<< "Backward activation failed. Config: " << activ_config;
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}
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std::string GetActivationModeName(miopenActivationMode_t mode)
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{
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switch(mode)
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{
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case miopenActivationPASTHRU: return "PASSTHRU";
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case miopenActivationLOGISTIC: return "LOGISTIC";
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case miopenActivationTANH: return "TANH";
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case miopenActivationRELU: return "RELU";
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case miopenActivationSOFTRELU: return "SOFTRELU";
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case miopenActivationABS: return "ABS";
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case miopenActivationPOWER: return "POWER";
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case miopenActivationLEAKYRELU: return "LEAKYRELU";
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case miopenActivationELU: return "ELU";
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case miopenActivationCLIPPEDRELU: return "CLIPPEDRELU";
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case miopenActivationCLAMP: return "UNKNOWN";
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}
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}
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struct PrintToStringParamName
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{
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std::string operator()(
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const testing::TestParamInfo<std::tuple<miopenActivationMode_t, ActivationConfig>>& info)
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const
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{
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auto activ_mode = std::get<0>(info.param);
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std::string mode_str = GetActivationModeName(activ_mode);
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return std::to_string(info.index) + "_" + mode_str;
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}
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};
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INSTANTIATE_TEST_SUITE_P(Full,
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GPU_TestActivation_FP32,
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::testing::Combine(::testing::Values(miopenActivationPASTHRU,
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miopenActivationLOGISTIC,
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miopenActivationTANH,
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miopenActivationRELU,
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miopenActivationSOFTRELU,
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miopenActivationABS,
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miopenActivationPOWER,
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// miopenActivationCLIPPEDRELU,
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miopenActivationLEAKYRELU,
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miopenActivationELU),
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::testing::Values(ActivationConfig{128, 128, 16, 16},
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ActivationConfig{128, 16, 16, 16},
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ActivationConfig{16, 128, 16, 16},
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ActivationConfig{16, 32, 8, 8},
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ActivationConfig{32, 16, 8, 8},
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ActivationConfig{2, 16, 5, 4},
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ActivationConfig{2, 2, 2, 2})),
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PrintToStringParamName());
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INSTANTIATE_TEST_SUITE_P(Full,
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GPU_TestActivation_FP16,
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::testing::Combine(::testing::Values(miopenActivationPASTHRU,
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miopenActivationLOGISTIC,
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miopenActivationTANH,
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miopenActivationRELU,
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miopenActivationSOFTRELU,
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miopenActivationABS,
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miopenActivationPOWER,
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// miopenActivationCLIPPEDRELU,
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miopenActivationLEAKYRELU,
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miopenActivationELU),
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::testing::Values(ActivationConfig{128, 128, 16, 16},
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ActivationConfig{128, 16, 16, 16},
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ActivationConfig{16, 128, 16, 16},
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ActivationConfig{16, 32, 8, 8},
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ActivationConfig{32, 16, 8, 8},
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ActivationConfig{2, 16, 5, 4},
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ActivationConfig{2, 2, 2, 2})),
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PrintToStringParamName());
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