CUTLASS 2.5
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@@ -1,4 +1,4 @@
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# Copyright (c) 2017-2020, NVIDIA CORPORATION. All rights reserved.
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# Copyright (c) 2017-2021, NVIDIA CORPORATION. All rights reserved.
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#
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# Redistribution and use in source and binary forms, with or without modification, are permitted
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# provided that the following conditions are met:
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@@ -1,5 +1,5 @@
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/***************************************************************************************************
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* Copyright (c) 2017-2020, NVIDIA CORPORATION. All rights reserved.
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* Copyright (c) 2017-2021, NVIDIA CORPORATION. All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without modification, are permitted
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* provided that the following conditions are met:
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@@ -485,6 +485,7 @@ Result profile_convolution(Options const &options) {
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// Split K dimension into 1 partitions
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int split_k_slices = 1;
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// Construct Conv2dProblemSize with user defined output size
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cutlass::conv::Conv2dProblemSize problem_size(
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options.input_size,
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options.filter_size,
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@@ -495,6 +496,8 @@ Result profile_convolution(Options const &options) {
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mode,
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split_k_slices);
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// Construct ImplicitGemm::Argument structure with conv2d
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// problem size, data pointers, and epilogue values
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typename ImplicitGemm::Arguments arguments{
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problem_size,
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tensor_a.device_ref(),
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@@ -515,6 +518,9 @@ Result profile_convolution(Options const &options) {
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// Allocate workspace memory
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cutlass::device_memory::allocation<uint8_t> workspace(workspace_size);
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result.status = implicit_gemm_op.can_implement(arguments);
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CUTLASS_CHECK(result.status);
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result.status = implicit_gemm_op.initialize(arguments, workspace.get());
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CUTLASS_CHECK(result.status);
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