masahi commented on a change in pull request #9737: URL: https://github.com/apache/tvm/pull/9737#discussion_r768971377
########## File path: python/tvm/contrib/cutlass/conv2d_profiler.py ########## @@ -0,0 +1,163 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. +# pylint: disable=import-outside-toplevel, invalid-name +"""Instantiate a C++ source for profiling CUTLASS kernels.""" + + +class Conv2dProfilerEmitter(object): + """Emit a C++ source for profiling CUTLASS kernels.""" + + def __init__(self): + from jinja2 import Template + + self.template = Template( + """ +#include <iostream> +#include "cutlass/cutlass.h" +#include "cutlass/conv/kernel/default_conv2d_fprop.h" +#include "cutlass/conv/device/implicit_gemm_convolution.h" +#include "cutlass/util/command_line.h" +#include "cutlass/util/host_tensor.h" +#include "cutlass/util/reference/host/tensor_fill.h" + +#define CUTLASS_CHECK(status) \ + { \ + cutlass::Status error = status; \ + if (error != cutlass::Status::kSuccess) { \ + std::cerr << "Got cutlass error: " << cutlassGetStatusString(error) << " at: " << __LINE__ \ + << std::endl; \ + exit(EXIT_FAILURE); \ + } \ + } + +{{OperatorDef}} +using ImplicitGemm = cutlass::conv::device::ImplicitGemmConvolution<{{OperatorName}}>; + +struct Options { + cutlass::Tensor4DCoord input_size; + cutlass::Tensor4DCoord filter_size; + cutlass::Tensor4DCoord padding; + cutlass::MatrixCoord conv_stride; + cutlass::MatrixCoord dilation; + + void parse(int argc, char const **args) { + cutlass::CommandLine cmd(argc, args); + cmd.get_cmd_line_argument("n", input_size.n()); + cmd.get_cmd_line_argument("h", input_size.h()); + cmd.get_cmd_line_argument("w", input_size.w()); + cmd.get_cmd_line_argument("c", input_size.c()); + cmd.get_cmd_line_argument("k", filter_size.n()); + cmd.get_cmd_line_argument("r", filter_size.h()); + cmd.get_cmd_line_argument("s", filter_size.w()); + int pad_h, pad_w, stride_h, stride_w, dilation_h, dilation_w; + cmd.get_cmd_line_argument("pad_h", pad_h); + cmd.get_cmd_line_argument("pad_w", pad_w); + cmd.get_cmd_line_argument("stride_h", stride_h); + cmd.get_cmd_line_argument("stride_w", stride_w); + cmd.get_cmd_line_argument("dilation_h", dilation_h); + cmd.get_cmd_line_argument("dilation_w", dilation_w); + filter_size.c() = input_size.c(); + padding = {pad_h, pad_h, pad_w, pad_w}; + conv_stride = {stride_h, stride_w}; + dilation = {dilation_h, dilation_w}; + } + + cutlass::Tensor4DCoord output_size() const { + auto dilated_h = (filter_size.h() - 1) * dilation.row() + 1; + auto dilated_w = (filter_size.w() - 1) * dilation.column() + 1; + auto h = (input_size.h() + padding.n() + padding.h() - dilated_h) / conv_stride.row() + 1; + auto w = (input_size.w() + padding.w() + padding.c() - dilated_w) / conv_stride.column() + 1; + return cutlass::Tensor4DCoord(input_size.n(), h, w, filter_size.n()); + } +}; + +double profile_convolution(Options const &options) { + using ElementOutput = typename ImplicitGemm::ElementC; + using ElementInputA = typename ImplicitGemm::ElementA; + using ElementInputB = typename ImplicitGemm::ElementB; + auto oshape = options.output_size(); + cutlass::HostTensor<ElementInputA, typename ImplicitGemm::LayoutA> tensor_a(options.input_size); + cutlass::HostTensor<ElementInputB, typename ImplicitGemm::LayoutB> tensor_b(options.filter_size); + cutlass::HostTensor<ElementOutput, typename ImplicitGemm::LayoutC> tensor_c(oshape); + cutlass::HostTensor<ElementOutput, typename ImplicitGemm::LayoutC> tensor_ref_c(oshape); + + cutlass::conv::Conv2dProblemSize problem_size( + options.input_size, + options.filter_size, + options.padding, + options.conv_stride, + options.dilation, + options.output_size(), + cutlass::conv::Mode::kCrossCorrelation, + 1 + ); + + using ElementComputeEpilogue = typename ImplicitGemm::ElementCompute; + typename ImplicitGemm::Arguments arguments{ + problem_size, + tensor_a.device_ref(), + tensor_b.device_ref(), + tensor_c.device_ref(), + tensor_c.device_ref(), + {ElementComputeEpilogue(1), ElementComputeEpilogue(0)}, + }; + + ImplicitGemm implicit_gemm_op; + size_t workspace_size = implicit_gemm_op.get_workspace_size(arguments); + cutlass::device_memory::allocation<uint8_t> workspace(workspace_size); + auto status = implicit_gemm_op.can_implement(arguments); + CUTLASS_CHECK(status); + + status = implicit_gemm_op.initialize(arguments, workspace.get()); + CUTLASS_CHECK(status); + status = implicit_gemm_op(); + CUTLASS_CHECK(status); + + cudaEvent_t events[2]; + for (auto & event : events) { + cudaEventCreate(&event); + } + cudaEventRecord(events[0]); Review comment: Anyway, I want to defer addressing this problem in future PR. -- This is an automated message from the Apache Git Service. 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