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9e049a32a1
* WIP POC of dispatcher * Dispatcher python workflow setup. * Dispatcher cleanup and updates. Further dispatcher cleanup and updates. Build fixes Improvements and python to CK example Improvements to readme * Fixes to python paths * Cleaning up code * Improving dispatcher support for different arch Fixing typos * Fix formatting errors * Cleaning up examples * Improving codegeneration * Improving and fixing C++ examples * Adding conv functionality (fwd,bwd,bwdw) and examples. * Fixes based on feedback. * Further fixes based on feedback. * Adding stress test for autogeneration and autocorrection, and fixing preshuffle bug. * Another round of improvements based on feedback. * Trimming out unnecessary code. * Fixing the multi-D implementation. * Using gpu verification for gemms and fixing convolutions tflops calculation. * Fix counter usage issue and arch filtering per ops. * Adding changelog and other fixes. * Improve examples and resolve critical bugs. * Reduce build time for python examples. * Fixing minor bug. * Fix compilation error. * Improve installation instructions for dispatcher. * Add docker based installation instructions for dispatcher. * Fixing arch-based filtering to match tile engine. * Remove dead code and fix arch filtering. * Minor bugfix. * Updates after rebase. * Trimming code. * Fix copyright headers. * Consolidate examples, cut down code. * Minor fixes. * Improving python examples. * Update readmes. * Remove conv functionality. * Cleanup following conv removable.
97 lines
1.9 KiB
C++
97 lines
1.9 KiB
C++
// Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
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// SPDX-License-Identifier: MIT
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/// Unit tests for Problem using Google Test
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#include "ck_tile/dispatcher/problem.hpp"
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#include <gtest/gtest.h>
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using namespace ck_tile::dispatcher;
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TEST(ProblemTest, DefaultConstruction)
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{
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Problem p;
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EXPECT_EQ(p.M, 0);
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EXPECT_EQ(p.N, 0);
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EXPECT_EQ(p.K, 0);
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EXPECT_EQ(p.k_batch, 1);
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EXPECT_FALSE(p.is_valid());
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}
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TEST(ProblemTest, ConstructorWithDimensions)
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{
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Problem p(1024, 1024, 1024);
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EXPECT_EQ(p.M, 1024);
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EXPECT_EQ(p.N, 1024);
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EXPECT_EQ(p.K, 1024);
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EXPECT_TRUE(p.is_valid());
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}
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TEST(ProblemTest, Validation)
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{
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Problem p;
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// Invalid: all zeros
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p.M = 0;
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p.N = 0;
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p.K = 0;
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EXPECT_FALSE(p.is_valid());
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// Invalid: negative
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p.M = -1;
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p.N = 1024;
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p.K = 1024;
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EXPECT_FALSE(p.is_valid());
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// Invalid: zero K
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p.M = 1024;
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p.N = 1024;
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p.K = 0;
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EXPECT_FALSE(p.is_valid());
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// Valid
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p.M = 1024;
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p.N = 1024;
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p.K = 1024;
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EXPECT_TRUE(p.is_valid());
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// Invalid k_batch
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p.k_batch = 0;
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EXPECT_FALSE(p.is_valid());
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p.k_batch = 1;
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EXPECT_TRUE(p.is_valid());
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}
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TEST(ProblemTest, NumOps)
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{
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Problem p(100, 200, 300);
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// 2 * M * N * K (multiply-add = 2 ops)
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std::int64_t expected = 2 * 100 * 200 * 300;
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EXPECT_EQ(p.num_ops(), expected);
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}
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TEST(ProblemTest, Configuration)
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{
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Problem p(1024, 1024, 1024);
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// Set preferences
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p.prefer_persistent = true;
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p.enable_validation = true;
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p.smem_budget = 65536;
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p.k_batch = 2;
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EXPECT_TRUE(p.prefer_persistent);
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EXPECT_TRUE(p.enable_validation);
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EXPECT_EQ(p.smem_budget, 65536);
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EXPECT_EQ(p.k_batch, 2);
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}
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TEST(ProblemTest, LargeDimensions)
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{
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Problem p(1024, 1024, 1024); // Use smaller but still large dimensions
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EXPECT_TRUE(p.is_valid());
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EXPECT_GT(p.num_ops(), 0);
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}
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