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buffer init fix and gpu_hlo_runner test
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| /* Copyright 2022 The OpenXLA Authors. | ||
| Licensed 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. | ||
| ==============================================================================*/ | ||
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| #include <fstream> | ||
| #include <sstream> | ||
| #include "xla/error_spec.h" | ||
| #include "xla/literal_comparison.h" | ||
| #include "xla/service/custom_call_target_registry.h" | ||
| #include "xla/service/gpu/tests/gpu_codegen_test.h" | ||
| #include "xla/tests/hlo_test_base.h" | ||
| #include "xla/tests/test_utils.h" | ||
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| namespace xla { | ||
| namespace gpu { | ||
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| template <class T> | ||
| std::vector<T*> MakePointerVector(std::vector<T>& input_vec) { | ||
| std::vector<T*> output_pointers; | ||
| output_pointers.reserve(input_vec.size()); | ||
| for (auto& input : input_vec) { | ||
| output_pointers.push_back(&input); | ||
| } | ||
| return output_pointers; | ||
| } | ||
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| class HloRunnerTest : public GpuCodegenTest {}; | ||
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| TEST_F(HloRunnerTest, RunSingle) { | ||
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| std::ifstream ifs("input.hlo"); | ||
| ASSERT_TRUE(ifs.good()); | ||
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| std::stringstream buffer; | ||
| buffer << ifs.rdbuf(); | ||
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| HloModuleConfig config = GetModuleConfigForTest(); | ||
| #if 1 | ||
| //config.set_num_partitions(8); | ||
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| TF_ASSERT_OK_AND_ASSIGN(auto module, ParseAndReturnVerifiedModule(buffer.str(), | ||
| config)); | ||
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| auto ref_module = module->Clone(); | ||
| TF_ASSERT_OK_AND_ASSIGN(auto exec, test_runner_.CreateExecutable(std::move(module), true)); | ||
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| VLOG(0) << "Creating fake args.."; | ||
| TF_ASSERT_OK_AND_ASSIGN(auto fake_arguments, xla::MakeFakeArguments(ref_module.get(), | ||
| true, /*pseudo-random*/ | ||
| false /* use large range*/)); | ||
| auto arg_ptrs = MakePointerVector<xla::Literal>(fake_arguments); | ||
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| auto& ref_runner = HloTestBase::reference_runner_; | ||
| TF_ASSERT_OK_AND_ASSIGN( | ||
| auto ref_exec, ref_runner.CreateExecutable(std::move(ref_module), true)); | ||
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| // TF_ASSERT_OK_AND_ASSIGN(auto truth, | ||
| // ReadLiteralFromProto("/tf/xla/expected.pb")); | ||
| // TF_ASSERT_OK_AND_ASSIGN(auto truth, | ||
| // ref_runner.ExecuteWithExecutable(ref_exec.get(), arg_ptrs, nullptr)); | ||
| // WriteLiteralToTempFile(truth, "expected"); | ||
| //VLOG(0) << "Got expected literal from file.. running test"; | ||
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| TF_ASSERT_OK_AND_ASSIGN( | ||
| auto test_res, test_runner_.ExecuteWithExecutable(exec.get(), arg_ptrs)); | ||
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| VLOG(0) << "Running reference exec.."; | ||
| TF_ASSERT_OK_AND_ASSIGN( | ||
| auto truth, ref_runner.ExecuteWithExecutable(ref_exec.get(), arg_ptrs)); | ||
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| ErrorSpec error_spec{1e-2, 1e-3}; | ||
| //ErrorSpec error_spec(1e-5 /*abs*/, 1e-5 /*rel*/); | ||
| ASSERT_EQ(literal_comparison::Near(/*expected=*/truth, | ||
| /*actual=*/test_res, | ||
| /*error=*/error_spec, | ||
| /*detailed_message=*/true, {}), absl::OkStatus()); | ||
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| // EXPECT_TRUE(RunAndCompare(std::move(module), | ||
| // // absl::Span< xla::Literal * const>(arg_ptrs.data(), arg_ptrs.size()), error_spec)); | ||
| #else | ||
| int NumReplicas = 8, NumParts = 1; | ||
| config.set_replica_count(NumReplicas); | ||
| config.set_num_partitions(NumParts); | ||
| TF_ASSERT_OK_AND_ASSIGN( | ||
| auto module, ParseAndReturnVerifiedModule(buffer.str(), config)); | ||
| DeviceAssignment assn(/*replica_count=*/NumReplicas, | ||
| /*computation_count=*/NumParts); | ||
| for (int64_t i = 0, k = 0; i < NumReplicas; i++) | ||
| for (int64_t j = 0; j < NumParts; j++) { | ||
| assn(i, j) = k++; | ||
| } | ||
| auto fake_arguments = xla::MakeFakeArguments( | ||
| module.get(), | ||
| true, /*pseudo-random*/ | ||
| false /* use large range*/).ValueOrDie(); | ||
| TF_ASSERT_OK_AND_ASSIGN(auto exec, | ||
| test_runner_.CreateExecutable(std::move(module), true)); | ||
| for(int i = 0; i < 10; i++) { | ||
| VLOG(0) << "Running iteration #" << i; | ||
| TF_ASSERT_OK_AND_ASSIGN(std::vector<Literal> results, | ||
| HloTestBase::ExecuteReplicated( | ||
| [&](int64_t){ return exec.get(); }, | ||
| [&fake_arguments](int64_t replica_id) | ||
| { return fake_arguments.size(); }, | ||
| [&fake_arguments](int64_t replica_id, int64_t idx) | ||
| { return &fake_arguments[idx]; }, | ||
| NumReplicas, false /*run hlo*/, &assn)); | ||
| ASSERT_EQ(results.size(), NumReplicas); | ||
| } | ||
| #endif | ||
| } | ||
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| } // namespace gpu | ||
| } // namespace xla | ||
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