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## Job Test running on most CI jobs. ## Test binary * `test_main.cpp`: entry for gtest * `test_operator_registration.cpp`: test cases for gtest ## Helper sources * `operator_registry.h/cpp`: simple operator registry for testing purpose. * `Evalue.h`: a boxed data type that wraps ATen types, for testing purpose. * `selected_operators.yaml`: operators Executorch care about so far, we should cover all of them. ## Templates * `NativeFunctions.h`: for generating headers for native functions. (not compiled in the test, since we will be using `libtorch`) * `RegisterCodegenUnboxedKernels.cpp`: for registering boxed operators. * `Functions.h`: for declaring operator C++ APIs. Generated `Functions.h` merely wraps `ATen/Functions.h`. ## Build files * `CMakeLists.txt`: generate code to register ops. * `build.sh`: driver file, to be called by CI job. Pull Request resolved: https://github.com/pytorch/pytorch/pull/89596 Approved by: https://github.com/ezyang
29 lines
821 B
C++
29 lines
821 B
C++
#include "operator_registry.h"
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#include <gtest/gtest.h>
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namespace torch {
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namespace executor {
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// add.out(Tensor self, Tensor other, *, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!)
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TEST(OperatorRegistrationTest, Add) {
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EValue values[4];
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values[0] = EValue(at::ones({2, 3}));
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values[1] = EValue(at::ones({2, 3}));
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values[2] = EValue(int64_t(1));
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values[3] = EValue(at::zeros({2, 3}));
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ASSERT_TRUE(hasOpsFn("aten::add.out"));
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auto op = getOpsFn("aten::add.out");
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EValue* kernel_values[4];
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for (size_t i = 0; i < 4; i++) {
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kernel_values[i] = &values[i];
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}
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op(kernel_values);
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at::Tensor expected = at::ones({2, 3});
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expected = at::fill(expected, 2);
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ASSERT_TRUE(expected.equal(kernel_values[3]->toTensor()));
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}
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} // namespace executor
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} // namespace torch
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