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dfdb86a595
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/24801 This is to fix the ODR-violations in fbcode static builds, which have been broken for several months. This PR is unfortunately quite large, but the changes are only mechanical: 1. Tests defined in header files -> tests defined in cpp files 2. Remove the `torch::jit::testing` namespace -> `torch::jit`. 3. Single `test.h` file that aggregates all tests. 4. Separate out files for gtest and python versions of the tests instead of using a build flag 5. Add a readme for how to add a new test, and explaining a bit about why the cpp tests are the way they are. Test Plan: Imported from OSS Differential Revision: D16878605 Pulled By: suo fbshipit-source-id: 27b5c077dadd990a5f74e25d01731f9c1f491603
32 lines
1.0 KiB
C++
32 lines
1.0 KiB
C++
#include "test/cpp/jit/test_base.h"
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#include "test/cpp/jit/test_utils.h"
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namespace torch {
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namespace jit {
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void testInterp() {
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constexpr int batch_size = 4;
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constexpr int input_size = 256;
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constexpr int seq_len = 32;
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int hidden_size = 2 * input_size;
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auto input = at::randn({seq_len, batch_size, input_size}, at::kCUDA);
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auto hx = at::randn({batch_size, hidden_size}, at::kCUDA);
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auto cx = at::randn({batch_size, hidden_size}, at::kCUDA);
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auto w_ih = t_def(at::randn({4 * hidden_size, input_size}, at::kCUDA));
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auto w_hh = t_def(at::randn({4 * hidden_size, hidden_size}, at::kCUDA));
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auto lstm_g = build_lstm();
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Code lstm_function(lstm_g);
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InterpreterState lstm_interp(lstm_function);
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auto outputs = run(lstm_interp, {input[0], hx, cx, w_ih, w_hh});
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std::tie(hx, cx) = lstm(input[0], hx, cx, w_ih, w_hh);
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// std::cout << almostEqual(outputs[0],hx) << "\n";
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ASSERT_TRUE(exactlyEqual(outputs[0], hx));
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ASSERT_TRUE(exactlyEqual(outputs[1], cx));
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}
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} // namespace jit
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} // namespace torch
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