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358450e02b
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/33834 This changes how we report Tracebacks to make them more clear when there are both serialized and non-serialized ranges. It now looks like: ``` Traceback (most recent call last): File "foo.py", line 25, in <module> s2(a, b) File "/scratch/zdevito/pytorch/torch/nn/modules/module.py", line 550, in __call__ result = self.forward(*input, **kwargs) RuntimeError: The following operation failed in the TorchScript interpreter. Traceback of TorchScript, serialized code (most recent call last): File "code/__torch__.py", line 7, in forward x: Tensor, y: Tensor) -> Tensor: return (self).bar(x, y, ) ~~~~~~~~~ <--- HERE def bar(self: __torch__.Moo, x: Tensor, File "code/__torch__.py", line 11, in bar x: Tensor, y: Tensor) -> Tensor: _0 = (self).baz(x, y, ) ~~~~~~~~~ <--- HERE _1 = torch.ones([3], dtype=None, layout=None, device=None, pin_memory=None) return torch.add(_0, _1, alpha=1) File "code/__torch__.py", line 17, in baz x: Tensor, y: Tensor) -> Tensor: return torch.add(x, y, alpha=1) ~~~~~~~~~ <--- HERE Traceback of TorchScript, original code (most recent call last): File "foo.py", line 11, in forward def forward(self, x, y): return self.bar(x, y) ~~~~~~~~ <--- HERE File "foo.py", line 9, in bar def bar(self, x, y): return self.baz(x, y) + torch.ones(3) ~~~~~~~~ <--- HERE File "foo.py", line 7, in baz def baz(self, x, y): return x + y ~~~~~ <--- HERE RuntimeError: The size of tensor a (4) must match the size of tensor b (5) at non-singleton dimension 1 ``` It follows Python convension of having the most important information last and reading from the bottom up. Changes: * Moved the error message to the end, to copy Python * Report original traceback separate from serialized traceback * Make sure root functions have names in the interpreter trace. Test Plan: Imported from OSS Differential Revision: D20126136 Pulled By: zdevito fbshipit-source-id: fd01f9985e5d74e04c4d064c02e8bc320f4fac13
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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