已合并
test(nn): add NPU tests for global full backward hooks #37875
coconut创建于 6月8日
test(nn): add NPU tests for global full backward hooks #37875
已合并
共 1 个文件变更+63-0
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| 1 | +""" | ||
| 2 | +Add validation cases for torch.nn global module hook APIs on NPU: | ||
| 3 | + | ||
| 4 | +1. PyTorch community lacks direct validations for some global backward hook APIs. | ||
| 5 | +2. This file validates torch.nn.modules.module.register_module_full_backward_hook and | ||
| 6 | + torch.nn.modules.module.register_module_full_backward_pre_hook. | ||
| 7 | + | ||
| 8 | +""" | ||
| 9 | + | ||
| 10 | +import torch | ||
| 11 | +from torch.testing._internal.common_utils import TestCase, run_tests | ||
| 12 | + | ||
| 13 | + | ||
| 14 | +device_type = acc.type if (acc := torch.accelerator.current_accelerator()) else "cpu" | ||
| 15 | + | ||
| 16 | + | ||
| 17 | +class TestGlobalModuleFullBackwardHooks(TestCase): | ||
| 18 | + | ||
| 19 | + def test_register_module_full_backward_hook(self): | ||
| 20 | + module = torch.nn.Sigmoid().to(device_type) | ||
| 21 | + inp = torch.randn(5, 5, device=device_type, requires_grad=True) | ||
| 22 | + sig_x = torch.sigmoid(inp) | ||
| 23 | + calls = [] | ||
| 24 | + | ||
| 25 | + def hook(mod, grad_input, grad_output): | ||
| 26 | + if isinstance(mod, torch.nn.Sigmoid): | ||
| 27 | + calls.append(mod) | ||
| 28 | + return (grad_input[0] * 2,) | ||
| 29 | + return None | ||
| 30 | + | ||
| 31 | + handle = torch.nn.modules.module.register_module_full_backward_hook(hook) | ||
| 32 | + try: | ||
| 33 | + module(inp).backward(torch.ones(5, 5, device=device_type)) | ||
| 34 | + finally: | ||
| 35 | + handle.remove() | ||
| 36 | + | ||
| 37 | + self.assertEqual(len(calls), 1) | ||
| 38 | + self.assertEqual(inp.grad, sig_x * (1 - sig_x) * 2) | ||
| 39 | + | ||
| 40 | + def test_register_module_full_backward_pre_hook(self): | ||
| 41 | + module = torch.nn.Sigmoid().to(device_type) | ||
| 42 | + inp = torch.randn(5, 5, device=device_type, requires_grad=True) | ||
| 43 | + sig_x = torch.sigmoid(inp) | ||
| 44 | + calls = [] | ||
| 45 | + | ||
| 46 | + def hook(mod, grad_output): | ||
| 47 | + if isinstance(mod, torch.nn.Sigmoid): | ||
| 48 | + calls.append(mod) | ||
| 49 | + return (grad_output[0] * 0.5,) | ||
| 50 | + return None | ||
| 51 | + | ||
| 52 | + handle = torch.nn.modules.module.register_module_full_backward_pre_hook(hook) | ||
| 53 | + try: | ||
| 54 | + module(inp).backward(torch.ones(5, 5, device=device_type)) | ||
| 55 | + finally: | ||
| 56 | + handle.remove() | ||
| 57 | + | ||
| 58 | + self.assertEqual(len(calls), 1) | ||
| 59 | + self.assertEqual(inp.grad, sig_x * (1 - sig_x) * 0.5) | ||
| 60 | + | ||
| 61 | + | ||
| 62 | +if __name__ == "__main__": | ||
| 63 | + run_tests() | ||