test/test_modules.py

from torch.testing._internal.common_device_type import instantiate_device_type_tests
from torch.testing._internal.common_modules import module_db, modules
from torch.testing._internal.common_utils import TestCase, run_tests, freeze_rng_state


class TestModule(TestCase):
    _do_cuda_memory_leak_check = True
    _do_cuda_non_default_stream = True
    precision = 1e-5
    rel_tol = 1e-5

    @modules(module_db)
    def test_forward(self, device, dtype, module_info):
        module_cls = module_info.module_cls
        module_inputs = module_info.module_inputs_func(module_info, device=device, dtype=dtype,
                                                       requires_grad=False)
        for module_input in module_inputs:
            if module_input.forward_input is None:
                continue

            with freeze_rng_state():
                # === Instantiate the module. ===
                args, kwargs = module_input.constructor_input.args, module_input.constructor_input.kwargs
                m = module_cls(*args, **kwargs)
                m.to(device).to(dtype)

                # === Do forward pass. ===
                args, kwargs = module_input.forward_input.args, module_input.forward_input.kwargs
                outputs = m(*args, **kwargs)

                # === Compare outputs to a reference if one is specified. ===
                # TODO: Handle precision
                reference_fn = module_input.reference_fn
                if reference_fn is not None:
                    ref_outputs = reference_fn(m, *args, **kwargs)
                    self.assertEqual(outputs, ref_outputs)


instantiate_device_type_tests(TestModule, globals())

if __name__ == '__main__':
    run_tests()