initializers_test.py 文件源码

def test_regex_matches_are_initialized_correctly(self):
        class Net(torch.nn.Module):
            def __init__(self):
                super(Net, self).__init__()
                self.linear_1_with_funky_name = torch.nn.Linear(5, 10)
                self.linear_2 = torch.nn.Linear(10, 5)
                self.conv = torch.nn.Conv1d(5, 5, 5)

            def forward(self, inputs):  # pylint: disable=arguments-differ
                pass

        # pyhocon does funny things if there's a . in a key.  This test makes sure that we
        # handle these kinds of regexes correctly.
        json_params = """{"initializer": [
        ["conv", {"type": "constant", "val": 5}],
        ["funky_na.*bi", {"type": "constant", "val": 7}]
        ]}
        """
        params = Params(pyhocon.ConfigFactory.parse_string(json_params))
        initializers = InitializerApplicator.from_params(params['initializer'])
        model = Net()
        initializers(model)

        for parameter in model.conv.parameters():
            assert torch.equal(parameter.data, torch.ones(parameter.size()) * 5)

        parameter = model.linear_1_with_funky_name.bias
        assert torch.equal(parameter.data, torch.ones(parameter.size()) * 7)