def update()

in ignite/metrics/gan/fid.py [0:0]

• 13 lines of code
• 9 McCabe index (conditional complexity)

    def update(self, output: Sequence[torch.Tensor]) -> None:

        train, test = output
        train_features = self._extract_features(train)
        test_features = self._extract_features(test)

        if train_features.shape[0] != test_features.shape[0] or train_features.shape[1] != test_features.shape[1]:
            raise ValueError(
                f"""
    Number of Training Features and Testing Features should be equal ({train_features.shape} != {test_features.shape})
                """
            )

        # Updates the mean and covariance for the train features
        for features in train_features:
            self._online_update(features, self._train_total, self._train_sigma)

        # Updates the mean and covariance for the test features
        for features in test_features:
            self._online_update(features, self._test_total, self._test_sigma)

        self._num_examples += train_features.shape[0]