Avoid too many return statements within this function.

Open

        return socketio_webhook

Avoid too many return statements within this function.

Open

            return response.text("success")

Avoid too many return statements within this function.

Open

                return response.text("success")

Avoid too many return statements within this function.

Open

                    return

Avoid too many return statements within this function.

Open

        return 1 if target else -1

Avoid too many return statements within this function.

Open

                    return 0

Function create_report_file has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

def create_report_file() -> None:
    data = {}
    for dirpath, dirnames, files in os.walk(os.environ["RESULT_DIR"]):
        for f in files:
            if f not in TASK_MAPPING.keys():

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Function validate_outdoor_seating has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

    def validate_outdoor_seating(
        self,
        value: Text,
        dispatcher: CollectingDispatcher,
        tracker: Tracker,

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Function get_local_model has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

def get_local_model(model_path: Text = DEFAULT_MODELS_PATH) -> Text:
    """Returns verified path to local model archive.

    Args:
        model_path: Path to the zipped model. If it's a directory, the latest

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Function main has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

def main() -> None:
    """Run as standalone python application."""
    parse_last_positional_argument_as_model_path()
    arg_parser = create_argument_parser()
    cmdline_arguments = arg_parser.parse_args()

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Function _rasa_predict has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

    def _rasa_predict(
        self, batch_in: Tuple[np.ndarray, ...]
    ) -> Dict[Text, Union[np.ndarray, Dict[Text, Any]]]:
        """Custom prediction method that builds tf graph on the first call.

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Function convert_to_data_format has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

def convert_to_data_format(
    features: Union[
        List[List[Dict[Text, List["Features"]]]], List[Dict[Text, List["Features"]]]
    ],
    fake_features: Optional[Dict[Text, List["Features"]]] = None,

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Function Grid has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

  grid-column-gap: ${({ spacious, tiny, noGap }) =>
    noGap ? 0 : spacious ? '5rem' : tiny ? '.75rem' : '1.875rem'};

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Function send_all_to_datadog has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

def send_all_to_datadog() -> None:
    results = []
    for dirpath, dirnames, files in os.walk(os.environ["RESULT_DIR"]):
        for f in files:
            if any(f.endswith(valid_name) for valid_name in TASK_MAPPING.keys()):

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Function _anonymizer has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

def _anonymizer(
    _: structlog.BoundLogger, __: str, event_dict: Dict[str, Any]
) -> Dict[str, Any]:
    """Anonymizes event dict."""
    anonymizable_keys = [

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Function _sparse_feature_sizes_have_increased has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

    def _sparse_feature_sizes_have_increased(
        new_sparse_feature_sizes: Dict[Text, Dict[Text, List[int]]],
        old_sparse_feature_sizes: Dict[Text, Dict[Text, List[int]]],
    ) -> bool:
        """Checks if the sizes of sparse features have increased during fine-tuning.

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Function _features_as_token_ids has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

    def _features_as_token_ids(
        self, features: List[Union[tf.Tensor, tf.SparseTensor]]
    ) -> Optional[tf.Tensor]:
        """Creates dense labels (token IDs) used for negative sampling in MLM."""
        # If there are dense features, we use them as labels - taking the first dense

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Function apply_mask_and_scaling has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

    def apply_mask_and_scaling(
        self, loss: tf.Tensor, mask: Optional[tf.Tensor]
    ) -> tf.Tensor:
        """Scales the loss and applies the mask if necessary.

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Function as_story_string has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

    def as_story_string(self, flat: bool = False, e2e: bool = False) -> Text:
        story_content = ""
        for step in self.story_steps:
            story_content += step.as_story_string(flat, e2e)

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Function load_data has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

def load_data(resource_name: Text, language: Optional[Text] = "en") -> "TrainingData":
    """Load training data from disk.

    Merges them if loaded from disk and multiple files are found.
    """

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