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 telegram_webhook

Avoid too many return statements within this function.

Open

                        return response.text("success")

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 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 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 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 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 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 _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 _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 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 _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 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 _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 _init_from_dict has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

    def _init_from_dict(self, _dict: Dict[Text, Any], parent_directory: Text) -> None:
        imports = _dict.get("imports") or []
        imports = [os.path.join(parent_directory, i) for i in imports]
        # clean out relative paths
        imports = [os.path.abspath(i) for i in imports]

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

Open

def require_response_keys(
    responses: List[Dict[Text, Any]], _: Dict, __: Text
) -> Union[SchemaError, bool]:
    """Validates that response dicts have either the "text" key or the "custom" key."""
    for response in responses:

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