quick_anomaly_detector.data_process.check_valid_tensor_data

quick_anomaly_detector.data_process.check_valid_tensor_data(input_tensor)

Perform checks on the input tensor.

Parameters:

input_tensor (torch.Tensor) – Input tensor to be checked.

Returns:

A tuple containing a boolean indicating whether the input passes all checks and a message indicating the result of the checks.

Return type:

tuple[bool, str]

Example:

from quick_anomaly_detector.data_process import check_valid_tensor_data

input_tensor = torch.tensor([1.0, 2.0, float('nan'), 4.0])  # Example tensor with NaN
valid, message = check_valid_tensor_data(input_tensor)
print(valid, message)