Infery includes error-handling logically.
In this page we will go through their meaning.
InferyError- A base class for all the of infery's exceptions.
Inference (Runtime) Exceptions
InputTypeError- Inputs are passed in wrong data structure (e.g. torch.Tensor instead of List).
ModelFrameworkRuntimeError- An error that occurred in the model's framework runtime, after the model was loaded.
ForwardPassNotImplemented- A pure forward-pass method is not implemented for the inferencer, thus it cannot be used.
DTypeError- Mismatch between expected dtype and received dtype.
MaxBatchSizeExceededError- In dynamic batch size models, Specified batch size exceeds maximum value allowed by model.
MappingKeyError- Unrecognized key or attribute was passed to a mapping data structure (dict, Enum, Schema, etc.)
ModelFrameworkDetectionError- The framework type could not be automatically inferred from the checkpoint. Please specify the framework type explicitly, by passing 'framework_type=...' to infery.load.
EmptyInputValue- A required value was not provided.
Model Loading Exceptions
FrameworkNotSupportedError- The specified framework is not supported. Please refer to FrameworkType enum for valid values.
CheckpointFileDoesNotExistError- The specified checkpoint file does not exist at the specified path.
InvalidInputDimensions- The specified input dimensions is not a valid tuple.
InvalidStaticBatchSize- The specified static batch size is not a valid int.
InvalidInferenceHardware- The specified inference hardware is not valid. Please refer to InferenceHardware enum for valid values.
InvalidLoggingLevel- The specified logging level is not valid. Please select from the logging package's standard logging level values.
InputDimensionsNotSpecifiedError- The model's input dimensions were not specified, but they are required for benchmarks inputs generation. Please specify the input dimensions via 'input_dims' argument.
FailedToLoadCheckpointError- The checkpoint failed to load for any reason.
CorruptedModelCompressionError- Failed to unpack the saved model zip/tar file, corrupted zip/tar.
CorruptedSavedModelZipError- Failed to unpack the saved model zip file, corrupted zip.
BadSavedModelZipError- Failed to load the saved model from the provided zip file, it may be missing.
MissingFileModelError- Failed to load the saved model from the provided zip/tar file, the model is missing.
ModelFrameworkNotLoadedError- An internal error indicating an import is missing for running inference for the model's framework.
ModelValueError- An error that occurred in the model's initialization/preperation, before or while the model was loaded.