altametris.sara.core.exceptions¶

Custom exceptions for Altametris libraries.

Provides a hierarchy of exceptions for different error scenarios: - AltametrisException: Base exception - ModelError: Model-related errors (loading, architecture, weights) - TrainingError: Training-related errors (dataset, convergence, OOM) - InferenceError: Inference-related errors (input format, device) - ExportError: Export-related errors (format, validation) - ConfigurationError: Configuration-related errors (invalid parameters)

Exceptions¶

`AltametrisException`	Base exception for all Altametris libraries.
`ModelError`	Exception raised for model-related errors.
`TrainingError`	Exception raised for training-related errors.
`InferenceError`	Exception raised for inference-related errors.
`ExportError`	Exception raised for export-related errors.
`ConfigurationError`	Exception raised for configuration-related errors.

Functions¶

validate_param(→ None)

Validate a parameter and raise ConfigurationError if invalid.

Module Contents¶

exception altametris.sara.core.exceptions.AltametrisException(message: str, details: dict[str, Any] | None = None)¶

Bases: Exception

Base exception for all Altametris libraries.

All custom exceptions inherit from this base class to allow catching all Altametris-specific errors with a single except clause.

Parameters:

message – Error message describing what went wrong
details – Optional dictionary with additional error context

Example

>>> try:
...     raise AltametrisException("Something went wrong", {"code": 500})
... except AltametrisException as e:
...     print(e)
...     print(e.details)

message¶

details¶

__str__() → str¶: Return string representation of exception.

__repr__() → str¶: Return repr representation of exception.

exception altametris.sara.core.exceptions.ModelError(message: str, details: dict[str, Any] | None = None)¶

Bases: AltametrisException

Exception raised for model-related errors.

Scenarios: - Failed to load model weights - Invalid model architecture - Corrupted checkpoint file - Incompatible model version - Missing required model files

Example

>>> raise ModelError(
...     "Failed to load weights",
...     {"path": "model.pt", "reason": "File not found"}
... )

exception altametris.sara.core.exceptions.TrainingError(message: str, details: dict[str, Any] | None = None)¶

Bases: AltametrisException

Exception raised for training-related errors.

Scenarios: - Dataset not found or invalid format - Training divergence (NaN loss) - Out of memory during training - Invalid hyperparameters - Checkpoint save failure

Example

>>> raise TrainingError(
...     "Training diverged",
...     {"epoch": 10, "loss": float('nan'), "lr": 0.001}
... )

exception altametris.sara.core.exceptions.InferenceError(message: str, details: dict[str, Any] | None = None)¶

Bases: AltametrisException

Exception raised for inference-related errors.

Scenarios: - Invalid input format (wrong shape, type) - Device mismatch (model on CUDA, input on CPU) - Prediction failure - Post-processing error - Batch size too large for memory

Example

>>> raise InferenceError(
...     "Invalid input shape",
...     {"expected": (3, 640, 640), "got": (640, 640)}
... )

exception altametris.sara.core.exceptions.ExportError(message: str, details: dict[str, Any] | None = None)¶

Bases: AltametrisException

Exception raised for export-related errors.

Scenarios: - Unsupported export format - Export validation failed - Missing export dependencies (onnx, tensorrt) - Dynamic shapes not supported - Export optimization failed

Example

>>> raise ExportError(
...     "ONNX export failed",
...     {"format": "onnx", "reason": "Dynamic axes not supported"}
... )

exception altametris.sara.core.exceptions.ConfigurationError(message: str, details: dict[str, Any] | None = None)¶

Bases: AltametrisException

Exception raised for configuration-related errors.

Scenarios: - Invalid configuration parameter - Missing required configuration key - Configuration validation failed - Incompatible configuration values - Invalid YAML/JSON format

Example

>>> raise ConfigurationError(
...     "Invalid batch_size",
...     {"parameter": "batch_size", "value": -1, "expected": "> 0"}
... )

altametris.sara.core.exceptions.validate_param(condition: bool, param_name: str, value: Any, expected: str) → None¶

Validate a parameter and raise ConfigurationError if invalid.

Parameters:

condition – Condition that must be True (if False, raises exception)
param_name – Name of the parameter being validated
value – Current value of the parameter
expected – Description of expected value

Raises:

ConfigurationError – If condition is False

Example

>>> validate_param(batch_size > 0, "batch_size", batch_size, "> 0")
>>> validate_param(device in ["cpu", "cuda"], "device", device, "cpu or cuda")