sometimes

Sometimes

Bases: NumpyOp

Perform a NumpyOp with a given probability.

Parameters:

Name	Type	Description	Default
numpy_op	NumpyOp	The operator to be performed.	required
prob	float	The probability of execution, which should be in the range: [0-1).	0.5

Source code in fastestimator\fastestimator\op\numpyop\meta\sometimes.py

class Sometimes(NumpyOp):
    """Perform a NumpyOp with a given probability.

    Args:
        numpy_op: The operator to be performed.
        prob: The probability of execution, which should be in the range: [0-1).
    """
    def __init__(self, numpy_op: NumpyOp, prob: float = 0.5) -> None:
        super().__init__(inputs=numpy_op.inputs, outputs=numpy_op.outputs, mode=numpy_op.mode)
        self.numpy_op = numpy_op
        self.prob = prob

    def forward(self, data: Union[np.ndarray, List[np.ndarray]],
                state: Dict[str, Any]) -> Union[np.ndarray, List[np.ndarray]]:
        """Execute the wrapped operator a certain fraction of the time.

        Args:
            data: The information to be passed to the wrapped operator.
            state: Information about the current execution context, for example {"mode": "train"}.

        Returns:
            The original `data`, or the `data` after running it through the wrapped operator.
        """
        if self.prob > np.random.uniform():
            data = self.numpy_op.forward(data, state)
        return data

forward

Execute the wrapped operator a certain fraction of the time.

Parameters:

Name	Type	Description	Default
data	Union[np.ndarray, List[np.ndarray]]	The information to be passed to the wrapped operator.	required
state	Dict[str, Any]	Information about the current execution context, for example {"mode": "train"}.	required

Returns:

Type	Description
Union[np.ndarray, List[np.ndarray]]	The original data, or the data after running it through the wrapped operator.

Source code in fastestimator\fastestimator\op\numpyop\meta\sometimes.py

def forward(self, data: Union[np.ndarray, List[np.ndarray]],
            state: Dict[str, Any]) -> Union[np.ndarray, List[np.ndarray]]:
    """Execute the wrapped operator a certain fraction of the time.

    Args:
        data: The information to be passed to the wrapped operator.
        state: Information about the current execution context, for example {"mode": "train"}.

    Returns:
        The original `data`, or the `data` after running it through the wrapped operator.
    """
    if self.prob > np.random.uniform():
        data = self.numpy_op.forward(data, state)
    return data