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expand_dims

ExpandDims

Bases: NumpyOp

Expand the dimension of inputs by inserting a new axis to the specified axis position.

Parameters:

Name Type Description Default
inputs Union[str, Iterable[str]]

Key(s) of inputs to be modified.

 required
outputs Union[str, Iterable[str]]

Key(s) into which to write the modified inputs.

 required
mode Union[None, str, Iterable[str]]

What mode(s) to execute this Op in. For example, "train", "eval", "test", or "infer". To execute regardless of mode, pass None. To execute in all modes except for a particular one, you can pass an argument like "!infer" or "!train".

 None
ds_id Union[None, str, Iterable[str]]

What dataset id(s) to execute this Op in. To execute regardless of ds_id, pass None. To execute in all ds_ids except for a particular one, you can pass an argument like "!ds1".

 None
axis int

The axis to expand.

 -1
Source code in fastestimator/fastestimator/op/numpyop/univariate/expand_dims.py 
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@traceable()
class ExpandDims(NumpyOp):
    """Expand the dimension of inputs by inserting a new axis to the specified axis position.

    Args:
        inputs: Key(s) of inputs to be modified.
        outputs: Key(s) into which to write the modified inputs.
        mode: What mode(s) to execute this Op in. For example, "train", "eval", "test", or "infer". To execute
            regardless of mode, pass None. To execute in all modes except for a particular one, you can pass an argument
            like "!infer" or "!train".
        ds_id: What dataset id(s) to execute this Op in. To execute regardless of ds_id, pass None. To execute in all
            ds_ids except for a particular one, you can pass an argument like "!ds1".
        axis: The axis to expand.
    """
    def __init__(self,
                 inputs: Union[str, Iterable[str]],
                 outputs: Union[str, Iterable[str]],
                 mode: Union[None, str, Iterable[str]] = None,
                 ds_id: Union[None, str, Iterable[str]] = None,
                 axis: int = -1):
        super().__init__(inputs=inputs, outputs=outputs, mode=mode, ds_id=ds_id)
        self.axis = axis
        self.in_list, self.out_list = True, True

    def forward(self, data: List[np.ndarray], state: Dict[str, Any]) -> List[np.ndarray]:
        return [np.expand_dims(elem, self.axis) for elem in data]