Skip to content

fuse

Fuse

Bases: NumpyOp

Run a sequence of NumpyOps as a single Op.

Parameters:

Name Type Description Default
ops Union[NumpyOp, List[NumpyOp]]

A sequence of NumpyOps to run. They must all share the same mode. It also doesn't support scheduled ops at the moment, though the Fuse itself may be scheduled.

 required

Raises:

Type Description
ValueError

If repeat or ops are invalid.
Source code in fastestimator\fastestimator\op\numpyop\meta\fuse.py 
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
@traceable()
class Fuse(NumpyOp):
    """Run a sequence of NumpyOps as a single Op.

    Args:
        ops: A sequence of NumpyOps to run. They must all share the same mode. It also doesn't support scheduled ops at
            the moment, though the Fuse itself may be scheduled.

    Raises:
        ValueError: If `repeat` or `ops` are invalid.
    """
    def __init__(self, ops: Union[NumpyOp, List[NumpyOp]]) -> None:
        ops = to_list(ops)
        if len(ops) < 1:
            raise ValueError("Fuse requires at least one op")
        inputs = []
        outputs = []
        mode = ops[0].mode
        ds_id = ops[0].ds_id
        for op in ops:
            if op.mode != mode:
                raise ValueError(f"All Fuse ops must share the same mode, but got {mode} and {op.mode}")
            if op.ds_id != ds_id:
                raise ValueError(f"All Fuse ops must share the same ds_id, but got {ds_id} and {op.ds_id}")
            for inp in op.inputs:
                if inp not in inputs and inp not in outputs:
                    inputs.append(inp)
            for out in op.outputs:
                if out not in outputs:
                    outputs.append(out)
        super().__init__(inputs=inputs, outputs=outputs, mode=mode, ds_id=ds_id)
        self.ops = ops

    def __getstate__(self) -> Dict[str, List[Dict[Any, Any]]]:
        return {'ops': [elem.__getstate__() if hasattr(elem, '__getstate__') else {} for elem in self.ops]}

    def set_rua_level(self, magnitude_coef: float) -> None:
        """Set the augmentation intensity based on the magnitude_coef.

        This method is specifically designed to be invoked by the RUA Op.

        Args:
            magnitude_coef: The desired augmentation intensity (range [0-1]).

        Raises:
            AttributeError: If ops don't have a 'set_rua_level' method.
        """
        for op in self.ops:
            if hasattr(op, "set_rua_level") and inspect.ismethod(getattr(op, "set_rua_level")):
                op.set_rua_level(magnitude_coef=magnitude_coef)
            else:
                raise AttributeError(
                    "RUA Augmentations should have a 'set_rua_level' method but it's not present in Op: {}".format(
                        op.__class__.__name__))

    def forward(self, data: List[np.ndarray], state: Dict[str, Any]) -> List[np.ndarray]:
        data = {key: elem for key, elem in zip(self.inputs, data)}
        forward_numpyop(self.ops, data, state)
        return [data[key] for key in self.outputs]

set_rua_level

Set the augmentation intensity based on the magnitude_coef.

This method is specifically designed to be invoked by the RUA Op.

Parameters:

Name Type Description Default
magnitude_coef float

The desired augmentation intensity (range [0-1]).

 required

Raises:

Type Description
AttributeError

If ops don't have a 'set_rua_level' method.
Source code in fastestimator\fastestimator\op\numpyop\meta\fuse.py 
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
def set_rua_level(self, magnitude_coef: float) -> None:
    """Set the augmentation intensity based on the magnitude_coef.

    This method is specifically designed to be invoked by the RUA Op.

    Args:
        magnitude_coef: The desired augmentation intensity (range [0-1]).

    Raises:
        AttributeError: If ops don't have a 'set_rua_level' method.
    """
    for op in self.ops:
        if hasattr(op, "set_rua_level") and inspect.ismethod(getattr(op, "set_rua_level")):
            op.set_rua_level(magnitude_coef=magnitude_coef)
        else:
            raise AttributeError(
                "RUA Augmentations should have a 'set_rua_level' method but it's not present in Op: {}".format(
                    op.__class__.__name__))