OR

class hybrid_learning.fuzzy_logic.tnorm_connectives.boolean.OR(*in_keys, bool_thresh=None, **kwargs)[source]

Bases: AbstractOR, BoolTorchOrNumpyOperation

Union/OR operation on binary masks and scalars. Store union of in_keys masks as out_key. OR with just one input key x is treated like x||True, i.e. identity.

Public Data Attributes:

Inherited from : py: class:AbstractOR

SYMB

The string symbol of this class (override for sub-classes).

IS_COMMUTATIVE

Whether instances are equivalent to ones with permuted in_keys.

Inherited from : py: class:BoolTorchOrNumpyOperation

settings

Settings to reproduce the instance.

setting_defaults

Defaults used for settings.

Inherited from : py: class:Merge

SYMB

The string symbol of this class (override for sub-classes).

ARITY

The arity of the operation.

IS_COMMUTATIVE

Whether instances are equivalent to ones with permuted in_keys.

is_variadic

Whether the instance is variadic.

settings

Settings to reproduce the instance.

setting_defaults

Defaults used for settings.

pretty_op_symb

Name of the operation symbol suitable for filenames etc.

children

The input keys which are child operations.

all_children

All children operations in the flattened computational tree, sorted depth first.

consts

The constant string keys in the input keys.

operation_keys

The list of keys used for this parent operation in original order (constants and children output keys).

all_in_keys

All string input keys both of self and of all child operations.

all_out_keys

Output keys of self and all child operations.

Inherited from : py: class:DictTransform

settings

Settings to reproduce the instance.

Inherited from : py: class:Transform

IDENTITY_CLASS

The identity class or classes for composition / addition.

settings

Settings to reproduce the instance.

Public Methods:

Inherited from : py: class:BoolTorchOrNumpyOperation

numpy_operation(*inputs[, bool_thresh])

Threshold the inputs at bool_thresh and apply operation.

torch_operation(*inputs[, bool_thresh])

AND on pytorch tensors.

Inherited from : py: class:TorchOrNumpyOperation

operation(annotation_vals)

Operation on either torch tensors or Booleans, numpy arrays and numbers.

Inherited from : py: class:TorchOperation

operation(annotation_vals)

Operation on either torch tensors or Booleans, numpy arrays and numbers.

Inherited from : py: class:Merge

to_infix_notation([sort_key, ...])

Return an infix str encoding equal for differently sorted operations.

to_str(**infix_notation_kwargs)

Alias for to_infix_notation().

to_pretty_str(**infix_notation_kwargs)

Same as to_str() but using pretty operation names suitable for filenames etc.

to_repr([settings, defaults, sort_key, ...])

Return str representation which can be used to reproduce and compare the instance.

treerecurse_replace_keys(**replace_map)

Return a new formula with all occurences of variables in replace_map replaced and else identical settings.

treerecurse(fun)

Apply the given function recursively to this and all children instances.

apply_to(annotations[, keep_keys])

Apply this operation to the annotations dict.

variadic_apply_to(annotations)

Return the result of operation on the values/items of a mapping or sequence of arbitrary length.

operation(annotation_vals)

Operation on either torch tensors or Booleans, numpy arrays and numbers.

Inherited from : py: class:DictTransform

apply_to(annotations[, keep_keys])

Apply this operation to the annotations dict.

Inherited from : py: class:Transform

apply_to(annotations[, keep_keys])

Apply this operation to the annotations dict.

Special Methods:

Inherited from : py: class:BoolTorchOrNumpyOperation

__init__(*in_keys[, bool_thresh])

Init.

Inherited from : py: class:Merge

__init__(*in_keys[, bool_thresh])

Init.

__str__()

Return str(self).

__repr__()

Call to_repr() without sorting.

__eq__(other)

Two merge operations are considered equal, if their normalized representations coincide.

__copy__()

Return a deep copy of self using settings.

__call__(annotations[, keep_keys])

Call method modifying a given dictionary.

Inherited from : py: class:DictTransform

__call__(annotations[, keep_keys])

Call method modifying a given dictionary.

Inherited from : py: class:Transform

__repr__()

Call to_repr() without sorting.

__eq__(other)

Two merge operations are considered equal, if their normalized representations coincide.

__copy__()

Return a deep copy of self using settings.

__add__(other)

Return a flat composition of self with other.

__radd__(other)

Return a flat composition of other and self.

__call__(annotations[, keep_keys])

Call method modifying a given dictionary.


Parameters

bool_thresh (float) –

static bool_numpy_operation(*inputs)[source]

OR on numpy-like vectors.

Parameters

inputs (ndarray) –

Return type

ndarray

static bool_torch_operation(*inputs)[source]

OR on torch tensors.

Parameters

inputs (Tensor) –

Return type

Tensor

cache_duplicates: bool

Whether to cache duplicate child operation outputs with duplicate out_key. If set to false, all children and children children are evaluated and the values of duplicate out_keys are evaluated several times and overwritten, possibly leading to more computational time while using less memory. Note that the order of children execution is determined by their order in in_keys, depth first for nested operations.

in_keys: Sequence[Union[str, 'Merge']]

The keys of segmentation masks to unite in given order. Keys are either constant strings or a merge operation.

keep_keys: Optional[Collection[str]]

The keys of intermediate outputs in all_out_keys which should be added to the return of a call. Default (None or empty collection): duplicate children outputs are cached but not returned to save memory.

out_key: str

The key to use to store the merge output in the annotations dict. Take care to not accidentally overwrite existing keys (cf. overwrite).

overwrite: Union[bool, Literal['noop']]

Whether to overwrite a value in the input dictionary when applying this operation. The operation is defined in operation(). The key that may be overwritten is stored in out_key. An exception is raised if this is False and the key exists. If set to 'noop' and out_key is in the given annotations dict, it is returned unchanged.

replace_none: Optional[Any]

If not None, any received None value is replaced by the given value. This is done only for computation, the None value in the received dict is left unchanged. Key-value pairs with None value may come from the input or from child operations.

skip_none: bool

If set to True, when a None input value is encountered simply None is returned. If False, an error is raised.