tff.types.TensorType

An implementation of tff.Type representing types of tensors in TFF.

Inherits From: Type

tff.types.TensorType(
    dtype: _DtypeLike, shape: array_shape._ArrayShapeLike = ()
)

dtype The np.dtype of the array.
shape The shape of the array.

TypeError if arguments are of the wrong types.

dtype

shape

Methods

check_assignable_from

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check_assignable_from(
    source_type: 'Type'
) -> None

Raises if values of source_type cannot be cast to this type.

check_equivalent_to

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check_equivalent_to(
    other: 'Type'
) -> None

Raises if values of 'other' cannot be cast to and from this type.

check_identical_to

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check_identical_to(
    other: 'Type'
) -> None

Raises if other and Type are not exactly identical.

children

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children() -> Iterator[Type]

Returns a generator yielding immediate child types.

compact_representation

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compact_representation() -> str

Returns the compact string representation of this type.

formatted_representation

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formatted_representation() -> str

Returns the formatted string representation of this type.

is_assignable_from

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is_assignable_from(
    source_type: tff.types.Type
) -> bool

Returns whether values of source_type can be cast to this type.

is_equivalent_to

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is_equivalent_to(
    other: 'Type'
) -> bool

Returns whether values of other can be cast to and from this type.

is_identical_to

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is_identical_to(
    other: 'Type'
) -> bool

Returns whether or not self and other are exactly identical.

__eq__

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__eq__(
    other
)

Determines whether two type definitions are identical.

Note that this notion of equality is stronger than equivalence. Two types with equivalent definitions may not be identical, e.g., if they represent templates with differently named type variables in their definitions.

Args
other The other type to compare against.

Returns
True if type definitions are syntactically identical (as defined above), otherwise False.

Raises
NotImplementedError If not implemented in the derived class.

__ne__

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__ne__(
    other
)

Return self!=value.