Mojo struct
TensorSpec
A space efficient representation of a tensor shape and dtype. This struct implements value semantics and owns its underlying data.
Fields
- shape (
TensorShape): The underlying shape of the specification.
Implemented traits
AnyType,
CollectionElement,
Copyable,
EqualityComparable,
Formattable,
Movable,
Stringable
Methods
__init__
__init__(inout self: Self)
Default initializer for TensorShape.
__init__(inout self: Self, type: DType, *shapes: Int)
Initializes a Tensorspec from the dtype and shapes provided.
Args:
- type (
DType): The dtype of the specification. - *shapes (
Int): The shapes to initialize the shape with.
__init__(inout self: Self, type: DType, shape: Tuple[element_types])
Initializes a Tensorspec from the dtype and shapes provided.
Args:
- type (
DType): The dtype of the specification. - shape (
Tuple[element_types]): The shapes to initialize the shape with.
__init__(inout self: Self, type: DType, shapes: VariadicList[Int])
Initializes a Tensorspec from the dtype and shapes provided.
Args:
- type (
DType): The dtype of the specification. - shapes (
VariadicList[Int]): The shapes to initialize the shape with.
__init__(inout self: Self, type: DType, shapes: List[Int, hint_trivial_type])
Initializes a Tensorspec from the dtype and shapes provided.
Args:
- type (
DType): The dtype of the specification. - shapes (
List[Int, hint_trivial_type]): The shapes to initialize the shape with.
__init__(inout self: Self, type: DType, owned shape: TensorShape)
Initializes a Tensorspec from the dtype and shape provided.
Args:
- type (
DType): The dtype of the specification. - shape (
TensorShape): The shapes to initialize the shape with.
__copyinit__
__copyinit__(inout self: Self, other: Self)
Creates a deep copy of an existing spec.
Args:
- other (
Self): The spec to copy.
__moveinit__
__moveinit__(inout self: Self, owned existing: Self)
Move initializer for the spec.
Args:
- existing (
Self): The spec to move.
__getitem__
__getitem__(self: Self, index: Int) -> Int
Gets the dimension at the specified index.
Args:
- index (
Int): The dimension index.
Returns:
The dimension at the specified index.
__eq__
__eq__(self: Self, other: Self) -> Bool
Returns True if the two values are the same and False otherwise.
Args:
- other (
Self): The other TensorSpec to compare against.
Returns:
True if the two specs are the same and False otherwise.
__ne__
__ne__(self: Self, other: Self) -> Bool
Returns True if the two values are not the same and False otherwise.
Args:
- other (
Self): The other TensorSpec to compare against.
Returns:
True if the two specs are the not the same and False otherwise.
rank
rank(self: Self) -> Int
Gets the rank of the spec.
Returns:
The rank of the spec.
dtype
dtype(self: Self) -> DType
Gets the DType of the spec.
Returns:
The DType of the spec.
num_elements
num_elements(self: Self) -> Int
Gets the total number of elements in the spec.
Returns:
The total number of elements in the spec.
bytecount
bytecount(self: Self) -> Int
Gets the total byte count.
Returns:
The total byte count.
__repr__
__repr__(self: Self) -> String
Returns the string representation of the spec.
Returns:
The string representation of the spec.
__str__
__str__(self: Self) -> String
Returns the string representation of the spec.
Returns:
The string representation of the spec.
format_to
format_to(self: Self, inout writer: Formatter)
Formats this TensorSpec to the provided formatter.
Args:
- writer (
Formatter): The formatter to write to.
from_bytes
static from_bytes(data: UnsafePointer[SIMD[uint8, 1], 0, 0, alignof[::AnyType,__mlir_type.!kgen.target]() if triple_is_nvidia_cuda() else 1]) -> Self
Create a TensorSpec object from serialized bytes.
Args:
- data (
UnsafePointer[SIMD[uint8, 1], 0, 0, alignof[::AnyType,__mlir_type.!kgen.target]() if triple_is_nvidia_cuda() else 1]): UnsafePointer to serialized bytes.
Returns:
Given bytes as TensorSpec.
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