Interface: Tensor

torchlive/torch.Tensor

Indexable

▪ [index: number]: Tensor

Access tensor with index.

const tensor = torch.rand([2]);
console.log(tensor.data, tensor[0].data);
// [0.8339180946350098, 0.17733973264694214], [0.8339180946350098]

https://pytorch.org/cppdocs/notes/tensor_indexing.html

Properties

dtype

• dtype: Dtype

A dtype is an string that represents the data type of a torch.Tensor.

https://pytorch.org/docs/1.12/tensor_attributes.html

---

shape

• shape: number[]

Returns the size of the tensor.

https://pytorch.org/docs/1.12/generated/torch.Tensor.size.html

Methods

abs

▸ abs(): Tensor

Computes the absolute value of each element in input.

https://pytorch.org/docs/1.12/generated/torch.Tensor.abs.html

Returns

Tensor

---

add

▸ add(other, options?): Tensor

Add a scalar or tensor to this tensor.

https://pytorch.org/docs/1.12/generated/torch.Tensor.add.html

Parameters

Name	Type
other	Tensor
options?	Object
options.alpha?	Number

Returns

Tensor

▸ add(other, options?): Tensor

Parameters

Name	Type
other	number
options?	Object
options.alpha?	Number

Returns

Tensor

---

argmax

▸ argmax(options?): Tensor

Returns the indices of the maximum value of all elements in the input tensor.

https://pytorch.org/docs/1.12/generated/torch.Tensor.argmax.html

Parameters

Name	Type
options?	Object
options.dim?	number
options.keepdim?	boolean

Returns

Tensor

---

argmin

▸ argmin(options?): Tensor

Returns the indices of the minimum value(s) of the flattened tensor or along a dimension

https://pytorch.org/docs/1.12/generated/torch.Tensor.argmin.html

Parameters

Name	Type
options?	Object
options.dim?	number
options.keepdim?	boolean

Returns

Tensor

---

clamp

▸ clamp(min, max?): Tensor

Clamps all elements in input into the range [ min, max ].

If min is undefined, there is no lower bound. Or, if max is undefined there is no upper bound.

https://pytorch.org/docs/1.12/generated/torch.Tensor.clamp.html

Parameters

Name	Type	Description
min	number | Tensor	Lower-bound of the range to be clamped to
max?	number | Tensor	Upper-bound of the range to be clamped to

Returns

Tensor

▸ clamp(options): Tensor

Clamps all elements in input into the range [ min, max ].

If min is undefined, there is no lower bound. Or, if max is undefined there is no upper bound.

https://pytorch.org/docs/1.12/generated/torch.Tensor.clamp.html

Parameters

Name	Type	Description
options	Object	-
options.max?	number | Tensor	Upper-bound of the range to be clamped to
options.min?	number | Tensor	Lower-bound of the range to be clamped to

Returns

Tensor

---

contiguous

▸ contiguous(options?): Tensor

Returns a contiguous in memory tensor containing the same data as this tensor. If this tensor is already in the specified memory format, this function returns this tensor.

https://pytorch.org/docs/1.12/generated/torch.Tensor.contiguous.html

Parameters

Name	Type
options?	Object
options.memoryFormat?	MemoryFormat

Returns

Tensor

---

data

▸ data(): TypedArray

Returns the tensor data as TypedArray buffer.

A valid TypeScript expression is as follows:

torch.rand([2, 3]).data()[3];

note

The function only exists in JavaScript.

experimental

https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray

Returns

TypedArray

---

div

▸ div(other, options): Tensor

Divides each element of the input input by the corresponding element of other.

https://pytorch.org/docs/1.12/generated/torch.Tensor.div.html

Parameters

Name	Type
other	Tensor
options	Object
options.roundingMode	"trunc" | "floor"

Returns

Tensor

▸ div(other, options): Tensor

Parameters

Name	Type
other	number
options	Object
options.roundingMode	"trunc" | "floor"

Returns

Tensor

▸ div(other): Tensor

Parameters

Name	Type
other	Tensor

Returns

Tensor

▸ div(other): Tensor

Parameters

Name	Type
other	number

Returns

Tensor

---

expand

▸ expand(size, options?): Tensor

Returns a new view of the tensor expanded to a larger size.

https://pytorch.org/docs/1.12/generated/torch.Tensor.expand.html

Parameters

Name	Type
size	number[]
options?	Object
options.implicit?	boolean

Returns

Tensor

---

flip

▸ flip(dims): Tensor

Reverse the order of a n-D tensor along given axis in dims.

https://pytorch.org/docs/1.12/generated/torch.Tensor.flip.html

Parameters

Name	Type
dims	number[]

Returns

Tensor

---

item

▸ item(): number

Returns the value of this tensor as a number. This only works for tensors with one element.

https://pytorch.org/docs/1.12/generated/torch.Tensor.item.html

Returns

number

---

matmul

▸ matmul(other): Tensor

Performs matrix multiplication with other tensor.

https://pytorch.org/docs/1.12/generated/torch.Tensor.matmul.html

Parameters

Name	Type
other	Tensor

Returns

Tensor

---

mul

▸ mul(other): Tensor

Multiplies input by other scalar or tensor.

https://pytorch.org/docs/1.12/generated/torch.Tensor.mul.html

Parameters

Name	Type
other	Tensor

Returns

Tensor

▸ mul(other): Tensor

Parameters

Name	Type
other	number

Returns

Tensor

---

permute

▸ permute(dims): Tensor

Returns a view of the original tensor input with its dimensions permuted.

https://pytorch.org/docs/1.12/generated/torch.Tensor.permute.html

Parameters

Name	Type
dims	number[]

Returns

Tensor

---

reshape

▸ reshape(shape): Tensor

Returns a tensor with the same data and number of elements as input, but with the specified shape.

https://pytorch.org/docs/1.12/generated/torch.Tensor.reshape.html

Parameters

Name	Type
shape	number[]

Returns

Tensor

---

size

▸ size(): number[]

Returns the size of the tensor.

https://pytorch.org/docs/1.12/generated/torch.Tensor.size.html

Returns

number[]

---

softmax

▸ softmax(dim): Tensor

Applies a softmax function. It is applied to all slices along dim, and will re-scale them so that the elements lie in the range [0, 1] and sum to 1.

https://pytorch.org/docs/1.12/generated/torch.nn.functional.softmax.html

Parameters

Name	Type	Description
dim	number	A dimension along which softmax will be computed.

Returns

Tensor

---

sqrt

▸ sqrt(): Tensor

Computes the square-root value of each element in input.

https://pytorch.org/docs/1.12/generated/torch.Tensor.sqrt.html

Returns

Tensor

---

squeeze

▸ squeeze(dim?): Tensor

Returns a tensor with all the dimensions of input of size 1 removed.

https://pytorch.org/docs/1.12/generated/torch.Tensor.squeeze.html

Parameters

Name	Type	Description
dim?	number	If given, the input will be squeezed only in this dimension.

Returns

Tensor

---

stride

▸ stride(): number[]

Returns the stride of the tensor.

https://pytorch.org/docs/1.12/generated/torch.Tensor.stride.html

Returns

number[]

▸ stride(dim): number

Returns the stride of the tensor.

https://pytorch.org/docs/1.12/generated/torch.Tensor.stride.html

Parameters

Name	Type	Description
dim	number	The desired dimension in which stride is required.

Returns

number

---

sub

▸ sub(other, options?): Tensor

Subtracts other from input.

https://pytorch.org/docs/1.12/generated/torch.Tensor.sub.html

Parameters

Name	Type
other	Tensor
options?	Object
options.alpha?	Number

Returns

Tensor

▸ sub(other, options?): Tensor

Parameters

Name	Type
other	number
options?	Object
options.alpha?	Number

Returns

Tensor

---

sum

▸ sum(): Tensor

Returns the sum of all elements in the input tensor.

https://pytorch.org/docs/1.12/generated/torch.Tensor.sum.html

Returns

Tensor

▸ sum(dim, options?): Tensor

Returns the sum of each row of the input tensor in the given dimension dim. If dim is a list of dimensions, reduce over all of them.

https://pytorch.org/docs/1.12/generated/torch.Tensor.sum.html

Parameters

Name	Type	Description
dim	number | number[]	The dimension or dimensions to reduce.
options?	Object	-
options.keepdim?	boolean	Whether the output tensor has dim retained or not.

Returns

Tensor

---

to

▸ to(options): Tensor

Performs Tensor conversion.

https://pytorch.org/docs/1.12/generated/torch.Tensor.to.html

Parameters

Name	Type	Description
options	TensorOptions	Tensor options.

Returns

Tensor

---

topk

▸ topk(k, options?): [Tensor, Tensor]

Returns a list of two Tensors where the first represents the k largest elements of the given input tensor, and the second represents the indices of the k largest elements.

https://pytorch.org/docs/1.12/generated/torch.Tensor.topk.html

Parameters

Name	Type
k	number
options?	Object
options.dim?	number
options.largest?	boolean
options.sorted?	boolean

Returns

[Tensor, Tensor]

---

unsqueeze

▸ unsqueeze(dim): Tensor

Returns a new tensor with a dimension of size one inserted at the specified position.

https://pytorch.org/docs/1.12/generated/torch.Tensor.unsqueeze.html

Parameters

Name	Type
dim	number

Returns

Tensor