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	Description
k	number	The k in "top-k"
options?	Object	topk Options as keywords argument in pytorch
options.dim?	number	The dimension to sort along. If dim is not given, the last dimension of the input is chosen.
options.largest?	boolean	Controls whether to return largest or smallest elements. It is set to True by default.
options.sorted?	boolean	Controls whether to return the elements in sorted order. It is set to True by default.

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