utils/tensor

Helper module for Tensor processing.

These functions and classes are only used internally, meaning an end-user shouldn’t need to access anything here.


utils/tensor.Tensor

Kind: static class of utils/tensor


new Tensor(...args)

Create a new Tensor or copy an existing Tensor.

ParamType
...args*

tensor.Symbol.iterator()Iterator

Returns an iterator object for iterating over the tensor data in row-major order. If the tensor has more than one dimension, the iterator will yield subarrays.

Kind: instance method of Tensor
Returns: Iterator - An iterator object for iterating over the tensor data in row-major order.


tensor._getitem(index)Tensor

Index into a Tensor object.

Kind: instance method of Tensor
Returns: Tensor - The data at the specified index.

ParamTypeDescription
indexnumber

The index to access.


tensor.indexOf(item)number

Kind: instance method of Tensor
Returns: number - The index of the first occurrence of item in the tensor data.

ParamTypeDescription
itemnumber | bigint

The item to search for in the tensor


tensor._subarray(index, iterSize, iterDims)Tensor

Kind: instance method of Tensor

ParamType
indexnumber
iterSizenumber
iterDimsany

tensor.item()number

Returns the value of this tensor as a standard JavaScript Number. This only works for tensors with one element. For other cases, see Tensor.tolist().

Kind: instance method of Tensor
Returns: number - The value of this tensor as a standard JavaScript Number.
Throws:


tensor.tolist()Array

Convert tensor data to a n-dimensional JS list

Kind: instance method of Tensor


tensor.sigmoid()Tensor

Return a new Tensor with the sigmoid function applied to each element.

Kind: instance method of Tensor
Returns: Tensor - The tensor with the sigmoid function applied.


tensor.sigmoid_()Tensor

Applies the sigmoid function to the tensor in place.

Kind: instance method of Tensor
Returns: Tensor - Returns this.


tensor.transpose(...dims)Tensor

Return a transposed version of this Tensor, according to the provided dimensions.

Kind: instance method of Tensor
Returns: Tensor - The transposed tensor.

ParamTypeDescription
...dimsnumber

Dimensions to transpose.


tensor.sum([dim], keepdim)

Returns the sum of each row of the input tensor in the given dimension dim.

Kind: instance method of Tensor
Returns: The summed tensor

ParamTypeDefaultDescription
[dim]number

The dimension or dimensions to reduce. If null, all dimensions are reduced.

keepdimbooleanfalse

Whether the output tensor has dim retained or not.


tensor.norm([p], [dim], [keepdim])Tensor

Returns the matrix norm or vector norm of a given tensor.

Kind: instance method of Tensor
Returns: Tensor - The norm of the tensor.

ParamTypeDefaultDescription
[p]number | string'fro'

The order of norm

[dim]number

Specifies which dimension of the tensor to calculate the norm across. If dim is None, the norm will be calculated across all dimensions of input.

[keepdim]booleanfalse

Whether the output tensors have dim retained or not.


tensor.normalize_([p], [dim])Tensor

Performs L_p normalization of inputs over specified dimension. Operates in place.

Kind: instance method of Tensor
Returns: Tensor - this for operation chaining.

ParamTypeDefaultDescription
[p]number2

The exponent value in the norm formulation

[dim]number1

The dimension to reduce


tensor.normalize([p], [dim])Tensor

Performs L_p normalization of inputs over specified dimension.

Kind: instance method of Tensor
Returns: Tensor - The normalized tensor.

ParamTypeDefaultDescription
[p]number2

The exponent value in the norm formulation

[dim]number1

The dimension to reduce


tensor.stride()Array.<number>

Compute and return the stride of this tensor. Stride is the jump necessary to go from one element to the next one in the specified dimension dim.

Kind: instance method of Tensor
Returns: Array.<number> - The stride of this tensor.


tensor.squeeze([dim])

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

NOTE: The returned tensor shares the storage with the input tensor, so changing the contents of one will change the contents of the other. If you would like a copy, use tensor.clone() before squeezing.

Kind: instance method of Tensor
Returns: The squeezed tensor

ParamTypeDefaultDescription
[dim]number

If given, the input will be squeezed only in the specified dimensions.


tensor.squeeze_()

In-place version of @see Tensor.squeeze

Kind: instance method of Tensor


tensor.unsqueeze(dim)

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

NOTE: The returned tensor shares the same underlying data with this tensor.

Kind: instance method of Tensor
Returns: The unsqueezed tensor

ParamTypeDefaultDescription
dimnumber

The index at which to insert the singleton dimension


tensor.unsqueeze_()

In-place version of @see Tensor.unsqueeze

Kind: instance method of Tensor


tensor.flatten_()

In-place version of @see Tensor.flatten

Kind: instance method of Tensor


tensor.flatten(start_dim, end_dim)

Flattens input by reshaping it into a one-dimensional tensor. If start_dim or end_dim are passed, only dimensions starting with start_dim and ending with end_dim are flattened. The order of elements in input is unchanged.

Kind: instance method of Tensor
Returns: The flattened tensor.

ParamTypeDefaultDescription
start_dimnumber0

the first dim to flatten

end_dimnumber

the last dim to flatten


tensor.view(...dims)Tensor

Returns a new tensor with the same data as the self tensor but of a different shape.

Kind: instance method of Tensor
Returns: Tensor - The tensor with the same data but different shape

ParamTypeDescription
...dimsnumber

the desired size


utils/tensor.transpose(tensor, axes)Tensor

Transposes a tensor according to the provided axes.

Kind: static method of utils/tensor
Returns: Tensor - The transposed tensor.

ParamTypeDescription
tensorany

The input tensor to transpose.

axesArray

The axes to transpose the tensor along.


utils/tensor.interpolate(input, size, mode, align_corners)Tensor

Interpolates an Tensor to the given size.

Kind: static method of utils/tensor
Returns: Tensor - The interpolated tensor.

ParamTypeDescription
inputTensor

The input tensor to interpolate. Data must be channel-first (i.e., [c, h, w])

sizeArray.<number>

The output size of the image

modestring

The interpolation mode

align_cornersboolean

Whether to align corners.


utils/tensor.mean_pooling(last_hidden_state, attention_mask)Tensor

Perform mean pooling of the last hidden state followed by a normalization step.

Kind: static method of utils/tensor
Returns: Tensor - Returns a new Tensor of shape [batchSize, embedDim].

ParamTypeDescription
last_hidden_stateTensor

Tensor of shape [batchSize, seqLength, embedDim]

attention_maskTensor

Tensor of shape [batchSize, seqLength]


utils/tensor.cat(tensors, dim)Tensor

Concatenates an array of tensors along a specified dimension.

Kind: static method of utils/tensor
Returns: Tensor - The concatenated tensor.

ParamTypeDescription
tensorsArray.<Tensor>

The array of tensors to concatenate.

dimnumber

The dimension to concatenate along.


utils/tensor.stack(tensors, dim)Tensor

Stack an array of tensors along a specified dimension.

Kind: static method of utils/tensor
Returns: Tensor - The stacked tensor.

ParamTypeDescription
tensorsArray.<Tensor>

The array of tensors to stack.

dimnumber

The dimension to stack along.


utils/tensor.std_mean(input, dim, correction, keepdim)Array.<Tensor>

Calculates the standard deviation and mean over the dimensions specified by dim. dim can be a single dimension or null to reduce over all dimensions.

Kind: static method of utils/tensor
Returns: Array.<Tensor> - A tuple of (std, mean) tensors.

ParamTypeDescription
inputTensor

the input tenso

dimnumber | null

the dimension to reduce. If None, all dimensions are reduced.

correctionnumber

difference between the sample size and sample degrees of freedom. Defaults to Bessel's correction, correction=1.

keepdimboolean

whether the output tensor has dim retained or not.


utils/tensor.mean(input, dim, keepdim)

Returns the mean value of each row of the input tensor in the given dimension dim.

Kind: static method of utils/tensor
Returns: A new tensor with means taken along the specified dimension.

ParamTypeDescription
inputTensor

the input tensor.

dimnumber | null

the dimension to reduce.

keepdimboolean

whether the output tensor has dim retained or not.


utils/tensor.dynamicTimeWarping(matrix)Array.<Array<number>>

Measures similarity between two temporal sequences (e.g., input audio and output tokens to generate token-level timestamps).

Kind: static method of utils/tensor

ParamType
matrixTensor

utils/tensor~ONNXTensor : Object

Kind: inner constant of utils/tensor


utils/tensor~reshape(data, dimensions)*

Reshapes a 1-dimensional array into an n-dimensional array, according to the provided dimensions.

Kind: inner method of utils/tensor
Returns: * - The reshaped array.

ParamTypeDescription
dataArray.<T>

The input array to reshape.

dimensionsDIM

The target shape/dimensions.

Example

reshape([10                    ], [1      ]); // Type: number[]      Value: [10]
  reshape([1, 2, 3, 4            ], [2, 2   ]); // Type: number[][]    Value: [[1, 2], [3, 4]]
  reshape([1, 2, 3, 4, 5, 6, 7, 8], [2, 2, 2]); // Type: number[][][]  Value: [[[1, 2], [3, 4]], [[5, 6], [7, 8]]]
  reshape([1, 2, 3, 4, 5, 6, 7, 8], [4, 2   ]); // Type: number[][]    Value: [[1, 2], [3, 4], [5, 6], [7, 8]]

reshape~reshapedArray : any

Kind: inner property of reshape


utils/tensor~AnyTypedArray : *

Kind: inner typedef of utils/tensor


utils/tensor~NestArray : *

This creates a nested array of a given type and depth (see examples).

Kind: inner typedef of utils/tensor
Example

NestArray<string, 1>; // string[]

Example

NestArray<number, 2>; // number[][]

Example

NestArray<string, 3>; // string[][][] etc.