+
+ |
+
+ |
+
+
+
+ 
+ 
+
+
+ 
+ 
+
+
+ 
+ 
+
+
+ Computes the element-wise absolute value of the given input tensor.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new tensor with the arccosine of the elements of input.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Return the element-wise addition of the two tensors.
+
+
+ -
+
+ a
+
+ :
+
Tensor
+
+ -
+
+ The first tensor.
+
+
+ -
+
+ b
+
+ :
+
Tensor
+
+ -
+
+ The second tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a 1-D tensor of size \(\left\lceil \frac{\text{end} - \text{start}}{\text{step}} \right\rceil\)
+ with values from the interval [start, end) taken with common difference step beginning from start.
+
+
+
+ -
+
+ endVal
+
+ :
+
int
+
+ -
+
+ The ending value for the set of points.
+
+
+ -
+
+ ?startVal
+
+ :
+
int
+
+ -
+
+ The starting value for the set of points. Default: 0.
+
+
+ -
+
+ ?step
+
+ :
+
int
+
+ -
+
+ The gap between each pair of adjacent points. Default: 1.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, uses Device.Default.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, uses Dtype.Default.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, uses Backend.Default.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a 1-D tensor of size \(\left\lceil \frac{\text{end} - \text{start}}{\text{step}} \right\rceil\)
+ with values from the interval [start, end) taken with common difference step beginning from start.
+
+
+
+ -
+
+ endVal
+
+ :
+
float
+
+ -
+
+ The ending value for the set of points.
+
+
+ -
+
+ ?startVal
+
+ :
+
float
+
+ -
+
+ The starting value for the set of points. Default: 0.
+
+
+ -
+
+ ?step
+
+ :
+
float
+
+ -
+
+ The gap between each pair of adjacent points. Default: 1.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, uses Device.Default.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, uses Dtype.Default.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, uses Backend.Default.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ A version of FurnaceImage.arange with characteristics based on the input tensor.
+
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The shape and characteristics of input will determine those of the output tensor.
+
+
+ -
+
+ endVal
+
+ :
+
int
+
+ -
+
+ The ending value for the set of points.
+
+
+ -
+
+ ?startVal
+
+ :
+
int
+
+ -
+
+ The starting value for the set of points. Default: 0.
+
+
+ -
+
+ ?step
+
+ :
+
int
+
+ -
+
+ The gap between each pair of adjacent points. Default: 1.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, the device of the input tensor is used.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, the element type of the input tensor is used.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, the backend of the input tensor is used.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ A version of FurnaceImage.arange with characteristics based on the input tensor.
+
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The shape and characteristics of input will determine those of the output tensor.
+
+
+ -
+
+ endVal
+
+ :
+
float
+
+ -
+
+ The ending value for the set of points.
+
+
+ -
+
+ ?startVal
+
+ :
+
float
+
+ -
+
+ The starting value for the set of points. Default: 0.
+
+
+ -
+
+ ?step
+
+ :
+
float
+
+ -
+
+ The gap between each pair of adjacent points. Default: 1.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, the device of the input tensor is used.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, the element type of the input tensor is used.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, the backend of the input tensor is used.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns the indices of the maximum value of all elements in the input tensor.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ dim
+
+ :
+
int
+
+ -
+
+ The dimension.
+
+
+ -
+
+ ?keepDim
+
+ :
+
bool
+
+ -
+
+ Whether the output tensor has dim retained or not.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns the indices of the maximum value of all elements in the input tensor.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
int[]
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns the indices of the minimum value of all elements in the input tensor.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ dim
+
+ :
+
int
+
+ -
+
+ The dimension.
+
+
+ -
+
+ ?keepDim
+
+ :
+
bool
+
+ -
+
+ Whether the output tensor has dim retained or not.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns the indices of the minimum value of all elements in the input tensor.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
int[]
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new tensor with the arcsine of the elements of input.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new tensor with the arctangent of the elements of input.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns the list of available backends.
+
+
+ -
+
+ Returns:
+
+
Backend list
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns the list of available backends and devices available for each backend.
+
+
+ -
+
+ Returns:
+
+
(Backend * Device list) list
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Creates a criterion that measures the Binary Cross Entropy between the target and the output
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ target
+
+ :
+
Tensor
+
+ -
+
+ The target tensor.
+
+
+ -
+
+ ?weight
+
+ :
+
Tensor
+
+ -
+
+ A manual rescaling weight given to the loss of each batch element.
+
+
+ -
+
+ ?reduction
+
+ :
+
string
+
+ -
+
+ Optionally specifies the reduction to apply to the output: 'none' | 'mean' | 'sum'. 'none': no reduction will be applied, 'mean': the sum of the output will be divided by the number of elements in the output, 'sum': the output will be summed. Note: size_average and reduce are in the process of being deprecated, and in the meantime, specifying either of those two args will override reduction. Default: 'mean'.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Draws binary random numbers (0 or 1) from a Bernoulli distribution
+
+
+ -
+
+ probs
+
+ :
+
Tensor
+
+ -
+
+ The input tensor of probability values for the Bernoulli distribution.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, uses Device.Default.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, uses Dtype.Default.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, uses Backend.Default.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Convert the tensor to one with the given element type.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Concatenates the given sequence of seq tensors in the given dimension. All tensors must either have the same shape (except in the concatenating dimension) or be empty.
+
+
+ -
+
+ tensors
+
+ :
+
seq<Tensor>
+
+ -
+
+ The sequence of tensors to concatenate.
+
+
+ -
+
+ ?dim
+
+ :
+
int
+
+ -
+
+ The the dimension over which the tensors are concatenated.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new tensor with the ceil of the elements of input, the smallest integer greater than or equal to each element.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Clamp all elements in input into the range [ low..high] and return a resulting tensor
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ ?low
+
+ :
+
scalar
+
+ -
+
+ The lower-bound of the range to be clamped to.
+
+
+ -
+
+ ?high
+
+ :
+
scalar
+
+ -
+
+ The upper-bound of the range to be clamped to.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new tensor with the same characteristics and storage cloned.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Configure the default device, element type, backend, printer. Only floating point dtypes are supported as the default.
+
+
+ -
+
+ configuration
+
+ :
+
Device * Dtype * Backend * Printer
+
+ -
+
+ A tuple of the new default device, default element type, default backend, and default printer.
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Return the current default device, element type, backend, and printer.
+
+
+ -
+
+ Returns:
+
+
Device * Dtype * Backend * Printer
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Configure the default device, dtype, and/or backend.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The new default device.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The new default element type. Only floating point dtypes are supported as the default.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The new default backend.
+
+
+ -
+
+ ?printer
+
+ :
+
Printer
+
+ -
+
+ The new default printer.
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Applies a 1D convolution over an input signal composed of several input planes
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ filters
+
+ :
+
Tensor
+
+ -
+
+ The filters.
+
+
+ -
+
+ ?stride
+
+ :
+
int
+
+ -
+
+ The stride of the convolving kernel.
+
+
+ -
+
+ ?padding
+
+ :
+
int
+
+ -
+
+ The implicit paddings on both sides of the input.
+
+
+ -
+
+ ?dilation
+
+ :
+
int
+
+ -
+
+ The spacing between kernel elements.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Applies a 2D convolution over an input signal composed of several input planes
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ filters
+
+ :
+
Tensor
+
+ -
+
+ The filters.
+
+
+ -
+
+ ?stride
+
+ :
+
int
+
+ -
+
+ The stride of the convolving kernel.
+
+
+ -
+
+ ?strides
+
+ :
+
seq<int>
+
+ -
+
+ The strides of the convolving kernel.
+
+
+ -
+
+ ?padding
+
+ :
+
int
+
+ -
+
+ The implicit padding on corresponding sides of the input.
+
+
+ -
+
+ ?paddings
+
+ :
+
seq<int>
+
+ -
+
+ The implicit paddings on corresponding sides of the input.
+
+
+ -
+
+ ?dilation
+
+ :
+
int
+
+ -
+
+ The spacing between kernel elements.
+
+
+ -
+
+ ?dilations
+
+ :
+
seq<int>
+
+ -
+
+ The spacings between kernel elements.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Applies a 3D convolution over an input signal composed of several input planes
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ filters
+
+ :
+
Tensor
+
+ -
+
+ The filters.
+
+
+ -
+
+ ?stride
+
+ :
+
int
+
+ -
+
+ The stride of the convolving kernel.
+
+
+ -
+
+ ?strides
+
+ :
+
seq<int>
+
+ -
+
+ The strides of the convolving kernel.
+
+
+ -
+
+ ?padding
+
+ :
+
int
+
+ -
+
+ The implicit padding on corresponding sides of the input.
+
+
+ -
+
+ ?paddings
+
+ :
+
seq<int>
+
+ -
+
+ The implicit paddings on corresponding sides of the input.
+
+
+ -
+
+ ?dilation
+
+ :
+
int
+
+ -
+
+ The spacing between kernel elements.
+
+
+ -
+
+ ?dilations
+
+ :
+
seq<int>
+
+ -
+
+ The spacings between kernel elements.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Applies a 1D transposed convolution operator over an input signal composed of several input planes, sometimes also called 'deconvolution'.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ filters
+
+ :
+
Tensor
+
+ -
+
+ The filters.
+
+
+ -
+
+ ?stride
+
+ :
+
int
+
+ -
+
+ The stride of the convolving kernel.
+
+
+ -
+
+ ?padding
+
+ :
+
int
+
+ -
+
+ The implicit padding on both sides of the input.
+
+
+ -
+
+ ?dilation
+
+ :
+
int
+
+ -
+
+ The spacing between kernel elements.
+
+
+ -
+
+ ?outputPadding
+
+ :
+
int
+
+ -
+
+ The additional size added to one side of each dimension in the output shape.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Applies a 2D transposed convolution operator over an input signal composed of several input planes, sometimes also called 'deconvolution'.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ filters
+
+ :
+
Tensor
+
+ -
+
+ The filters.
+
+
+ -
+
+ ?stride
+
+ :
+
int
+
+ -
+
+ The stride of the convolving kernel.
+
+
+ -
+
+ ?padding
+
+ :
+
int
+
+ -
+
+ The implicit padding on both sides of the input.
+
+
+ -
+
+ ?dilation
+
+ :
+
int
+
+ -
+
+ The spacing between kernel elements.
+
+
+ -
+
+ ?outputPadding
+
+ :
+
int
+
+ -
+
+ The additional size added to one side of each dimension in the output shape.
+
+
+ -
+
+ ?strides
+
+ :
+
seq<int>
+
+ -
+
+ The strides of the convolving kernel.
+
+
+ -
+
+ ?paddings
+
+ :
+
seq<int>
+
+ -
+
+ The implicit paddings on corresponding sides of the input.
+
+
+ -
+
+ ?dilations
+
+ :
+
seq<int>
+
+ -
+
+ The spacings between kernel elements.
+
+
+ -
+
+ ?outputPaddings
+
+ :
+
seq<int>
+
+ -
+
+ The additional sizes added to one side of each dimension in the output shape.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Applies a 3D transposed convolution operator over an input signal composed of several input planes, sometimes also called 'deconvolution'.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ filters
+
+ :
+
Tensor
+
+ -
+
+ The filters.
+
+
+ -
+
+ ?stride
+
+ :
+
int
+
+ -
+
+ The stride of the convolving kernel.
+
+
+ -
+
+ ?padding
+
+ :
+
int
+
+ -
+
+ The implicit padding on both sides of the input.
+
+
+ -
+
+ ?dilation
+
+ :
+
int
+
+ -
+
+ The spacing between kernel elements.
+
+
+ -
+
+ ?outputPadding
+
+ :
+
int
+
+ -
+
+ The additional size added to one side of each dimension in the output shape.
+
+
+ -
+
+ ?strides
+
+ :
+
seq<int>
+
+ -
+
+ The strides of the convolving kernel.
+
+
+ -
+
+ ?paddings
+
+ :
+
seq<int>
+
+ -
+
+ The implicit paddings on corresponding sides of the input.
+
+
+ -
+
+ ?dilations
+
+ :
+
seq<int>
+
+ -
+
+ The spacings between kernel elements.
+
+
+ -
+
+ ?outputPaddings
+
+ :
+
seq<int>
+
+ -
+
+ The additional sizes added to one side of each dimension in the output shape.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Estimates the Pearson correlation coefficient matrix for the given tensor. The tensor's first
+ dimension should index variables and the second dimension should
+ index observations for each variable.
+
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+ -
+
+
+ The correlation coefficient matrix \(R\) is computed from the covariance
+ matrix
+ Returns a square tensor representing the correlation coefficient matrix.
+ Given a tensor with \(N\) variables \(X=[x_1,x_2,\ldots,x_N]\) the
+ \(R_{i,j}\) entry on the correlation matrix is the correlation between
+ \(x_i\) and \(x_j\).
+
+
+
+
+
+
+
+ let x = FurnaceImage.tensor([-0.2678; -0.0908; -0.3766; 0.2780])
+ let y = FurnaceImage.tensor([-0.5812; 0.1535; 0.2387; 0.2350])
+ let xy = FurnaceImage.stack([x;y])
+ FurnaceImage.corrcoef(xy)
+ Evaluates to
+
+ tensor([[1.0000, 0.3582],
+ [0.3582, 1.0000]])
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new tensor with the cosine of the elements of input
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new tensor with the hyperbolic cosine of the elements of input.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Estimates the covariance matrix of the given tensor. The tensor's first
+ dimension should index variables and the second dimension should
+ index observations for each variable.
+
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ ?correction
+
+ :
+
int64
+
+ -
+
+ Difference between the sample size and the sample degrees of freedom. Defaults to 1 (Bessel's correction).
+
+
+ -
+
+ ?fweights
+
+ :
+
Tensor
+
+ -
+
+ Frequency weights represent the number of times each observation was observed.
+ Should be given as a tensor of integers. Defaults to no weights.
+
+
+ -
+
+ ?aweights
+
+ :
+
Tensor
+
+ -
+
+ Relative importance weights, larger weights for observations that
+ should have a larger effect on the estimate.
+ Should be given as a tensor of floating point numbers. Defaults to no weights.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+ -
+
+ Returns a square tensor representing the covariance matrix.
+ Given a tensor with \(N\) variables \(X=[x_1,x_2,\ldots,x_N]\) the
+ \(C_{i,j}\) entry on the covariance matrix is the covariance between
+ \(x_i\) and \(x_j\).
+
+
+
+
+
+
+
+ let x = FurnaceImage.tensor([0.0;3.4;5.0])
+ let y = FurnaceImage.tensor([1.0;2.3;-3.0])
+ let xy = FurnaceImage.stack([x;y])
+ xy.cov()
+ Evaluates to
+
+ tensor([[ 6.5200, -4.0100],
+ [-4.0100, 7.6300]])
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Create a new 1D tensor using the given value for each element.
+
+
+ -
+
+ count
+
+ :
+
int
+
+ -
+
+ The number of elements in the tensor.
+
+
+ -
+
+ value
+
+ :
+
'a
+
+ -
+
+ The initial value for each element of the tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ This criterion combines logsoftmax and nllLoss in a single function
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ target
+
+ :
+
Tensor
+
+ -
+
+ The target tensor.
+
+
+ -
+
+ ?weight
+
+ :
+
Tensor
+
+ -
+
+ A optional manual rescaling weight given to the loss of each batch element.
+
+
+ -
+
+ ?reduction
+
+ :
+
string
+
+ -
+
+ Optionally specifies the reduction to apply to the output: 'none' | 'mean' | 'sum'. 'none': no reduction will be applied, 'mean': the sum of the output will be divided by the number of elements in the output, 'sum': the output will be summed. Note: size_average and reduce are in the process of being deprecated, and in the meantime, specifying either of those two args will override reduction. Default: 'mean'.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ TBD
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ TBD
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor * Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Get the derivative value of the tensor.
+
+
+ -
+
+ tensor
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns the list of available devices for a given backend.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ Return information for this backend. Defaults to Backend.Default.
+
+
+ -
+
+ ?deviceType
+
+ :
+
DeviceType
+
+ -
+
+ If given, only return devices for this device type.
+
+
+
+
+ -
+
+ Returns:
+
+
Device list
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a tensor with the diagonal elements with respect to dim1 and dim2.
+ The argument offset controls which diagonal to consider.
+
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor. Must be at least 2-dimensional.
+
+
+ -
+
+ ?offset
+
+ :
+
int
+
+ -
+
+ Which diagonal to consider. Default: 0.
+
+
+ -
+
+ ?dim1
+
+ :
+
int
+
+ -
+
+ The first dimension with respect to which to take diagonal. Default: 0..
+
+
+ -
+
+ ?dim2
+
+ :
+
int
+
+ -
+
+ The second dimension with respect to which to take diagonal. Default: 1.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ TBD
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ TBD
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ TBD
+
+
+ -
+
+ n
+
+ :
+
int
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Dilate the tensor in using the given dilations in each corresponding dimension.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ dilations
+
+ :
+
seq<int>
+
+ -
+
+ The dilations to use.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Return the element-wise division of the two tensors.
+
+
+ -
+
+ a
+
+ :
+
Tensor
+
+ -
+
+ The first tensor.
+
+
+ -
+
+ b
+
+ :
+
Tensor
+
+ -
+
+ The second tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ TBD
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Computes the dot product (inner product) of two tensors.
+
+
+ -
+
+ a
+
+ :
+
Tensor
+
+ -
+
+ The first tensor.
+
+
+ -
+
+ b
+
+ :
+
Tensor
+
+ -
+
+ The second tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Randomly zeroes some of the elements of the input tensor with probability p using samples from a Bernoulli distribution
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ ?p
+
+ :
+
double
+
+ -
+
+ The probability of an element to be zeroed. Default: 0.5.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Randomly zero out entire channels (a channel is a 2D feature map, e.g., the jj -th channel of the ii -th sample in the batched input is a 2D tensor \text{input}[i, j]input[i,j] ). Each channel will be zeroed out independently on every forward call with probability p using samples from a Bernoulli distribution
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ ?p
+
+ :
+
double
+
+ -
+
+ The probability of an element to be zeroed. Default: 0.5.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Randomly zero out entire channels (a channel is a 3D feature map, e.g., the jj -th channel of the ii -th sample in the batched input is a 3D tensor \text{input}[i, j]input[i,j] ). Each channel will be zeroed out independently on every forward call with probability p using samples from a Bernoulli distribution.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ ?p
+
+ :
+
double
+
+ -
+
+ The probability of an element to be zeroed. Default: 0.5.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new empty tensor holding no data, for the given element type and configuration
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, uses Device.Default.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, uses Dtype.Default.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, uses Backend.Default.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new uninitialized tensor filled with arbitrary values for the given length, element type and configuration
+
+
+ -
+
+ length
+
+ :
+
int
+
+ -
+
+ The length of the returned tensor.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, uses Device.Default.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, uses Dtype.Default.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, uses Backend.Default.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new uninitialized tensor filled with arbitrary values for the given shape, element type and configuration
+
+
+ -
+
+ shape
+
+ :
+
seq<int>
+
+ -
+
+ The desired shape of returned tensor.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, uses Device.Default.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, uses Dtype.Default.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, uses Backend.Default.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a boolean tensor for the element-wise equality comparison of the elements in the two tensors.
+
+
+ -
+
+ a
+
+ :
+
Tensor
+
+ -
+
+ The first tensor.
+
+
+ -
+
+ b
+
+ :
+
Tensor
+
+ -
+
+ The second tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ TBD
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+
+ -
+
+ v
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor * Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ TBD
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+
+ -
+
+ v
+
+ :
+
Tensor[]
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor[]
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ TBD
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor * (Tensor -> Tensor)
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Applies the exp function element-wise.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new view of the input tensor with singleton dimensions expanded to a larger size
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ shape
+
+ :
+
seq<int>
+
+ -
+
+ The desired shape of returned tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Expand the input tensor to the same size as other tensor
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ other
+
+ :
+
Tensor
+
+ -
+
+ The result tensor has the same size as other.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a 2-D tensor with ones on the diagonal and zeros elsewhere.
+
+
+ -
+
+ rows
+
+ :
+
int
+
+ -
+
+ The number of rows
+
+
+ -
+
+ ?cols
+
+ :
+
int
+
+ -
+
+ The number of columns with default being n
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, uses Device.Default.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, uses Dtype.Default.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, uses Backend.Default.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ TBD
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor * Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ TBD
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor * Tensor * Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ TBD
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor * Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ TBD
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor * Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ TBD
+
+
+ -
+
+ n
+
+ :
+
int
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor * Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ TBD
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor * Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ TBD
+
+
+ -
+
+ n
+
+ :
+
int
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor[]
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ TBD
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor * Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ TBD
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor * Tensor * Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ TBD
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+
+ -
+
+ v
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor * Tensor * Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ TBD
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+ -
+
+ TBD
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+ -
+
+ TBD
+
+
+ -
+
+ v
+
+ :
+
Tensor
+
+ -
+
+ TBD
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor * Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ TBD
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor * Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ TBD
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+
+ -
+
+ v
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor * Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ TBD
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor * Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Original value and transposed Jacobian-vector product of a vector-to-vector function `f`, at point `x`, along vector `v`
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+ -
+
+ vector-to-vector function
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+ -
+
+ Point at which the function f will be evaluated, it must have a single dimension.
+
+
+ -
+
+ v
+
+ :
+
Tensor
+
+ -
+
+ Vector
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor * Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ TBD
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+ -
+
+ TBD
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+ -
+
+ TBD
+
+
+ -
+
+ v
+
+ :
+
Tensor
+
+ -
+
+ TBD
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor * Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ TBD
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor * Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Flattens a contiguous range of dims in a tensor.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ ?startDim
+
+ :
+
int
+
+ -
+
+ The first dim to flatten.
+
+
+ -
+
+ ?endDim
+
+ :
+
int
+
+ -
+
+ The last dim to flatten.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Reverse the order of a n-D tensor along given axis in dims
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ dims
+
+ :
+
seq<int>
+
+ -
+
+ The axis to flip on.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new tensor with the floor of the elements of input, the largest integer less than or equal to each element.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Produce a new tensor suitable for calculating the forward-mode derivative at the given level tag.
+
+
+ -
+
+ nestingTag
+
+ :
+
uint32
+
+ -
+
+ The level tag.
+
+
+ -
+
+ derivative
+
+ :
+
Tensor
+
+ -
+
+ The derivative of the input.
+
+
+ -
+
+ tensor
+
+ :
+
Tensor
+
+ -
+
+ The input.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new tensor of the given length filled with value, for the given element type and configuration
+
+
+ -
+
+ length
+
+ :
+
int
+
+ -
+
+ The length of the returned tensor.
+
+
+ -
+
+ value
+
+ :
+
scalar
+
+ -
+
+ The scalar giving the the initial values for the tensor.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, uses Device.Default.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, uses Dtype.Default.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, uses Backend.Default.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new tensor filled with the scalar value, for the given shape, element type and configuration
+
+
+ -
+
+ shape
+
+ :
+
seq<int>
+
+ -
+
+ The desired shape of returned tensor.
+
+
+ -
+
+ value
+
+ :
+
scalar
+
+ -
+
+ The scalar used to form the initial values for the tensor.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, uses Device.Default.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, uses Dtype.Default.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, uses Backend.Default.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new tensor filled with the given scalar value with characteristics based on the input tensor.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The shape and characteristics of input will determine those of the output tensor.
+
+
+ -
+
+ value
+
+ :
+
scalar
+
+ -
+
+ The scalar giving the the initial values for the tensor.
+
+
+ -
+
+ ?shape
+
+ :
+
seq<int>
+
+ -
+
+ The desired shape of returned tensor. Default: If None, the shape of the input tensor is used.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, the device of the input tensor is used.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, the element type of the input tensor is used.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, the backend of the input tensor is used.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Gathers values along an axis specified by dim.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ dim
+
+ :
+
int
+
+ -
+
+ The axis along which to index.
+
+
+ -
+
+ indices
+
+ :
+
Tensor
+
+ -
+
+ The the indices of elements to gather.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a boolean tensor for the element-wise greater-than-or-equal comparison of the elements in the two tensors.
+
+
+ -
+
+ a
+
+ :
+
Tensor
+
+ -
+
+ The first tensor.
+
+
+ -
+
+ b
+
+ :
+
Tensor
+
+ -
+
+ The second tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ TBD
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ TBD
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor * Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ TBD
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+
+ -
+
+ v
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor * Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ TBD
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+
+ -
+
+ v
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a boolean tensor for the element-wise greater-than comparison of the elements in the two tensors.
+
+
+ -
+
+ a
+
+ :
+
Tensor
+
+ -
+
+ The first tensor.
+
+
+ -
+
+ b
+
+ :
+
Tensor
+
+ -
+
+ The second tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a boolean indicating if any element of the tensor is infinite.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
bool
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a boolean indicating if any element of the tensor is a not-a-number (NaN) value.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
bool
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ TBD
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ TBD
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+
+ -
+
+ v
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Create a new 1D tensor using the given initializer for each element.
+
+
+ -
+
+ count
+
+ :
+
int
+
+ -
+
+ The length of the tensor.
+
+
+ -
+
+ initializer
+
+ :
+
int -> 'a
+
+ -
+
+ The function used to initialize each element.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Create a new 2D tensor using the given initializer for each element.
+
+
+ -
+
+ length1
+
+ :
+
int
+
+ -
+
+ The length of the tensor in the first dimension.
+
+
+ -
+
+ length2
+
+ :
+
int
+
+ -
+
+ The length of the tensor in the second dimension.
+
+
+ -
+
+ initializer
+
+ :
+
int -> int -> 'a
+
+ -
+
+ The function used to initialize each element.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Create a new 3D tensor using the given initializer for each element.
+
+
+ -
+
+ length1
+
+ :
+
int
+
+ -
+
+ The length of the tensor in the 1st dimension.
+
+
+ -
+
+ length2
+
+ :
+
int
+
+ -
+
+ The length of the tensor in the 2nd dimension.
+
+
+ -
+
+ length3
+
+ :
+
int
+
+ -
+
+ The length of the tensor in the 3rd dimension.
+
+
+ -
+
+ initializer
+
+ :
+
int -> int -> int -> 'a
+
+ -
+
+ The function used to initialize each element.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Create a new 4D tensor using the given initializer for each element.
+
+
+ -
+
+ length1
+
+ :
+
int
+
+ -
+
+ The length of the tensor in the 1st dimension.
+
+
+ -
+
+ length2
+
+ :
+
int
+
+ -
+
+ The length of the tensor in the 2nd dimension.
+
+
+ -
+
+ length3
+
+ :
+
int
+
+ -
+
+ The length of the tensor in the 3rd dimension.
+
+
+ -
+
+ length4
+
+ :
+
int
+
+ -
+
+ The length of the tensor in the 4th dimension.
+
+
+ -
+
+ initializer
+
+ :
+
int -> int -> int -> int -> 'a
+
+ -
+
+ The function used to initialize each element.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Indicates if a given backend is available.
+
+
+ -
+
+ backend
+
+ :
+
Backend
+
+
+
+
+ -
+
+ Returns:
+
+
bool
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Indicates if CUDA is available for a given backend.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ Return information for this backend. Defaults to Backend.Default.
+
+
+
+
+ -
+
+ Returns:
+
+
bool
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Indicates if a given device is available for a given backend.
+
+
+ -
+
+ device
+
+ :
+
Device
+
+ -
+
+ The requested device.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ Return information for this backend. Defaults to Backend.Default.
+
+
+
+
+ -
+
+ Returns:
+
+
bool
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Indicates if a given device type is available for a given backend.
+
+
+ -
+
+ deviceType
+
+ :
+
DeviceType
+
+ -
+
+ The requested device type.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ Return information for this backend. Defaults to Backend.Default.
+
+
+
+
+ -
+
+ Returns:
+
+
bool
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Indicates if an object is a tensor
+
+
+ -
+
+ value
+
+ :
+
obj
+
+
+
+
+ -
+
+ Returns:
+
+
bool
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a boolean tensor where each element indicates if the corresponding element in the input tensor is an infinity value.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a boolean tensor where each element indicates if the corresponding element in the input tensor is a NaN (not-a-number) value.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ TBD
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Transposed Jacobian-vector product of a vector-to-vector function `f`, at point `x`, along vector `v`
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+ -
+
+ vector-to-vector function
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+ -
+
+ Point at which the function f will be evaluated, it must have a single dimension.
+
+
+ -
+
+ v
+
+ :
+
Tensor
+
+ -
+
+ Vector
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ TBD
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+
+ -
+
+ v
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ TBD
+
+
+ -
+
+ f
+
+ :
+
Tensor -> Tensor
+
+
+ -
+
+ x
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Return a boolean tensor for the element-wise less-than-or-equal comparison of the elements in the two tensors.
+
+
+ -
+
+ a
+
+ :
+
Tensor
+
+ -
+
+ The first tensor.
+
+
+ -
+
+ b
+
+ :
+
Tensor
+
+ -
+
+ The second tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Applies the leaky rectified linear unit function element-wise
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ ?negativeSlope
+
+ :
+
float
+
+ -
+
+ Controls the angle of the negative slope. Default: 0.01.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new tensor based on the given .NET value with characteristics based on the input tensor.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The shape and characteristics of input will determine those of the output tensor.
+
+
+ -
+
+ value
+
+ :
+
obj
+
+ -
+
+ The .NET object giving the the initial values for the tensor.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, the device of the input tensor is used.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, the element type of the input tensor is used.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, the backend of the input tensor is used.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a 1-D tensor of size steps whose values are evenly spaced from startVal to endVal. The values are going to be: \(
+ (\text{startVal},
+ \text{startVal} + \frac{\text{endVal} - \text{startVal}}{\text{steps} - 1},
+ \ldots,
+ \text{startVal} + (\text{steps} - 2) * \frac{\text{endVal} - \text{startVal}}{\text{steps} - 1},
+ \text{endVal})
+ \)
+
+
+
+ -
+
+ startVal
+
+ :
+
int
+
+ -
+
+ The starting value for the set of points.
+
+
+ -
+
+ endVal
+
+ :
+
int
+
+ -
+
+ The ending value for the set of points.
+
+
+ -
+
+ steps
+
+ :
+
int
+
+ -
+
+ The size of the returned tensor.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, uses Device.Default.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, uses Dtype.Default.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, uses Backend.Default.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a 1-D tensor of size steps whose values are evenly spaced from startVal to endVal. The values are going to be: \(
+ (\text{startVal},
+ \text{startVal} + \frac{\text{endVal} - \text{startVal}}{\text{steps} - 1},
+ \ldots,
+ \text{startVal} + (\text{steps} - 2) * \frac{\text{endVal} - \text{startVal}}{\text{steps} - 1},
+ \text{endVal})
+ \)
+
+
+
+ -
+
+ startVal
+
+ :
+
float
+
+ -
+
+ The starting value for the set of points.
+
+
+ -
+
+ endVal
+
+ :
+
float
+
+ -
+
+ The ending value for the set of points.
+
+
+ -
+
+ steps
+
+ :
+
int
+
+ -
+
+ The size of the returned tensor.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, uses Device.Default.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, uses Dtype.Default.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, uses Backend.Default.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Loads an object from the given file using a bespoke binary format.
+
+
+ -
+
+ fileName
+
+ :
+
string
+
+
+
+
+ -
+
+ Returns:
+
+
'b
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new tensor with the natural logarithm of the elements of input.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new tensor with the logarithm to the base 10 of the elements of input.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Applies a softmax followed by a logarithm.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ dim
+
+ :
+
int
+
+ -
+
+ A dimension along which softmax will be computed.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a 1-D tensor of size steps whose values are evenly spaced logarithmically from \(\text{baseVal}^{\text{startVal}}\) to \(\text{baseVal}^{\text{endVal}}\). The values are going to be: \(
+ (\text{baseVal}^{\text{startVal}},
+ \text{baseVal}^{(\text{startVal} + \frac{\text{endVal} - \text{startVal}}{ \text{steps} - 1})},
+ \ldots,
+ \text{baseVal}^{(\text{startVal} + (\text{steps} - 2) * \frac{\text{endVal} - \text{startVal}}{ \text{steps} - 1})},
+ \text{baseVal}^{\text{endVal}})
+ \)
+
+
+
+ -
+
+ startVal
+
+ :
+
int
+
+ -
+
+ The starting value for the set of points.
+
+
+ -
+
+ endVal
+
+ :
+
int
+
+ -
+
+ The ending value for the set of points.
+
+
+ -
+
+ steps
+
+ :
+
int
+
+ -
+
+ The size of the returned tensor.
+
+
+ -
+
+ ?baseVal
+
+ :
+
int
+
+ -
+
+ The base of the logarithm. Default: 10.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, uses Device.Default.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, uses Dtype.Default.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, uses Backend.Default.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a 1-D tensor of size steps whose values are evenly spaced logarithmically from \(\text{baseVal}^{\text{startVal}}\) to \(\text{baseVal}^{\text{endVal}}\). The values are going to be: \(
+ (\text{baseVal}^{\text{startVal}},
+ \text{baseVal}^{(\text{startVal} + \frac{\text{endVal} - \text{startVal}}{ \text{steps} - 1})},
+ \ldots,
+ \text{baseVal}^{(\text{startVal} + (\text{steps} - 2) * \frac{\text{endVal} - \text{startVal}}{ \text{steps} - 1})},
+ \text{baseVal}^{\text{endVal}})
+ \)
+
+
+
+ -
+
+ startVal
+
+ :
+
float
+
+ -
+
+ The starting value for the set of points.
+
+
+ -
+
+ endVal
+
+ :
+
float
+
+ -
+
+ The ending value for the set of points.
+
+
+ -
+
+ steps
+
+ :
+
int
+
+ -
+
+ The size of the returned tensor.
+
+
+ -
+
+ ?baseVal
+
+ :
+
float
+
+ -
+
+ The base of the logarithm. Default: 10.0.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, uses Device.Default.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, uses Dtype.Default.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, uses Backend.Default.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Applies a logsumexp followed by a logarithm.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ dim
+
+ :
+
int
+
+ -
+
+ The dimension to reduce.
+
+
+ -
+
+ ?keepDim
+
+ :
+
bool
+
+ -
+
+ Whether the output tensor has dim retained or not.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a boolean tensor for the element-wise less-than comparison of the elements in the two tensors.
+
+
+ -
+
+ a
+
+ :
+
Tensor
+
+ -
+
+ The first tensor.
+
+
+ -
+
+ b
+
+ :
+
Tensor
+
+ -
+
+ The second tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Produce a new tensor by mapping a function over all elements of the input tensor.
+
+
+ -
+
+ mapping
+
+ :
+
Tensor -> Tensor
+
+ -
+
+ The function to apply to each element of the tensor.
+
+
+ -
+
+ tensor
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Produce a new tensor by mapping a function over all corresponding elements of two input tensors.
+
+
+ -
+
+ mapping
+
+ :
+
Tensor -> Tensor -> Tensor
+
+ -
+
+ The function to apply to each element of the tensor.
+
+
+ -
+
+ tensor1
+
+ :
+
Tensor
+
+ -
+
+ The first input tensor.
+
+
+ -
+
+ tensor2
+
+ :
+
Tensor
+
+ -
+
+ The second input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Produce a new tensor by mapping a function over all corresponding elements of three input tensors.
+
+
+ -
+
+ mapping
+
+ :
+
Tensor -> Tensor -> Tensor -> Tensor
+
+ -
+
+ The function to apply to each element of the tensor.
+
+
+ -
+
+ tensor1
+
+ :
+
Tensor
+
+ -
+
+ The first input tensor.
+
+
+ -
+
+ tensor2
+
+ :
+
Tensor
+
+ -
+
+ The second input tensor.
+
+
+ -
+
+ tensor3
+
+ :
+
Tensor
+
+ -
+
+ The third input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Produce a new tensor by mapping a function over all elements of the input tensor.
+
+
+ -
+
+ mapping
+
+ :
+
int[] -> Tensor -> Tensor
+
+ -
+
+ The function is passed the index of each element. The function to apply to each element of the tensor.
+
+
+ -
+
+ tensor
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Produce a new tensor by mapping a function over all corresponding elements of two input tensors.
+
+
+ -
+
+ mapping
+
+ :
+
int[] -> Tensor -> Tensor -> Tensor
+
+ -
+
+ The function to apply to each element of the tensor.
+
+
+ -
+
+ tensor1
+
+ :
+
Tensor
+
+ -
+
+ The first input tensor.
+
+
+ -
+
+ tensor2
+
+ :
+
Tensor
+
+ -
+
+ The second input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Produce a new tensor by mapping a function over all corresponding elements of three input tensors.
+
+
+ -
+
+ mapping
+
+ :
+
int[] -> Tensor -> Tensor -> Tensor -> Tensor
+
+ -
+
+ The function to apply to each element of the tensor.
+
+
+ -
+
+ tensor1
+
+ :
+
Tensor
+
+ -
+
+ The first input tensor.
+
+
+ -
+
+ tensor2
+
+ :
+
Tensor
+
+ -
+
+ The second input tensor.
+
+
+ -
+
+ tensor3
+
+ :
+
Tensor
+
+ -
+
+ The third input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Matrix product of two tensors.
+
+
+ -
+
+ a
+
+ :
+
Tensor
+
+ -
+
+ The first tensor.
+
+
+ -
+
+ b
+
+ :
+
Tensor
+
+ -
+
+ The second tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns the maximum value of all elements in the input tensor along the given dimension.
+
+
+ -
+
+ a
+
+ :
+
Tensor
+
+ -
+
+ The tensor.
+
+
+ -
+
+ dim
+
+ :
+
int
+
+ -
+
+ The dimension.
+
+
+ -
+
+ ?keepDim
+
+ :
+
bool
+
+ -
+
+ Whether the output tensor has dim retained or not.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Each element of the tensor input is compared with the corresponding element of the tensor other and an element-wise maximum is taken.
+
+
+ -
+
+ a
+
+ :
+
Tensor
+
+ -
+
+ The first tensor.
+
+
+ -
+
+ b
+
+ :
+
Tensor
+
+ -
+
+ The second tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns the maximum value of all elements in the input tensor.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Applies a 1D max pooling over an input signal composed of several input planes.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ kernelSize
+
+ :
+
int
+
+ -
+
+ The size of the window to take a max over.
+
+
+ -
+
+ ?stride
+
+ :
+
int
+
+ -
+
+ The stride of the window. Default value is kernelSize.
+
+
+ -
+
+ ?padding
+
+ :
+
int
+
+ -
+
+ The implicit zero padding to be added on both sides.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Applies a 1D max pooling over an input signal composed of several input planes, returning the max indices along with the outputs.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ kernelSize
+
+ :
+
int
+
+ -
+
+ The size of the window to take a max over.
+
+
+ -
+
+ ?stride
+
+ :
+
int
+
+ -
+
+ The stride of the window. Default value is kernelSize.
+
+
+ -
+
+ ?padding
+
+ :
+
int
+
+ -
+
+ The implicit zero padding to be added on both sides.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor * Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Applies a 2D max pooling over an input signal composed of several input planes.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ ?kernelSize
+
+ :
+
int
+
+ -
+
+ The size of the window to take a max over.
+
+
+ -
+
+ ?stride
+
+ :
+
int
+
+ -
+
+ The stride of the window. Default value is kernelSize.
+
+
+ -
+
+ ?padding
+
+ :
+
int
+
+ -
+
+ The implicit zero padding to be added on both sides.
+
+
+ -
+
+ ?kernelSizes
+
+ :
+
seq<int>
+
+ -
+
+ The sizes of the window to take a max over.
+
+
+ -
+
+ ?strides
+
+ :
+
seq<int>
+
+ -
+
+ The strides of the window. Default value is kernelSize.
+
+
+ -
+
+ ?paddings
+
+ :
+
seq<int>
+
+ -
+
+ The implicit zero paddings to be added on corresponding sides.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Applies a 2D max pooling over an input signal composed of several input planes, returning the max indices along with the outputs.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ ?kernelSize
+
+ :
+
int
+
+ -
+
+ The size of the window to take a max over.
+
+
+ -
+
+ ?stride
+
+ :
+
int
+
+ -
+
+ The stride of the window. Default value is kernelSize.
+
+
+ -
+
+ ?padding
+
+ :
+
int
+
+ -
+
+ The implicit zero padding to be added on both sides.
+
+
+ -
+
+ ?kernelSizes
+
+ :
+
seq<int>
+
+ -
+
+ The sizes of the window to take a max over.
+
+
+ -
+
+ ?strides
+
+ :
+
seq<int>
+
+ -
+
+ The strides of the window. Default value is kernelSize.
+
+
+ -
+
+ ?paddings
+
+ :
+
seq<int>
+
+ -
+
+ The implicit zero paddings to be added on corresponding sides.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor * Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Applies a 3D max pooling over an input signal composed of several input planes.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ ?kernelSize
+
+ :
+
int
+
+ -
+
+ The size of the window to take a max over.
+
+
+ -
+
+ ?stride
+
+ :
+
int
+
+ -
+
+ The stride of the window. Default value is kernelSize.
+
+
+ -
+
+ ?padding
+
+ :
+
int
+
+ -
+
+ The implicit zero padding to be added on both sides.
+
+
+ -
+
+ ?kernelSizes
+
+ :
+
seq<int>
+
+ -
+
+ The sizes of the window to take a max over.
+
+
+ -
+
+ ?strides
+
+ :
+
seq<int>
+
+ -
+
+ The strides of the window. Default value is kernelSizes.
+
+
+ -
+
+ ?paddings
+
+ :
+
seq<int>
+
+ -
+
+ The implicit zero paddings to be added on corresponding sides.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Applies a 3D max pooling over an input signal composed of several input planes, returning the max indices along with the outputs.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ ?kernelSize
+
+ :
+
int
+
+ -
+
+ The size of the window to take a max over.
+
+
+ -
+
+ ?stride
+
+ :
+
int
+
+ -
+
+ The stride of the window. Default value is kernelSize.
+
+
+ -
+
+ ?padding
+
+ :
+
int
+
+ -
+
+ The implicit zero padding to be added on both sides.
+
+
+ -
+
+ ?kernelSizes
+
+ :
+
seq<int>
+
+ -
+
+ The sizes of the window to take a max over.
+
+
+ -
+
+ ?strides
+
+ :
+
seq<int>
+
+ -
+
+ The strides of the window. Default value is kernelSize.
+
+
+ -
+
+ ?paddings
+
+ :
+
seq<int>
+
+ -
+
+ The implicit zero paddings to be added on corresponding sides.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor * Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Computes a partial inverse of maxpool1di
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ indices
+
+ :
+
Tensor
+
+ -
+
+ The indices selected by maxpool1di.
+
+
+ -
+
+ kernelSize
+
+ :
+
int
+
+ -
+
+ The size of the window to take a max over.
+
+
+ -
+
+ ?stride
+
+ :
+
int
+
+ -
+
+ The stride of the window. Default value is kernelSize.
+
+
+ -
+
+ ?padding
+
+ :
+
int
+
+ -
+
+ The implicit zero padding to be added on both sides.
+
+
+ -
+
+ ?outputSize
+
+ :
+
seq<int>
+
+ -
+
+ The targeted output size.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Computes a partial inverse of maxpool2di
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ indices
+
+ :
+
Tensor
+
+ -
+
+ The indices selected by maxpool2di.
+
+
+ -
+
+ ?kernelSize
+
+ :
+
int
+
+ -
+
+ The size of the window to take a max over.
+
+
+ -
+
+ ?stride
+
+ :
+
int
+
+ -
+
+ The stride of the window. Default value is kernelSize.
+
+
+ -
+
+ ?padding
+
+ :
+
int
+
+ -
+
+ The implicit zero padding to be added on both sides.
+
+
+ -
+
+ ?kernelSizes
+
+ :
+
seq<int>
+
+ -
+
+ The sizes of the window to take a max over.
+
+
+ -
+
+ ?strides
+
+ :
+
seq<int>
+
+ -
+
+ The strides of the window. Default value is kernelSizes.
+
+
+ -
+
+ ?paddings
+
+ :
+
seq<int>
+
+ -
+
+ The implicit zero paddings to be added on corresponding sides.
+
+
+ -
+
+ ?outputSize
+
+ :
+
seq<int>
+
+ -
+
+ The targeted output size.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Computes a partial inverse of maxpool3di
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ indices
+
+ :
+
Tensor
+
+ -
+
+ The indices selected by maxpool3di.
+
+
+ -
+
+ ?kernelSize
+
+ :
+
int
+
+ -
+
+ The size of the window to take a max over.
+
+
+ -
+
+ ?stride
+
+ :
+
int
+
+ -
+
+ The stride of the window. Default value is kernelSize.
+
+
+ -
+
+ ?padding
+
+ :
+
int
+
+ -
+
+ The implicit zero padding to be added on both sides.
+
+
+ -
+
+ ?kernelSizes
+
+ :
+
seq<int>
+
+ -
+
+ The sizes of the window to take a max over.
+
+
+ -
+
+ ?strides
+
+ :
+
seq<int>
+
+ -
+
+ The strides of the window. Default value is kernelSizes.
+
+
+ -
+
+ ?paddings
+
+ :
+
seq<int>
+
+ -
+
+ The implicit zero paddings to be added on corresponding sides.
+
+
+ -
+
+ ?outputSize
+
+ :
+
seq<int>
+
+ -
+
+ The targeted output size.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns the mean value of each row of the input tensor in the given dimension dim. If dim is a list of dimensions, reduce over all of them.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ dim
+
+ :
+
int
+
+ -
+
+ The dimension to reduce.
+
+
+ -
+
+ ?keepDim
+
+ :
+
bool
+
+ -
+
+ Whether the output tensor has dim retained or not.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns the mean value of all elements in the input tensor.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns the minimum value of all elements in the input tensor along the given dimension.
+
+
+ -
+
+ a
+
+ :
+
Tensor
+
+ -
+
+ The tensor.
+
+
+ -
+
+ dim
+
+ :
+
int
+
+ -
+
+ The dimension.
+
+
+ -
+
+ ?keepDim
+
+ :
+
bool
+
+ -
+
+ Whether the output tensor has dim retained or not.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Each element of the tensor input is compared with the corresponding element of the tensor other and an element-wise minimum is taken.
+
+
+ -
+
+ a
+
+ :
+
Tensor
+
+ -
+
+ The first tensor.
+
+
+ -
+
+ b
+
+ :
+
Tensor
+
+ -
+
+ The second tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns the minimum value of all elements in the input tensor.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Move the tensor to a difference device, backend and/or change its element type.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, the device of the input tensor is used.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, the element type of the input tensor is used.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, the backend of the input tensor is used.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Creates a criterion that measures the mean squared error (squared L2 norm) between each element in the input and the target.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ target
+
+ :
+
Tensor
+
+ -
+
+ The target tensor.
+
+
+ -
+
+ ?reduction
+
+ :
+
string
+
+ -
+
+ Optionally specifies the reduction to apply to the output: 'none' | 'mean' | 'sum'. 'none': no reduction will be applied, 'mean': the sum of the output will be divided by the number of elements in the output, 'sum': the output will be summed. Note: size_average and reduce are in the process of being deprecated, and in the meantime, specifying either of those two args will override reduction. Default: 'mean'.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Return the element-wise multiplication of the two tensors.
+
+
+ -
+
+ a
+
+ :
+
Tensor
+
+ -
+
+ The first tensor.
+
+
+ -
+
+ b
+
+ :
+
Tensor
+
+ -
+
+ The second tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a tensor where each row contains numSamples indices sampled from the multinomial probability distribution located in the corresponding row of tensor input.
+
+
+ -
+
+ probs
+
+ :
+
Tensor
+
+ -
+
+ The input tensor containing probabilities.
+
+
+ -
+
+ numSamples
+
+ :
+
int
+
+ -
+
+ The number of samples to draw.
+
+
+ -
+
+ ?normalize
+
+ :
+
bool
+
+ -
+
+ Indicates where the probabilities should first be normalized by their sum.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, uses Device.Default.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, uses Dtype.Default.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, uses Backend.Default.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a boolean tensor for the element-wise non-equality comparison of the elements in the two tensors.
+
+
+ -
+
+ a
+
+ :
+
Tensor
+
+ -
+
+ The first tensor.
+
+
+ -
+
+ b
+
+ :
+
Tensor
+
+ -
+
+ The second tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Return the element-wise negation of the input tensor.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns the total number of elements in the input tensor.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
int
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Set the global nesting level for automatic differentiation.
+
+
+ -
+
+ level
+
+ :
+
uint32
+
+ -
+
+ The new nesting level.
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Increase the global nesting level for automatic differentiation.
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Get the global nesting level for automatic differentiation.
+
+
+ -
+
+ Returns:
+
+
uint32
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Reset the global nesting level for automatic differentiation to zero.
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ The negative log likelihood loss.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ target
+
+ :
+
Tensor
+
+ -
+
+ The target tensor.
+
+
+ -
+
+ ?weight
+
+ :
+
Tensor
+
+ -
+
+ A optional manual rescaling weight given to the loss of each batch element.
+
+
+ -
+
+ ?reduction
+
+ :
+
string
+
+ -
+
+ Optionally specifies the reduction to apply to the output: 'none' | 'mean' | 'sum'. 'none': no reduction will be applied, 'mean': the sum of the output will be divided by the number of elements in the output, 'sum': the output will be summed. Note: size_average and reduce are in the process of being deprecated, and in the meantime, specifying either of those two args will override reduction. Default: 'mean'.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Produce a new constant (non-differentiated) tensor.
+
+
+ -
+
+ tensor
+
+ :
+
Tensor
+
+ -
+
+ The input.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Normalizes a vector so all the values are between zero and one (min-max scaling to 0..1).
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Get the scalar '1' tensor for the given configuration
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, uses Device.Default.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, uses Dtype.Default.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, uses Backend.Default.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns the '0' scalar tensor with characteristics based on the input tensor.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The shape and characteristics of input will determine those of the output tensor.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, the device of the input tensor is used.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, the element type of the input tensor is used.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, the backend of the input tensor is used.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a one-hot tensor, with one location set to 1, and all others 0.
+
+
+ -
+
+ length
+
+ :
+
int
+
+ -
+
+ The length of the returned tensor.
+
+
+ -
+
+ hot
+
+ :
+
int
+
+ -
+
+ The location to set to 1.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, uses Device.Default.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, uses Dtype.Default.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, uses Backend.Default.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ A version of FurnaceImage.onehot with characteristics based on the input tensor.
+
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The shape and characteristics of input will determine those of the output tensor.
+
+
+ -
+
+ length
+
+ :
+
int
+
+ -
+
+ The length of the returned tensor.
+
+
+ -
+
+ hot
+
+ :
+
int
+
+ -
+
+ The location to set to 1.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, the device of the input tensor is used.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, the element type of the input tensor is used.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, the backend of the input tensor is used.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new tensor of the given length filled with '1' values for the given element type and configuration
+
+
+ -
+
+ length
+
+ :
+
int
+
+ -
+
+ The length of the returned tensor.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, uses Device.Default.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, uses Dtype.Default.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, uses Backend.Default.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new tensor filled with '1' values for the given shape, element type and configuration
+
+
+ -
+
+ shape
+
+ :
+
seq<int>
+
+ -
+
+ The desired shape of returned tensor.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, uses Device.Default.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, uses Dtype.Default.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, uses Backend.Default.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new tensor filled with '1' values with characteristics based on the input tensor.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The shape and characteristics of input will determine those of the output tensor.
+
+
+ -
+
+ ?shape
+
+ :
+
seq<int>
+
+ -
+
+ The desired shape of returned tensor. Default: If None, the shape of the input tensor is used.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, the device of the input tensor is used.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, the element type of the input tensor is used.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, the backend of the input tensor is used.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Add zero padding to each side of a tensor
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ paddings
+
+ :
+
seq<int>
+
+ -
+
+ The implicit paddings on corresponding sides of the input.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns the original tensor with its dimensions permuted.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ permutation
+
+ :
+
seq<int>
+
+ -
+
+ The desired ordering of dimensions.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Return the element-wise exponentiation of the two tensors.
+
+
+ -
+
+ a
+
+ :
+
Tensor
+
+ -
+
+ The first tensor.
+
+
+ -
+
+ b
+
+ :
+
Tensor
+
+ -
+
+ The second tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Get the primal value of the tensor.
+
+
+ -
+
+ tensor
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Get the primal and derivative values of the tensor.
+
+
+ -
+
+ tensor
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor * Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a tensor filled with random numbers from a uniform distribution on the interval [0, 1)
+
+
+ -
+
+ length
+
+ :
+
int
+
+ -
+
+ The length of the returned tensor.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, uses Device.Default.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, uses Dtype.Default.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, uses Backend.Default.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a tensor filled with random numbers from a uniform distribution on the interval [0, 1)
+
+
+ -
+
+ shape
+
+ :
+
seq<int>
+
+ -
+
+ The desired shape of returned tensor.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, uses Device.Default.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, uses Dtype.Default.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, uses Backend.Default.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a tensor filled with random numbers from a uniform distribution on the interval [0, 1) with characteristics based on the input tensor
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The shape and characteristics of input will determine those of the output tensor.
+
+
+ -
+
+ ?shape
+
+ :
+
seq<int>
+
+ -
+
+ The desired shape of returned tensor. Default: If None, the shape of the input tensor is used.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, the device of the input tensor is used.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, the element type of the input tensor is used.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, the backend of the input tensor is used.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a tensor filled with random integers generated uniformly between low (inclusive) and high (exclusive).
+
+
+ -
+
+ low
+
+ :
+
int
+
+ -
+
+ Lowest integer to be drawn from the distribution. Default: 0..
+
+
+ -
+
+ high
+
+ :
+
int
+
+ -
+
+ One above the highest integer to be drawn from the distribution.
+
+
+ -
+
+ length
+
+ :
+
int
+
+ -
+
+ The length of the returned tensor.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, uses Device.Default.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, uses Dtype.Default.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, uses Backend.Default.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a tensor filled with random integers generated uniformly between low (inclusive) and high (exclusive).
+
+
+ -
+
+ low
+
+ :
+
int
+
+ -
+
+ Lowest integer to be drawn from the distribution. Default: 0..
+
+
+ -
+
+ high
+
+ :
+
int
+
+ -
+
+ One above the highest integer to be drawn from the distribution.
+
+
+ -
+
+ shape
+
+ :
+
seq<int>
+
+ -
+
+ The desired shape of returned tensor.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, uses Device.Default.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, uses Dtype.Default.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, uses Backend.Default.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a tensor with the same shape as Tensor input filled with random integers generated uniformly between low (inclusive) and high (exclusive) with characteristics based on the input tensor.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The shape and characteristics of input will determine those of the output tensor.
+
+
+ -
+
+ low
+
+ :
+
int
+
+ -
+
+ Lowest integer to be drawn from the distribution. Default: 0..
+
+
+ -
+
+ high
+
+ :
+
int
+
+ -
+
+ One above the highest integer to be drawn from the distribution.
+
+
+ -
+
+ ?shape
+
+ :
+
seq<int>
+
+ -
+
+ The desired shape of returned tensor. Default: If None, the shape of the input tensor is used.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, the device of the input tensor is used.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, the element type of the input tensor is used.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, the backend of the input tensor is used.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a tensor filled with random numbers from a normal distribution with mean 0 and variance 1 (also called the standard normal distribution).
+
+
+ -
+
+ length
+
+ :
+
int
+
+ -
+
+ The length of the returned tensor.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, uses Device.Default.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, uses Dtype.Default.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, uses Backend.Default.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a tensor filled with random numbers from a normal distribution with mean 0 and variance 1 (also called the standard normal distribution).
+
+
+ -
+
+ shape
+
+ :
+
seq<int>
+
+ -
+
+ The desired shape of returned tensor.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, uses Device.Default.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, uses Dtype.Default.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, uses Backend.Default.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a tensor filled with random numbers from a normal distribution with mean 0 and variance 1 (also called the standard normal distribution) with characteristics based on the input tensor.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The shape and characteristics of input will determine those of the output tensor.
+
+
+ -
+
+ ?shape
+
+ :
+
seq<int>
+
+ -
+
+ The desired shape of returned tensor. Default: If None, the shape of the input tensor is used.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, the device of the input tensor is used.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, the element type of the input tensor is used.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, the backend of the input tensor is used.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Applies the rectified linear unit function element-wise.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Repeat elements of a tensor
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ dim
+
+ :
+
int
+
+ -
+
+ The dimension along which to repeat values.
+
+
+ -
+
+ times
+
+ :
+
int
+
+ -
+
+ The number of repetitions for each element.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Compute the reverse-mode derivative at the given output tensor.
+
+
+ -
+
+ value
+
+ :
+
Tensor
+
+ -
+
+ The value to apply.
+
+
+ -
+
+ tensor
+
+ :
+
Tensor
+
+ -
+
+ The output tensor.
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Produce a new tensor suitable for calculating the reverse-mode derivative at the given level tag.
+
+
+ -
+
+ nestingTag
+
+ :
+
uint32
+
+ -
+
+ The level tag.
+
+
+ -
+
+ tensor
+
+ :
+
Tensor
+
+ -
+
+ The output tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Push the given value as part of the reverse-mode computation at the given output tensor.
+
+
+ -
+
+ value
+
+ :
+
Tensor
+
+ -
+
+ The value to apply.
+
+
+ -
+
+ tensor
+
+ :
+
Tensor
+
+ -
+
+ The output tensor.
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Reset the reverse mode computation associated with the given output tensor.
+
+
+ -
+
+ tensor
+
+ :
+
Tensor
+
+ -
+
+ The output tensor.
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new tensor with each of the elements of input rounded to the closest integer.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns the logarithm of the tensor after clamping the tensor so that all its elements are greater than epsilon. This is to avoid a -inf result for elements equal to zero.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ ?epsilon
+
+ :
+
float
+
+ -
+
+ The smallest value a tensor element can take before the logarithm is applied. Default: 1e-12
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Saves the object to the given file using a bespoke binary format.
+
+
+ -
+
+ value
+
+ :
+
obj
+
+
+ -
+
+ fileName
+
+ :
+
string
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new scalar tensor with the value value, for the given element type and configuration
+
+
+ -
+
+ value
+
+ :
+
scalar
+
+ -
+
+ The scalar giving the the initial values for the tensor.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, uses Device.Default.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, uses Dtype.Default.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, uses Backend.Default.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Gathers values along an axis specified by dim.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ dim
+
+ :
+
int
+
+ -
+
+ The axis along which to index.
+
+
+ -
+
+ indices
+
+ :
+
Tensor
+
+ -
+
+ The the indices of elements to gather.
+
+
+ -
+
+ destinationShape
+
+ :
+
seq<int>
+
+ -
+
+ The destination shape.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Seeds all backends with the given random seed, or a new seed based on the current time if no seed is specified.
+
+
+ -
+
+ ?seed
+
+ :
+
int
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Applies the sigmoid element-wise function
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new tensor with the signs of the elements of input.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new tensor with the sine of the elements of input
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new tensor with the hyperbolic sine of the elements of input.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Get a slice of a tensor
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ index
+
+ :
+
seq<int>
+
+ -
+
+ Index describing the slice.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Applies a softmax function.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ dim
+
+ :
+
int
+
+ -
+
+ A dimension along which softmax will be computed.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Applies the softplus function element-wise.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Splits the tensor into chunks. The tensor will be split into sizes.Length chunks each with a corresponding size in the given dimension.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The tensor to split.
+
+
+ -
+
+ sizes
+
+ :
+
seq<int>
+
+ -
+
+ The size of a single chunk or list of sizes for each chunk.
+
+
+ -
+
+ ?dim
+
+ :
+
int
+
+ -
+
+ The dimension along which to split the tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor[]
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new tensor with the square-root of the elements of input.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a tensor with all the dimensions of input of size 1 removed.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ ?dim
+
+ :
+
int
+
+ -
+
+ If given, the input will be squeezed only in this dimension.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Concatenates sequence of tensors along a new dimension
+
+
+ -
+
+ tensors
+
+ :
+
seq<Tensor>
+
+ -
+
+ The sequence of tensors to concatenate.
+
+
+ -
+
+ ?dim
+
+ :
+
int
+
+ -
+
+ The dimension to insert. Has to be between 0 and the number of dimensions of concatenated tensors (inclusive).
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns the tensor after standardization (z-score normalization)
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns the standard deviation of each row of the input tensor in the given dimension dim. If dim is a list of dimensions, reduce over all of them.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ dim
+
+ :
+
int
+
+ -
+
+ The dimension to reduce.
+
+
+ -
+
+ ?keepDim
+
+ :
+
bool
+
+ -
+
+ Whether the output tensor has dim retained or not.
+
+
+ -
+
+ ?unbiased
+
+ :
+
bool
+
+ -
+
+ Whether to use the unbiased estimation or not.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns the standard deviation of all elements in the input tensor.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ ?unbiased
+
+ :
+
bool
+
+ -
+
+ Whether to use the unbiased estimation or not.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Return the element-wise subtraction of the two tensors.
+
+
+ -
+
+ a
+
+ :
+
Tensor
+
+ -
+
+ The first tensor.
+
+
+ -
+
+ b
+
+ :
+
Tensor
+
+ -
+
+ The second tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
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.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ dim
+
+ :
+
int
+
+ -
+
+ The dimension to reduce.
+
+
+ -
+
+ ?keepDim
+
+ :
+
bool
+
+ -
+
+ Whether the output tensor has dim retained or not.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns the sum of all elements in the input tensor
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new tensor with the tangent of the elements of input
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new tensor with the hyperbolic tangent of the elements of input.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Creates a new tensor from the given data, using the given element type and configuration.
+
+
+
+ -
+
+ value
+
+ :
+
obj
+
+ -
+
+ The .NET object used to form the initial values for the tensor.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, uses Device.Default.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, uses Dtype.Default.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, uses Backend.Default.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+
+
+
+ let t1 = FurnaceImage.tensor [ 1 .. 10 ]
+ let t2 = FurnaceImage.tensor [ [ 1.0; 3.0; 4.0 ];
+ [ 1.02; 3.04; 4.01 ] ]
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Convert tensor to an image tensor with shape Channels x Height x Width
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ ?pixelMin
+
+ :
+
double
+
+ -
+
+ The minimum pixel value.
+
+
+ -
+
+ ?pixelMax
+
+ :
+
double
+
+ -
+
+ The maximum pixel value.
+
+
+ -
+
+ ?normalize
+
+ :
+
bool
+
+ -
+
+ If True, shift the image to the range (0, 1), by the min and max values specified by range.
+
+
+ -
+
+ ?gridCols
+
+ :
+
int
+
+ -
+
+ Number of columns of images in the grid.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Convert tensor to a grayscale image tensor and return a string representation approximating grayscale values
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ ?pixelMin
+
+ :
+
double
+
+ -
+
+ The minimum pixel value.
+
+
+ -
+
+ ?pixelMax
+
+ :
+
double
+
+ -
+
+ The maximum pixel value.
+
+
+ -
+
+ ?normalize
+
+ :
+
bool
+
+ -
+
+ If True, shift the image to the range (0, 1), by the min and max values specified by range.
+
+
+ -
+
+ ?gridCols
+
+ :
+
int
+
+ -
+
+ Number of columns of images in the grid.
+
+
+ -
+
+ ?asciiPalette
+
+ :
+
string
+
+ -
+
+ The ASCII pallette to use.
+
+
+
+
+ -
+
+ Returns:
+
+
string
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns the sum of the elements of the diagonal of the input 2-D matrix
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a tensor that is a transposed version of input with dimensions 0 and 1 swapped.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a tensor that is a transposed version of input. The given dimensions dim0 and dim1 are swapped.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ dim0
+
+ :
+
int
+
+ -
+
+ The first dimension to be transposed.
+
+
+ -
+
+ dim1
+
+ :
+
int
+
+ -
+
+ The second dimension to be transposed.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Reverse the dilation of the tensor in using the given dilations in each corresponding dimension.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ dilations
+
+ :
+
seq<int>
+
+ -
+
+ The dilations to use.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Unflattens a tensor dimension by expanding it to the given shape.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ dim
+
+ :
+
int
+
+ -
+
+ The dimension to unflatten.
+
+
+ -
+
+ unflattenedShape
+
+ :
+
seq<int>
+
+ -
+
+ New shape of the unflattened dimenension.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new tensor with a dimension of size one inserted at the specified position
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ dim
+
+ :
+
int
+
+ -
+
+ The index at which to insert the singleton dimension.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new tensor with dimensions of size one appended to the end until the number of dimensions is the same as the other tensor.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ other
+
+ :
+
Tensor
+
+ -
+
+ The other tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Removes a tensor dimension
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ ?dim
+
+ :
+
int
+
+ -
+
+ The dimension to remove.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor[]
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns the variance of each row of the input tensor in the given dimension dim. If dim is a list of dimensions, reduce over all of them.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ dim
+
+ :
+
int
+
+ -
+
+ The dimension to reduce.
+
+
+ -
+
+ ?keepDim
+
+ :
+
bool
+
+ -
+
+ Whether the output tensor has dim retained or not.
+
+
+ -
+
+ ?unbiased
+
+ :
+
bool
+
+ -
+
+ Whether to use the unbiased estimation or not.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns the variance of all elements in the input tensor.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ ?unbiased
+
+ :
+
bool
+
+ -
+
+ Whether to use the unbiased estimation or not.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns the version of the Furnace.Core assembly.
+
+
+ -
+
+ Returns:
+
+
string
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new tensor with the same data as the self tensor but of a different shape.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ shape
+
+ :
+
int
+
+ -
+
+ The desired shape of returned tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new tensor with the same data as the self tensor but of a different shape.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ shape
+
+ :
+
seq<int>
+
+ -
+
+ The desired shape of returned tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ View this tensor as the same size as other.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The input tensor.
+
+
+ -
+
+ other
+
+ :
+
Tensor
+
+ -
+
+ The result tensor has the same size as other.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Get the scalar zero tensor for the given configuration
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, uses Device.Default.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, uses Dtype.Default.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, uses Backend.Default.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Create a new 1D tensor using '0' as value for each element.
+
+
+ -
+
+ count
+
+ :
+
int
+
+ -
+
+ The number of elements in the tensor.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns the '0' scalar tensor with characteristics based on the input tensor.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The shape and characteristics of input will determine those of the output tensor.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, the device of the input tensor is used.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, the element type of the input tensor is used.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, the backend of the input tensor is used.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new tensor filled with '0' values for the given length, element type and configuration
+
+
+ -
+
+ length
+
+ :
+
int
+
+ -
+
+ The length of the returned tensor.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, uses Device.Default.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, uses Dtype.Default.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, uses Backend.Default.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new tensor filled with '0' values for the given shape, element type and configuration
+
+
+ -
+
+ shape
+
+ :
+
seq<int>
+
+ -
+
+ The desired shape of returned tensor.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, uses Device.Default.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, uses Dtype.Default.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, uses Backend.Default.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ |
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Returns a new tensor filled with '0' values with characteristics based on the input tensor.
+
+
+ -
+
+ input
+
+ :
+
Tensor
+
+ -
+
+ The shape and characteristics of input will determine those of the output tensor.
+
+
+ -
+
+ ?shape
+
+ :
+
seq<int>
+
+ -
+
+ The desired shape of returned tensor. Default: If None, the shape of the input tensor is used.
+
+
+ -
+
+ ?device
+
+ :
+
Device
+
+ -
+
+ The desired device of returned tensor. Default: if None, the device of the input tensor is used.
+
+
+ -
+
+ ?dtype
+
+ :
+
Dtype
+
+ -
+
+ The desired element type of returned tensor. Default: if None, the element type of the input tensor is used.
+
+
+ -
+
+ ?backend
+
+ :
+
Backend
+
+ -
+
+ The desired backend of returned tensor. Default: if None, the backend of the input tensor is used.
+
+
+
+
+ -
+
+ Returns:
+
+
Tensor
+
+
+
+ |
+
+
+ 
+
+
+ 
+
+(**
+## Practical, Familiar and Efficient
+
+Furnace comes with a [LibTorch](https://pytorch.org/cppdocs/) backend, using the same C++ and CUDA implementations for tensor computations that power [PyTorch](https://pytorch.org/). On top of these raw tensors (LibTorch's ATen, excluding autograd), Furnace implements its own computation graph and differentiation capabilities. It is tested on Linux, macOS, and Windows, and it supports CUDA and GPUs.
+
+The Furnace API is designed to be similar to [the PyTorch Python API](https://pytorch.org/docs/stable/index.html) through very similar naming and idioms, and where elements have similar names the PyTorch documentation can generally be used as a guide.
+
+Furnace uses [the incredible F# programming language](https://dot.net/fsharp) for tensor programming. F# code is generally faster and more robust than equivalent Python code, while still being succinct and compact like Python, making it an ideal modern AI and machine learning implementation language. This allows fluent and productive code for tensor programming.
+
+*)
+
+
+(**
+## Interactive Notebooks
+
+All documentation pages in this website are interactive notebooks which you can execute directly in your browser without installing anything in your local machine.
+
+Using the [](https://colab.research.google.com/github/fsprojects/Furnace/blob/gh-pages/index.ipynb) on the top of each page, you can execute the page as an interactive notebook running on cloud servers provided by [Google Colab](https://colab.research.google.com/).
+
+Using the buttons [](index.fsx)
+[](index.ipynb) you can also download a page as a script or an interactive notebook, which you can execute locally in [Jupyter](https://jupyter.org/) or [Visual Studio Code](https://code.visualstudio.com/) using [dotnet interactive](https://github.com/dotnet/interactive).
+
+## Example
+
+Define and add two tensors:
+
+*)
+open Furnace
+
+let t1 = FurnaceImage.tensor [ 0.0 ..0.2.. 1.0 ] // Gives [0., 0.2, 0.4, 0.6, 0.8, 1.]
+let t2 = FurnaceImage.tensor [ 1, 2, 3, 4, 5, 6 ]
+
+t1 + t2(* output:
+No value returned by any evaluator*)
+(**
+Compute a convolution:
+
+*)
+let t3 = FurnaceImage.tensor [[[[0.0 .. 10.0]]]]
+let t4 = FurnaceImage.tensor [[[[0.0 ..0.1.. 1.0]]]]
+
+t3.conv2d(t4)(* output:
+No value returned by any evaluator*)
+(**
+Take the gradient of a vector-to-scalar function:
+
+*)
+let f (x: Tensor) = x.exp().sum()
+
+FurnaceImage.grad f (FurnaceImage.tensor([1.8, 2.5]))(* output:
+No value returned by any evaluator*)
+(**
+Compute a nested derivative (checking for [perturbation confusion](https://doi.org/10.1007/s10990-008-9037-1)):
+
+*)
+let x0 = FurnaceImage.tensor(1.)
+let y0 = FurnaceImage.tensor(2.)
+FurnaceImage.diff (fun x -> x * FurnaceImage.diff (fun y -> x * y) y0) x0(* output:
+No value returned by any evaluator*)
+(**
+Define a model and optimize it:
+
+*)
+open Furnace
+open Furnace.Data
+open Furnace.Model
+open Furnace.Compose
+open Furnace.Util
+open Furnace.Optim
+
+let epochs = 2
+let batchSize = 32
+let numBatches = 5
+
+let trainSet = MNIST("../data", train=true, transform=id)
+let trainLoader = trainSet.loader(batchSize=batchSize, shuffle=true)
+
+let validSet = MNIST("../data", train=false, transform=id)
+let validLoader = validSet.loader(batchSize=batchSize, shuffle=false)
+
+let encoder =
+ Conv2d(1, 32, 4, 2)
+ --> FurnaceImage.relu
+ --> Conv2d(32, 64, 4, 2)
+ --> FurnaceImage.relu
+ --> Conv2d(64, 128, 4, 2)
+ --> FurnaceImage.flatten(1)
+
+let decoder =
+ FurnaceImage.unflatten(1, [128;1;1])
+ --> ConvTranspose2d(128, 64, 4, 2)
+ --> FurnaceImage.relu
+ --> ConvTranspose2d(64, 32, 4, 3)
+ --> FurnaceImage.relu
+ --> ConvTranspose2d(32, 1, 4, 2)
+ --> FurnaceImage.sigmoid
+
+let model = VAE([1;28;28], 64, encoder, decoder)
+
+let lr = FurnaceImage.tensor(0.001)
+let optimizer = Adam(model, lr=lr)
+
+for epoch = 1 to epochs do
+ let batches = trainLoader.epoch(numBatches)
+ for i, x, _ in batches do
+ model.reverseDiff()
+ let l = model.loss(x)
+ l.reverse()
+ optimizer.step()
+ print $"Epoch: {epoch} minibatch: {i} loss: {l}"
+
+let validLoss =
+ validLoader.epoch()
+ |> Seq.sumBy (fun (_, x, _) -> model.loss(x, normalize=false))
+print $"Validation loss: {validLoss/validSet.length}"
+(**
+Numerous other model definition, differentiation, and training patterns are supported. See the tutorials in the left-hand menu and [examples](https://github.com/fsprojects/Furnace/tree/dev/examples) on GitHub.
+
+## More Information
+
+Furnace is developed by [Atılım Güneş Baydin](http://www.robots.ox.ac.uk/~gunes/), [Don Syme](https://www.microsoft.com/en-us/research/people/dsyme/)
+and other contributors, having started as a project supervised by the automatic differentiation wizards [Barak Pearlmutter](https://scholar.google.com/citations?user=AxFrw0sAAAAJ&hl=en) and [Jeffrey Siskind](https://scholar.google.com/citations?user=CgSBtPYAAAAJ&hl=en).
+
+Please join us [on GitHub](https://github.com/fsprojects/Furnace)!
+
+*)
+
diff --git a/index.html b/index.html
new file mode 100644
index 00000000..be11e842
--- /dev/null
+++ b/index.html
@@ -0,0 +1,400 @@
+
+
+
+
+ 
+(**
+## Dotnet Applications
+
+You can add Furnace to your dotnet application using the [dotnet](https://dotnet.microsoft.com/) command-line interface (CLI).
+
+For example, the following creates a new F# console application and adds the latest pre-release version of the `Furnace-cpu` package as a dependency.
+
+ dotnet new console -lang "F#" -o src/app
+ cd src/app
+ dotnet add package --prerelease Furnace-cpu
+ dotnet run
+
+## Packages
+
+We provide several package bundles for a variety of use cases.
+
+* [Furnace-cpu](https://www.nuget.org/packages/Furnace-cpu)
+Includes LibTorch CPU binaries for Linux, macOS, and Windows.
+
+* [Furnace-cuda-linux](https://www.nuget.org/packages/Furnace-cuda-linux) / [Furnace-cuda-windows](https://www.nuget.org/packages/Furnace-cuda-windows)
+Include LibTorch CPU and CUDA GPU binaries for Linux and Windows. Large download.
+
+* [Furnace-lite](https://www.nuget.org/packages/Furnace-lite)
+Includes the Torch backend but not the LibTorch binaries.
+
+### Using local LibTorch binaries (optional)
+
+You can combine the `Furnace-lite` package bundle with existing local native binaries of LibTorch for your OS (Linux, Mac, or Windows) installed through other means.
+
+LibTorch is the main tensor computation core implemented in C++/CUDA and it is used by PyTorch in Python and by other projects in various programming languages. The following are two common ways of having LibTorch in your system.
+
+* If you use Python and have [PyTorch](https://pytorch.org/) installed, this comes with LibTorch as a part of the PyTorch distribution. If your GPU works in this PyTorch installation without any issues, it will also work in Furnace.
+
+* You can download the native LibTorch package without Python by following the [get started](https://pytorch.org/get-started/locally/) instructions in the PyTorch website, and extracting the downloaded archive to a folder in your system.
+
+Before using the `Torch` backend in Furnace, you will have to add an explicit load of the LibTorch native library, which you can do as follows. In order to find the location of LibTorch binaries, searching for `libtorch.so` in your system might be helpful. Note that this file is called `libtorch.so` in Linux, `libtorch.dylib` in macOS, and `torch.dll` in Windows.
+
+ open System.Runtime.InteropServices
+ NativeLibrary.Load("/home/user/anaconda3/lib/python3.8/site-packages/torch/lib/libtorch.so")
+
+
+## Backends and Devices
+
+Furnace currently provides two computation backends.
+
+* The `Torch` backend is the default and recommended backend based on [LibTorch](https://pytorch.org/cppdocs/), using the same C++ and CUDA implementations for tensor computations that power [PyTorch](https://pytorch.org/). On top of these raw tensors (LibTorch's ATen, excluding autograd), Furnace implements its own computation graph and differentiation capabilities. This backend requires platform-specific binaries of LibTorch, which we provide and test on Linux, macOS, and Windows.
+
+
+* The `Reference` backend is implemented purely in F# and can run on any hardware platform where [dotnet](https://dotnet.microsoft.com/) can run (for example iOS, Android, Raspberry Pi). This backend has reasonable performance for use cases dominated by scalar and small tensor operations, and is not recommended for use cases involving large tensor operations (such as machine learning). This backend is always available.
+
+
+### Configuration of Default Backend, Device, and Tensor Type
+
+Selection of the default backend, device, and tensor type is done using [FurnaceImage.config](https://fsprojects.github.io/Furnace/reference/furnace-furnaceimage.html#config).
+
+* [Dtype](https://fsprojects.github.io/Furnace/reference/furnace-dtype.html) choices available: `BFloat16`, `Bool`, `Byte`, `Float16`, `Float32`, `Float64`, `Int16`, `Int32`, `Int64`, `Int8`
+
+
+* [Device](https://fsprojects.github.io/Furnace/reference/furnace-device.html) choices available: `CPU`, `GPU`
+
+
+* [Backend](https://fsprojects.github.io/Furnace/reference/furnace-backend.html) choices available: `Reference`, `Torch`
+
+
+For example, the following selects the `Torch` backend with single precision tensors as the default tensor type and GPU (CUDA) execution.
+
+*)
+open Furnace
+
+FurnaceImage.config(dtype=Dtype.Float32, device=Device.GPU, backend=Backend.Torch)
+(**
+The following selects the `Reference` backend.
+
+*)
+FurnaceImage.config(backend=Backend.Reference)
+(**
+A tensor's backend and device can be inspected as follows.
+
+*)
+let t = FurnaceImage.tensor [ 0 .. 10 ]
+
+let device = t.device
+let backend = t.backend
+(**
+Tensors can be moved between devices (for example from CPU to GPU) using [Tensor.move](https://fsprojects.github.io/Furnace/reference/furnace-tensor.html#move). For example:
+
+*)
+let t2 = t.move(Device.GPU)
+(**
+## Developing Furnace Libraries
+
+To develop libraries built on Furnace, you can use the following guideline to reference the various packages.
+
+* Reference `Furnace.Core` and `Furnace.Data` in your library code.
+
+* Reference `Furnace.Backends.Reference` in your correctness testing code.
+
+* Reference `Furnace.Backends.Torch` and `libtorch-cpu` in your CPU testing code.
+
+* Reference `Furnace.Backends.Torch` and `libtorch-cuda-linux` or `libtorch-cuda-windows` in your (optional) GPU testing code.
+
+*)
+
diff --git a/install.html b/install.html
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+
+
+
+
+