Struct BackendRouter

pub struct BackendRouter<R: RunnerChannel> { /* private fields */ }

A backend that forwards the tensor operations to the appropriate backend (given multiple backends).

Trait Implementations

impl<R: RunnerChannel> ActivationOps<BackendRouter<R>> for BackendRouter<R>

fn leaky_relu( tensor: <B as Backend>::FloatTensorPrimitive, negative_slope: <B as Backend>::FloatElem, ) -> <B as Backend>::FloatTensorPrimitive

Applies the LeakyReLU activation function.

fn relu( tensor: <B as Backend>::FloatTensorPrimitive, ) -> <B as Backend>::FloatTensorPrimitive

Applies the ReLU activation function.

fn relu_backward( output: <B as Backend>::FloatTensorPrimitive, grad: <B as Backend>::FloatTensorPrimitive, ) -> <B as Backend>::FloatTensorPrimitive

Applies the ReLU activation function backward.

fn gelu( tensor: <B as Backend>::FloatTensorPrimitive, ) -> <B as Backend>::FloatTensorPrimitive

Applies the Gelu activation function.

fn prelu( tensor: <B as Backend>::FloatTensorPrimitive, alpha: <B as Backend>::FloatTensorPrimitive, ) -> <B as Backend>::FloatTensorPrimitive

Applies the PReLu activation function.

fn gelu_backward( x: <B as Backend>::FloatTensorPrimitive, grad: <B as Backend>::FloatTensorPrimitive, ) -> <B as Backend>::FloatTensorPrimitive

Applies the Gelu activation function backward.

fn sigmoid( tensor: <B as Backend>::FloatTensorPrimitive, ) -> <B as Backend>::FloatTensorPrimitive

Applies the Sigmoid activation function.

fn sigmoid_backward( output: <B as Backend>::FloatTensorPrimitive, grad: <B as Backend>::FloatTensorPrimitive, ) -> <B as Backend>::FloatTensorPrimitive

Applies the Sigmoid activation function backward.

fn hard_sigmoid( tensor: <B as Backend>::FloatTensorPrimitive, alpha: <B as Backend>::FloatElem, beta: <B as Backend>::FloatElem, ) -> <B as Backend>::FloatTensorPrimitive

Applies the hard Sigmoid activation function.

fn log_sigmoid( tensor: <B as Backend>::FloatTensorPrimitive, ) -> <B as Backend>::FloatTensorPrimitive

Applies the LogSigmoid activation function.

fn log_sigmoid_backward( x: <B as Backend>::FloatTensorPrimitive, grad: <B as Backend>::FloatTensorPrimitive, ) -> <B as Backend>::FloatTensorPrimitive

Applies the LogSigmoid activation function backward.

impl<R: RunnerChannel> Backend for BackendRouter<R>

type Device = <R as RunnerChannel>::Device

Device type.

type FloatTensorPrimitive = RouterTensor<<R as RunnerChannel>::Client>

Tensor primitive to be used for all float operations.

type FloatElem = <R as RunnerChannel>::FloatElem

Default float element type.

type IntTensorPrimitive = RouterTensor<<R as RunnerChannel>::Client>

Tensor primitive to be used for all int operations.

type IntElem = <R as RunnerChannel>::IntElem

Int element type.

type BoolTensorPrimitive = RouterTensor<<R as RunnerChannel>::Client>

Tensor primitive to be used for all bool operations.

type BoolElem = <R as RunnerChannel>::BoolElem

Tensor primitive to be used for all bool operations.

type QuantizedTensorPrimitive = RouterTensor<<R as RunnerChannel>::Client>

Tensor primitive to be used for all quantized operations.

type QuantizedEncoding = u32

Quantized tensor encoding type.

fn name(device: &Self::Device) -> String

Name of the backend.

fn seed(seed: u64)

Seed the backend.

fn sync(device: &Self::Device)

Sync the backend, ensure that all computation are finished.

fn ad_enabled() -> bool

If autodiff is enabled.

impl<R: RunnerChannel> BoolTensorOps<BackendRouter<R>> for BackendRouter<R>

fn bool_empty(shape: Shape, device: &Device<Self>) -> BoolTensor<Self>

Creates a new bool tensor.

async fn bool_into_data(tensor: BoolTensor<Self>) -> TensorData

Converts the tensor to a data structure.

fn bool_from_data(data: TensorData, device: &Device<Self>) -> BoolTensor<Self>

Creates a tensor from the data structure.

fn bool_into_int(tensor: BoolTensor<Self>) -> IntTensor<Self>

Converts bool tensor to int tensor.

fn bool_into_float(tensor: BoolTensor<Self>) -> FloatTensor<Self>

Converts bool tensor to float tensor.

fn bool_device(tensor: &BoolTensor<Self>) -> Device<Self>

Gets the device of the tensor.

fn bool_to_device( tensor: BoolTensor<Self>, device: &Device<Self>, ) -> BoolTensor<Self>

Moves the tensor to the device.

fn bool_reshape(tensor: BoolTensor<Self>, shape: Shape) -> BoolTensor<Self>

Reshapes the tensor.

fn bool_slice( tensor: BoolTensor<Self>, ranges: &[Range<usize>], ) -> BoolTensor<Self>

Gets the values from the tensor for the given ranges.

fn bool_slice_assign( tensor: BoolTensor<Self>, ranges: &[Range<usize>], value: BoolTensor<Self>, ) -> BoolTensor<Self>

Sets the values in the tensor for the given ranges.

fn bool_equal(lhs: BoolTensor<Self>, rhs: BoolTensor<Self>) -> BoolTensor<Self>

Equates the two tensors.

fn bool_not(tensor: BoolTensor<Self>) -> BoolTensor<Self>

Inverses boolean values.

fn bool_and(lhs: BoolTensor<Self>, rhs: BoolTensor<Self>) -> BoolTensor<Self>

Executes the logical and (&&) operation on two boolean tensors.

fn bool_or(lhs: BoolTensor<Self>, rhs: BoolTensor<Self>) -> BoolTensor<Self>

Executes the logical or (||) operation on two boolean tensors.

fn bool_swap_dims( tensor: BoolTensor<Self>, dim1: usize, dim2: usize, ) -> BoolTensor<Self>

Swaps two dimensions of a bool tensor.

fn bool_permute(tensor: BoolTensor<Self>, axes: &[usize]) -> BoolTensor<Self>

Permutes the dimensions of a tensor.

fn bool_flip(tensor: BoolTensor<Self>, axes: &[usize]) -> BoolTensor<Self>

Reverse the order of elements in a tensor along the given axes.

fn bool_expand(tensor: BoolTensor<Self>, shape: Shape) -> BoolTensor<Self>

Broadcasts the bool tensor to the given shape.

fn bool_cat(tensors: Vec<BoolTensor<Self>>, dim: usize) -> BoolTensor<Self>

Concatenates the tensors along the given dimension.

fn bool_repeat_dim( tensor: BoolTensor<Self>, dim: usize, times: usize, ) -> BoolTensor<Self>

Repeats one dimension of the tensor a given number of times along that dimension.

fn bool_not_equal( lhs: <B as Backend>::BoolTensorPrimitive, rhs: <B as Backend>::BoolTensorPrimitive, ) -> <B as Backend>::BoolTensorPrimitive

Element-wise non-equality comparison.

fn bool_transpose( tensor: <B as Backend>::BoolTensorPrimitive, ) -> <B as Backend>::BoolTensorPrimitive

Transposes a bool tensor.

fn bool_narrow( tensor: <B as Backend>::BoolTensorPrimitive, dim: usize, start: usize, length: usize, ) -> <B as Backend>::BoolTensorPrimitive

Returns a new tensor with the given dimension narrowed to the given range.

fn bool_chunk( tensor: <B as Backend>::BoolTensorPrimitive, chunks: usize, dim: usize, ) -> Vec<<B as Backend>::BoolTensorPrimitive>

Split the tensor along the given dimension into chunks.

fn bool_split( tensor: <B as Backend>::BoolTensorPrimitive, split_size: usize, dim: usize, ) -> Vec<<B as Backend>::BoolTensorPrimitive>

Split the tensor along the given dimension into chunks of split_size.

fn bool_split_with_sizes( tensor: <B as Backend>::BoolTensorPrimitive, split_sizes: Vec<usize>, dim: usize, ) -> Vec<<B as Backend>::BoolTensorPrimitive>

Split the tensor along the given dimension into chunks with sizes in dim according to split_sizes.

fn bool_any( tensor: <B as Backend>::BoolTensorPrimitive, ) -> <B as Backend>::BoolTensorPrimitive

Tests if any element in the boolean tensor evaluates to True.

fn bool_any_dim( tensor: <B as Backend>::BoolTensorPrimitive, dim: usize, ) -> <B as Backend>::BoolTensorPrimitive

Tests if any element in the boolean tensor evaluates to True along a given dimension dim.

fn bool_all( tensor: <B as Backend>::BoolTensorPrimitive, ) -> <B as Backend>::BoolTensorPrimitive

Tests if all elements in the boolean tensor evaluate to True.

fn bool_all_dim( tensor: <B as Backend>::BoolTensorPrimitive, dim: usize, ) -> <B as Backend>::BoolTensorPrimitive

Tests if all elements in the boolean tensor evaluate to True along a given dimension dim.

fn bool_argwhere( tensor: <B as Backend>::BoolTensorPrimitive, ) -> impl Future<Output = <B as Backend>::IntTensorPrimitive> + Send + 'static

Compute the indices of the elements that are non-zero, grouped by element.

fn bool_nonzero( tensor: <B as Backend>::BoolTensorPrimitive, ) -> impl Future<Output = Vec<<B as Backend>::IntTensorPrimitive>> + Send + 'static

Compute the indices of the elements that are non-zero.

impl<R: RunnerChannel> Clone for BackendRouter<R>

fn clone(&self) -> Self

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl<R: RunnerChannel> Debug for BackendRouter<R>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl<R: RunnerChannel> Default for BackendRouter<R>

fn default() -> Self

Returns the “default value” for a type.

impl<R: RunnerChannel> FloatTensorOps<BackendRouter<R>> for BackendRouter<R>

fn float_from_data(data: TensorData, device: &Device<Self>) -> FloatTensor<Self>

Creates a new tensor from the data structure.

fn float_random( shape: Shape, distribution: Distribution, device: &Device<Self>, ) -> FloatTensor<Self>

Creates a new tensor with random values.

fn float_zeros(shape: Shape, device: &Device<Self>) -> FloatTensor<Self>

Creates a new tensor with zeros.

fn float_ones(shape: Shape, device: &Device<Self>) -> FloatTensor<Self>

Creates a new tensor with ones.

fn float_full( shape: Shape, fill_value: FloatElem<Self>, device: &Device<Self>, ) -> FloatTensor<Self>

Creates a tensor filled with given value.

async fn float_into_data(tensor: FloatTensor<Self>) -> TensorData

Converts the tensor to a data structure.

fn float_device(tensor: &FloatTensor<Self>) -> Device<Self>

Gets the device of the tensor.

fn float_to_device( tensor: FloatTensor<Self>, device: &Device<Self>, ) -> FloatTensor<Self>

Moves the tensor to the given device.

fn float_into_int(tensor: FloatTensor<Self>) -> IntTensor<Self>

Converts float tensor to int tensor.

fn float_empty(shape: Shape, device: &Device<Self>) -> FloatTensor<Self>

Creates an empty tensor with the given shape.

fn float_add( lhs: FloatTensor<Self>, rhs: FloatTensor<Self>, ) -> FloatTensor<Self>

Adds two tensors together.

fn float_add_scalar( lhs: FloatTensor<Self>, rhs: FloatElem<Self>, ) -> FloatTensor<Self>

Adds a scalar to a tensor.

fn float_clamp( tensor: FloatTensor<Self>, min: FloatElem<Self>, max: FloatElem<Self>, ) -> FloatTensor<Self>

Clamps a tensor between a minimum and maximum value.

fn float_sub( lhs: FloatTensor<Self>, rhs: FloatTensor<Self>, ) -> FloatTensor<Self>

Subtracts two tensors.

fn float_sub_scalar( lhs: FloatTensor<Self>, rhs: FloatElem<Self>, ) -> FloatTensor<Self>

Subtracts a scalar from a tensor.

fn float_mul( lhs: FloatTensor<Self>, rhs: FloatTensor<Self>, ) -> FloatTensor<Self>

Multiplies two tensors together element-wise.

fn float_mul_scalar( lhs: FloatTensor<Self>, rhs: FloatElem<Self>, ) -> FloatTensor<Self>

Multiplies a tensor by a scalar.

fn float_div( lhs: FloatTensor<Self>, rhs: FloatTensor<Self>, ) -> FloatTensor<Self>

Divides two tensors element-wise.

fn float_div_scalar( lhs: FloatTensor<Self>, rhs: FloatElem<Self>, ) -> FloatTensor<Self>

Divides a tensor by a scalar.

fn float_remainder( lhs: FloatTensor<Self>, rhs: FloatTensor<Self>, ) -> FloatTensor<Self>

Computes the remainder of division between two tensors element-wise.

fn float_remainder_scalar( lhs: FloatTensor<Self>, rhs: FloatElem<Self>, ) -> FloatTensor<Self>

Computes the modulus of a tensor given a scalar.

fn float_matmul( lhs: FloatTensor<Self>, rhs: FloatTensor<Self>, ) -> FloatTensor<Self>

Multiplies two tensors together using matrix multiplication.

fn float_swap_dims( tensor: FloatTensor<Self>, dim1: usize, dim2: usize, ) -> FloatTensor<Self>

Swaps two dimensions of a tensor.

fn float_reshape(tensor: FloatTensor<Self>, shape: Shape) -> FloatTensor<Self>

Reshapes a tensor.

fn float_gather( dim: usize, tensor: FloatTensor<Self>, indices: IntTensor<Self>, ) -> FloatTensor<Self>

Gather elements from a tensor.

fn float_scatter( dim: usize, tensor: FloatTensor<Self>, indices: IntTensor<Self>, value: FloatTensor<Self>, ) -> FloatTensor<Self>

Scatter elements into a tensor.

fn float_select( tensor: FloatTensor<Self>, dim: usize, indices: IntTensor<Self>, ) -> FloatTensor<Self>

Select tensor elements along the given dimension corresponding for the given indices.

fn float_select_assign( tensor: FloatTensor<Self>, dim: usize, indices: IntTensor<Self>, value: FloatTensor<Self>, ) -> FloatTensor<Self>

Assign the selected elements along the given dimension corresponding for the given indices to the given value.

fn float_slice( tensor: FloatTensor<Self>, ranges: &[Range<usize>], ) -> FloatTensor<Self>

Select tensor elements corresponding for the given ranges.

fn float_slice_assign( tensor: FloatTensor<Self>, ranges: &[Range<usize>], value: FloatTensor<Self>, ) -> FloatTensor<Self>

Assign the selected elements corresponding for the given ranges to the given value.

fn float_mask_where( tensor: FloatTensor<Self>, mask: BoolTensor<Self>, value: FloatTensor<Self>, ) -> FloatTensor<Self>

Update the given tensor with the value tensor where the mask is true.

fn float_mask_fill( tensor: FloatTensor<Self>, mask: BoolTensor<Self>, value: FloatElem<Self>, ) -> FloatTensor<Self>

Update the given tensor with the value where the mask is true.

fn float_equal( lhs: FloatTensor<Self>, rhs: FloatTensor<Self>, ) -> BoolTensor<Self>

Equal comparison of two tensors.

fn float_equal_elem( lhs: FloatTensor<Self>, rhs: FloatElem<Self>, ) -> BoolTensor<Self>

Equal comparison of a tensor and a scalar.

fn float_greater( lhs: FloatTensor<Self>, rhs: FloatTensor<Self>, ) -> BoolTensor<Self>

Greater than comparison of two tensors.

fn float_greater_elem( lhs: FloatTensor<Self>, rhs: FloatElem<Self>, ) -> BoolTensor<Self>

Greater than comparison of a tensor and a scalar.

fn float_greater_equal( lhs: FloatTensor<Self>, rhs: FloatTensor<Self>, ) -> BoolTensor<Self>

Greater than or equal comparison of two tensors.

fn float_greater_equal_elem( lhs: FloatTensor<Self>, rhs: FloatElem<Self>, ) -> BoolTensor<Self>

Greater than or equal comparison of a tensor and a scalar.

fn float_lower( lhs: FloatTensor<Self>, rhs: FloatTensor<Self>, ) -> BoolTensor<Self>

Less than comparison of two tensors.

fn float_lower_elem( lhs: FloatTensor<Self>, rhs: FloatElem<Self>, ) -> BoolTensor<Self>

Less than comparison of a tensor and a scalar.

fn float_lower_equal( lhs: FloatTensor<Self>, rhs: FloatTensor<Self>, ) -> BoolTensor<Self>

Less than or equal comparison of two tensors.

fn float_lower_equal_elem( lhs: FloatTensor<Self>, rhs: FloatElem<Self>, ) -> BoolTensor<Self>

Less than or equal comparison of a tensor and a scalar.

fn float_sum(tensor: FloatTensor<Self>) -> FloatTensor<Self>

Sum of all elements in a tensor.

fn float_sum_dim(tensor: FloatTensor<Self>, axis: usize) -> FloatTensor<Self>

Sum of all elements in a tensor along a dimension.

fn float_prod(tensor: IntTensor<Self>) -> IntTensor<Self>

Product of all elements in a tensor.

fn float_prod_dim(tensor: IntTensor<Self>, dim: usize) -> IntTensor<Self>

Product of all elements in a tensor along a dimension.

fn float_mean(tensor: FloatTensor<Self>) -> FloatTensor<Self>

Mean of all elements in a tensor.

fn float_mean_dim(tensor: FloatTensor<Self>, dim: usize) -> FloatTensor<Self>

Mean of all elements in a tensor along a dimension.

fn float_exp(lhs: FloatTensor<Self>) -> FloatTensor<Self>

Returns a new tensor with exponential values.

fn float_log(tensor: FloatTensor<Self>) -> FloatTensor<Self>

Returns a new tensor with natural logarithm values.

fn float_log1p(tensor: FloatTensor<Self>) -> FloatTensor<Self>

Returns a new tensor with logarithm values of (1 + Xi).

fn float_powf_scalar(lhs: FloatTensor<Self>, rhs: f32) -> FloatTensor<Self>

Returns a new tensor with values raised to the power of float value.

fn float_sqrt(tensor: FloatTensor<Self>) -> FloatTensor<Self>

Returns a new tensor with square root values.

fn float_abs(tensor: FloatTensor<Self>) -> FloatTensor<Self>

Returns a new tensor with absolute values.

fn float_cos(tensor: FloatTensor<Self>) -> FloatTensor<Self>

Returns a new tensor with cosine values.

fn float_sin(tensor: FloatTensor<Self>) -> FloatTensor<Self>

Returns a new tensor with sine values.

fn float_tanh(tensor: FloatTensor<Self>) -> FloatTensor<Self>

Returns a new tensor with hyperbolic tangent values.

fn float_round(tensor: FloatTensor<Self>) -> FloatTensor<Self>

Returns a new tensor with rounded values.

fn float_floor(tensor: FloatTensor<Self>) -> FloatTensor<Self>

Returns a new tensor with floored values.

fn float_ceil(tensor: FloatTensor<Self>) -> FloatTensor<Self>

Returns a new tensor with ceiled values.

fn float_recip(tensor: FloatTensor<Self>) -> FloatTensor<Self>

Calculates the reciprocals element-wise

fn float_erf(tensor: FloatTensor<Self>) -> FloatTensor<Self>

Returns a new tensor with the error function values.

fn float_cat(tensors: Vec<FloatTensor<Self>>, dim: usize) -> FloatTensor<Self>

Concatenates tensors along a dimension.

fn float_argmax(tensor: FloatTensor<Self>, dim: usize) -> IntTensor<Self>

Gets the indices of the maximum elements of a tensor along an axis.

fn float_repeat_dim( tensor: FloatTensor<Self>, dim: usize, times: usize, ) -> FloatTensor<Self>

Repeat the tensor along the given dimension.

fn float_argmin(tensor: FloatTensor<Self>, dim: usize) -> IntTensor<Self>

Gets the indices of the minimum elements of a tensor along an axis.

fn float_max(tensor: FloatTensor<Self>) -> FloatTensor<Self>

Gets the maximum element of a tensor.

fn float_max_dim(tensor: FloatTensor<Self>, dim: usize) -> FloatTensor<Self>

Gets the maximum elements of a tensor along an axis.

fn float_max_dim_with_indices( tensor: FloatTensor<Self>, dim: usize, ) -> (FloatTensor<Self>, IntTensor<Self>)

Gets the maximum elements of a tensor along an axis and their indices.

fn float_min(tensor: FloatTensor<Self>) -> FloatTensor<Self>

Gets the minimum element of a tensor.

fn float_min_dim(tensor: FloatTensor<Self>, dim: usize) -> FloatTensor<Self>

Gets the minimum elements of a tensor along an axis.

fn float_min_dim_with_indices( tensor: FloatTensor<Self>, dim: usize, ) -> (FloatTensor<Self>, IntTensor<Self>)

Gets the minimum elements of a tensor along an axis and their indices.

fn float_powf( lhs: FloatTensor<Self>, rhs: FloatTensor<Self>, ) -> FloatTensor<Self>

Element-wise power with a FloatTensor.

fn float_permute(tensor: FloatTensor<Self>, axes: &[usize]) -> FloatTensor<Self>

Permutes the dimensions of a tensor.

fn float_expand(tensor: FloatTensor<Self>, shape: Shape) -> FloatTensor<Self>

Broadcasts the float tensor to the given shape.

fn float_flip(tensor: FloatTensor<Self>, axes: &[usize]) -> FloatTensor<Self>

Reverse the order of elements in a tensor along the given axes.

fn float_cast(tensor: FloatTensor<Self>, dtype: FloatDType) -> FloatTensor<Self>

Converts a tensor to another floating point data type.

fn float_clamp_min( tensor: <B as Backend>::FloatTensorPrimitive, min: <B as Backend>::FloatElem, ) -> <B as Backend>::FloatTensorPrimitive

Clamps a tensor under a minimum value.

fn float_clamp_max( tensor: <B as Backend>::FloatTensorPrimitive, max: <B as Backend>::FloatElem, ) -> <B as Backend>::FloatTensorPrimitive

Clamps a tensor over a maximum value.

fn float_neg( tensor: <B as Backend>::FloatTensorPrimitive, ) -> <B as Backend>::FloatTensorPrimitive

Negates a tensor element-wise.

fn float_transpose( tensor: <B as Backend>::FloatTensorPrimitive, ) -> <B as Backend>::FloatTensorPrimitive

Transposes a tensor.

fn float_not_equal( lhs: <B as Backend>::FloatTensorPrimitive, rhs: <B as Backend>::FloatTensorPrimitive, ) -> <B as Backend>::BoolTensorPrimitive

Element-wise non-equality comparison.

fn float_not_equal_elem( lhs: <B as Backend>::FloatTensorPrimitive, rhs: <B as Backend>::FloatElem, ) -> <B as Backend>::BoolTensorPrimitive

Element-wise non-equality comparison with a scalar.

fn float_detach( tensor: <B as Backend>::FloatTensorPrimitive, ) -> <B as Backend>::FloatTensorPrimitive

Detaches a tensor from the computation graph.

fn float_set_require_grad( tensor: <B as Backend>::FloatTensorPrimitive, _require_grad: bool, ) -> <B as Backend>::FloatTensorPrimitive

Sets the require_grad flag of a tensor.

fn float_is_require_grad(_tensor: &<B as Backend>::FloatTensorPrimitive) -> bool

Returns the require_grad flag of a tensor.

fn float_powi( lhs: <B as Backend>::FloatTensorPrimitive, rhs: <B as Backend>::IntTensorPrimitive, ) -> <B as Backend>::FloatTensorPrimitive

Element-wise power with an IntTensor.

fn float_powi_scalar( lhs: <B as Backend>::FloatTensorPrimitive, rhs: <B as Backend>::IntElem, ) -> <B as Backend>::FloatTensorPrimitive

raises a tensor to the power of an int scalar.

fn float_tan( tensor: <B as Backend>::FloatTensorPrimitive, ) -> <B as Backend>::FloatTensorPrimitive

Returns a new tensor with tangent values.

fn float_cosh( tensor: <B as Backend>::FloatTensorPrimitive, ) -> <B as Backend>::FloatTensorPrimitive

Returns a new tensor with hyperbolic cosine values.

fn float_sinh( tensor: <B as Backend>::FloatTensorPrimitive, ) -> <B as Backend>::FloatTensorPrimitive

Returns a new tensor with hyperbolic sine values.

fn float_max_abs( tensor: <B as Backend>::FloatTensorPrimitive, ) -> <B as Backend>::FloatTensorPrimitive

Gets the maximum absolute element of a tensor.

fn float_max_abs_dim( tensor: <B as Backend>::FloatTensorPrimitive, dim: usize, ) -> <B as Backend>::FloatTensorPrimitive

Gets the maximum absolute elements of a tensor along an axis.

fn float_narrow( tensor: <B as Backend>::FloatTensorPrimitive, dim: usize, start: usize, length: usize, ) -> <B as Backend>::FloatTensorPrimitive

Returns a new tensor with the given dimension narrowed to the given range.

fn float_chunk( tensor: <B as Backend>::FloatTensorPrimitive, chunks: usize, dim: usize, ) -> Vec<<B as Backend>::FloatTensorPrimitive>

Split the tensor along the given dimension into chunks.

fn float_split( tensor: <B as Backend>::FloatTensorPrimitive, split_size: usize, dim: usize, ) -> Vec<<B as Backend>::FloatTensorPrimitive>

Split the tensor along the given dimension into chunks of split_size.

fn float_split_with_sizes( tensor: <B as Backend>::FloatTensorPrimitive, split_sizes: Vec<usize>, dim: usize, ) -> Vec<<B as Backend>::FloatTensorPrimitive>

Split the tensor along the given dimension into chunks with sizes in dim according to split_sizes.

fn float_any( tensor: <B as Backend>::FloatTensorPrimitive, ) -> <B as Backend>::BoolTensorPrimitive

Tests if any element in the float tensor evaluates to True.

fn float_any_dim( tensor: <B as Backend>::FloatTensorPrimitive, dim: usize, ) -> <B as Backend>::BoolTensorPrimitive

Tests if any element in the float tensor evaluates to True along a given dimension dim.

fn float_all( tensor: <B as Backend>::FloatTensorPrimitive, ) -> <B as Backend>::BoolTensorPrimitive

Tests if all elements in the float tensor evaluate to True.

fn float_all_dim( tensor: <B as Backend>::FloatTensorPrimitive, dim: usize, ) -> <B as Backend>::BoolTensorPrimitive

Tests if all elements in the float tensor evaluate to True along a given dimension dim.

fn float_sign( tensor: <B as Backend>::FloatTensorPrimitive, ) -> <B as Backend>::FloatTensorPrimitive

Returns the signs of the float tensor.

fn float_sort( tensor: <B as Backend>::FloatTensorPrimitive, dim: usize, descending: bool, ) -> <B as Backend>::FloatTensorPrimitive

Sort the elements of the input tensor by value in along a given dimension.

fn float_sort_with_indices( tensor: <B as Backend>::FloatTensorPrimitive, dim: usize, descending: bool, ) -> (<B as Backend>::FloatTensorPrimitive, <B as Backend>::IntTensorPrimitive)

Sort the elements of the input tensor by value in along a given dimension.

fn float_argsort( tensor: <B as Backend>::FloatTensorPrimitive, dim: usize, descending: bool, ) -> <B as Backend>::IntTensorPrimitive

Returns the indices that sort the elements of the input tensor by value along a given dimension.

impl<R: RunnerChannel> IntTensorOps<BackendRouter<R>> for BackendRouter<R>

fn int_empty(shape: Shape, device: &Device<Self>) -> IntTensor<Self>

Creates a new int tensor.

async fn int_into_data(tensor: IntTensor<Self>) -> TensorData

Converts the tensor to a data structure.

fn int_from_data(data: TensorData, device: &Device<Self>) -> IntTensor<Self>

Creates a tensor from the data structure.

fn int_device(tensor: &IntTensor<Self>) -> Device<Self>

Gets the device of the tensor.

fn int_to_device( tensor: IntTensor<Self>, device: &Device<Self>, ) -> IntTensor<Self>

Moves the tensor to the given device.

fn int_reshape(tensor: IntTensor<Self>, shape: Shape) -> IntTensor<Self>

Reshapes the tensor.

fn int_slice( tensor: IntTensor<Self>, ranges: &[Range<usize>], ) -> IntTensor<Self>

Gets the element at the given indices.

fn int_slice_assign( tensor: IntTensor<Self>, ranges: &[Range<usize>], value: IntTensor<Self>, ) -> IntTensor<Self>

Sets the element at the given indices.

fn int_mask_where( tensor: IntTensor<Self>, mask: BoolTensor<Self>, value: IntTensor<Self>, ) -> IntTensor<Self>

Fills the tensor with values from the source tensor if the mask is true at the given indices.

fn int_mask_fill( tensor: IntTensor<Self>, mask: BoolTensor<Self>, value: IntElem<Self>, ) -> IntTensor<Self>

Fills the tensor with the given value if the mask is true at the given indices.

fn int_gather( dim: usize, tensor: IntTensor<Self>, indices: IntTensor<Self>, ) -> IntTensor<Self>

Gather elements from the tensor at the given indices.

fn int_scatter( dim: usize, tensor: IntTensor<Self>, indices: IntTensor<Self>, value: IntTensor<Self>, ) -> IntTensor<Self>

Scatter a given value to the tensor at the given indices.

fn int_select( tensor: IntTensor<Self>, dim: usize, indices: IntTensor<Self>, ) -> IntTensor<Self>

Select tensor elements along the given dimension corresponding to the given indices.

fn int_select_assign( tensor: IntTensor<Self>, dim: usize, indices: IntTensor<Self>, value: IntTensor<Self>, ) -> IntTensor<Self>

Assign the selected elements along the given dimension corresponding to the given indices to the given value.

fn int_cat(tensors: Vec<IntTensor<Self>>, dim: usize) -> IntTensor<Self>

Concatenates the given tensors along the given dimension.

fn int_equal(lhs: IntTensor<Self>, rhs: IntTensor<Self>) -> BoolTensor<Self>

Element-wise equality comparison.

fn int_equal_elem(lhs: IntTensor<Self>, rhs: IntElem<Self>) -> BoolTensor<Self>

Element-wise equality comparison with a scalar.

fn int_greater(lhs: IntTensor<Self>, rhs: IntTensor<Self>) -> BoolTensor<Self>

Element-wise greater than comparison.

fn int_greater_elem( lhs: IntTensor<Self>, rhs: IntElem<Self>, ) -> BoolTensor<Self>

Element-wise greater than comparison with a scalar.

fn int_greater_equal( lhs: IntTensor<Self>, rhs: IntTensor<Self>, ) -> BoolTensor<Self>

Element-wise greater than or equal comparison.

fn int_greater_equal_elem( lhs: IntTensor<Self>, rhs: IntElem<Self>, ) -> BoolTensor<Self>

Element-wise greater than or equal comparison with a scalar.

fn int_lower(lhs: IntTensor<Self>, rhs: IntTensor<Self>) -> BoolTensor<Self>

Element-wise less than comparison.

fn int_lower_elem(lhs: IntTensor<Self>, rhs: IntElem<Self>) -> BoolTensor<Self>

Element-wise less than comparison with a scalar.

fn int_lower_equal( lhs: IntTensor<Self>, rhs: IntTensor<Self>, ) -> BoolTensor<Self>

Element-wise less than or equal comparison.

fn int_lower_equal_elem( lhs: IntTensor<Self>, rhs: IntElem<Self>, ) -> BoolTensor<Self>

Element-wise less than or equal comparison with a scalar.

fn int_add(lhs: IntTensor<Self>, rhs: IntTensor<Self>) -> IntTensor<Self>

Element-wise addition.

fn int_add_scalar(lhs: IntTensor<Self>, rhs: IntElem<Self>) -> IntTensor<Self>

Element-wise addition with a scalar.

fn int_sub(lhs: IntTensor<Self>, rhs: IntTensor<Self>) -> IntTensor<Self>

Element-wise subtraction.

fn int_sub_scalar(lhs: IntTensor<Self>, rhs: IntElem<Self>) -> IntTensor<Self>

Element-wise subtraction with a scalar.

fn int_mul(lhs: IntTensor<Self>, rhs: IntTensor<Self>) -> IntTensor<Self>

Element-wise multiplication.

fn int_mul_scalar(lhs: IntTensor<Self>, rhs: IntElem<Self>) -> IntTensor<Self>

Element-wise multiplication with a scalar.

fn int_div(lhs: IntTensor<Self>, rhs: IntTensor<Self>) -> IntTensor<Self>

Element-wise division.

fn int_div_scalar(lhs: IntTensor<Self>, rhs: IntElem<Self>) -> IntTensor<Self>

Element-wise division with a scalar.

fn int_remainder(lhs: IntTensor<Self>, rhs: IntTensor<Self>) -> IntTensor<Self>

Element-wise modulus.

fn int_remainder_scalar( lhs: IntTensor<Self>, rhs: IntElem<Self>, ) -> IntTensor<Self>

Element-wise modulus with a scalar.

fn int_zeros(shape: Shape, device: &Device<Self>) -> IntTensor<Self>

Creates a tensor of zeros.

fn int_ones(shape: Shape, device: &Device<Self>) -> IntTensor<Self>

Creates a tensor of ones.

fn int_sum(tensor: IntTensor<Self>) -> IntTensor<Self>

Sums all elements in the tensor.

fn int_sum_dim(tensor: IntTensor<Self>, axis: usize) -> IntTensor<Self>

Sums all elements in the tensor along a dimension.

fn int_prod(tensor: IntTensor<Self>) -> IntTensor<Self>

Computes the product of all elements in the tensor.

fn int_prod_dim(tensor: IntTensor<Self>, dim: usize) -> IntTensor<Self>

Computes the product of all elements in the tensor along a dimension.

fn int_mean(tensor: IntTensor<Self>) -> IntTensor<Self>

Computes the mean of all elements in the tensor.

fn int_mean_dim(tensor: IntTensor<Self>, dim: usize) -> IntTensor<Self>

Computes the mean of all elements in the tensor along a dimension.

fn int_argmax(tensor: IntTensor<Self>, dim: usize) -> IntTensor<Self>

Gets the indices of the maximum elements along a dimension.

fn int_argmin(tensor: IntTensor<Self>, dim: usize) -> IntTensor<Self>

Gets the indices of the minimum elements along a dimension.

fn int_clamp( tensor: IntTensor<Self>, min: IntElem<Self>, max: IntElem<Self>, ) -> IntTensor<Self>

Clamps a tensor between a minimum and maximum value.

fn int_abs(tensor: IntTensor<Self>) -> IntTensor<Self>

Returns a new tensor with absolute values.

fn int_into_float(tensor: IntTensor<Self>) -> FloatTensor<Self>

Converts int tensor to float tensor.

fn int_swap_dims( tensor: IntTensor<Self>, dim1: usize, dim2: usize, ) -> IntTensor<Self>

Swaps two dimensions of an int tensor.

fn int_max(tensor: IntTensor<Self>) -> IntTensor<Self>

Gets the maximum element in the tensor.

fn int_max_dim(tensor: IntTensor<Self>, dim: usize) -> IntTensor<Self>

Gets the maximum element in the tensor along a dimension.

fn int_max_dim_with_indices( tensor: IntTensor<Self>, dim: usize, ) -> (IntTensor<Self>, IntTensor<Self>)

Gets the maximum elements and corresponding indices along a dimension.

fn int_max_abs(tensor: IntTensor<Self>) -> IntTensor<Self>

Gets the maximum absolute element in the tensor.

fn int_max_abs_dim(tensor: IntTensor<Self>, dim: usize) -> IntTensor<Self>

Gets the maximum absolute element in the tensor along a dimension.

fn int_min(tensor: IntTensor<Self>) -> IntTensor<Self>

Gets the minimum element in the tensor.

fn int_min_dim(tensor: IntTensor<Self>, dim: usize) -> IntTensor<Self>

Gets the minimum elements in the tensor along a dimension.

fn int_min_dim_with_indices( tensor: IntTensor<Self>, dim: usize, ) -> (IntTensor<Self>, IntTensor<Self>)

Gets the minimum elements and corresponding indices along a dimension.

fn int_random( shape: Shape, distribution: Distribution, device: &Device<Self>, ) -> IntTensor<Self>

Creates a new int tensor with random values.

fn int_permute(tensor: IntTensor<Self>, axes: &[usize]) -> IntTensor<Self>

Permutes the dimensions of a tensor.

fn int_expand(tensor: IntTensor<Self>, shape: Shape) -> IntTensor<Self>

Broadcasts the int tensor to the given shape.

fn int_flip(tensor: IntTensor<Self>, axes: &[usize]) -> IntTensor<Self>

Reverse the order of elements in a tensor along the given axes.

fn int_repeat_dim( tensor: IntTensor<Self>, dim: usize, times: usize, ) -> IntTensor<Self>

Repeats the tensor along the given dimension the given number of times.

fn bitwise_and(lhs: IntTensor<Self>, rhs: IntTensor<Self>) -> IntTensor<Self>

Bitwise AND operation for Int Tensors

fn bitwise_or(lhs: IntTensor<Self>, rhs: IntTensor<Self>) -> IntTensor<Self>

Bitwise OR operation for Int Tensors

fn bitwise_xor(lhs: IntTensor<Self>, rhs: IntTensor<Self>) -> IntTensor<Self>

Bitwise XOR operation for Int Tensors

fn bitwise_not(tensor: IntTensor<Self>) -> IntTensor<Self>

Bitwise NOT operation for Int Tensors

fn bitwise_and_scalar( lhs: IntTensor<Self>, rhs: IntElem<Self>, ) -> IntTensor<Self>

Bitwise AND operation for Int Tensors with a scalar

fn bitwise_or_scalar( lhs: IntTensor<Self>, rhs: IntElem<Self>, ) -> IntTensor<Self>

Bitwise OR operation for Int Tensors with a scalar

fn bitwise_xor_scalar( lhs: IntTensor<Self>, rhs: IntElem<Self>, ) -> IntTensor<Self>

Bitwise XOR operation for Int Tensors with a scalar

fn bitwise_left_shift( lhs: IntTensor<Self>, rhs: IntTensor<Self>, ) -> IntTensor<Self>

Bitwise left shift operation for Int Tensors

fn bitwise_left_shift_scalar( lhs: IntTensor<Self>, rhs: IntElem<Self>, ) -> IntTensor<Self>

Bitwise left shift operation for Int Tensors with a scalar

fn bitwise_right_shift( lhs: IntTensor<Self>, rhs: IntTensor<Self>, ) -> IntTensor<Self>

Bitwise right shift operation for Int Tensors

fn bitwise_right_shift_scalar( lhs: IntTensor<Self>, rhs: IntElem<Self>, ) -> IntTensor<Self>

Bitwise right shift operation for Int Tensors with a scalar

fn int_not_equal( lhs: <B as Backend>::IntTensorPrimitive, rhs: <B as Backend>::IntTensorPrimitive, ) -> <B as Backend>::BoolTensorPrimitive

Element-wise non-equality comparison.

fn int_not_equal_elem( lhs: <B as Backend>::IntTensorPrimitive, rhs: <B as Backend>::IntElem, ) -> <B as Backend>::BoolTensorPrimitive

Element-wise non-equality comparison with a scalar.

fn int_powi( lhs: <B as Backend>::IntTensorPrimitive, rhs: <B as Backend>::IntTensorPrimitive, ) -> <B as Backend>::IntTensorPrimitive

Element-wise power with a IntTensor.

fn int_powf( lhs: <B as Backend>::IntTensorPrimitive, rhs: <B as Backend>::FloatTensorPrimitive, ) -> <B as Backend>::IntTensorPrimitive

Element-wise power with a floatTensor.

fn int_powi_scalar( lhs: <B as Backend>::IntTensorPrimitive, rhs: <B as Backend>::IntElem, ) -> <B as Backend>::IntTensorPrimitive

Element-wise power with a scalar.

fn int_powf_scalar( lhs: <B as Backend>::IntTensorPrimitive, rhs: f32, ) -> <B as Backend>::IntTensorPrimitive

Element-wise power with a floatTensor.

fn int_clamp_min( tensor: <B as Backend>::IntTensorPrimitive, min: <B as Backend>::IntElem, ) -> <B as Backend>::IntTensorPrimitive

Clamps a tensor under a minimum value.

fn int_clamp_max( tensor: <B as Backend>::IntTensorPrimitive, max: <B as Backend>::IntElem, ) -> <B as Backend>::IntTensorPrimitive

Clamps a tensor over a maximum value.

fn int_neg( tensor: <B as Backend>::IntTensorPrimitive, ) -> <B as Backend>::IntTensorPrimitive

Element-wise negation.

fn int_full( shape: Shape, fill_value: <B as Backend>::IntElem, device: &<B as Backend>::Device, ) -> <B as Backend>::IntTensorPrimitive

Creates a tensor filled with given value.

fn int_transpose( tensor: <B as Backend>::IntTensorPrimitive, ) -> <B as Backend>::IntTensorPrimitive

Transposes an int tensor.

fn int_narrow( tensor: <B as Backend>::IntTensorPrimitive, dim: usize, start: usize, length: usize, ) -> <B as Backend>::IntTensorPrimitive

Returns a new tensor with the given dimension narrowed to the given range.

fn int_chunk( tensor: <B as Backend>::IntTensorPrimitive, chunks: usize, dim: usize, ) -> Vec<<B as Backend>::IntTensorPrimitive>

Split the tensor along the given dimension into chunks.

fn int_split( tensor: <B as Backend>::IntTensorPrimitive, split_size: usize, dim: usize, ) -> Vec<<B as Backend>::IntTensorPrimitive>

Split the tensor along the given dimension into chunks of split_size.

fn int_split_with_sizes( tensor: <B as Backend>::IntTensorPrimitive, split_sizes: Vec<usize>, dim: usize, ) -> Vec<<B as Backend>::IntTensorPrimitive>

Split the tensor along the given dimension into chunks with sizes in dim according to split_sizes.

fn int_arange_step( range: Range<i64>, step: usize, device: &<B as Backend>::Device, ) -> <B as Backend>::IntTensorPrimitive

Creates a new tensor with values from the given range with the given step size.

fn int_arange( range: Range<i64>, device: &<B as Backend>::Device, ) -> <B as Backend>::IntTensorPrimitive

Creates a new tensor with values from the given range.

fn int_any( tensor: <B as Backend>::IntTensorPrimitive, ) -> <B as Backend>::BoolTensorPrimitive

Tests if any element in the int tensor evaluates to True.

fn int_any_dim( tensor: <B as Backend>::IntTensorPrimitive, dim: usize, ) -> <B as Backend>::BoolTensorPrimitive

Tests if any element in the int tensor evaluates to True along a given dimension dim.

fn int_all( tensor: <B as Backend>::IntTensorPrimitive, ) -> <B as Backend>::BoolTensorPrimitive

Tests if all elements in the int tensor evaluate to True.

fn int_all_dim( tensor: <B as Backend>::IntTensorPrimitive, dim: usize, ) -> <B as Backend>::BoolTensorPrimitive

Tests if all elements in the int tensor evaluate to True along a given dimension dim.

fn int_sign( tensor: <B as Backend>::IntTensorPrimitive, ) -> <B as Backend>::IntTensorPrimitive

Returns the signs of the int tensor.

fn int_sort( tensor: <B as Backend>::IntTensorPrimitive, dim: usize, descending: bool, ) -> <B as Backend>::IntTensorPrimitive

Sort the elements of the input tensor by value along a given dimension.

fn int_sort_with_indices( tensor: <B as Backend>::IntTensorPrimitive, dim: usize, descending: bool, ) -> (<B as Backend>::IntTensorPrimitive, <B as Backend>::IntTensorPrimitive)

Sort the elements of the input tensor by value along a given dimension.

fn int_argsort( tensor: <B as Backend>::IntTensorPrimitive, dim: usize, descending: bool, ) -> <B as Backend>::IntTensorPrimitive

Returns the indices that sort the elements of the input tensor by value along a given dimension.

impl<R: RunnerChannel> ModuleOps<BackendRouter<R>> for BackendRouter<R>

fn conv1d( x: FloatTensor<Self>, weight: FloatTensor<Self>, bias: Option<FloatTensor<Self>>, options: ConvOptions<1>, ) -> FloatTensor<Self>

One dimensional convolution.

fn conv2d( x: FloatTensor<Self>, weight: FloatTensor<Self>, bias: Option<FloatTensor<Self>>, options: ConvOptions<2>, ) -> FloatTensor<Self>

Two dimensional convolution.

fn conv3d( x: FloatTensor<Self>, weight: FloatTensor<Self>, bias: Option<FloatTensor<Self>>, options: ConvOptions<3>, ) -> FloatTensor<Self>

Three dimensional convolution.

fn conv_transpose1d( x: FloatTensor<Self>, weight: FloatTensor<Self>, bias: Option<FloatTensor<Self>>, options: ConvTransposeOptions<1>, ) -> FloatTensor<Self>

One dimensional transposed convolution.

fn conv_transpose2d( x: FloatTensor<Self>, weight: FloatTensor<Self>, bias: Option<FloatTensor<Self>>, options: ConvTransposeOptions<2>, ) -> FloatTensor<Self>

Two dimensional transposed convolution.

fn conv_transpose3d( x: FloatTensor<Self>, weight: FloatTensor<Self>, bias: Option<FloatTensor<Self>>, options: ConvTransposeOptions<3>, ) -> FloatTensor<Self>

Three dimensional transposed convolution.

fn avg_pool1d( x: FloatTensor<Self>, kernel_size: usize, stride: usize, padding: usize, count_include_pad: bool, ) -> FloatTensor<Self>

One dimensional avg pooling.

fn avg_pool2d( x: FloatTensor<Self>, kernel_size: [usize; 2], stride: [usize; 2], padding: [usize; 2], count_include_pad: bool, ) -> FloatTensor<Self>

Two dimensional avg pooling.

fn avg_pool1d_backward( x: FloatTensor<Self>, grad: FloatTensor<Self>, kernel_size: usize, stride: usize, padding: usize, count_include_pad: bool, ) -> FloatTensor<Self>

Backward pass for the avg pooling 1d operation.

fn avg_pool2d_backward( x: FloatTensor<Self>, grad: FloatTensor<Self>, kernel_size: [usize; 2], stride: [usize; 2], padding: [usize; 2], count_include_pad: bool, ) -> FloatTensor<Self>

Backward pass for the avg pooling 2d operation.

fn max_pool1d( x: FloatTensor<Self>, kernel_size: usize, stride: usize, padding: usize, dilation: usize, ) -> FloatTensor<Self>

One dimensional max pooling.

fn max_pool2d( x: FloatTensor<Self>, kernel_size: [usize; 2], stride: [usize; 2], padding: [usize; 2], dilation: [usize; 2], ) -> FloatTensor<Self>

Two dimensional max pooling.

fn max_pool1d_with_indices( x: FloatTensor<Self>, kernel_size: usize, stride: usize, padding: usize, dilation: usize, ) -> MaxPool1dWithIndices<Self>

One dimensional max pooling with indices.

fn max_pool2d_with_indices( x: FloatTensor<Self>, kernel_size: [usize; 2], stride: [usize; 2], padding: [usize; 2], dilation: [usize; 2], ) -> MaxPool2dWithIndices<Self>

Two dimensional max pooling with indices.

fn max_pool1d_with_indices_backward( x: FloatTensor<Self>, kernel_size: usize, stride: usize, padding: usize, dilation: usize, output_grad: FloatTensor<Self>, indices: IntTensor<Self>, ) -> MaxPool1dBackward<Self>

Backward pass for the max pooling 1d operation.

fn max_pool2d_with_indices_backward( x: FloatTensor<Self>, kernel_size: [usize; 2], stride: [usize; 2], padding: [usize; 2], dilation: [usize; 2], output_grad: FloatTensor<Self>, indices: IntTensor<Self>, ) -> MaxPool2dBackward<Self>

Backward pass for the max pooling 2d operation.

fn adaptive_avg_pool1d( x: FloatTensor<Self>, output_size: usize, ) -> FloatTensor<Self>

One dimensional adaptive avg pooling.

fn adaptive_avg_pool2d( x: FloatTensor<Self>, output_size: [usize; 2], ) -> FloatTensor<Self>

Two dimensional adaptive avg pooling.

fn adaptive_avg_pool1d_backward( x: FloatTensor<Self>, grad: FloatTensor<Self>, ) -> FloatTensor<Self>

Backward pass for the adaptive avg pooling 1d operation.

fn adaptive_avg_pool2d_backward( x: FloatTensor<Self>, grad: FloatTensor<Self>, ) -> FloatTensor<Self>

Backward pass for the adaptive avg pooling 2d operation.

fn interpolate( x: FloatTensor<Self>, output_size: [usize; 2], options: InterpolateOptions, ) -> FloatTensor<Self>

Down/up samples the input.

fn interpolate_backward( x: FloatTensor<Self>, grad: FloatTensor<Self>, output_size: [usize; 2], options: InterpolateOptions, ) -> FloatTensor<Self>

Backward pass for the interpolate operation.

fn deform_conv2d( x: FloatTensor<Self>, offset: FloatTensor<Self>, weight: FloatTensor<Self>, mask: Option<FloatTensor<Self>>, bias: Option<FloatTensor<Self>>, options: DeformConvOptions<2>, ) -> FloatTensor<Self>

Two dimensional deformable convolution.

fn deform_conv2d_backward( x: FloatTensor<Self>, offset: FloatTensor<Self>, weight: FloatTensor<Self>, mask: Option<FloatTensor<Self>>, bias: Option<FloatTensor<Self>>, output_grad: FloatTensor<Self>, options: DeformConvOptions<2>, ) -> DeformConv2dBackward<Self>

Backward pass for the deform_conv2d operation.

fn embedding( weights: <B as Backend>::FloatTensorPrimitive, indices: <B as Backend>::IntTensorPrimitive, ) -> <B as Backend>::FloatTensorPrimitive

Embedding operation.

fn embedding_backward( weights: <B as Backend>::FloatTensorPrimitive, output_grad: <B as Backend>::FloatTensorPrimitive, indices: <B as Backend>::IntTensorPrimitive, ) -> <B as Backend>::FloatTensorPrimitive

Embedding backward operation.

fn conv1d_x_backward( x: <B as Backend>::FloatTensorPrimitive, weight: <B as Backend>::FloatTensorPrimitive, output_grad: <B as Backend>::FloatTensorPrimitive, options: ConvOptions<1>, ) -> <B as Backend>::FloatTensorPrimitive

Backward pass for the conv1d operation, returning the gradient for x.

fn conv1d_weight_backward( x: <B as Backend>::FloatTensorPrimitive, weight: <B as Backend>::FloatTensorPrimitive, output_grad: <B as Backend>::FloatTensorPrimitive, options: ConvOptions<1>, ) -> <B as Backend>::FloatTensorPrimitive

Backward pass for the conv1d operation, returning the gradient for weight.

fn conv1d_bias_backward( x: <B as Backend>::FloatTensorPrimitive, bias: <B as Backend>::FloatTensorPrimitive, output_grad: <B as Backend>::FloatTensorPrimitive, ) -> <B as Backend>::FloatTensorPrimitive

Backward pass for the conv1d operation, returning the gradient for bias.

fn conv2d_x_backward( x: <B as Backend>::FloatTensorPrimitive, weight: <B as Backend>::FloatTensorPrimitive, output_grad: <B as Backend>::FloatTensorPrimitive, options: ConvOptions<2>, ) -> <B as Backend>::FloatTensorPrimitive

Backward pass for the conv2d operation, returning the gradient for x.

fn conv2d_weight_backward( x: <B as Backend>::FloatTensorPrimitive, weight: <B as Backend>::FloatTensorPrimitive, output_grad: <B as Backend>::FloatTensorPrimitive, options: ConvOptions<2>, ) -> <B as Backend>::FloatTensorPrimitive

Backward pass for the conv2d operation, returning the gradient for weight.

fn conv2d_bias_backward( x: <B as Backend>::FloatTensorPrimitive, weight: <B as Backend>::FloatTensorPrimitive, bias: <B as Backend>::FloatTensorPrimitive, output_grad: <B as Backend>::FloatTensorPrimitive, ) -> <B as Backend>::FloatTensorPrimitive

Backward pass for the conv2d operation, returning the gradient for bias.

fn conv3d_x_backward( x: <B as Backend>::FloatTensorPrimitive, weight: <B as Backend>::FloatTensorPrimitive, output_grad: <B as Backend>::FloatTensorPrimitive, options: ConvOptions<3>, ) -> <B as Backend>::FloatTensorPrimitive

Backward pass for the conv3d operation, returning the gradient for x.

fn conv3d_weight_backward( x: <B as Backend>::FloatTensorPrimitive, weight: <B as Backend>::FloatTensorPrimitive, output_grad: <B as Backend>::FloatTensorPrimitive, options: ConvOptions<3>, ) -> <B as Backend>::FloatTensorPrimitive

Backward pass for the conv3d operation, returning the gradient for weight.

fn conv3d_bias_backward( x: <B as Backend>::FloatTensorPrimitive, weight: <B as Backend>::FloatTensorPrimitive, bias: <B as Backend>::FloatTensorPrimitive, output_grad: <B as Backend>::FloatTensorPrimitive, ) -> <B as Backend>::FloatTensorPrimitive

Backward pass for the conv3d operation, returning the gradient for bias.

fn conv_transpose1d_x_backward( weight: <B as Backend>::FloatTensorPrimitive, output_grad: <B as Backend>::FloatTensorPrimitive, options: ConvTransposeOptions<1>, ) -> <B as Backend>::FloatTensorPrimitive

Backward pass for the conv transpose 1d operation, returning the gradient for x.

fn conv_transpose1d_weight_backward( x: <B as Backend>::FloatTensorPrimitive, weight: <B as Backend>::FloatTensorPrimitive, output_grad: <B as Backend>::FloatTensorPrimitive, options: ConvTransposeOptions<1>, ) -> <B as Backend>::FloatTensorPrimitive

Backward pass for the conv transpose 1d operation, returning the gradient for weight.

fn conv_transpose1d_bias_backward( x: <B as Backend>::FloatTensorPrimitive, bias: <B as Backend>::FloatTensorPrimitive, output_grad: <B as Backend>::FloatTensorPrimitive, ) -> <B as Backend>::FloatTensorPrimitive

Backward pass for the conv transpose 1d operation, returning the gradient for bias.

fn conv_transpose2d_x_backward( weight: <B as Backend>::FloatTensorPrimitive, output_grad: <B as Backend>::FloatTensorPrimitive, options: ConvTransposeOptions<2>, ) -> <B as Backend>::FloatTensorPrimitive

Backward pass for the conv transpose 2d operation, returning the gradient for x.

fn conv_transpose2d_weight_backward( x: <B as Backend>::FloatTensorPrimitive, weight: <B as Backend>::FloatTensorPrimitive, output_grad: <B as Backend>::FloatTensorPrimitive, options: ConvTransposeOptions<2>, ) -> <B as Backend>::FloatTensorPrimitive

Backward pass for the conv transpose 2d operation, returning the gradient for weight.

fn conv_transpose2d_bias_backward( x: <B as Backend>::FloatTensorPrimitive, bias: <B as Backend>::FloatTensorPrimitive, output_grad: <B as Backend>::FloatTensorPrimitive, ) -> <B as Backend>::FloatTensorPrimitive

Backward pass for the conv transpose 2d operation, returning the gradient for bias.

fn conv_transpose3d_x_backward( weight: <B as Backend>::FloatTensorPrimitive, output_grad: <B as Backend>::FloatTensorPrimitive, options: ConvTransposeOptions<3>, ) -> <B as Backend>::FloatTensorPrimitive

Backward pass for the conv transpose 3d operation, returning the gradient for x.

fn conv_transpose3d_weight_backward( x: <B as Backend>::FloatTensorPrimitive, weight: <B as Backend>::FloatTensorPrimitive, output_grad: <B as Backend>::FloatTensorPrimitive, options: ConvTransposeOptions<3>, ) -> <B as Backend>::FloatTensorPrimitive

Backward pass for the conv transpose 3d operation, returning the gradient for weight.

fn conv_transpose3d_bias_backward( x: <B as Backend>::FloatTensorPrimitive, bias: <B as Backend>::FloatTensorPrimitive, output_grad: <B as Backend>::FloatTensorPrimitive, ) -> <B as Backend>::FloatTensorPrimitive

Backward pass for the conv transpose 3d operation, returning the gradient for bias.

fn unfold4d( x: <B as Backend>::FloatTensorPrimitive, kernel_size: [usize; 2], options: UnfoldOptions, ) -> <B as Backend>::FloatTensorPrimitive

Four-dimensional unfolding.

impl<R: RunnerChannel> QTensorOps<BackendRouter<R>> for BackendRouter<R>

fn q_from_data( _data: TensorData, _device: &Device<Self>, ) -> QuantizedTensor<Self>

Creates a new tensor from the data structure.

fn quantize( _tensor: FloatTensor<Self>, _scheme: &QuantizationScheme, _qparams: QuantizationParametersPrimitive<Self>, ) -> QuantizedTensor<Self>

Convert the tensor to a lower precision data type based on the quantization scheme and parameters.

fn quantize_dynamic( _tensor: FloatTensor<Self>, _scheme: &QuantizationScheme, ) -> QuantizedTensor<Self>

Dynamically convert the tensor to a lower precision data type based on the quantization scheme.

fn dequantize(_tensor: QuantizedTensor<Self>) -> FloatTensor<Self>

Convert the tensor back to a higher precision data type.

fn q_device(_tensor: &QuantizedTensor<Self>) -> Device<Self>

Gets the device of the tensor.

fn q_to_device( _tensor: QuantizedTensor<Self>, _device: &Device<Self>, ) -> QuantizedTensor<Self>

Moves the tensor to the given device.

fn q_reshape( _tensor: QuantizedTensor<Self>, _shape: Shape, ) -> QuantizedTensor<Self>

Reshapes a tensor.

async fn q_into_data(_tensor: QuantizedTensor<Self>) -> TensorData

Converts the tensor to a data structure.

fn q_swap_dims( _tensor: QuantizedTensor<Self>, _dim1: usize, _dim2: usize, ) -> QuantizedTensor<Self>

Swaps two dimensions of a tensor.

fn q_permute( _tensor: QuantizedTensor<Self>, _axes: &[usize], ) -> QuantizedTensor<Self>

Permutes the dimensions of a tensor.

fn q_flip( _tensor: QuantizedTensor<Self>, _axes: &[usize], ) -> QuantizedTensor<Self>

Reverse the order of elements in a tensor along the given axes.

fn q_gather( _dim: usize, _tensor: QuantizedTensor<Self>, _indices: IntTensor<Self>, ) -> QuantizedTensor<Self>

Gather elements from a tensor.

fn q_select( _tensor: QuantizedTensor<Self>, _dim: usize, _indices: IntTensor<Self>, ) -> QuantizedTensor<Self>

Select tensor elements along the given dimension corresponding for the given indices.

fn q_slice( _tensor: QuantizedTensor<Self>, _ranges: &[Range<usize>], ) -> QuantizedTensor<Self>

Select tensor elements corresponding for the given ranges.

fn q_expand( _tensor: QuantizedTensor<Self>, _shape: Shape, ) -> QuantizedTensor<Self>

Broadcasts the tensor to the given shape.

fn q_detach( tensor: <B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::QuantizedTensorPrimitive

Detaches a tensor from the computation graph.

fn q_set_require_grad( tensor: <B as Backend>::QuantizedTensorPrimitive, _require_grad: bool, ) -> <B as Backend>::QuantizedTensorPrimitive

Sets the require_grad flag of a tensor.

fn q_is_require_grad(_tensor: &<B as Backend>::QuantizedTensorPrimitive) -> bool

Returns the require_grad flag of a tensor.

fn q_repeat_dim( tensor: <B as Backend>::QuantizedTensorPrimitive, dim: usize, times: usize, ) -> <B as Backend>::QuantizedTensorPrimitive

Repeat the tensor along the given dimension.

fn q_add( lhs: <B as Backend>::QuantizedTensorPrimitive, rhs: <B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::QuantizedTensorPrimitive

Adds two tensors together.

fn q_add_scalar( lhs: <B as Backend>::QuantizedTensorPrimitive, rhs: <B as Backend>::FloatElem, ) -> <B as Backend>::QuantizedTensorPrimitive

Adds a scalar to a tensor.

fn q_clamp_min( tensor: <B as Backend>::QuantizedTensorPrimitive, min: <B as Backend>::FloatElem, ) -> <B as Backend>::QuantizedTensorPrimitive

Clamps a tensor under a minimum value.

fn q_clamp_max( tensor: <B as Backend>::QuantizedTensorPrimitive, max: <B as Backend>::FloatElem, ) -> <B as Backend>::QuantizedTensorPrimitive

Clamps a tensor over a maximum value.

fn q_clamp( tensor: <B as Backend>::QuantizedTensorPrimitive, min: <B as Backend>::FloatElem, max: <B as Backend>::FloatElem, ) -> <B as Backend>::QuantizedTensorPrimitive

Clamps a tensor between a minimum and maximum value.

fn q_sub( lhs: <B as Backend>::QuantizedTensorPrimitive, rhs: <B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::QuantizedTensorPrimitive

Subtracts two tensors.

fn q_sub_scalar( lhs: <B as Backend>::QuantizedTensorPrimitive, rhs: <B as Backend>::FloatElem, ) -> <B as Backend>::QuantizedTensorPrimitive

Subtracts a scalar from a tensor.

fn q_mul( lhs: <B as Backend>::QuantizedTensorPrimitive, rhs: <B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::QuantizedTensorPrimitive

Multiplies two tensors together element-wise.

fn q_mul_scalar( lhs: <B as Backend>::QuantizedTensorPrimitive, rhs: <B as Backend>::FloatElem, ) -> <B as Backend>::QuantizedTensorPrimitive

Multiplies a tensor by a scalar.

fn q_div( lhs: <B as Backend>::QuantizedTensorPrimitive, rhs: <B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::QuantizedTensorPrimitive

Divides two tensors element-wise.

fn q_div_scalar( lhs: <B as Backend>::QuantizedTensorPrimitive, rhs: <B as Backend>::FloatElem, ) -> <B as Backend>::QuantizedTensorPrimitive

Divides a tensor by a scalar.

fn q_remainder( lhs: <B as Backend>::QuantizedTensorPrimitive, rhs: <B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::QuantizedTensorPrimitive

Computes the remainder of division between two tensors element-wise.

fn q_remainder_scalar( lhs: <B as Backend>::QuantizedTensorPrimitive, rhs: <B as Backend>::FloatElem, ) -> <B as Backend>::QuantizedTensorPrimitive

Computes the modulus of a tensor given a scalar.

fn q_matmul( lhs: <B as Backend>::QuantizedTensorPrimitive, rhs: <B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::QuantizedTensorPrimitive

Multiplies two tensors together using matrix multiplication.

fn q_neg( tensor: <B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::QuantizedTensorPrimitive

Negates a tensor element-wise.

fn q_recip( tensor: <B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::QuantizedTensorPrimitive

Calculates the reciprocals element-wise

fn q_transpose( tensor: <B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::QuantizedTensorPrimitive

Transposes a tensor.

fn q_scatter( dim: usize, tensor: <B as Backend>::QuantizedTensorPrimitive, indices: <B as Backend>::IntTensorPrimitive, value: <B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::QuantizedTensorPrimitive

Scatter elements into a tensor.

fn q_select_assign( tensor: <B as Backend>::QuantizedTensorPrimitive, dim: usize, indices: <B as Backend>::IntTensorPrimitive, value: <B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::QuantizedTensorPrimitive

Assign the selected elements along the given dimension corresponding for the given indices to the given value.

fn q_slice_assign( tensor: <B as Backend>::QuantizedTensorPrimitive, ranges: &[Range<usize>], value: <B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::QuantizedTensorPrimitive

Assign the selected elements corresponding for the given ranges to the given value.

fn q_mask_where( tensor: <B as Backend>::QuantizedTensorPrimitive, mask: <B as Backend>::BoolTensorPrimitive, value: <B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::QuantizedTensorPrimitive

Update the given tensor with the value tensor where the mask is true.

fn q_mask_fill( tensor: <B as Backend>::QuantizedTensorPrimitive, mask: <B as Backend>::BoolTensorPrimitive, value: <B as Backend>::FloatElem, ) -> <B as Backend>::QuantizedTensorPrimitive

Update the given tensor with the value where the mask is true.

fn q_sum( tensor: <B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::QuantizedTensorPrimitive

Sum of all elements in a tensor.

fn q_sum_dim( tensor: <B as Backend>::QuantizedTensorPrimitive, dim: usize, ) -> <B as Backend>::QuantizedTensorPrimitive

Sum of all elements in a tensor along a dimension.

fn q_prod( tensor: <B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::QuantizedTensorPrimitive

Product of all elements in a tensor.

fn q_prod_dim( tensor: <B as Backend>::QuantizedTensorPrimitive, dim: usize, ) -> <B as Backend>::QuantizedTensorPrimitive

Product of all elements in a tensor along a dimension.

fn q_mean( tensor: <B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::QuantizedTensorPrimitive

Mean of all elements in a tensor.

fn q_mean_dim( tensor: <B as Backend>::QuantizedTensorPrimitive, dim: usize, ) -> <B as Backend>::QuantizedTensorPrimitive

Mean of all elements in a tensor along a dimension.

fn q_exp( tensor: <B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::QuantizedTensorPrimitive

Returns a new tensor with exponential values.

fn q_log( tensor: <B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::QuantizedTensorPrimitive

Returns a new tensor with natural logarithm values.

fn q_log1p( tensor: <B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::QuantizedTensorPrimitive

Returns a new tensor with logarithm values of (1 + Xi).

fn q_powf( lhs: <B as Backend>::QuantizedTensorPrimitive, rhs: <B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::QuantizedTensorPrimitive

Element-wise power with another tensor.

fn q_powi( lhs: <B as Backend>::QuantizedTensorPrimitive, rhs: <B as Backend>::IntTensorPrimitive, ) -> <B as Backend>::QuantizedTensorPrimitive

Element-wise power with an IntTensor.

fn q_powi_scalar( lhs: <B as Backend>::QuantizedTensorPrimitive, rhs: <B as Backend>::IntElem, ) -> <B as Backend>::QuantizedTensorPrimitive

Element-wise power with an int scalar.

fn q_powf_scalar( tensor: <B as Backend>::QuantizedTensorPrimitive, value: f32, ) -> <B as Backend>::QuantizedTensorPrimitive

Element-wise power with a float scalar.

fn q_sqrt( tensor: <B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::QuantizedTensorPrimitive

Returns a new tensor with square root values.

fn q_abs( tensor: <B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::QuantizedTensorPrimitive

Returns a new tensor with absolute values.

fn q_cos( tensor: <B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::QuantizedTensorPrimitive

Returns a new tensor with cosine values.

fn q_sin( tensor: <B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::QuantizedTensorPrimitive

Returns a new tensor with sine values.

fn q_tan( tensor: <B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::QuantizedTensorPrimitive

Returns a new tensor with tangent values.

fn q_cosh( tensor: <B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::QuantizedTensorPrimitive

Returns a new tensor with hyperbolic cosine values.

fn q_sinh( tensor: <B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::QuantizedTensorPrimitive

Returns a new tensor with hyperbolic sine values.

fn q_tanh( tensor: <B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::QuantizedTensorPrimitive

Returns a new tensor with hyperbolic tangent values.

fn q_erf( tensor: <B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::QuantizedTensorPrimitive

Returns a new tensor with the error function values.

fn q_cat( tensors: Vec<<B as Backend>::QuantizedTensorPrimitive>, dim: usize, ) -> <B as Backend>::QuantizedTensorPrimitive

Concatenates tensors along a dimension.

fn q_argmax( tensor: <B as Backend>::QuantizedTensorPrimitive, dim: usize, ) -> <B as Backend>::IntTensorPrimitive

Gets the indices of the maximum elements of a tensor along an axis.

fn q_argmin( tensor: <B as Backend>::QuantizedTensorPrimitive, dim: usize, ) -> <B as Backend>::IntTensorPrimitive

Gets the indices of the minimum elements of a tensor along an axis.

fn q_max( tensor: <B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::QuantizedTensorPrimitive

Gets the maximum element of a tensor.

fn q_max_dim( tensor: <B as Backend>::QuantizedTensorPrimitive, dim: usize, ) -> <B as Backend>::QuantizedTensorPrimitive

Gets the maximum elements of a tensor along an axis.

fn q_max_dim_with_indices( tensor: <B as Backend>::QuantizedTensorPrimitive, dim: usize, ) -> (<B as Backend>::QuantizedTensorPrimitive, <B as Backend>::IntTensorPrimitive)

Gets the maximum elements of a tensor along an axis and their indices.

fn q_min( tensor: <B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::QuantizedTensorPrimitive

Gets the minimum element of a tensor.

fn q_min_dim( tensor: <B as Backend>::QuantizedTensorPrimitive, dim: usize, ) -> <B as Backend>::QuantizedTensorPrimitive

Gets the minimum elements of a tensor along an axis.

fn q_min_dim_with_indices( tensor: <B as Backend>::QuantizedTensorPrimitive, dim: usize, ) -> (<B as Backend>::QuantizedTensorPrimitive, <B as Backend>::IntTensorPrimitive)

Gets the minimum elements of a tensor along an axis and their indices.

fn q_max_abs( tensor: <B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::QuantizedTensorPrimitive

Gets the maximum element of a tensor.

fn q_max_abs_dim( tensor: <B as Backend>::QuantizedTensorPrimitive, dim: usize, ) -> <B as Backend>::QuantizedTensorPrimitive

Gets the maximum elements of a tensor along an axis.

fn q_narrow( tensor: <B as Backend>::QuantizedTensorPrimitive, dim: usize, start: usize, length: usize, ) -> <B as Backend>::QuantizedTensorPrimitive

Returns a new tensor with the given dimension narrowed to the given range.

fn q_chunk( tensor: <B as Backend>::QuantizedTensorPrimitive, chunks: usize, dim: usize, ) -> Vec<<B as Backend>::QuantizedTensorPrimitive>

Split the tensor along the given dimension into chunks.

fn q_split( tensor: <B as Backend>::QuantizedTensorPrimitive, split_size: usize, dim: usize, ) -> Vec<<B as Backend>::QuantizedTensorPrimitive>

Split the tensor along the given dimension into chunks of split_size.

fn q_split_with_sizes( tensor: <B as Backend>::QuantizedTensorPrimitive, split_sizes: Vec<usize>, dim: usize, ) -> Vec<<B as Backend>::QuantizedTensorPrimitive>

Split the tensor along the given dimension into chunks with sizes in dim according to split_sizes.

fn q_any( tensor: <B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::BoolTensorPrimitive

Tests if any element in the tensor evaluates to True.

fn q_any_dim( tensor: <B as Backend>::QuantizedTensorPrimitive, dim: usize, ) -> <B as Backend>::BoolTensorPrimitive

Tests if any element in the float tensor evaluates to True along a given dimension dim.

fn q_all( tensor: <B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::BoolTensorPrimitive

Tests if all elements in the tensor evaluate to True.

fn q_all_dim( tensor: <B as Backend>::QuantizedTensorPrimitive, dim: usize, ) -> <B as Backend>::BoolTensorPrimitive

Tests if all elements in the tensor evaluate to True along a given dimension dim.

fn q_sort( tensor: <B as Backend>::QuantizedTensorPrimitive, dim: usize, descending: bool, ) -> <B as Backend>::QuantizedTensorPrimitive

Sort the elements of the input tensor by value in along a given dimension.

fn q_sort_with_indices( tensor: <B as Backend>::QuantizedTensorPrimitive, dim: usize, descending: bool, ) -> (<B as Backend>::QuantizedTensorPrimitive, <B as Backend>::IntTensorPrimitive)

Sort the elements of the input tensor by value in along a given dimension.

fn q_argsort( tensor: <B as Backend>::QuantizedTensorPrimitive, dim: usize, descending: bool, ) -> <B as Backend>::IntTensorPrimitive

Returns the indices that sort the elements of the input tensor by value along a given dimension.

impl<R: RunnerChannel> TransactionOps<BackendRouter<R>> for BackendRouter<R>

fn tr_execute( transaction: TransactionPrimitive<B>, ) -> impl Future<Output = TransactionPrimitiveResult> + Send + 'static

Executes a transaction and return its result.