Struct LibTorch 

pub struct LibTorch<E = f32> { /* private fields */ }

Tensor backend that uses LibTorch with the tch crate for executing tensor operations.

This backend is compatible with a wide range of hardwares ranging from CPUs to GPUs, but requires LibTorch to be installed correctly. The CPU version can be downloaded automatically and the CUDA version as well by setting the TORCH_CUDA_VERSION environment variable. For more complex configurations, check out the manual installation for burn-tch.

Refer to the tch crate for more information.

Trait Implementations

impl<E: TchElement> ActivationOps<LibTorch<E>> for LibTorch<E>

fn relu(tensor: TchTensor) -> TchTensor

Applies the ReLU activation function.

fn gelu(tensor: TchTensor) -> TchTensor

Applies the Gelu activation function.

fn gelu_backward(tensor: TchTensor, grad: TchTensor) -> TchTensor

Applies the Gelu activation function backward.

fn sigmoid(tensor: TchTensor) -> TchTensor

Applies the Sigmoid activation function.

fn log_sigmoid(tensor: TchTensor) -> TchTensor

Applies the LogSigmoid activation function.

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

Applies the ReLU activation function backward.

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

Applies the PReLu 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_backward( x: <B as Backend>::FloatTensorPrimitive, grad: <B as Backend>::FloatTensorPrimitive, ) -> <B as Backend>::FloatTensorPrimitive

Applies the LogSigmoid activation function backward.

impl<E: TchElement> Backend for LibTorch<E>

type Device = LibTorchDevice

Device type.

type FloatTensorPrimitive = TchTensor

Tensor primitive to be used for all float operations.

type FloatElem = E

Default float element type.

type IntTensorPrimitive = TchTensor

Tensor primitive to be used for all int operations.

type IntElem = i64

Int element type.

type BoolTensorPrimitive = TchTensor

Tensor primitive to be used for all bool operations.

type BoolElem = bool

Tensor primitive to be used for all bool operations.

type QuantizedTensorPrimitive = TchTensor

Tensor primitive to be used for all quantized operations.

fn seed(_device: &Self::Device, seed: u64)

Seeds the backend on the specified device.

fn ad_enabled() -> bool

If autodiff is enabled.

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

Name of the backend.

fn sync(device: &Self::Device)

Sync the backend, ensure that all computation are finished.

fn memory_persistent_allocations<Output, Input, Func>( device: &Self::Device, input: Input, func: Func, ) -> Output

where Func: Fn(Input) -> Output,

Sets the current allocation mode to persistent.

fn memory_cleanup(device: &Self::Device)

Manually triggers a memory cleanup on the given device.

impl<E: TchElement> BoolTensorOps<LibTorch<E>> for LibTorch<E>

fn bool_from_data(data: TensorData, device: &LibTorchDevice) -> TchTensor

Creates a tensor from the data structure.

fn bool_repeat_dim(tensor: TchTensor, dim: usize, times: usize) -> TchTensor

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

async fn bool_into_data(tensor: TchTensor) -> TensorData

Converts the tensor to a data structure.

fn bool_to_device(tensor: TchTensor, device: &LibTorchDevice) -> TchTensor

Moves the tensor to the device.

fn bool_reshape(tensor: TchTensor, shape: Shape) -> TchTensor

Reshapes the tensor.

fn bool_device(tensor: &TchTensor) -> LibTorchDevice

Gets the device of the tensor.

fn bool_empty( shape: Shape, device: &<LibTorch<E> as Backend>::Device, ) -> TchTensor

Creates a new bool tensor.

fn bool_zeros( shape: Shape, device: &<LibTorch<E> as Backend>::Device, ) -> TchTensor

Creates a new bool tensor filled false.

fn bool_ones( shape: Shape, device: &<LibTorch<E> as Backend>::Device, ) -> TchTensor

Creates a new bool tensor filled true.

fn bool_slice(tensor: TchTensor, slices: &[Slice]) -> TchTensor

Gets the values from the tensor for the given ranges.

fn bool_slice_assign( tensor: TchTensor, slices: &[Slice], value: TchTensor, ) -> TchTensor

Sets the values in the tensor for the given ranges.

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

Concatenates the tensors along the given dimension.

fn bool_equal(lhs: TchTensor, rhs: TchTensor) -> TchTensor

Equates the two tensors.

fn bool_not(tensor: TchTensor) -> TchTensor

Inverses boolean values.

fn bool_and(lhs: TchTensor, rhs: TchTensor) -> TchTensor

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

fn bool_or(lhs: TchTensor, rhs: TchTensor) -> TchTensor

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

fn bool_into_int(tensor: TchTensor) -> TchTensor

Converts bool tensor to int tensor.

fn bool_into_float(tensor: TchTensor) -> TchTensor

Converts bool tensor to float tensor.

fn bool_swap_dims(tensor: TchTensor, dim1: usize, dim2: usize) -> TchTensor

Swaps two dimensions of a bool tensor.

fn bool_permute(tensor: TchTensor, axes: &[usize]) -> TchTensor

Permutes the dimensions of a tensor.

fn bool_flip(tensor: TchTensor, axes: &[usize]) -> TchTensor

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

async fn bool_argwhere(tensor: TchTensor) -> TchTensor

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

fn bool_select(tensor: TchTensor, dim: usize, indices: TchTensor) -> TchTensor

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

fn bool_select_assign( tensor: TchTensor, dim: usize, indices: TchTensor, value: TchTensor, ) -> TchTensor

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

fn bool_expand(tensor: TchTensor, shape: Shape) -> TchTensor

Broadcasts the bool tensor to the given shape.

fn bool_unfold( tensor: IntTensor<Self>, dim: usize, size: usize, step: usize, ) -> IntTensor<Self>

Unfold windows along a 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_xor( lhs: <B as Backend>::BoolTensorPrimitive, rhs: <B as Backend>::BoolTensorPrimitive, ) -> <B as Backend>::BoolTensorPrimitive

Element-wise exclusive or.

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

Transposes a bool tensor.

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.

impl<E: Clone> Clone for LibTorch<E>

fn clone(&self) -> LibTorch<E>

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<E: Debug> Debug for LibTorch<E>

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

Formats the value using the given formatter.

impl<E: Default> Default for LibTorch<E>

fn default() -> LibTorch<E>

Returns the “default value” for a type.

impl<E: TchElement> FloatTensorOps<LibTorch<E>> for LibTorch<E>

fn float_from_data(data: TensorData, device: &LibTorchDevice) -> TchTensor

Creates a new tensor from the data structure.

fn float_random( shape: Shape, distribution: Distribution, device: &LibTorchDevice, ) -> TchTensor

Creates a new tensor with random values.

fn float_repeat_dim(tensor: TchTensor, dim: usize, times: usize) -> TchTensor

Repeat the tensor along the given dimension.

fn float_zeros( shape: Shape, device: &LibTorchDevice, dtype: FloatDType, ) -> TchTensor

Creates a new tensor with zeros.

fn float_ones( shape: Shape, device: &LibTorchDevice, dtype: FloatDType, ) -> TchTensor

Creates a new tensor with ones.

async fn float_into_data(tensor: TchTensor) -> TensorData

Converts the tensor to a data structure.

fn float_device(tensor: &TchTensor) -> LibTorchDevice

Gets the device of the tensor.

fn float_to_device(tensor: TchTensor, device: &LibTorchDevice) -> TchTensor

Moves the tensor to the given device.

fn float_empty( shape: Shape, device: &<LibTorch<E> as Backend>::Device, dtype: FloatDType, ) -> TchTensor

Creates an empty tensor with the given shape.

fn float_add(lhs: TchTensor, rhs: TchTensor) -> TchTensor

Adds two tensors together.

fn float_add_scalar(lhs: TchTensor, rhs: E) -> TchTensor

Adds a scalar to a tensor.

fn float_sub(lhs: TchTensor, rhs: TchTensor) -> TchTensor

Subtracts two tensors.

fn float_sub_scalar(lhs: TchTensor, rhs: E) -> TchTensor

Subtracts a scalar from a tensor.

fn float_mul(lhs: TchTensor, rhs: TchTensor) -> TchTensor

Multiplies two tensors together element-wise.

fn float_mul_scalar(lhs: TchTensor, rhs: E) -> TchTensor

Multiplies a tensor by a scalar.

fn float_div(lhs: TchTensor, rhs: TchTensor) -> TchTensor

Divides two tensors element-wise.

fn float_div_scalar(lhs: TchTensor, rhs: E) -> TchTensor

Divides a tensor by a scalar.

fn float_remainder(lhs: TchTensor, rhs: TchTensor) -> TchTensor

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

fn float_remainder_scalar(lhs: TchTensor, rhs: E) -> TchTensor

Computes the modulus of a tensor given a scalar.

fn float_matmul(lhs: TchTensor, rhs: TchTensor) -> TchTensor

Multiplies two tensors together using matrix multiplication.

fn float_cross(lhs: TchTensor, rhs: TchTensor, dim: usize) -> TchTensor

Computes the cross product of two tensors along a given dimension.

fn float_neg(tensor: TchTensor) -> TchTensor

Negates a tensor element-wise.

fn float_recip(tensor: TchTensor) -> TchTensor

Calculates the reciprocals element-wise

fn float_swap_dims(tensor: TchTensor, dim1: usize, dim2: usize) -> TchTensor

Swaps two dimensions of a tensor.

fn float_reshape(tensor: TchTensor, shape: Shape) -> TchTensor

Reshapes a tensor.

fn float_gather(dim: usize, tensor: TchTensor, indices: TchTensor) -> TchTensor

Gather elements from a tensor.

fn float_scatter( dim: usize, tensor: TchTensor, indices: TchTensor, value: TchTensor, ) -> TchTensor

Scatter elements into a tensor.

fn float_select(tensor: TchTensor, dim: usize, indices: TchTensor) -> TchTensor

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

fn float_select_assign( tensor: TchTensor, dim: usize, indices: TchTensor, value: TchTensor, ) -> TchTensor

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

fn float_slice(tensor: TchTensor, slices: &[Slice]) -> TchTensor

Select tensor elements corresponding to the given slices.

fn float_slice_assign( tensor: TchTensor, slices: &[Slice], value: TchTensor, ) -> TchTensor

Assign the selected elements corresponding to the given slices to the given value.

fn float_mask_where( tensor: TchTensor, mask: TchTensor, value: TchTensor, ) -> TchTensor

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

fn float_mask_fill(tensor: TchTensor, mask: TchTensor, value: E) -> TchTensor

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

fn float_equal(lhs: TchTensor, rhs: TchTensor) -> TchTensor

Equal comparison of two tensors.

fn float_equal_elem(lhs: TchTensor, rhs: E) -> TchTensor

Equal comparison of a tensor and a scalar.

fn float_greater(lhs: TchTensor, rhs: TchTensor) -> TchTensor

Greater than comparison of two tensors.

fn float_greater_elem(lhs: TchTensor, rhs: E) -> TchTensor

Greater than comparison of a tensor and a scalar.

fn float_greater_equal(lhs: TchTensor, rhs: TchTensor) -> TchTensor

Greater than or equal comparison of two tensors.

fn float_greater_equal_elem(lhs: TchTensor, rhs: E) -> TchTensor

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

fn float_lower(lhs: TchTensor, rhs: TchTensor) -> TchTensor

Less than comparison of two tensors.

fn float_lower_elem(lhs: TchTensor, rhs: E) -> TchTensor

Less than comparison of a tensor and a scalar.

fn float_lower_equal(lhs: TchTensor, rhs: TchTensor) -> TchTensor

Less than or equal comparison of two tensors.

fn float_lower_equal_elem(lhs: TchTensor, rhs: E) -> TchTensor

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

fn float_mean(tensor: TchTensor) -> TchTensor

Mean of all elements in a tensor.

fn float_sum(tensor: TchTensor) -> TchTensor

Sum of all elements in a tensor.

fn float_sum_dim(tensor: TchTensor, dim: usize) -> TchTensor

Sum of all elements in a tensor along a dimension.

fn float_mean_dim(tensor: TchTensor, dim: usize) -> TchTensor

Mean of all elements in a tensor along a dimension.

fn float_cumsum(tensor: TchTensor, dim: usize) -> TchTensor

Computes the cumulative sum of elements along a dimension.

fn float_cumprod(tensor: TchTensor, dim: usize) -> TchTensor

Computes the cumulative product of elements along a dimension.

fn float_cummin(tensor: TchTensor, dim: usize) -> TchTensor

Computes the cumulative minimum of elements along a dimension.

fn float_cummax(tensor: TchTensor, dim: usize) -> TchTensor

Computes the cumulative maximum of elements along a dimension.

fn float_prod(tensor: TchTensor) -> TchTensor

Product of all elements in a tensor.

fn float_prod_dim(tensor: TchTensor, dim: usize) -> TchTensor

Product of all elements in a tensor along a dimension.

fn float_argmax(tensor: TchTensor, dim: usize) -> TchTensor

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

fn float_argmin(tensor: TchTensor, dim: usize) -> TchTensor

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

fn float_max_dim(tensor: TchTensor, dim: usize) -> TchTensor

Gets the maximum elements of a tensor along an axis.

fn float_max_dim_with_indices( tensor: TchTensor, dim: usize, ) -> (TchTensor, TchTensor)

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

fn float_min_dim(tensor: TchTensor, dim: usize) -> TchTensor

Gets the minimum elements of a tensor along an axis.

fn float_min_dim_with_indices( tensor: TchTensor, dim: usize, ) -> (TchTensor, TchTensor)

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

fn float_exp(tensor: TchTensor) -> TchTensor

Returns a new tensor with exponential values.

fn float_log(tensor: TchTensor) -> TchTensor

Returns a new tensor with natural logarithm values.

fn float_log1p(tensor: TchTensor) -> TchTensor

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

fn float_powf_scalar_impl(tensor: TchTensor, value: f32) -> TchTensor

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

fn float_sqrt(tensor: TchTensor) -> TchTensor

Returns a new tensor with square root values.

fn float_abs(tensor: TchTensor) -> TchTensor

Returns a new tensor with absolute values.

fn float_cos(tensor: TchTensor) -> TchTensor

Returns a new tensor with cosine values.

fn float_sin(tensor: TchTensor) -> TchTensor

Returns a new tensor with sine values.

fn float_tanh(tensor: TchTensor) -> TchTensor

Returns a new tensor with hyperbolic tangent values.

fn float_round(tensor: TchTensor) -> TchTensor

Returns a new tensor with rounded values.

fn float_floor(tensor: TchTensor) -> TchTensor

Returns a new tensor with floored values.

fn float_ceil(tensor: TchTensor) -> TchTensor

Returns a new tensor with ceiled values.

fn float_trunc(tensor: TchTensor) -> TchTensor

Returns a new tensor with truncated values.

fn float_erf(tensor: TchTensor) -> TchTensor

Returns a new tensor with the error function values.

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

Concatenates tensors along a dimension.

fn float_clamp_min(tensor: TchTensor, min: E) -> TchTensor

Clamps a tensor under a minimum value.

fn float_clamp_max( tensor: TchTensor, max: <LibTorch<E> as Backend>::FloatElem, ) -> TchTensor

Clamps a tensor over a maximum value.

fn float_clamp( tensor: TchTensor, min: <LibTorch<E> as Backend>::FloatElem, max: <LibTorch<E> as Backend>::FloatElem, ) -> TchTensor

Clamps a tensor between a minimum and maximum value.

fn float_into_int(tensor: TchTensor) -> TchTensor

Converts float tensor to int tensor.

fn float_powf(lhs: TchTensor, rhs: TchTensor) -> TchTensor

Element-wise power with a FloatTensor.

fn float_permute(tensor: TchTensor, axes: &[usize]) -> TchTensor

Permutes the dimensions of a tensor.

fn float_flip(tensor: TchTensor, axes: &[usize]) -> TchTensor

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

fn float_sign(tensor: TchTensor) -> TchTensor

Returns the signs of the float tensor.

fn float_expand(tensor: TchTensor, shape: Shape) -> TchTensor

Broadcasts the float tensor to the given shape.

fn float_sort(tensor: TchTensor, dim: usize, descending: bool) -> TchTensor

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

fn float_sort_with_indices( tensor: TchTensor, dim: usize, descending: bool, ) -> (TchTensor, TchTensor)

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

fn float_argsort( tensor: TchTensor, dim: usize, descending: bool, ) -> IntTensor<Self>

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

fn float_cast(tensor: TchTensor, dtype: FloatDType) -> TchTensor

Converts a tensor to another floating point data type.

fn float_unfold( tensor: FloatTensor<Self>, dim: usize, size: usize, step: usize, ) -> FloatTensor<Self>

Unfold windows along a dimension.

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

Returns a new tensor with boolean elements indicating whether each element of the input is NaN.

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

Returns a new tensor with boolean elements indicating whether each element of the input is infinite (either +INF or -INF).

fn float_full( shape: Shape, fill_value: <B as Backend>::FloatElem, device: &<B as Backend>::Device, dtype: FloatDType, ) -> <B as Backend>::FloatTensorPrimitive

Creates a tensor filled with given value.

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_powi_scalar_impl( 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_powf_scalar( tensor: <B as Backend>::FloatTensorPrimitive, value: f32, ) -> <B as Backend>::FloatTensorPrimitive

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

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

Gets the maximum element of a tensor.

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

Gets the minimum element of a tensor.

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_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_grid_sample_2d( tensor: <B as Backend>::FloatTensorPrimitive, grid: <B as Backend>::FloatTensorPrimitive, method: InterpolateMode, ) -> <B as Backend>::FloatTensorPrimitive

Samples tensor as a two-dimensional spatial grid of (possibly multi-channel) values, using the given locations in [-1, 1].

impl<E: TchElement> IntTensorOps<LibTorch<E>> for LibTorch<E>

fn int_from_data(data: TensorData, device: &LibTorchDevice) -> TchTensor

Creates a tensor from the data structure.

fn int_repeat_dim(tensor: TchTensor, dim: usize, times: usize) -> TchTensor

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

async fn int_into_data(tensor: TchTensor) -> TensorData

Converts the tensor to a data structure.

fn int_to_device(tensor: TchTensor, device: &LibTorchDevice) -> TchTensor

Moves the tensor to the given device.

fn int_reshape(tensor: TchTensor, shape: Shape) -> TchTensor

Reshapes the tensor.

fn int_device(tensor: &TchTensor) -> LibTorchDevice

Gets the device of the tensor.

fn int_empty( shape: Shape, device: &<LibTorch<E> as Backend>::Device, dtype: IntDType, ) -> TchTensor

Creates a new int tensor.

fn int_slice(tensor: TchTensor, slices: &[Slice]) -> TchTensor

Gets the element at the given indices.

fn int_slice_assign( tensor: TchTensor, slices: &[Slice], value: TchTensor, ) -> TchTensor

Sets the values in the tensor for the given ranges.

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

Concatenates the given tensors along the given dimension.

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

Multiplies two tensors together using matrix multiplication.

fn int_equal(lhs: TchTensor, rhs: TchTensor) -> TchTensor

Element-wise equality comparison.

fn int_equal_elem(lhs: TchTensor, rhs: i64) -> TchTensor

Element-wise equality comparison with a scalar.

fn int_greater(lhs: TchTensor, rhs: TchTensor) -> TchTensor

Element-wise greater than comparison.

fn int_greater_elem(lhs: TchTensor, rhs: i64) -> TchTensor

Element-wise greater than comparison with a scalar.

fn int_greater_equal(lhs: TchTensor, rhs: TchTensor) -> TchTensor

Element-wise greater than or equal comparison.

fn int_greater_equal_elem(lhs: TchTensor, rhs: i64) -> TchTensor

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

fn int_lower(lhs: TchTensor, rhs: TchTensor) -> TchTensor

Element-wise less than comparison.

fn int_lower_elem(lhs: TchTensor, rhs: i64) -> TchTensor

Element-wise less than comparison with a scalar.

fn int_lower_equal(lhs: TchTensor, rhs: TchTensor) -> TchTensor

Element-wise less than or equal comparison.

fn int_lower_equal_elem(lhs: TchTensor, rhs: i64) -> TchTensor

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

fn int_add(lhs: TchTensor, rhs: TchTensor) -> TchTensor

Element-wise addition.

fn int_add_scalar(lhs: TchTensor, rhs: i64) -> TchTensor

Element-wise addition with a scalar.

fn int_sub(lhs: TchTensor, rhs: TchTensor) -> TchTensor

Element-wise subtraction.

fn int_sub_scalar(lhs: TchTensor, rhs: i64) -> TchTensor

Element-wise subtraction with a scalar.

fn int_mul(lhs: TchTensor, rhs: TchTensor) -> TchTensor

Element-wise multiplication.

fn int_mul_scalar(lhs: TchTensor, rhs: i64) -> TchTensor

Element-wise multiplication with a scalar.

fn int_div(lhs: TchTensor, rhs: TchTensor) -> TchTensor

Element-wise division.

fn int_div_scalar(lhs: TchTensor, rhs: i64) -> TchTensor

Element-wise division with a scalar.

fn int_remainder(lhs: TchTensor, rhs: TchTensor) -> TchTensor

Element-wise modulus.

fn int_remainder_scalar(lhs: TchTensor, rhs: i64) -> TchTensor

Element-wise modulus with a scalar.

fn int_neg(tensor: TchTensor) -> TchTensor

Element-wise negation.

fn int_zeros( shape: Shape, device: &<LibTorch<E> as Backend>::Device, dtype: IntDType, ) -> TchTensor

Creates a tensor of zeros.

fn int_ones( shape: Shape, device: &<LibTorch<E> as Backend>::Device, dtype: IntDType, ) -> TchTensor

Creates a tensor of ones.

fn int_full( shape: Shape, fill_value: i64, device: &<LibTorch<E> as Backend>::Device, dtype: IntDType, ) -> TchTensor

Creates a tensor filled with given value.

fn int_sum(tensor: TchTensor) -> TchTensor

Sums all elements in the tensor.

fn int_sum_dim(tensor: TchTensor, dim: usize) -> TchTensor

Sums all elements in the tensor along a dimension.

fn int_prod(tensor: TchTensor) -> TchTensor

Computes the product of all elements in the tensor.

fn int_prod_dim(tensor: TchTensor, dim: usize) -> TchTensor

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

fn int_mean(tensor: TchTensor) -> TchTensor

Computes the mean of all elements in the tensor.

fn int_mean_dim(tensor: TchTensor, dim: usize) -> TchTensor

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

fn int_cumsum(tensor: TchTensor, dim: usize) -> TchTensor

Computes the cumulative sum of elements along a dimension.

fn int_cumprod(tensor: TchTensor, dim: usize) -> TchTensor

Computes the cumulative product of elements along a dimension.

fn int_cummin(tensor: TchTensor, dim: usize) -> TchTensor

Computes the cumulative minimum of elements along a dimension.

fn int_cummax(tensor: TchTensor, dim: usize) -> TchTensor

Computes the cumulative maximum of elements along a dimension.

fn int_gather(dim: usize, tensor: TchTensor, indices: TchTensor) -> TchTensor

Gather elements from the tensor at the given indices.

fn int_scatter( dim: usize, tensor: TchTensor, indices: TchTensor, value: TchTensor, ) -> TchTensor

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

fn int_select(tensor: TchTensor, dim: usize, indices: TchTensor) -> TchTensor

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

fn int_select_assign( tensor: TchTensor, dim: usize, indices: TchTensor, value: TchTensor, ) -> TchTensor

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

fn int_mask_where( tensor: TchTensor, mask: TchTensor, source: TchTensor, ) -> TchTensor

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

fn int_mask_fill(tensor: TchTensor, mask: TchTensor, value: i64) -> TchTensor

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

fn int_argmax(tensor: TchTensor, dim: usize) -> TchTensor

Gets the indices of the maximum elements along a dimension.

fn int_argmin(tensor: TchTensor, dim: usize) -> TchTensor

Gets the indices of the minimum elements along a dimension.

fn int_max_dim(tensor: TchTensor, dim: usize) -> TchTensor

Gets the maximum element in the tensor along a dimension.

fn int_max_dim_with_indices( tensor: TchTensor, dim: usize, ) -> (TchTensor, TchTensor)

Gets the maximum elements and corresponding indices along a dimension.

fn int_min_dim(tensor: TchTensor, dim: usize) -> TchTensor

Gets the minimum elements in the tensor along a dimension.

fn int_min_dim_with_indices( tensor: TchTensor, dim: usize, ) -> (TchTensor, TchTensor)

Gets the minimum elements and corresponding indices along a dimension.

fn int_clamp_min(tensor: TchTensor, min: i64) -> TchTensor

Clamps a tensor under a minimum value.

fn int_clamp_max(tensor: TchTensor, max: i64) -> TchTensor

Clamps a tensor over a maximum value.

fn int_clamp(tensor: TchTensor, min: i64, max: i64) -> TchTensor

Clamps a tensor between a minimum and maximum value.

fn int_abs(tensor: TchTensor) -> TchTensor

Returns a new tensor with absolute values.

fn int_into_float(tensor: TchTensor) -> TchTensor

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_random( shape: Shape, distribution: Distribution, device: &LibTorchDevice, ) -> TchTensor

Creates a new int tensor with random values.

fn int_arange(range: Range<i64>, device: &LibTorchDevice) -> TchTensor

Creates a new tensor with values from the given range.

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

Permutes the dimensions of a tensor.

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

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

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

Returns the signs of the int tensor.

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

Broadcasts the int tensor to the given shape.

fn int_sort( tensor: IntTensor<Self>, dim: usize, descending: bool, ) -> IntTensor<Self>

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

fn int_argsort( tensor: IntTensor<Self>, dim: usize, descending: bool, ) -> IntTensor<Self>

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

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_right_shift( lhs: IntTensor<Self>, rhs: IntTensor<Self>, ) -> IntTensor<Self>

Bitwise right 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_scalar( lhs: IntTensor<Self>, rhs: IntElem<Self>, ) -> IntTensor<Self>

Bitwise right shift operation for Int Tensors with a scalar

fn int_cast(tensor: IntTensor<Self>, dtype: IntDType) -> IntTensor<Self>

Converts a tensor to another integer data type.

fn int_unfold( tensor: IntTensor<Self>, dim: usize, size: usize, step: usize, ) -> IntTensor<Self>

Unfold windows along a dimension.

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_powi_scalar_impl( 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_powf_scalar_impl( lhs: <B as Backend>::IntTensorPrimitive, rhs: f32, ) -> <B as Backend>::IntTensorPrimitive

Element-wise power with a floatTensor.

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

Gets the maximum element in the tensor.

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

Gets the maximum absolute element in the tensor.

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

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

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

Gets the minimum element in the tensor.

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

Transposes an int tensor.

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_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_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.

impl<E: TchElement> ModuleOps<LibTorch<E>> for LibTorch<E>

fn embedding(weights: TchTensor, indices: TchTensor) -> TchTensor

Embedding operation.

fn embedding_backward( weights: TchTensor, output: TchTensor, indices: TchTensor, ) -> TchTensor

Embedding backward operation.

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

One dimensional convolution.

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

Two dimensional convolution.

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

Three dimensional convolution.

fn deform_conv2d( _x: TchTensor, _offset: TchTensor, _weight: TchTensor, _mask: Option<TchTensor>, _bias: Option<TchTensor>, _options: DeformConvOptions<2>, ) -> TchTensor

Two dimensional deformable convolution.

fn deform_conv2d_backward( _x: TchTensor, _offset: TchTensor, _weight: TchTensor, _mask: Option<TchTensor>, _bias: Option<TchTensor>, _out_grad: TchTensor, _options: DeformConvOptions<2>, ) -> DeformConv2dBackward<Self>

Backward pass for the deform_conv2d operation.

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

One dimensional transposed convolution.

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

Two dimensional transposed convolution.

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

Three dimensional transposed convolution.

fn avg_pool1d( x: TchTensor, kernel_size: usize, stride: usize, padding: usize, count_include_pad: bool, ) -> TchTensor

One dimensional avg pooling.

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

Two dimensional avg pooling.

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

Backward pass for the avg pooling 2d operation.

fn max_pool1d( x: TchTensor, kernel_size: usize, stride: usize, padding: usize, dilation: usize, ) -> TchTensor

One dimensional max pooling.

fn max_pool1d_with_indices( x: TchTensor, kernel_size: usize, stride: usize, padding: usize, dilation: usize, ) -> MaxPool1dWithIndices<LibTorch<E>>

One dimensional max pooling with indices.

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

Two dimensional max pooling.

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

Two dimensional max pooling with indices.

fn max_pool2d_with_indices_backward( x: TchTensor, kernel_size: [usize; 2], stride: [usize; 2], padding: [usize; 2], dilation: [usize; 2], output_grad: TchTensor, indices: TchTensor, ) -> MaxPool2dBackward<LibTorch<E>>

Backward pass for the max pooling 2d operation.

fn adaptive_avg_pool2d(x: TchTensor, output_size: [usize; 2]) -> TchTensor

Two dimensional adaptive avg pooling.

fn adaptive_avg_pool2d_backward(x: TchTensor, grad: TchTensor) -> TchTensor

Backward pass for the adaptive avg pooling 2d operation.

fn adaptive_avg_pool1d(x: TchTensor, output_size: usize) -> TchTensor

One dimensional adaptive avg pooling.

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

Down/up samples the input.

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

Backward pass for the interpolate 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.

fn avg_pool1d_backward( x: <B as Backend>::FloatTensorPrimitive, grad: <B as Backend>::FloatTensorPrimitive, kernel_size: usize, stride: usize, padding: usize, count_include_pad: bool, ) -> <B as Backend>::FloatTensorPrimitive

Backward pass for the avg pooling 1d operation.

fn adaptive_avg_pool1d_backward( x: <B as Backend>::FloatTensorPrimitive, grad: <B as Backend>::FloatTensorPrimitive, ) -> <B as Backend>::FloatTensorPrimitive

Backward pass for the adaptive avg pooling 1d operation.

fn max_pool1d_with_indices_backward( x: <B as Backend>::FloatTensorPrimitive, kernel_size: usize, stride: usize, padding: usize, dilation: usize, output_grad: <B as Backend>::FloatTensorPrimitive, indices: <B as Backend>::IntTensorPrimitive, ) -> MaxPool1dBackward<B>

Backward pass for the max pooling 1d operation.

impl<E: TchElement> QTensorOps<LibTorch<E>> for LibTorch<E>

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

Creates a new tensor from the data structure.

fn quantize( _tensor: FloatTensor<Self>, _scheme: &QuantScheme, _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: &QuantScheme, ) -> 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>) -> LibTorchDevice

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_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>, _slices: &[Slice], ) -> QuantizedTensor<Self>

Select tensor elements corresponding to the given slices.

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

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

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

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

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

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

fn q_max_dim( _tensor: QuantizedTensor<Self>, _dim: usize, ) -> QuantizedTensor<Self>

Gets the maximum elements of a tensor along an axis.

fn q_min_dim( _tensor: QuantizedTensor<Self>, _dim: usize, ) -> QuantizedTensor<Self>

Gets the minimum elements of a tensor along an axis.

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

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

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

Broadcasts the tensor to the given shape.

fn q_sort( _tensor: QuantizedTensor<Self>, _dim: usize, _descending: bool, ) -> QuantizedTensor<Self>

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

fn q_sort_with_indices( _tensor: QuantizedTensor<Self>, _dim: usize, _descending: bool, ) -> (QuantizedTensor<Self>, IntTensor<Self>)

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

fn q_argsort( _tensor: QuantizedTensor<Self>, _dim: usize, _descending: bool, ) -> IntTensor<Self>

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

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

Transposes a tensor.

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

Gather elements from 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, ) -> TensorPrimitive<B>

Adds two tensors together.

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

Adds a scalar to a tensor.

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

Clamps a tensor under a minimum value.

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

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, ) -> TensorPrimitive<B>

Clamps a tensor between a minimum and maximum value.

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

Subtracts two tensors.

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

Subtracts a scalar from a tensor.

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

Multiplies two tensors together element-wise.

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

Multiplies a tensor by a scalar.

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

Divides two tensors element-wise.

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

Divides a tensor by a scalar.

fn q_matmul( lhs: TensorPrimitive<B>, rhs: TensorPrimitive<B>, ) -> TensorPrimitive<B>

Multiplies two tensors together using matrix multiplication.

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

Negates a tensor element-wise.

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

Calculates the reciprocals element-wise

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

Sum of all elements in a tensor.

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

Sum of all elements in a tensor along a dimension.

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

Product of all elements in a tensor.

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

Product of all elements in a tensor along a dimension.

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

Mean of all elements in a tensor.

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

Mean of all elements in a tensor along a dimension.

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

Computes the cumulative sum of elements along a dimension.

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

Computes the cumulative product of elements along a dimension.

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

Computes the cumulative minimum of elements along a dimension.

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

Computes the cumulative maximum of elements along a dimension.

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

Returns a new tensor with exponential values.

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

Returns a new tensor with natural logarithm values.

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

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

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

Element-wise power with another tensor.

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

Element-wise power with an IntTensor.

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

Element-wise power with an int scalar.

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

Element-wise power with a float scalar.

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

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) -> TensorPrimitive<B>

Returns a new tensor with cosine values.

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

Returns a new tensor with sine values.

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

Returns a new tensor with tangent values.

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

Returns a new tensor with hyperbolic cosine values.

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

Returns a new tensor with hyperbolic sine values.

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

Returns a new tensor with hyperbolic tangent values.

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

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

Gets the maximum element of a tensor.

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

Gets the minimum element of a tensor.

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_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.

impl<E: TchElement> TransactionOps<LibTorch<E>> for LibTorch<E>

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

Executes a transaction and return its result.

impl<E: Copy> Copy for LibTorch<E>