Struct CubeBackend 

pub struct CubeBackend;

Tensor backend that compiles just-in-time for whichever runtime its device names.

Implementations

impl CubeBackend

pub fn new() -> CubeBackend

Constructs a new CubeBackend.

Trait Implementations

impl ActivationOps<CubeBackend> for CubeBackend

fn leaky_relu( tensor: <B as BackendTypes>::FloatTensorPrimitive, negative_slope: Scalar, ) -> <B as BackendTypes>::FloatTensorPrimitive

Applies the LeakyReLU activation function.

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

Applies the ReLU activation function.

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

Applies the ReLU activation function backward.

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

Applies the Gelu activation function.

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

Applies the PReLu activation function.

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

Applies the Gelu activation function backward.

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

Applies the Sigmoid activation function.

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

Applies the Sigmoid activation function backward.

fn hard_sigmoid( tensor: <B as BackendTypes>::FloatTensorPrimitive, alpha: Scalar, beta: Scalar, ) -> <B as BackendTypes>::FloatTensorPrimitive

Applies the hard Sigmoid activation function.

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

Applies the LogSigmoid activation function.

fn softmax( tensor: <B as BackendTypes>::FloatTensorPrimitive, dim: usize, ) -> <B as BackendTypes>::FloatTensorPrimitive

Applies the softmax function along the given dimension.

fn log_softmax( tensor: <B as BackendTypes>::FloatTensorPrimitive, dim: usize, ) -> <B as BackendTypes>::FloatTensorPrimitive

Applies the log-softmax function along the given dimension.

fn softmin( tensor: <B as BackendTypes>::FloatTensorPrimitive, dim: usize, ) -> <B as BackendTypes>::FloatTensorPrimitive

Applies the softmin function along the given dimension.

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

Applies the LogSigmoid activation function backward.

impl Backend for CubeBackend

fn profile_abandon( device: &<CubeBackend as BackendTypes>::Device, token: ProfileToken, )

Dropped on the stream it was opened on, without recording an end — cubecl returns the start event to its pool and nothing is measured.

fn name(device: &<CubeBackend as BackendTypes>::Device) -> String

Name of the backend.

fn seed(_device: &<CubeBackend as BackendTypes>::Device, seed: u64)

Seeds the backend on the specified device.

fn ad_enabled(_device: &<CubeBackend as BackendTypes>::Device) -> bool

If autodiff is enabled.

fn sync( device: &<CubeBackend as BackendTypes>::Device, ) -> Result<(), ExecutionError>

Sync the backend, ensure that all computation are finished.

fn profile<O>( device: &<CubeBackend as BackendTypes>::Device, options: ProfileOptions, func: impl FnOnce() -> O + Send, ) -> Result<(O, ProfileDuration), ExecutionError>

where O: Send + 'static,

Measure how long the device spends on the work func puts on the calling stream, in device time.

fn profile_start( device: &<CubeBackend as BackendTypes>::Device, ) -> Result<Option<ProfileToken>, ExecutionError>

Open a profiling window at the calling stream’s current position, to be closed with profile_end from the same stream.

fn profile_end( device: &<CubeBackend as BackendTypes>::Device, token: ProfileToken, _options: ProfileOptions, ) -> Result<ProfileDuration, ExecutionError>

Close the window token at the calling stream’s current position.

fn graph_prepare( device: &<CubeBackend as BackendTypes>::Device, ) -> Result<(), ExecutionError>

Prepare device for an upcoming graph capture: route allocations into a stable pool so every buffer allocated before graph_stop_capture can be pinned. Call before the warmup run. No-op by default.

fn graph_start_capture( device: &<CubeBackend as BackendTypes>::Device, ) -> Result<(), ExecutionError>

Begin recording launches on device into a graph (see graph_stop_capture). Errors on backends without hardware graph support, so callers fall back to re-running.

fn graph_stop_capture( device: &<CubeBackend as BackendTypes>::Device, ) -> Result<<CubeBackend as BackendTypes>::GraphPrimitive, ExecutionError>

Stop recording and return the captured graph, ready to graph_replay.

unsafe fn graph_replay( device: &<CubeBackend as BackendTypes>::Device, graph: &<CubeBackend as BackendTypes>::GraphPrimitive, ) -> Result<(), ExecutionError>

Replay a captured graph — one dispatch re-running the recorded launches against their original buffers.

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

where Output: Send, Input: Send, Func: Fn(Input) -> Output + Send,

Sets the current allocation mode to persistent.

fn memory_cleanup(device: &<CubeBackend as BackendTypes>::Device)

Manually triggers a memory cleanup on the given device.

fn memory_pool_report( device: &<CubeBackend as BackendTypes>::Device, ) -> Option<Vec<SlicedPoolReport>>

The dynamic pools’ measured state, in the order allocations are routed through them. None on a backend that does not report one, or whose stream has failed.

fn memory_pool_usage( device: &<CubeBackend as BackendTypes>::Device, ) -> Option<MemoryPoolUsage>

The device allocator’s current state. None on a backend that does not report one, or whose stream has failed.

fn staging<'a, Iter>(data: Iter, device: &<CubeBackend as BackendTypes>::Device)

where Iter: Iterator<Item = &'a mut TensorData>,

Marks the given data as being used as a staging buffer for transfer between CPU and accelerators like GPUs.

fn supports_dtype( device: &<CubeBackend as BackendTypes>::Device, dtype: DType, ) -> bool

Whether the type is fully supported by the specified device for general operations.

fn dtype_usage( device: &<CubeBackend as BackendTypes>::Device, dtype: DType, ) -> EnumSet<DTypeUsage>

Returns the DTypeUsageSet for the given DType on the specified device.

fn device_count(type_id: u16) -> usize

Returns the number of devices available on this backend. device is a reference device used to determine the underlying backend that should be queried. A CUDA device will return all devices available to CUDA, a Vulkan device will return all devices available to Vulkan, etc.

fn flush( device: &<CubeBackend as BackendTypes>::Device, ) -> Result<(), ExecutionError>

Flush any pending operation of the backend.

impl BackendIr for CubeBackend

type Handle = CubeFusionHandle

The type that can be used to point to a tensor of any kind.

fn float_tensor( handle: TensorHandle<<CubeBackend as BackendIr>::Handle>, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Convert a handle to a float tensor.

fn int_tensor( handle: TensorHandle<<CubeBackend as BackendIr>::Handle>, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Convert a handle to an int tensor.

fn bool_tensor( handle: TensorHandle<<CubeBackend as BackendIr>::Handle>, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Convert a handle to a bool tensor.

fn quantized_tensor( handle: TensorHandle<<CubeBackend as BackendIr>::Handle>, ) -> <CubeBackend as BackendTypes>::QuantizedTensorPrimitive

Convert a handle to a quantized tensor.

fn float_tensor_handle( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendIr>::Handle

Convert a float tensor to a handle.

fn int_tensor_handle( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, ) -> <CubeBackend as BackendIr>::Handle

Convert an int tensor to a handle.

fn bool_tensor_handle( tensor: <CubeBackend as BackendTypes>::BoolTensorPrimitive, ) -> <CubeBackend as BackendIr>::Handle

Convert a bool tensor to a handle.

fn quantized_tensor_handle( tensor: <CubeBackend as BackendTypes>::QuantizedTensorPrimitive, ) -> <CubeBackend as BackendIr>::Handle

Convert a quantized tensor to a handle.

impl BackendTypes for CubeBackend

type Device = Device

Device type.

type FloatTensorPrimitive = CubeTensor

Tensor primitive to be used for all float operations.

type IntTensorPrimitive = CubeTensor

Tensor primitive to be used for all int operations.

type BoolTensorPrimitive = CubeTensor

Tensor primitive to be used for all bool operations.

type QuantizedTensorPrimitive = CubeTensor

Tensor primitive to be used for all quantized operations.

type GraphPrimitive = CubeGraph

Captured graph primitive returned by Backend::graph_stop_capture and consumed by Backend::graph_replay: a backend-owned recording of a launch sequence that replays as a single dispatch.

impl BoolTensorOps<CubeBackend> for CubeBackend

fn bool_empty( shape: Shape, device: &<CubeBackend as BackendTypes>::Device, dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Creates a new bool tensor.

fn bool_zeros( shape: Shape, device: &<CubeBackend as BackendTypes>::Device, dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Creates a new bool tensor filled false.

fn bool_ones( shape: Shape, device: &<CubeBackend as BackendTypes>::Device, dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Creates a new bool tensor filled true.

async fn bool_into_data( tensor: <CubeBackend as BackendTypes>::BoolTensorPrimitive, ) -> Result<TensorData, ExecutionError>

Converts the tensor to a data structure.

fn bool_from_data( data: TensorData, device: &<CubeBackend as BackendTypes>::Device, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Creates a tensor from the data structure.

fn bool_into_int( tensor: <CubeBackend as BackendTypes>::BoolTensorPrimitive, out_dtype: IntDType, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Converts bool tensor to int tensor.

fn bool_to_device( tensor: <CubeBackend as BackendTypes>::BoolTensorPrimitive, device: &<CubeBackend as BackendTypes>::Device, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Moves the tensor to the device.

fn bool_reshape( tensor: <CubeBackend as BackendTypes>::BoolTensorPrimitive, shape: Shape, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Reshapes the tensor.

fn bool_slice( tensor: <CubeBackend as BackendTypes>::BoolTensorPrimitive, slices: &[Slice], ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Gets the values from the tensor for the given ranges.

fn bool_slice_assign( tensor: <CubeBackend as BackendTypes>::BoolTensorPrimitive, ranges: &[Slice], value: <CubeBackend as BackendTypes>::BoolTensorPrimitive, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Sets the values in the tensor for the given ranges.

fn bool_equal( lhs: <CubeBackend as BackendTypes>::BoolTensorPrimitive, rhs: <CubeBackend as BackendTypes>::BoolTensorPrimitive, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Equates the two tensors.

fn bool_not_equal( lhs: <CubeBackend as BackendTypes>::BoolTensorPrimitive, rhs: <CubeBackend as BackendTypes>::BoolTensorPrimitive, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Element-wise non-equality comparison.

fn bool_not( tensor: <CubeBackend as BackendTypes>::BoolTensorPrimitive, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Inverses boolean values.

fn bool_and( lhs: <CubeBackend as BackendTypes>::BoolTensorPrimitive, rhs: <CubeBackend as BackendTypes>::BoolTensorPrimitive, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

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

fn bool_or( lhs: <CubeBackend as BackendTypes>::BoolTensorPrimitive, rhs: <CubeBackend as BackendTypes>::BoolTensorPrimitive, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

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

fn bool_any( tensor: <CubeBackend as BackendTypes>::BoolTensorPrimitive, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

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

fn bool_any_dim( tensor: <CubeBackend as BackendTypes>::BoolTensorPrimitive, dim: usize, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

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

fn bool_all( tensor: <CubeBackend as BackendTypes>::BoolTensorPrimitive, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

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

fn bool_all_dim( tensor: <CubeBackend as BackendTypes>::BoolTensorPrimitive, dim: usize, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

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

fn bool_into_float( tensor: <CubeBackend as BackendTypes>::BoolTensorPrimitive, out_dtype: FloatDType, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Converts bool tensor to float tensor.

fn bool_swap_dims( tensor: <CubeBackend as BackendTypes>::BoolTensorPrimitive, dim1: usize, dim2: usize, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Swaps two dimensions of a bool tensor.

fn bool_repeat_dim( tensor: <CubeBackend as BackendTypes>::BoolTensorPrimitive, dim: usize, times: usize, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

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

fn bool_permute( tensor: <CubeBackend as BackendTypes>::BoolTensorPrimitive, axes: &[usize], ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Permutes the dimensions of a tensor.

fn bool_expand( tensor: <CubeBackend as BackendTypes>::BoolTensorPrimitive, shape: Shape, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Broadcasts the bool tensor to the given shape.

fn bool_select( tensor: <CubeBackend as BackendTypes>::BoolTensorPrimitive, dim: usize, indices: <CubeBackend as BackendTypes>::IntTensorPrimitive, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

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

fn bool_select_or( tensor: <CubeBackend as BackendTypes>::BoolTensorPrimitive, dim: usize, indices: <CubeBackend as BackendTypes>::IntTensorPrimitive, value: <CubeBackend as BackendTypes>::BoolTensorPrimitive, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

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

fn bool_flip( tensor: <CubeBackend as BackendTypes>::BoolTensorPrimitive, axes: &[usize], ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

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

fn bool_unfold( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, dim: usize, size: usize, step: usize, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Unfold windows along a dimension.

fn bool_mask_where( tensor: <CubeBackend as BackendTypes>::BoolTensorPrimitive, mask: <CubeBackend as BackendTypes>::BoolTensorPrimitive, value: <CubeBackend as BackendTypes>::BoolTensorPrimitive, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

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

fn bool_mask_fill( tensor: <CubeBackend as BackendTypes>::BoolTensorPrimitive, mask: <CubeBackend as BackendTypes>::BoolTensorPrimitive, value: Scalar, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

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

fn bool_gather( dim: usize, tensor: <CubeBackend as BackendTypes>::BoolTensorPrimitive, indices: <CubeBackend as BackendTypes>::IntTensorPrimitive, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Gather elements from the tensor at the given indices.

fn bool_scatter_or( dim: usize, tensor: <CubeBackend as BackendTypes>::BoolTensorPrimitive, indices: <CubeBackend as BackendTypes>::IntTensorPrimitive, value: <CubeBackend as BackendTypes>::BoolTensorPrimitive, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Scatter a given value to the tensor at the given indices using boolean or reduction.

fn bool_equal_elem( lhs: <CubeBackend as BackendTypes>::BoolTensorPrimitive, rhs: Scalar, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Element-wise equality comparison with a scalar.

fn bool_mask_select( tensor: <B as BackendTypes>::BoolTensorPrimitive, mask: <B as BackendTypes>::BoolTensorPrimitive, ) -> impl Future<Output = <B as BackendTypes>::BoolTensorPrimitive> + Send + 'static

Selects the elements of the tensor where the mask is true, returned as a 1D tensor.

fn bool_cat( tensors: Vec<<B as BackendTypes>::BoolTensorPrimitive>, dim: usize, ) -> <B as BackendTypes>::BoolTensorPrimitive

Concatenates the tensors along the given dimension.

fn bool_not_equal_elem( lhs: <B as BackendTypes>::BoolTensorPrimitive, rhs: Scalar, ) -> <B as BackendTypes>::BoolTensorPrimitive

Element-wise non-equality comparison with a scalar.

fn bool_xor( lhs: <B as BackendTypes>::BoolTensorPrimitive, rhs: <B as BackendTypes>::BoolTensorPrimitive, ) -> <B as BackendTypes>::BoolTensorPrimitive

Element-wise exclusive or.

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

Transposes a bool tensor.

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

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

impl Clone for CubeBackend

fn clone(&self) -> CubeBackend

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for CubeBackend

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

Formats the value using the given formatter.

impl Default for CubeBackend

fn default() -> CubeBackend

Returns the “default value” for a type.

impl DistributedOps<CubeBackend> for CubeBackend

fn all_reduce( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, op: ReduceOperation, device_ids: Vec<DeviceId>, ) -> CollectiveTensor<CubeBackend>

all_reduce operation.

fn sync_collective(device: &<CubeBackend as BackendTypes>::Device)

Sync the collective operations.

fn start_communication_server( devices: &[<B as BackendTypes>::Device], config: DistributedConfig, )

Start the communication server used to orchestrate tensor syncing between devices.

fn close_communication_server(_device: &<B as BackendTypes>::Device)

Close the communication server used to orchestrate syncing between devices.

fn register_sync_parameters( _device: &<B as BackendTypes>::Device, distributed_params: Vec<DistributedParams>, )

Register the parameters that will require gradient synchronization for the upcoming backward pass.

fn submit_sync_collective(device: &<B as BackendTypes>::Device)

Tell the gradient sync server that this device has submitted all its sync operations and is ready to be synchronized.

fn submit_gradient_sync( tensor: TensorRef<B>, distributed_params: DistributedParams, )

Submit a gradient tensor for synchronization across all devices.

unsafe fn comm_device(tensor: &TensorRef<B>) -> <B as BackendTypes>::Device

Get the device of the tensor reference.

unsafe fn float_from_ref( tensor: &TensorRef<B>, ) -> <B as BackendTypes>::FloatTensorPrimitive

Returns a clone of the float tensor from the tensor reference.

impl FloatTensorOps<CubeBackend> for CubeBackend

fn float_from_data( data: TensorData, device: &<CubeBackend as BackendTypes>::Device, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Creates a new tensor from the data structure.

fn float_random( shape: Shape, distribution: Distribution, device: &<CubeBackend as BackendTypes>::Device, dtype: FloatDType, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Creates a new tensor with random values.

async fn float_into_data( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> Result<TensorData, ExecutionError>

Converts the tensor to a data structure.

fn float_to_device( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, device: &<CubeBackend as BackendTypes>::Device, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Moves the tensor to the given device.

fn float_empty( shape: Shape, device: &<CubeBackend as BackendTypes>::Device, dtype: FloatDType, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Creates an empty tensor with the given shape.

fn float_add( lhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, rhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Adds two tensors together.

fn float_add_scalar( lhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, rhs: Scalar, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Adds a scalar to a tensor.

fn float_zeros( shape: Shape, device: &<CubeBackend as BackendTypes>::Device, dtype: FloatDType, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Creates a new tensor with zeros.

fn float_full( shape: Shape, fill_value: Scalar, device: &Device, dtype: FloatDType, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Creates a tensor filled with given value.

fn float_ones( shape: Shape, device: &<CubeBackend as BackendTypes>::Device, dtype: FloatDType, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Creates a new tensor with ones.

fn float_sub( lhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, rhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Subtracts two tensors.

fn float_sub_scalar( lhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, rhs: Scalar, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Subtracts a scalar from a tensor.

fn float_mul( lhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, rhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Multiplies two tensors together element-wise.

fn float_mul_scalar( lhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, rhs: Scalar, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Multiplies a tensor by a scalar.

fn float_div( lhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, rhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Divides two tensors element-wise.

fn float_div_scalar( lhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, rhs: Scalar, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Divides a tensor by a scalar.

fn float_remainder( lhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, rhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

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

fn float_remainder_scalar( lhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, rhs: Scalar, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Computes the modulus of a tensor given a scalar.

fn float_matmul( lhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, rhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Multiplies two tensors together using matrix multiplication.

fn float_cross( lhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, rhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, dim: usize, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

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

fn float_swap_dims( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, dim1: usize, dim2: usize, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Swaps two dimensions of a tensor.

fn float_reshape( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, shape: Shape, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Reshapes a tensor.

fn float_gather( dim: usize, tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, indices: <CubeBackend as BackendTypes>::IntTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Gather elements from a tensor.

fn float_scatter( dim: usize, tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, indices: <CubeBackend as BackendTypes>::IntTensorPrimitive, value: <CubeBackend as BackendTypes>::FloatTensorPrimitive, update: IndexingUpdateOp, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Scatter elements into a tensor using the specified update operation.

fn float_scatter_nd( data: <CubeBackend as BackendTypes>::FloatTensorPrimitive, indices: <CubeBackend as BackendTypes>::IntTensorPrimitive, values: <CubeBackend as BackendTypes>::FloatTensorPrimitive, reduction: IndexingUpdateOp, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Multi-dimensional scatter: update data at locations specified by indices with values.

fn float_gather_nd( data: <CubeBackend as BackendTypes>::FloatTensorPrimitive, indices: <CubeBackend as BackendTypes>::IntTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Multi-dimensional gather: collect slices from data at locations specified by indices.

fn float_select( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, dim: usize, indices: <CubeBackend as BackendTypes>::IntTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

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

fn float_select_assign( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, dim: usize, indices: <CubeBackend as BackendTypes>::IntTensorPrimitive, value: <CubeBackend as BackendTypes>::FloatTensorPrimitive, update: IndexingUpdateOp, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Assign selected elements along a dimension using the specified update operation.

fn float_slice( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, slices: &[Slice], ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Select tensor elements corresponding to the given slices.

fn float_slice_assign( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ranges: &[Slice], value: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

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

fn float_mask_where( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, mask: <CubeBackend as BackendTypes>::BoolTensorPrimitive, value: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

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

fn float_mask_fill( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, mask: <CubeBackend as BackendTypes>::BoolTensorPrimitive, value: Scalar, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

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

fn float_equal( lhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, rhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, out_dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Equal comparison of two tensors.

fn float_not_equal( lhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, rhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, out_dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Element-wise non-equality comparison.

fn float_equal_elem( lhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, rhs: Scalar, out_dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Equal comparison of a tensor and a scalar.

fn float_not_equal_elem( lhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, rhs: Scalar, out_dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Element-wise non-equality comparison with a scalar.

fn float_greater( lhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, rhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, out_dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Greater than comparison of two tensors.

fn float_greater_elem( lhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, rhs: Scalar, out_dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Greater than comparison of a tensor and a scalar.

fn float_greater_equal( lhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, rhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, out_dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Greater than or equal comparison of two tensors.

fn float_greater_equal_elem( lhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, rhs: Scalar, out_dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

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

fn float_lower( lhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, rhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, out_dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Less than comparison of two tensors.

fn float_lower_elem( lhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, rhs: Scalar, out_dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Less than comparison of a tensor and a scalar.

fn float_lower_equal( lhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, rhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, out_dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Less than or equal comparison of two tensors.

fn float_lower_equal_elem( lhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, rhs: Scalar, out_dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

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

fn float_sum( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Sum of all elements in a tensor.

fn float_max( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Gets the maximum element of a tensor.

fn float_max_dim( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, dim: usize, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Gets the maximum elements of a tensor along an axis.

fn float_min( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Gets the minimum element of a tensor.

fn float_min_dim( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, dim: usize, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Gets the minimum elements of a tensor along an axis.

fn float_max_abs( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Gets the maximum absolute element of a tensor.

fn float_max_abs_dim( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, dim: usize, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

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

fn float_any( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, out_dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

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

fn float_any_dim( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, dim: usize, out_dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

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

fn float_all( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, out_dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

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

fn float_all_dim( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, dim: usize, out_dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

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

fn float_sum_dim( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, dim: usize, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Sum of all elements in a tensor along a dimension.

fn float_sum_dims( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, dims: &[usize], ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Sum the tensor along several dimensions at once, keeping each of them with length one.

fn float_mean_dim( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, dim: usize, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Mean of all elements in a tensor along a dimension.

fn float_mean( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Mean of all elements in a tensor.

fn float_cumsum( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, dim: usize, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Computes the cumulative sum of elements along a dimension.

fn float_cumprod( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, dim: usize, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Computes the cumulative product of elements along a dimension.

fn float_cummin( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, dim: usize, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Computes the cumulative minimum of elements along a dimension.

fn float_cummax( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, dim: usize, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Computes the cumulative maximum of elements along a dimension.

fn float_prod( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Product of all elements in a tensor.

fn float_prod_dim( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, dim: usize, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Product of all elements in a tensor along a dimension.

fn float_exp( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Returns a new tensor with exponential values.

fn float_log( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Returns a new tensor with natural logarithm values.

fn float_log1p( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

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

fn float_powf_scalar_impl( lhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, rhs: Scalar, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

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

fn float_sqrt( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Returns a new tensor with square root values.

fn float_abs( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Returns a new tensor with absolute values.

fn float_sign( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Returns the signs of the float tensor.

fn float_cos( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Returns a new tensor with cosine values.

fn float_sin( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Returns a new tensor with sine values.

fn float_tan( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Returns a new tensor with tangent values.

fn float_cosh( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Returns a new tensor with hyperbolic cosine values.

fn float_sinh( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Returns a new tensor with hyperbolic sine values.

fn float_tanh( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Returns a new tensor with hyperbolic tangent values.

fn float_acos( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Returns a new tensor with inverse cosine values.

fn float_acosh( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Returns a new tensor with inverse hyperbolic cosine values.

fn float_asin( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Returns a new tensor with inverse sine values.

fn float_asinh( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Returns a new tensor with inverse hyperbolic sine values.

fn float_atan( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Returns a new tensor with the inverse tangent values.

fn float_atanh( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Returns a new tensor with the inverse hyperbolic tangent values.

fn float_atan2( lhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, rhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Returns a tensor with the four-quadrant inverse tangent values of y and x.

fn float_round( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Returns a new tensor with rounded values.

fn float_floor( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Returns a new tensor with floored values.

fn float_ceil( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Returns a new tensor with ceiled values.

fn float_trunc( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Returns a new tensor with truncated values.

fn float_erf( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Returns a new tensor with the error function values.

fn float_argmax( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, dim: usize, out_dtype: IntDType, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

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

fn float_argtopk( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, dim: usize, k: usize, out_dtype: IntDType, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Gets the indices of the k maximum elements of a tensor along an axis. if two elements are equals, it will be ordered by lowest indices

fn float_topk( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, dim: usize, k: usize, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Gets the values of the k maximum elements of a tensor along an axis.

fn float_topk_with_indices( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, dim: usize, k: usize, out_dtype: IntDType, ) -> (<CubeBackend as BackendTypes>::FloatTensorPrimitive, <CubeBackend as BackendTypes>::IntTensorPrimitive)

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

fn float_max_dim_with_indices( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, dim: usize, indices_dtype: IntDType, ) -> (<CubeBackend as BackendTypes>::FloatTensorPrimitive, <CubeBackend as BackendTypes>::IntTensorPrimitive)

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

fn float_min_dim_with_indices( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, dim: usize, indices_dtype: IntDType, ) -> (<CubeBackend as BackendTypes>::FloatTensorPrimitive, <CubeBackend as BackendTypes>::IntTensorPrimitive)

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

fn float_argmin( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, dim: usize, out_dtype: IntDType, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

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

fn float_into_int( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, out_dtype: IntDType, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Converts float tensor to int tensor.

fn float_clamp( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, min: Scalar, max: Scalar, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Clamps a tensor between a minimum and maximum value.

fn float_recip( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Calculates the reciprocals element-wise

fn float_repeat_dim( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, dim: usize, times: usize, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Repeat the tensor along the given dimension.

fn float_powf( lhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, rhs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Element-wise power with a FloatTensor.

fn float_permute( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, axes: &[usize], ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Permutes the dimensions of a tensor.

fn float_expand( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, shape: Shape, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Broadcasts the float tensor to the given shape.

fn float_flip( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, axes: &[usize], ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

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

fn float_cast( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, dtype: FloatDType, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Converts a tensor to another floating point data type.

fn float_unfold( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, dim: usize, size: usize, step: usize, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Unfold windows along a dimension.

fn float_is_nan( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, out_dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

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

fn float_is_inf( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, out_dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

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

fn float_grid_sample_2d( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, grid: <CubeBackend as BackendTypes>::FloatTensorPrimitive, options: GridSampleOptions, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

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

fn float_clamp_min( tensor: <B as BackendTypes>::FloatTensorPrimitive, min: Scalar, ) -> <B as BackendTypes>::FloatTensorPrimitive

Clamps a tensor under a minimum value.

fn float_clamp_max( tensor: <B as BackendTypes>::FloatTensorPrimitive, max: Scalar, ) -> <B as BackendTypes>::FloatTensorPrimitive

Clamps a tensor over a maximum value.

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

Negates a tensor element-wise.

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

Transposes a tensor.

fn float_mask_select( tensor: <B as BackendTypes>::FloatTensorPrimitive, mask: <B as BackendTypes>::BoolTensorPrimitive, ) -> impl Future<Output = <B as BackendTypes>::FloatTensorPrimitive> + Send + 'static

Selects the elements of the tensor where the mask is true, returned as a 1D tensor.

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

Detaches a tensor from the computation graph.

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

Sets the require_grad flag of a tensor.

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

Returns the require_grad flag of a tensor.

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

Element-wise power with an IntTensor.

fn float_powi_scalar( lhs: <B as BackendTypes>::FloatTensorPrimitive, rhs: Scalar, ) -> <B as BackendTypes>::FloatTensorPrimitive

Raises a tensor to the power of an int scalar.

fn float_powi_scalar_impl( lhs: <B as BackendTypes>::FloatTensorPrimitive, rhs: Scalar, ) -> <B as BackendTypes>::FloatTensorPrimitive

Raises a tensor to the power of an int scalar.

fn float_powf_scalar( tensor: <B as BackendTypes>::FloatTensorPrimitive, value: Scalar, ) -> <B as BackendTypes>::FloatTensorPrimitive

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

fn float_hypot( lhs: <B as BackendTypes>::FloatTensorPrimitive, rhs: <B as BackendTypes>::FloatTensorPrimitive, ) -> <B as BackendTypes>::FloatTensorPrimitive

Returns a new tensor with the Euclidean distance values.

fn float_cat( tensors: Vec<<B as BackendTypes>::FloatTensorPrimitive>, dim: usize, ) -> <B as BackendTypes>::FloatTensorPrimitive

Concatenates tensors along a dimension.

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

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

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

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

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

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

fn float_pad( tensor: <B as BackendTypes>::FloatTensorPrimitive, padding: &[(usize, usize)], mode: PadMode, ) -> <B as BackendTypes>::FloatTensorPrimitive

Pads a tensor with one (before, after) pair per dimension.

impl FusionBackend for CubeBackend

type FusionRuntime = FusionCubeRuntime

The runtime used for this backend.

type FullPrecisionBackend = CubeBackend

Pointer to the full precision fusion backend.

fn cast_float( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, dtype: DType, ) -> <CubeBackend as BackendIr>::Handle

Cast a float tensor and returns the resulting handle.

fn memory_persistent( device: &<CubeBackend as BackendTypes>::Device, enabled: bool, )

Set the standing persistent-allocation mode of the device stream that executes fused operations.

impl IntTensorOps<CubeBackend> for CubeBackend

fn int_empty( shape: Shape, device: &<CubeBackend as BackendTypes>::Device, dtype: IntDType, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Creates a new int tensor.

async fn int_into_data( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, ) -> Result<TensorData, ExecutionError>

Converts the tensor to a data structure.

fn int_from_data( data: TensorData, device: &<CubeBackend as BackendTypes>::Device, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Creates a tensor from the data structure.

fn int_to_device( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, device: &<CubeBackend as BackendTypes>::Device, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Moves the tensor to the given device.

fn int_reshape( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, shape: Shape, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Reshapes the tensor.

fn int_slice( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, slices: &[Slice], ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Gets the element at the given indices.

fn int_slice_assign( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, ranges: &[Slice], value: <CubeBackend as BackendTypes>::IntTensorPrimitive, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Sets the values in the tensor for the given ranges.

fn int_matmul( lhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, rhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Multiplies two tensors together using matrix multiplication.

fn int_mask_where( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, mask: <CubeBackend as BackendTypes>::BoolTensorPrimitive, value: <CubeBackend as BackendTypes>::IntTensorPrimitive, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

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

fn int_mask_fill( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, mask: <CubeBackend as BackendTypes>::BoolTensorPrimitive, value: Scalar, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

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

fn int_gather( dim: usize, tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, indices: <CubeBackend as BackendTypes>::IntTensorPrimitive, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Gather elements from the tensor at the given indices.

fn int_scatter( dim: usize, tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, indices: <CubeBackend as BackendTypes>::IntTensorPrimitive, value: <CubeBackend as BackendTypes>::IntTensorPrimitive, update: IndexingUpdateOp, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Scatter elements into a tensor using the specified update operation.

fn int_scatter_nd( data: <CubeBackend as BackendTypes>::IntTensorPrimitive, indices: <CubeBackend as BackendTypes>::IntTensorPrimitive, values: <CubeBackend as BackendTypes>::IntTensorPrimitive, reduction: IndexingUpdateOp, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Multi-dimensional scatter for int tensors.

fn int_gather_nd( data: <CubeBackend as BackendTypes>::IntTensorPrimitive, indices: <CubeBackend as BackendTypes>::IntTensorPrimitive, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Multi-dimensional gather for int tensors.

fn int_select( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, dim: usize, indices: <CubeBackend as BackendTypes>::IntTensorPrimitive, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

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

fn int_select_assign( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, dim: usize, indices: <CubeBackend as BackendTypes>::IntTensorPrimitive, value: <CubeBackend as BackendTypes>::IntTensorPrimitive, update: IndexingUpdateOp, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Assign selected elements along a dimension using the specified update operation.

fn int_equal( lhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, rhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, out_dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Element-wise equality comparison.

fn int_not_equal( lhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, rhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, out_dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Element-wise non-equality comparison.

fn int_equal_elem( lhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, rhs: Scalar, out_dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Element-wise equality comparison with a scalar.

fn int_not_equal_elem( lhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, rhs: Scalar, out_dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Element-wise non-equality comparison with a scalar.

fn int_greater( lhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, rhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, out_dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Element-wise greater than comparison.

fn int_greater_elem( lhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, rhs: Scalar, out_dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Element-wise greater than comparison with a scalar.

fn int_greater_equal( lhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, rhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, out_dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Element-wise greater than or equal comparison.

fn int_greater_equal_elem( lhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, rhs: Scalar, out_dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

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

fn int_lower( lhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, rhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, out_dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Element-wise less than comparison.

fn int_lower_elem( lhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, rhs: Scalar, out_dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Element-wise less than comparison with a scalar.

fn int_lower_equal( lhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, rhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, out_dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

Element-wise less than or equal comparison.

fn int_lower_equal_elem( lhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, rhs: Scalar, out_dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

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

fn int_add( lhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, rhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Element-wise addition.

fn int_add_scalar( lhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, rhs: Scalar, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Element-wise addition with a scalar.

fn int_sub( lhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, rhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Element-wise subtraction.

fn int_sub_scalar( lhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, rhs: Scalar, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Element-wise subtraction with a scalar.

fn int_mul( lhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, rhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Element-wise multiplication.

fn int_mul_scalar( lhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, rhs: Scalar, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Element-wise multiplication with a scalar.

fn int_div( lhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, rhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Element-wise division.

fn int_div_scalar( lhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, rhs: Scalar, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Element-wise division with a scalar.

fn int_remainder( lhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, rhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Element-wise floor modulo.

fn int_remainder_scalar( lhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, rhs: Scalar, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Element-wise floor modulo with a scalar.

fn int_zeros( shape: Shape, device: &<CubeBackend as BackendTypes>::Device, dtype: IntDType, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Creates a tensor of zeros.

fn int_ones( shape: Shape, device: &<CubeBackend as BackendTypes>::Device, dtype: IntDType, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Creates a tensor of ones.

fn int_full( shape: Shape, fill_value: Scalar, device: &<CubeBackend as BackendTypes>::Device, dtype: IntDType, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Creates a tensor filled with given value.

fn int_sum( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Sums all elements in the tensor.

fn int_sum_dim( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, dim: usize, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Sums all elements in the tensor along a dimension.

fn int_any( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, out_dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

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

fn int_any_dim( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, dim: usize, out_dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

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

fn int_all( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, out_dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

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

fn int_all_dim( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, dim: usize, out_dtype: BoolStore, ) -> <CubeBackend as BackendTypes>::BoolTensorPrimitive

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

fn int_prod( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Computes the product of all elements in the tensor.

fn int_prod_dim( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, dim: usize, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

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

fn int_max( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Gets the maximum element in the tensor.

fn int_max_dim( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, dim: usize, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Gets the maximum element in the tensor along a dimension.

fn int_topk( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, dim: usize, k: usize, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Gets the values of the k maximum elements along a dimension.

fn int_topk_with_indices( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, dim: usize, k: usize, ) -> (<CubeBackend as BackendTypes>::IntTensorPrimitive, <CubeBackend as BackendTypes>::IntTensorPrimitive)

Gets the values of the k maximum elements along a dimension, and their indices.

fn int_max_dim_with_indices( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, dim: usize, ) -> (<CubeBackend as BackendTypes>::IntTensorPrimitive, <CubeBackend as BackendTypes>::IntTensorPrimitive)

Gets the maximum elements and corresponding indices along a dimension.

fn int_min_dim_with_indices( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, dim: usize, ) -> (<CubeBackend as BackendTypes>::IntTensorPrimitive, <CubeBackend as BackendTypes>::IntTensorPrimitive)

Gets the minimum elements and corresponding indices along a dimension.

fn int_max_abs( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Gets the maximum absolute element in the tensor.

fn int_max_abs_dim( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, dim: usize, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

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

fn int_min( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Gets the minimum element in the tensor.

fn int_min_dim( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, dim: usize, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Gets the minimum elements in the tensor along a dimension.

fn int_mean_dim( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, dim: usize, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

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

fn int_cumsum( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, dim: usize, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Computes the cumulative sum of elements along a dimension.

fn int_cumprod( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, dim: usize, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Computes the cumulative product of elements along a dimension.

fn int_cummin( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, dim: usize, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Computes the cumulative minimum of elements along a dimension.

fn int_cummax( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, dim: usize, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Computes the cumulative maximum of elements along a dimension.

fn int_argmax( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, dim: usize, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Gets the indices of the maximum elements along a dimension.

fn int_argtopk( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, dim: usize, k: usize, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Gets the indices of the k maximum elements along a dimension. If two elements share the same value, it will be ordered by the lowest coordinate

fn int_argmin( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, dim: usize, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Gets the indices of the minimum elements along a dimension.

fn int_clamp( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, min: Scalar, max: Scalar, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Clamps a tensor between a minimum and maximum value.

fn int_abs( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Returns a new tensor with absolute values.

fn int_sign( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Returns the signs of the int tensor.

fn int_into_float( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, out_dtype: FloatDType, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Converts int tensor to float tensor.

fn int_swap_dims( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, dim1: usize, dim2: usize, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Swaps two dimensions of an int tensor.

fn int_repeat_dim( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, dim: usize, times: usize, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

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

fn int_random( shape: Shape, distribution: Distribution, device: &<CubeBackend as BackendTypes>::Device, dtype: IntDType, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Creates a new int tensor with random values.

fn int_permute( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, axes: &[usize], ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Permutes the dimensions of a tensor.

fn int_expand( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, shape: Shape, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Broadcasts the int tensor to the given shape.

fn int_flip( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, axes: &[usize], ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

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

fn bitwise_and( lhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, rhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Bitwise AND operation for Int Tensors

fn bitwise_and_scalar( lhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, rhs: Scalar, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Bitwise AND operation for Int Tensors with a scalar

fn bitwise_or( lhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, rhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Bitwise OR operation for Int Tensors

fn bitwise_or_scalar( lhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, rhs: Scalar, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Bitwise OR operation for Int Tensors with a scalar

fn bitwise_xor( lhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, rhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Bitwise XOR operation for Int Tensors

fn bitwise_xor_scalar( lhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, rhs: Scalar, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Bitwise XOR operation for Int Tensors with a scalar

fn bitwise_not( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Bitwise NOT operation for Int Tensors

fn bitwise_left_shift( lhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, rhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Bitwise left shift operation for Int Tensors

fn bitwise_left_shift_scalar( lhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, rhs: Scalar, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Bitwise left shift operation for Int Tensors with a scalar

fn bitwise_right_shift( lhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, rhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Bitwise right shift operation for Int Tensors

fn bitwise_right_shift_scalar( lhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, rhs: Scalar, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Bitwise right shift operation for Int Tensors with a scalar

fn int_cast( tensor: <CubeBackend as BackendTypes>::IntTensorPrimitive, dtype: IntDType, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Converts a tensor to another integer data type.

fn int_unfold( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, dim: usize, size: usize, step: usize, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Unfold windows along a dimension.

fn int_powi( lhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, rhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Element-wise power with a IntTensor.

fn int_powi_scalar_impl( lhs: <CubeBackend as BackendTypes>::IntTensorPrimitive, rhs: Scalar, ) -> <CubeBackend as BackendTypes>::IntTensorPrimitive

Element-wise power with a scalar.

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

Selects the elements of the tensor where the mask is true, returned as a 1D tensor.

fn int_cat( tensors: Vec<<B as BackendTypes>::IntTensorPrimitive>, dim: usize, ) -> <B as BackendTypes>::IntTensorPrimitive

Concatenates the given tensors along the given dimension.

fn int_square( tensor: <B as BackendTypes>::IntTensorPrimitive, ) -> <B as BackendTypes>::IntTensorPrimitive

Element-wise square with a IntTensor.

fn int_powi_scalar( lhs: <B as BackendTypes>::IntTensorPrimitive, rhs: Scalar, ) -> <B as BackendTypes>::IntTensorPrimitive

Element-wise power with a scalar.

fn int_clamp_min( tensor: <B as BackendTypes>::IntTensorPrimitive, min: Scalar, ) -> <B as BackendTypes>::IntTensorPrimitive

Clamps a tensor under a minimum value.

fn int_clamp_max( tensor: <B as BackendTypes>::IntTensorPrimitive, max: Scalar, ) -> <B as BackendTypes>::IntTensorPrimitive

Clamps a tensor over a maximum value.

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

Element-wise negation.

fn int_mean( tensor: <B as BackendTypes>::IntTensorPrimitive, ) -> <B as BackendTypes>::IntTensorPrimitive

Computes the mean of all elements in the tensor.

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

Transposes an int tensor.

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

Creates a new tensor with values from the given range.

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

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

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

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

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

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

fn int_pad( tensor: <B as BackendTypes>::IntTensorPrimitive, padding: &[(usize, usize)], mode: PadMode, ) -> <B as BackendTypes>::IntTensorPrimitive

Pads a tensor with one (before, after) pair per dimension.

impl ModuleOps<CubeBackend> for CubeBackend

fn conv1d( x: <CubeBackend as BackendTypes>::FloatTensorPrimitive, weight: <CubeBackend as BackendTypes>::FloatTensorPrimitive, bias: Option<<CubeBackend as BackendTypes>::FloatTensorPrimitive>, options: ConvOptions<1>, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

One dimensional convolution.

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

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

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

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

fn conv2d( x: <CubeBackend as BackendTypes>::FloatTensorPrimitive, weight: <CubeBackend as BackendTypes>::FloatTensorPrimitive, bias: Option<<CubeBackend as BackendTypes>::FloatTensorPrimitive>, options: ConvOptions<2>, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Two dimensional convolution.

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

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

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

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

fn deform_conv2d( x: <CubeBackend as BackendTypes>::FloatTensorPrimitive, offset: <CubeBackend as BackendTypes>::FloatTensorPrimitive, weight: <CubeBackend as BackendTypes>::FloatTensorPrimitive, mask: Option<<CubeBackend as BackendTypes>::FloatTensorPrimitive>, bias: Option<<CubeBackend as BackendTypes>::FloatTensorPrimitive>, options: DeformConvOptions<2>, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Two dimensional deformable convolution.

fn deform_conv2d_backward( x: <CubeBackend as BackendTypes>::FloatTensorPrimitive, offset: <CubeBackend as BackendTypes>::FloatTensorPrimitive, weight: <CubeBackend as BackendTypes>::FloatTensorPrimitive, mask: Option<<CubeBackend as BackendTypes>::FloatTensorPrimitive>, bias: Option<<CubeBackend as BackendTypes>::FloatTensorPrimitive>, output_grad: <CubeBackend as BackendTypes>::FloatTensorPrimitive, options: DeformConvOptions<2>, ) -> DeformConv2dBackward<CubeBackend>

Backward pass for the deform_conv2d operation.

fn conv3d( x: <CubeBackend as BackendTypes>::FloatTensorPrimitive, weight: <CubeBackend as BackendTypes>::FloatTensorPrimitive, bias: Option<<CubeBackend as BackendTypes>::FloatTensorPrimitive>, options: ConvOptions<3>, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Three dimensional convolution.

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

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

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

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

fn conv_transpose2d( x: <CubeBackend as BackendTypes>::FloatTensorPrimitive, weight: <CubeBackend as BackendTypes>::FloatTensorPrimitive, bias: Option<<CubeBackend as BackendTypes>::FloatTensorPrimitive>, options: ConvTransposeOptions<2>, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Two dimensional transposed convolution.

fn conv_transpose3d( x: <CubeBackend as BackendTypes>::FloatTensorPrimitive, weight: <CubeBackend as BackendTypes>::FloatTensorPrimitive, bias: Option<<CubeBackend as BackendTypes>::FloatTensorPrimitive>, options: ConvTransposeOptions<3>, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Three dimensional transposed convolution.

fn avg_pool2d( x: <CubeBackend as BackendTypes>::FloatTensorPrimitive, kernel_size: [usize; 2], stride: [usize; 2], padding: [usize; 2], count_include_pad: bool, ceil_mode: bool, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Two dimensional avg pooling.

fn avg_pool2d_backward( x: <CubeBackend as BackendTypes>::FloatTensorPrimitive, grad: <CubeBackend as BackendTypes>::FloatTensorPrimitive, kernel_size: [usize; 2], stride: [usize; 2], padding: [usize; 2], count_include_pad: bool, ceil_mode: bool, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Backward pass for the avg pooling 2d operation.

fn max_pool2d( x: <CubeBackend as BackendTypes>::FloatTensorPrimitive, kernel_size: [usize; 2], stride: [usize; 2], padding: [usize; 2], dilation: [usize; 2], ceil_mode: bool, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Two dimensional max pooling.

fn max_pool2d_with_indices( x: <CubeBackend as BackendTypes>::FloatTensorPrimitive, kernel_size: [usize; 2], stride: [usize; 2], padding: [usize; 2], dilation: [usize; 2], ceil_mode: bool, indices_dtype: IntDType, ) -> MaxPool2dWithIndices<CubeBackend>

Two dimensional max pooling with indices.

fn max_pool2d_with_indices_backward( x: <CubeBackend as BackendTypes>::FloatTensorPrimitive, kernel_size: [usize; 2], stride: [usize; 2], padding: [usize; 2], dilation: [usize; 2], ceil_mode: bool, output_grad: <CubeBackend as BackendTypes>::FloatTensorPrimitive, indices: <CubeBackend as BackendTypes>::IntTensorPrimitive, ) -> MaxPool2dBackward<CubeBackend>

Backward pass for the max pooling 2d operation.

fn adaptive_avg_pool2d( x: <CubeBackend as BackendTypes>::FloatTensorPrimitive, output_size: [usize; 2], ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Two dimensional adaptive avg pooling.

fn adaptive_avg_pool2d_backward( x: <CubeBackend as BackendTypes>::FloatTensorPrimitive, grad: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Backward pass for the adaptive avg pooling 2d operation.

fn adaptive_avg_pool3d( x: <CubeBackend as BackendTypes>::FloatTensorPrimitive, output_size: [usize; 3], ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Three dimensional adaptive avg pooling.

fn adaptive_avg_pool3d_backward( x: <CubeBackend as BackendTypes>::FloatTensorPrimitive, grad: <CubeBackend as BackendTypes>::FloatTensorPrimitive, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Backward pass for the adaptive avg pooling 3d operation.

fn interpolate( x: <CubeBackend as BackendTypes>::FloatTensorPrimitive, output_size: [usize; 2], options: InterpolateOptions, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Down/up samples the input.

fn interpolate_backward( x: <CubeBackend as BackendTypes>::FloatTensorPrimitive, grad: <CubeBackend as BackendTypes>::FloatTensorPrimitive, output_size: [usize; 2], options: InterpolateOptions, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Backward pass for the interpolate operation.

fn attention( query: <CubeBackend as BackendTypes>::FloatTensorPrimitive, key: <CubeBackend as BackendTypes>::FloatTensorPrimitive, value: <CubeBackend as BackendTypes>::FloatTensorPrimitive, mask: Option<<CubeBackend as BackendTypes>::BoolTensorPrimitive>, attn_bias: Option<<CubeBackend as BackendTypes>::FloatTensorPrimitive>, options: AttentionModuleOptions, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Computes scaled dot-product attention: softmax(QKᵗ * scale) · V, where scale defaults to 1/sqrt(head_dim). Optionally applies masking, additive bias, causal masking, and softcap to the attention scores.

fn has_ctc_loss_backward() -> bool

Returns true if this backend implements ctc_loss_backward natively.

fn ctc_loss( log_probs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, targets: <CubeBackend as BackendTypes>::IntTensorPrimitive, input_lengths: <CubeBackend as BackendTypes>::IntTensorPrimitive, target_lengths: <CubeBackend as BackendTypes>::IntTensorPrimitive, blank: usize, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Computes the Connectionist Temporal Classification (CTC) loss.

fn ctc_loss_backward( log_probs: <CubeBackend as BackendTypes>::FloatTensorPrimitive, targets: <CubeBackend as BackendTypes>::IntTensorPrimitive, input_lengths: <CubeBackend as BackendTypes>::IntTensorPrimitive, target_lengths: <CubeBackend as BackendTypes>::IntTensorPrimitive, grad_loss: <CubeBackend as BackendTypes>::FloatTensorPrimitive, blank: usize, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Backward pass for ctc_loss: gradient w.r.t. log_probs.

fn batch_norm( x: <B as BackendTypes>::FloatTensorPrimitive, gamma: <B as BackendTypes>::FloatTensorPrimitive, beta: <B as BackendTypes>::FloatTensorPrimitive, mean: <B as BackendTypes>::FloatTensorPrimitive, variance: <B as BackendTypes>::FloatTensorPrimitive, epsilon: f64, ) -> <B as BackendTypes>::FloatTensorPrimitive

Applies batch normalization using explicitly supplied channel statistics.

fn batch_norm_train( x: <B as BackendTypes>::FloatTensorPrimitive, gamma: <B as BackendTypes>::FloatTensorPrimitive, beta: <B as BackendTypes>::FloatTensorPrimitive, epsilon: f64, ) -> BatchNormTrain<B>

Applies batch normalization with the statistics of the batch itself, and returns them.

fn batch_norm_train_backward( x: <B as BackendTypes>::FloatTensorPrimitive, gamma: <B as BackendTypes>::FloatTensorPrimitive, mean: <B as BackendTypes>::FloatTensorPrimitive, variance: <B as BackendTypes>::FloatTensorPrimitive, epsilon: f64, output_grad: <B as BackendTypes>::FloatTensorPrimitive, ) -> BatchNormTrainBackward<B>

Gradients of batch_norm_train with respect to its input, gamma and beta, given the gradient of its output. mean and variance are the statistics it returned.

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

Embedding operation.

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

Embedding backward operation.

fn linear( x: <B as BackendTypes>::FloatTensorPrimitive, weight: <B as BackendTypes>::FloatTensorPrimitive, bias: Option<<B as BackendTypes>::FloatTensorPrimitive>, ) -> <B as BackendTypes>::FloatTensorPrimitive

Linear transformation.

fn linear_x_backward( weight: <B as BackendTypes>::FloatTensorPrimitive, output_grad: <B as BackendTypes>::FloatTensorPrimitive, ) -> <B as BackendTypes>::FloatTensorPrimitive

Backward pass for linear, returning the gradient for x.

fn linear_weight_backward( x: <B as BackendTypes>::FloatTensorPrimitive, output_grad: <B as BackendTypes>::FloatTensorPrimitive, ) -> <B as BackendTypes>::FloatTensorPrimitive

Backward pass for linear, returning the gradient for weight.

fn linear_bias_backward( output_grad: <B as BackendTypes>::FloatTensorPrimitive, ) -> <B as BackendTypes>::FloatTensorPrimitive

Backward pass for linear, returning the gradient for bias.

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

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

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

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

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

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

fn conv_transpose1d( x: <B as BackendTypes>::FloatTensorPrimitive, weight: <B as BackendTypes>::FloatTensorPrimitive, bias: Option<<B as BackendTypes>::FloatTensorPrimitive>, options: ConvTransposeOptions<1>, ) -> <B as BackendTypes>::FloatTensorPrimitive

One dimensional transposed convolution.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Four-dimensional unfolding.

fn fold4d( x: <B as BackendTypes>::FloatTensorPrimitive, output_size: [usize; 2], kernel_size: [usize; 2], options: UnfoldOptions, ) -> <B as BackendTypes>::FloatTensorPrimitive

Four dimensional fold (col2im), the adjoint of unfold4d.

fn avg_pool1d( x: <B as BackendTypes>::FloatTensorPrimitive, kernel_size: usize, stride: usize, padding: usize, count_include_pad: bool, ceil_mode: bool, ) -> <B as BackendTypes>::FloatTensorPrimitive

One dimensional avg pooling.

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

Backward pass for the avg pooling 1d operation.

fn adaptive_avg_pool1d( x: <B as BackendTypes>::FloatTensorPrimitive, output_size: usize, ) -> <B as BackendTypes>::FloatTensorPrimitive

One dimensional adaptive avg pooling.

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

Backward pass for the adaptive avg pooling 1d operation.

fn max_pool1d( x: <B as BackendTypes>::FloatTensorPrimitive, kernel_size: usize, stride: usize, padding: usize, dilation: usize, ceil_mode: bool, ) -> <B as BackendTypes>::FloatTensorPrimitive

One dimensional max pooling.

fn max_pool1d_with_indices( x: <B as BackendTypes>::FloatTensorPrimitive, kernel_size: usize, stride: usize, padding: usize, dilation: usize, ceil_mode: bool, indices_dtype: IntDType, ) -> MaxPool1dWithIndices<B>

One dimensional max pooling with indices.

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

Backward pass for the max pooling 1d operation.

fn layer_norm( tensor: <B as BackendTypes>::FloatTensorPrimitive, gamma: <B as BackendTypes>::FloatTensorPrimitive, beta: Option<<B as BackendTypes>::FloatTensorPrimitive>, epsilon: f64, ) -> <B as BackendTypes>::FloatTensorPrimitive

Applies Layer Normalization over the last dimension of the input tensor.

impl QTensorOps<CubeBackend> for CubeBackend

fn q_from_data( data: TensorData, device: &<CubeBackend as BackendTypes>::Device, ) -> <CubeBackend as BackendTypes>::QuantizedTensorPrimitive

Creates a new tensor from the data structure.

fn quantize( tensor: <CubeBackend as BackendTypes>::FloatTensorPrimitive, scheme: &QuantScheme, qparams: QuantizationParametersPrimitive<CubeBackend>, ) -> <CubeBackend as BackendTypes>::QuantizedTensorPrimitive

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

fn dequantize( tensor: <CubeBackend as BackendTypes>::QuantizedTensorPrimitive, dtype: FloatDType, ) -> <CubeBackend as BackendTypes>::FloatTensorPrimitive

Convert the tensor back to a higher precision data type.

fn q_to_device( tensor: <CubeBackend as BackendTypes>::QuantizedTensorPrimitive, device: &<CubeBackend as BackendTypes>::Device, ) -> <CubeBackend as BackendTypes>::QuantizedTensorPrimitive

Moves the tensor to the given device.

fn q_reshape( tensor: <CubeBackend as BackendTypes>::QuantizedTensorPrimitive, shape: Shape, ) -> <CubeBackend as BackendTypes>::QuantizedTensorPrimitive

Reshapes a tensor.

async fn q_into_data( tensor: <CubeBackend as BackendTypes>::QuantizedTensorPrimitive, ) -> Result<TensorData, ExecutionError>

Converts the tensor to a data structure.

fn q_swap_dims( tensor: <CubeBackend as BackendTypes>::QuantizedTensorPrimitive, dim1: usize, dim2: usize, ) -> <CubeBackend as BackendTypes>::QuantizedTensorPrimitive

Swaps two dimensions of a tensor.

fn q_permute( tensor: <CubeBackend as BackendTypes>::QuantizedTensorPrimitive, axes: &[usize], ) -> <CubeBackend as BackendTypes>::QuantizedTensorPrimitive

Permutes the dimensions of a tensor.

fn q_flip( _tensor: <CubeBackend as BackendTypes>::QuantizedTensorPrimitive, _axes: &[usize], ) -> <CubeBackend as BackendTypes>::QuantizedTensorPrimitive

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

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

Multiplies two tensors together using matrix multiplication.

fn quantize_dynamic( tensor: <B as BackendTypes>::FloatTensorPrimitive, scheme: &QuantScheme, ) -> <B as BackendTypes>::QuantizedTensorPrimitive

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

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

Detaches a tensor from the computation graph.

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

Sets the require_grad flag of a tensor.

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

Returns the require_grad flag of a tensor.

fn q_expand( tensor: <B as BackendTypes>::QuantizedTensorPrimitive, shape: Shape, ) -> <B as BackendTypes>::QuantizedTensorPrimitive

Broadcasts the tensor to the given shape.

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

Transposes a tensor.

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

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

fn q_slice( tensor: <B as BackendTypes>::QuantizedTensorPrimitive, slices: &[Slice], ) -> <B as BackendTypes>::QuantizedTensorPrimitive

Select tensor elements corresponding to the given slices.

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

Gather elements from a tensor.

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

Repeat the tensor along the given dimension.

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

Adds two tensors together.

fn q_add_scalar( lhs: <B as BackendTypes>::QuantizedTensorPrimitive, rhs: Scalar, ) -> TensorPrimitive<B>

Adds a scalar to a tensor.

fn q_clamp_min( tensor: <B as BackendTypes>::QuantizedTensorPrimitive, min: Scalar, ) -> TensorPrimitive<B>

Clamps a tensor under a minimum value.

fn q_clamp_max( tensor: <B as BackendTypes>::QuantizedTensorPrimitive, max: Scalar, ) -> TensorPrimitive<B>

Clamps a tensor over a maximum value.

fn q_clamp( tensor: <B as BackendTypes>::QuantizedTensorPrimitive, min: Scalar, max: Scalar, ) -> TensorPrimitive<B>

Clamps a tensor between a minimum and maximum value.

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

Subtracts two tensors.

fn q_sub_scalar( lhs: <B as BackendTypes>::QuantizedTensorPrimitive, rhs: Scalar, ) -> TensorPrimitive<B>

Subtracts a scalar from a tensor.

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

Multiplies two tensors together element-wise.

fn q_mul_scalar( lhs: <B as BackendTypes>::QuantizedTensorPrimitive, rhs: Scalar, ) -> TensorPrimitive<B>

Multiplies a tensor by a scalar.

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

Divides two tensors element-wise.

fn q_div_scalar( lhs: <B as BackendTypes>::QuantizedTensorPrimitive, rhs: Scalar, ) -> TensorPrimitive<B>

Divides a tensor by a scalar.

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

Negates a tensor element-wise.

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

Calculates the reciprocals element-wise

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

Sum of all elements in a tensor.

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

Sum of all elements in a tensor along a dimension.

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

Product of all elements in a tensor.

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

Product of all elements in a tensor along a dimension.

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

Mean of all elements in a tensor.

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

Mean of all elements in a tensor along a dimension.

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

Computes the cumulative sum of elements along a dimension.

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

Computes the cumulative product of elements along a dimension.

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

Computes the cumulative minimum of elements along a dimension.

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

Computes the cumulative maximum of elements along a dimension.

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

Returns a new tensor with exponential values.

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

Returns a new tensor with natural logarithm values.

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

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

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

Element-wise power with another tensor.

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

Element-wise power with an IntTensor.

fn q_powi_scalar( lhs: <B as BackendTypes>::QuantizedTensorPrimitive, rhs: Scalar, ) -> TensorPrimitive<B>

Element-wise power with an int scalar.

fn q_powf_scalar( tensor: <B as BackendTypes>::QuantizedTensorPrimitive, value: Scalar, ) -> TensorPrimitive<B>

Element-wise power with a float scalar.

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

Returns a new tensor with square root values.

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

Returns a new tensor with absolute values.

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

Returns a new tensor with cosine values.

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

Returns a new tensor with sine values.

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

Returns a new tensor with tangent values.

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

Returns a new tensor with hyperbolic cosine values.

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

Returns a new tensor with hyperbolic sine values.

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

Returns a new tensor with hyperbolic tangent values.

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

Returns a new tensor with the error function values.

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

Concatenates tensors along a dimension.

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

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

fn q_argtopk( tensor: <B as BackendTypes>::QuantizedTensorPrimitive, dim: usize, k: usize, out_dtype: IntDType, ) -> <B as BackendTypes>::IntTensorPrimitive

Gets the indices of the k maximum elements of a tensor along an axis. If two elements are equals, order them by the lowest indices

fn q_topk( tensor: <B as BackendTypes>::QuantizedTensorPrimitive, dim: usize, k: usize, ) -> <B as BackendTypes>::QuantizedTensorPrimitive

Gets the values of the k maximum elements of a tensor along an axis.

fn q_topk_with_indices( tensor: <B as BackendTypes>::QuantizedTensorPrimitive, dim: usize, k: usize, out_dtype: IntDType, ) -> (<B as BackendTypes>::QuantizedTensorPrimitive, <B as BackendTypes>::IntTensorPrimitive)

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

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

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

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

Gets the maximum element of a tensor.

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

Gets the maximum elements of a tensor along an axis.

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

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

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

Gets the minimum element of a tensor.

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

Gets the minimum elements of a tensor along an axis.

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

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

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

Gets the maximum element of a tensor.

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

Gets the maximum elements of a tensor along an axis.

fn q_any( tensor: <B as BackendTypes>::QuantizedTensorPrimitive, out_dtype: BoolStore, ) -> <B as BackendTypes>::BoolTensorPrimitive

Tests if any element in the tensor evaluates to True.

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

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

fn q_all( tensor: <B as BackendTypes>::QuantizedTensorPrimitive, out_dtype: BoolStore, ) -> <B as BackendTypes>::BoolTensorPrimitive

Tests if all elements in the tensor evaluate to True.

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

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

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

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

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

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

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

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

impl TransactionOps<CubeBackend> for CubeBackend

async fn tr_execute( transaction: TransactionPrimitive<CubeBackend>, ) -> Result<TransactionPrimitiveData, ExecutionError>

Executes a transaction and return its data.