mabor::tensor::ops

Trait QTensorOps

pub trait QTensorOps<B>
where
    B: Backend,
{

Show 74 methods    // Required methods
    fn q_from_data(
        data: TensorData,
        device: &<B as Backend>::Device,
    ) -> <B as Backend>::QuantizedTensorPrimitive;
    fn quantize(
        tensor: <B as Backend>::FloatTensorPrimitive,
        scheme: &QuantScheme,
        qparams: QuantizationParametersPrimitive<B>,
    ) -> <B as Backend>::QuantizedTensorPrimitive;
    fn dequantize(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
    ) -> <B as Backend>::FloatTensorPrimitive;
    fn q_device(
        tensor: &<B as Backend>::QuantizedTensorPrimitive,
    ) -> <B as Backend>::Device;
    fn q_to_device(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
        device: &<B as Backend>::Device,
    ) -> <B as Backend>::QuantizedTensorPrimitive;
    fn q_reshape(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
        shape: Shape,
    ) -> <B as Backend>::QuantizedTensorPrimitive;
    fn q_into_data(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
    ) -> impl Future<Output = TensorData> + Send;
    fn q_expand(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
        shape: Shape,
    ) -> <B as Backend>::QuantizedTensorPrimitive;
    fn q_swap_dims(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
        dim1: usize,
        dim2: usize,
    ) -> <B as Backend>::QuantizedTensorPrimitive;
    fn q_permute(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
        axes: &[usize],
    ) -> <B as Backend>::QuantizedTensorPrimitive;
    fn q_flip(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
        axes: &[usize],
    ) -> <B as Backend>::QuantizedTensorPrimitive;
    fn q_select(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
        dim: usize,
        indices: <B as Backend>::IntTensorPrimitive,
    ) -> <B as Backend>::QuantizedTensorPrimitive;
    fn q_slice(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
        ranges: &[Range<usize>],
    ) -> <B as Backend>::QuantizedTensorPrimitive;

    // Provided methods
    fn quantize_dynamic(
        tensor: <B as Backend>::FloatTensorPrimitive,
        scheme: &QuantScheme,
    ) -> <B as Backend>::QuantizedTensorPrimitive { ... }
    fn q_detach(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
    ) -> <B as Backend>::QuantizedTensorPrimitive { ... }
    fn q_set_require_grad(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
        _require_grad: bool,
    ) -> <B as Backend>::QuantizedTensorPrimitive { ... }
    fn q_is_require_grad(
        _tensor: &<B as Backend>::QuantizedTensorPrimitive,
    ) -> bool { ... }
    fn q_transpose(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
    ) -> <B as Backend>::QuantizedTensorPrimitive { ... }
    fn q_gather(
        dim: usize,
        tensor: <B as Backend>::QuantizedTensorPrimitive,
        indices: <B as Backend>::IntTensorPrimitive,
    ) -> <B as Backend>::QuantizedTensorPrimitive { ... }
    fn q_repeat_dim(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
        dim: usize,
        times: usize,
    ) -> <B as Backend>::QuantizedTensorPrimitive { ... }
    fn q_add(
        lhs: <B as Backend>::QuantizedTensorPrimitive,
        rhs: <B as Backend>::QuantizedTensorPrimitive,
    ) -> TensorPrimitive<B> { ... }
    fn q_add_scalar(
        lhs: <B as Backend>::QuantizedTensorPrimitive,
        rhs: <B as Backend>::FloatElem,
    ) -> TensorPrimitive<B> { ... }
    fn q_clamp_min(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
        min: <B as Backend>::FloatElem,
    ) -> TensorPrimitive<B> { ... }
    fn q_clamp_max(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
        max: <B as Backend>::FloatElem,
    ) -> TensorPrimitive<B> { ... }
    fn q_clamp(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
        min: <B as Backend>::FloatElem,
        max: <B as Backend>::FloatElem,
    ) -> TensorPrimitive<B> { ... }
    fn q_sub(
        lhs: <B as Backend>::QuantizedTensorPrimitive,
        rhs: <B as Backend>::QuantizedTensorPrimitive,
    ) -> TensorPrimitive<B> { ... }
    fn q_sub_scalar(
        lhs: <B as Backend>::QuantizedTensorPrimitive,
        rhs: <B as Backend>::FloatElem,
    ) -> TensorPrimitive<B> { ... }
    fn q_mul(
        lhs: <B as Backend>::QuantizedTensorPrimitive,
        rhs: <B as Backend>::QuantizedTensorPrimitive,
    ) -> TensorPrimitive<B> { ... }
    fn q_mul_scalar(
        lhs: <B as Backend>::QuantizedTensorPrimitive,
        rhs: <B as Backend>::FloatElem,
    ) -> TensorPrimitive<B> { ... }
    fn q_div(
        lhs: <B as Backend>::QuantizedTensorPrimitive,
        rhs: <B as Backend>::QuantizedTensorPrimitive,
    ) -> TensorPrimitive<B> { ... }
    fn q_div_scalar(
        lhs: <B as Backend>::QuantizedTensorPrimitive,
        rhs: <B as Backend>::FloatElem,
    ) -> TensorPrimitive<B> { ... }
    fn q_matmul(
        lhs: <B as Backend>::QuantizedTensorPrimitive,
        rhs: <B as Backend>::QuantizedTensorPrimitive,
    ) -> TensorPrimitive<B> { ... }
    fn q_neg(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
    ) -> TensorPrimitive<B> { ... }
    fn q_recip(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
    ) -> TensorPrimitive<B> { ... }
    fn q_sum(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
    ) -> TensorPrimitive<B> { ... }
    fn q_sum_dim(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
        dim: usize,
    ) -> TensorPrimitive<B> { ... }
    fn q_prod(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
    ) -> TensorPrimitive<B> { ... }
    fn q_prod_dim(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
        dim: usize,
    ) -> TensorPrimitive<B> { ... }
    fn q_mean(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
    ) -> TensorPrimitive<B> { ... }
    fn q_mean_dim(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
        dim: usize,
    ) -> TensorPrimitive<B> { ... }
    fn q_exp(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
    ) -> TensorPrimitive<B> { ... }
    fn q_log(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
    ) -> TensorPrimitive<B> { ... }
    fn q_log1p(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
    ) -> TensorPrimitive<B> { ... }
    fn q_powf(
        lhs: <B as Backend>::QuantizedTensorPrimitive,
        rhs: <B as Backend>::QuantizedTensorPrimitive,
    ) -> TensorPrimitive<B> { ... }
    fn q_powi(
        lhs: <B as Backend>::QuantizedTensorPrimitive,
        rhs: <B as Backend>::IntTensorPrimitive,
    ) -> TensorPrimitive<B> { ... }
    fn q_powi_scalar(
        lhs: <B as Backend>::QuantizedTensorPrimitive,
        rhs: <B as Backend>::IntElem,
    ) -> TensorPrimitive<B> { ... }
    fn q_powf_scalar(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
        value: f32,
    ) -> TensorPrimitive<B> { ... }
    fn q_sqrt(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
    ) -> TensorPrimitive<B> { ... }
    fn q_abs(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
    ) -> <B as Backend>::QuantizedTensorPrimitive { ... }
    fn q_cos(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
    ) -> TensorPrimitive<B> { ... }
    fn q_sin(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
    ) -> TensorPrimitive<B> { ... }
    fn q_tan(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
    ) -> TensorPrimitive<B> { ... }
    fn q_cosh(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
    ) -> TensorPrimitive<B> { ... }
    fn q_sinh(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
    ) -> TensorPrimitive<B> { ... }
    fn q_tanh(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
    ) -> TensorPrimitive<B> { ... }
    fn q_erf(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
    ) -> TensorPrimitive<B> { ... }
    fn q_cat(
        tensors: Vec<<B as Backend>::QuantizedTensorPrimitive>,
        dim: usize,
    ) -> <B as Backend>::QuantizedTensorPrimitive { ... }
    fn q_argmax(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
        dim: usize,
    ) -> <B as Backend>::IntTensorPrimitive { ... }
    fn q_argmin(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
        dim: usize,
    ) -> <B as Backend>::IntTensorPrimitive { ... }
    fn q_max(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
    ) -> <B as Backend>::QuantizedTensorPrimitive { ... }
    fn q_max_dim(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
        dim: usize,
    ) -> <B as Backend>::QuantizedTensorPrimitive { ... }
    fn q_max_dim_with_indices(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
        dim: usize,
    ) -> (<B as Backend>::QuantizedTensorPrimitive, <B as Backend>::IntTensorPrimitive) { ... }
    fn q_min(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
    ) -> <B as Backend>::QuantizedTensorPrimitive { ... }
    fn q_min_dim(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
        dim: usize,
    ) -> <B as Backend>::QuantizedTensorPrimitive { ... }
    fn q_min_dim_with_indices(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
        dim: usize,
    ) -> (<B as Backend>::QuantizedTensorPrimitive, <B as Backend>::IntTensorPrimitive) { ... }
    fn q_max_abs(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
    ) -> <B as Backend>::QuantizedTensorPrimitive { ... }
    fn q_max_abs_dim(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
        dim: usize,
    ) -> <B as Backend>::QuantizedTensorPrimitive { ... }
    fn q_any(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
    ) -> <B as Backend>::BoolTensorPrimitive { ... }
    fn q_any_dim(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
        dim: usize,
    ) -> <B as Backend>::BoolTensorPrimitive { ... }
    fn q_all(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
    ) -> <B as Backend>::BoolTensorPrimitive { ... }
    fn q_all_dim(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
        dim: usize,
    ) -> <B as Backend>::BoolTensorPrimitive { ... }
    fn q_sort(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
        dim: usize,
        descending: bool,
    ) -> <B as Backend>::QuantizedTensorPrimitive { ... }
    fn q_sort_with_indices(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
        dim: usize,
        descending: bool,
    ) -> (<B as Backend>::QuantizedTensorPrimitive, <B as Backend>::IntTensorPrimitive) { ... }
    fn q_argsort(
        tensor: <B as Backend>::QuantizedTensorPrimitive,
        dim: usize,
        descending: bool,
    ) -> <B as Backend>::IntTensorPrimitive { ... }

}
Expand description

Operations on quantized tensors.

§Return Type Semantics

The return type of each operation indicates how quantization is handled:

§QuantizedTensor<B>

If the method returns a QuantizedTensor<B>, the operation is expected to preserve the quantized representation. Implementations should avoid dequantizing when possible to maintain performance. For example, shape or layout changes such as expand or transpose preserve quantization.

Note: while this currently doesn’t affect the quantized tensor parameters (only per-tensor is supported at the time of writing), other quantization levels (e.g., per-block) may require re-ordering the quantization parameters to match the new layout.

§TensorPrimitive<B>

If the method returns a TensorPrimitive<B> enum, the return type should align with propagation strategy specified in the quantization scheme. The output should remain quantized (TensorPrimitive::QFloat) returned in floating-point form (TensorPrimitive::Float).

This distinction allows for fine-grained control over mixed-precision flows while still operating through a unified API.

Required Methods§

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

Creates a new tensor from the data structure.

§Arguments
  • data - The data structure.
  • device - The device to create the tensor on.
§Returns

The tensor with the given data.

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

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

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

Convert the tensor back to a higher precision data type.

fn q_device( tensor: &<B as Backend>::QuantizedTensorPrimitive, ) -> <B as Backend>::Device

Gets the device of the tensor.

§Arguments
  • tensor - The tensor.
§Returns

The device of the tensor.

fn q_to_device( tensor: <B as Backend>::QuantizedTensorPrimitive, device: &<B as Backend>::Device, ) -> <B as Backend>::QuantizedTensorPrimitive

Moves the tensor to the given device.

§Arguments
  • tensor - The tensor.
  • device - The device to move the tensor to.
§Returns

The tensor on the given device.

fn q_reshape( tensor: <B as Backend>::QuantizedTensorPrimitive, shape: Shape, ) -> <B as Backend>::QuantizedTensorPrimitive

Reshapes a tensor.

§Arguments
  • tensor - The tensor to reshape.
  • shape - The new shape of the tensor.
§Returns

The tensor with the new shape.

fn q_into_data( tensor: <B as Backend>::QuantizedTensorPrimitive, ) -> impl Future<Output = TensorData> + Send

Converts the tensor to a data structure.

§Arguments
  • tensor - The tensor.
§Returns

The data structure with the tensor’s data.

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

Broadcasts the tensor to the given shape.

fn q_swap_dims( tensor: <B as Backend>::QuantizedTensorPrimitive, dim1: usize, dim2: usize, ) -> <B as Backend>::QuantizedTensorPrimitive

Swaps two dimensions of a tensor.

§Arguments
  • tensor - The tensor to swap the dimensions of.
  • dim1 - The first dimension to swap.
  • dim2 - The second dimension to swap.
§Returns

The tensor with the dimensions swapped.

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

Permutes the dimensions of a tensor.

§Arguments
  • tensor - The tensor to permute the dimensions of.
  • axes - The new order of the dimensions.
§Returns

The tensor with the dimensions permuted.

fn q_flip( tensor: <B as Backend>::QuantizedTensorPrimitive, axes: &[usize], ) -> <B as Backend>::QuantizedTensorPrimitive

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

§Arguments
  • tensor - The tensor to reverse.
  • axes - The axes to reverse.

The tensor with the elements reversed.

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

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

§Arguments
  • tensor - The tensor to select from.
  • dim - The dimension to select from.
  • indices - The indices to select.
§Returns

The selected elements.

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

Select tensor elements corresponding for the given ranges.

§Arguments
  • tensor - The tensor to select from.
  • ranges - The ranges to select.
§Returns

The selected elements in a new tensor.

Provided Methods§

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

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

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

Detaches a tensor from the computation graph.

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

Sets the require_grad flag of a tensor.

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

Returns the require_grad flag of a tensor.

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

Transposes a tensor.

§Arguments
  • tensor - The tensor to transpose.
§Returns

The transposed tensor.

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

Gather elements from a tensor.

§Arguments
  • dim - The dimension to gather from.
  • tensor - The tensor to gather from.
  • indices - The indices to gather.
§Returns

The gathered elements.

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

Repeat the tensor along the given dimension.

§Arguments
  • tensor - The tensor.
  • dim - The dimension to repeat.
  • times - The number of times to repeat the dimension.
§Returns

The tensor with the given dimension repeated.

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

Adds two tensors together.

§Arguments
  • lhs - The left hand side tensor.
  • rhs - The right hand side tensor.
§Returns

The result of adding the two tensors together.

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

Adds a scalar to a tensor.

§Arguments
  • lhs - The left hand side tensor.
  • rhs - The right hand side scalar.
§Returns

The result of adding the scalar to the tensor.

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

Clamps a tensor under a minimum value.

§Arguments
  • tensor - The tensor to clamp.
  • min - The minimum value.
§Returns

The clamped tensor.

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

Clamps a tensor over a maximum value.

§Arguments
  • tensor - The tensor to clamp.
  • max - The maximum value.
§Returns

The clamped tensor.

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

Clamps a tensor between a minimum and maximum value.

§Arguments
  • tensor - The tensor to clamp.
  • min - The minimum value.
  • max - The maximum value.
§Returns

The clamped tensor.

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

Subtracts two tensors.

§Arguments
  • lhs - The left hand side tensor.
  • rhs - The right hand side tensor.
§Returns

The result of subtracting the two tensors.

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

Subtracts a scalar from a tensor.

§Arguments
  • lhs - The left hand side tensor.
  • rhs - The right hand side scalar.
§Returns

The result of subtracting the scalar from the tensor.

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

Multiplies two tensors together element-wise.

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

Multiplies a tensor by a scalar.

§Arguments
  • lhs - The left hand side tensor.
  • rhs - The right hand side scalar.
§Returns

The result of multiplying the tensor by the scalar.

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

Divides two tensors element-wise.

§Arguments
  • lhs - The left hand side tensor.
  • rhs - The right hand side tensor.
§Returns

The result of dividing the two tensors.

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

Divides a tensor by a scalar.

§Arguments
  • lhs - The left hand side tensor.
  • rhs - The right hand side scalar.
§Returns

The result of dividing the tensor by the scalar.

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

Multiplies two tensors together using matrix multiplication.

§Arguments
  • lhs - The left hand side tensor.
  • rhs - The right hand side tensor.
§Returns

The result of multiplying the two tensors together using matrix multiplication.

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

Negates a tensor element-wise.

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

Calculates the reciprocals element-wise

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

Sum of all elements in a tensor.

§Arguments
  • tensor - The tensor to sum.
§Returns

A scalar tensor with the sum of all elements in tensor.

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

Sum of all elements in a tensor along a dimension.

§Arguments
  • tensor - The tensor to sum.
  • dim - The dimension along which to sum.
§Returns

A tensor with the sum of all elements in tensor along dim.

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

Product of all elements in a tensor.

§Arguments
  • tensor - The tensor to product.
§Returns

A scalar tensor with the product of all elements in tensor.

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

Product of all elements in a tensor along a dimension.

§Arguments
  • tensor - The tensor to product.
§Returns

A tensor with the product of all elements in tensor along dim.

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

Mean of all elements in a tensor.

§Arguments
  • tensor - The tensor to mean.
§Returns

A scalar tensor with the mean of all elements in tensor.

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

Mean of all elements in a tensor along a dimension.

§Arguments
  • tensor - The tensor to mean.
  • dim - The dimension along which to mean.
§Returns

A tensor with the mean of all elements in tensor along dim.

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

Returns a new tensor with exponential values.

§Arguments
  • tensor - The tensor to exponentiate.
§Returns

A tensor with the same shape as tensor with exponential values.

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

Returns a new tensor with natural logarithm values.

§Arguments
  • tensor - The tensor to take the logarithm of.
§Returns

A tensor with the same shape as tensor with natural logarithm values.

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

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

§Arguments
  • tensor - The tensor to take the logarithm of.
§Returns

A tensor with the same shape as tensor with logarithm values of (1 + Xi).

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

Element-wise power with another tensor.

§Arguments
  • lhs - The left hand side tensor.
  • rhs - The right hand side tensor.
§Returns

The elements of lhs raised to the power of the elements of rhs.

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

Element-wise power with an IntTensor.

§Arguments
  • lhs - The left hand side tensor.
  • rhs - The right hand side floatTensor.
§Returns

The elements of lhs raised to the value of rhs. Result is an IntTensor.

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

Element-wise power with an int scalar.

§Arguments
  • lhs - The left hand side tensor.
  • rhs - The right hand side scalar.
§Returns

The elements of lhs raised to the value of rhs.

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

Element-wise power with a float scalar.

§Arguments
  • tensor - The tensor to exponentiate.
  • value - The exponent.
§Returns

A tensor with the same shape as tensor with values raised to the power of value.

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

Returns a new tensor with square root values.

§Arguments
  • tensor - The tensor to take the square root of.
§Returns

A tensor with the same shape as tensor with square root values.

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

Returns a new tensor with absolute values.

§Arguments
  • tensor - The tensor to take absolute value of.
§Returns

A tensor with the same shape as tensor with absolute values.

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

Returns a new tensor with cosine values.

§Arguments
  • tensor - The tensor to take the cosine of.
§Returns

A tensor with the same shape as tensor with cosine values.

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

Returns a new tensor with sine values.

§Arguments
  • tensor - The tensor to take the sine of.
§Returns

A tensor with the same shape as tensor with sine values.

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

Returns a new tensor with tangent values.

§Arguments
  • tensor - The tensor to take the tangent of.
§Returns

A tensor with the same shape as tensor with tangent values.

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

Returns a new tensor with hyperbolic cosine values.

§Arguments
  • tensor - The tensor to take the hyperbolic cosine of.
§Returns

A tensor with the same shape as tensor with hyperbolic cosine values.

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

Returns a new tensor with hyperbolic sine values.

§Arguments
  • tensor - The tensor to take the hyperbolic sine of.
§Returns

A tensor with the same shape as tensor with hyperbolic sine values.

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

Returns a new tensor with hyperbolic tangent values.

§Arguments
  • tensor - The tensor to take the hyperbolic tangent of.
§Returns

A tensor with the same shape as tensor with hyperbolic tangent values.

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

Returns a new tensor with the error function values.

§Arguments
  • tensor - The tensor to take the error function of.
§Returns

A tensor with the same shape as tensor with error function values.

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

Concatenates tensors along a dimension.

§Arguments
  • tensors - The tensors to concatenate.
  • dim - The dimension along which to concatenate.
§Returns

A tensor with the concatenated tensors along dim.

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

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

§Arguments
  • tensor - The tensor to get the maximum elements of.
  • dim - The dimension along which to get the maximum elements.
§Returns

A tensor with the indices of the maximum elements of tensor along dim.

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

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

§Arguments
  • tensor - The tensor to get the minimum elements of.
  • dim - The dimension along which to get the minimum elements.
§Returns

A tensor with the indices of the minimum elements of tensor along dim.

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

Gets the maximum element of a tensor.

§Arguments
  • tensor - The tensor to get the maximum elements of.
§Returns

A tensor with the maximum element of tensor.

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

Gets the maximum elements of a tensor along an axis.

§Arguments
  • tensor - The tensor to get the maximum elements of.
  • dim - The dimension along which to get the maximum elements.
§Returns

A tensor with the maximum elements of tensor along dim.

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

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

§Arguments
  • tensor - The tensor to get the maximum elements of.
  • dim - The dimension along which to get the maximum elements.
§Returns

A tuple with the maximum elements of tensor along dim and their indices.

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

Gets the minimum element of a tensor.

§Arguments
  • tensor - The tensor to get the minimum elements of.
§Returns

A tensor with the minimum element of tensor.

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

Gets the minimum elements of a tensor along an axis.

§Arguments
  • tensor - The tensor to get the minimum elements of.
  • dim - The dimension along which to get the minimum elements.
§Returns

A tensor with the minimum elements of tensor along dim.

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

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

§Arguments
  • tensor - The tensor to get the minimum elements of.
  • dim - The dimension along which to get the minimum elements.
§Returns

A tuple with the minimum elements of tensor along dim and their indices.

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

Gets the maximum element of a tensor.

§Arguments
  • tensor - The tensor to get the maximum elements of.
§Returns

A tensor with the maximum element of tensor.

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

Gets the maximum elements of a tensor along an axis.

§Arguments
  • tensor - The tensor to get the maximum elements of.
  • dim - The dimension along which to get the maximum elements.
§Returns

A tensor with the maximum elements of tensor along dim.

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

Tests if any element in the tensor evaluates to True.

§Arguments
  • tensor - The tensor to test.
§Returns

A boolean tensor with a single element, True if any element in the tensor is True, False otherwise.

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

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

§Arguments
  • tensor - The tensor to test.
  • dim - The axis along which to test.
§Returns

A boolean tensor Tensor<B, D, Bool> with the same size as input tensor, except in the dim axis where the size is 1. The elem in the dim axis is True if any element along this dim in the input evaluates to True, False otherwise.

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

Tests if all elements in the tensor evaluate to True.

§Arguments
  • tensor - The tensor to test.
§Returns

A boolean tensor Tensor<B, 1, Bool> with a single element, True if all elements in the input tensor evaluate to True, False otherwise.

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

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

§Arguments
  • tensor - The tensor to test.
  • dim - The axis along which to test.
§Returns

A boolean tensor Tensor<B, D, Bool> with the same size as input tensor, except in the dim axis where the size is 1. The elem in the dim axis is True if all elements along this dim in the input evaluates to True, False otherwise.

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

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

This sort is unstable (i.e., may reorder equal elements).

§Arguments
  • tensor - The input tensor.
  • dim - The axis along which to sort.
  • descending - The sorting order.
§Returns

A tensor with the same shape as the input tensor, where the elements are sorted by value.

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

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

This sort is unstable (i.e., may reorder equal elements).

§Arguments
  • tensor - The input tensor.
  • dim - The axis along which to sort.
  • descending - The sorting order.
§Returns

A tensor with the same shape as the input tensor and corresponding indices, where the elements are sorted by value and the indices map back to the original input tensor.

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

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

This sort is unstable (i.e., may reorder equal elements).

§Arguments
  • tensor - The input tensor.
  • dim - The axis along which to sort.
  • descending - The sorting order.
§Returns

A tensor with the same shape as the input tensor the indices map back to the original input tensor.

Dyn Compatibility§

This trait is not dyn compatible.

In older versions of Rust, dyn compatibility was called "object safety", so this trait is not object safe.

Implementations on Foreign Types§

§

impl<E, I, Q> QTensorOps<NdArray<E, I, Q>> for NdArray<E, I, Q>
where E: FloatNdArrayElement, I: IntNdArrayElement, Q: QuantElement,
§

fn q_from_data( data: TensorData, _device: &NdArrayDevice, ) -> <NdArray<E, I, Q> as Backend>::QuantizedTensorPrimitive

§

fn quantize( tensor: <NdArray<E, I, Q> as Backend>::FloatTensorPrimitive, scheme: &QuantScheme, qparams: QuantizationParametersPrimitive<NdArray<E, I, Q>>, ) -> <NdArray<E, I, Q> as Backend>::QuantizedTensorPrimitive

§

fn dequantize( tensor: <NdArray<E, I, Q> as Backend>::QuantizedTensorPrimitive, ) -> <NdArray<E, I, Q> as Backend>::FloatTensorPrimitive

§

fn q_device( _tensor: &<NdArray<E, I, Q> as Backend>::QuantizedTensorPrimitive, ) -> NdArrayDevice

§

fn q_to_device( tensor: <NdArray<E, I, Q> as Backend>::QuantizedTensorPrimitive, _device: &NdArrayDevice, ) -> <NdArray<E, I, Q> as Backend>::QuantizedTensorPrimitive

§

fn q_reshape( tensor: <NdArray<E, I, Q> as Backend>::QuantizedTensorPrimitive, shape: Shape, ) -> <NdArray<E, I, Q> as Backend>::QuantizedTensorPrimitive

§

async fn q_into_data( tensor: <NdArray<E, I, Q> as Backend>::QuantizedTensorPrimitive, ) -> TensorData

§

fn q_swap_dims( tensor: <NdArray<E, I, Q> as Backend>::QuantizedTensorPrimitive, dim1: usize, dim2: usize, ) -> <NdArray<E, I, Q> as Backend>::QuantizedTensorPrimitive

§

fn q_permute( tensor: <NdArray<E, I, Q> as Backend>::QuantizedTensorPrimitive, axes: &[usize], ) -> <NdArray<E, I, Q> as Backend>::QuantizedTensorPrimitive

§

fn q_flip( tensor: <NdArray<E, I, Q> as Backend>::QuantizedTensorPrimitive, axes: &[usize], ) -> <NdArray<E, I, Q> as Backend>::QuantizedTensorPrimitive

§

fn q_gather( dim: usize, tensor: <NdArray<E, I, Q> as Backend>::QuantizedTensorPrimitive, indices: <NdArray<E, I, Q> as Backend>::IntTensorPrimitive, ) -> <NdArray<E, I, Q> as Backend>::QuantizedTensorPrimitive

§

fn q_select( tensor: <NdArray<E, I, Q> as Backend>::QuantizedTensorPrimitive, dim: usize, indices: <NdArray<E, I, Q> as Backend>::IntTensorPrimitive, ) -> <NdArray<E, I, Q> as Backend>::QuantizedTensorPrimitive

§

fn q_slice( tensor: <NdArray<E, I, Q> as Backend>::QuantizedTensorPrimitive, ranges: &[Range<usize>], ) -> <NdArray<E, I, Q> as Backend>::QuantizedTensorPrimitive

§

fn q_argmax( tensor: <NdArray<E, I, Q> as Backend>::QuantizedTensorPrimitive, dim: usize, ) -> <NdArray<E, I, Q> as Backend>::IntTensorPrimitive

§

fn q_argmin( tensor: <NdArray<E, I, Q> as Backend>::QuantizedTensorPrimitive, dim: usize, ) -> <NdArray<E, I, Q> as Backend>::IntTensorPrimitive

§

fn q_expand( tensor: <NdArray<E, I, Q> as Backend>::QuantizedTensorPrimitive, shape: Shape, ) -> <NdArray<E, I, Q> as Backend>::QuantizedTensorPrimitive

Implementors§

§

impl<B, C> QTensorOps<Autodiff<B, C>> for Autodiff<B, C>
where B: Backend, C: CheckpointStrategy,