xtensor.type – Types and Variables

XTensorVariable creation functions

pytensor.xtensor.type.as_xtensor(x, dims=None, *, name=None)

Convert a variable or data to an XTensorVariable.

Parameters:

• x (Variable or data) –

• dims (Sequence[str] or None, optional) – If dims are provided, TensorVariable (or data) will be converted to an XTensorVariable with those dims. XTensorVariables will be returned as is, if the dims match. Otherwise, a ValueError is raised. If dims are not provided, and the data is not a scalar, an XTensorVariable or xarray.DataArray, an error is raised.

• name (str or None, optional) – Name of the resulting XTensorVariable.

pytensor.xtensor.type.xtensor(name=None, *, dims, dtype='floatX')

Create an XTensorVariable.

Parameters:

• name (str or None, optional) – The name of the variable

• dims (Sequence[AsDim]) – The dimensions of the tensor

• dtype (str or np.dtype, optional) – The data type of the tensor. Defaults to ‘floatX’ (config.floatX).

Returns:

A new XTensorVariable with the specified name, dims, shape, and dtype.

Return type:

XTensorVariable

pytensor.xtensor.type.xtensor_constant(x, name=None, dims=None)

Convert a constant value to an XTensorConstant.

XTensor Type and Variable classes

class pytensor.xtensor.type.XTensorConstant(type, data, name=None)

Constant of XtensorType.

class pytensor.xtensor.type.XTensorType(dtype, *, dims, name=None)

A Type for Xtensors (Xarray-like tensors with dims).

clone(dtype=None, dims=None, shape=None, **kwargs)

Clone a copy of this type with the given arguments/keyword values, if any.

constant_type

alias of XTensorConstant

convert_variable(var)

Produce a Variable that’s compatible with both self and var.type, if possible.

A compatible Variable is a Variable with a Type that’s the “narrower” of self and var.type.

If a compatible Type cannot be found, this method will return None.

filter(data, strict=False, allow_downcast=None)

Return data or an appropriately wrapped/converted data.

Subclass implementations should raise a TypeError exception if the data is not of an acceptable type.

Parameters:

• data (array-like) – The data to be filtered/converted.

• strict (bool (optional)) – If True, the data returned must be the same as the data passed as an argument.

• allow_downcast (bool (optional)) – If strict is False, and allow_downcast is True, the data may be cast to an appropriate type. If allow_downcast is False, it may only be up-cast and not lose precision. If allow_downcast is None (default), the behaviour can be type-dependent, but for now it means only Python floats can be down-casted, and only to floatX scalars.

filter_variable(other, allow_convert=True)

Convert a other into a Variable with a Type that’s compatible with self.

If the involved Types are not compatible, a TypeError will be raised.

is_super(otype)

Determine if self is a supertype of otype.

This method effectively implements the type relation >.

In general, t1.is_super(t2) == True implies that t1 can be replaced with t2.

See Type.in_same_class.

Return type:

None if the type relation cannot be applied/determined.

variable_type

alias of XTensorVariable

class pytensor.xtensor.type.XTensorVariable(type, owner, index=None, name=None)

Variable of XTensorType.

property T

Return the full transpose of the tensor.

This is equivalent to calling transpose() with no arguments.

Returns:

Fully transposed tensor.

Return type:

XTensorVariable

broadcast(*others, exclude=None)

Broadcast this tensor against other XTensorVariables.

broadcast_like(other, exclude=None)

Broadcast this tensor against another XTensorVariable.

diff(dim, n=1)

Compute the n-th discrete difference along the given dimension.

dot(other, dim=None)

Matrix multiplication with another XTensorVariable, contracting over matching or specified dims.

expand_dims(dim=None, create_index_for_new_dim=True, axis=None, **dim_kwargs)

Add one or more new dimensions to the tensor.

Parameters:

• dim (str | Sequence[str] | dict[str, int | Sequence] | None) –

  If str or sequence of str, new dimensions with size 1. If dict, keys are dimension names and values are either:

  • int: the new size

  • sequence: coordinates (length determines size)

• create_index_for_new_dim (bool, default: True) – Currently ignored. Reserved for future coordinate support. In xarray, when True (default), creates a coordinate index for the new dimension with values from 0 to size-1. When False, no coordinate index is created.

• axis (int | Sequence[int] | None, default: None) – Not implemented yet. In xarray, specifies where to insert the new dimension(s). By default (None), new dimensions are inserted at the beginning (axis=0). Symbolic axis is not supported yet. Negative values count from the end.

• **dim_kwargs (int | Sequence) – Alternative to dim dict. Only used if dim is None.

Returns:

A tensor with additional dimensions inserted at the front.

Return type:

XTensorVariable

squeeze(dim=None, drop=None, axis=None)

Remove dimensions of size 1 from an XTensorVariable.

Parameters:

• x (XTensorVariable) – The input tensor

• dim (str or None or iterable of str, optional) – The name(s) of the dimension(s) to remove. If None, all dimensions of size 1 (known statically) will be removed. Dimensions with unknown static shape will be retained, even if they have size 1 at runtime.

• drop (bool, optional) – If drop=True, drop squeezed coordinates instead of making them scalar.

• axis (int or iterable of int, optional) – The axis(es) to remove. If None, all dimensions of size 1 will be removed.

Returns:

A new tensor with the specified dimension(s) removed.

Return type:

XTensorVariable

transpose(*dim, missing_dims='raise')

Transpose dimensions of the tensor.

Parameters:

• *dim (str | Ellipsis) – Dimensions to transpose. If empty, performs a full transpose. Can use ellipsis (…) to represent remaining dimensions.

• missing_dims ({"raise", "warn", "ignore"}, default="raise") – How to handle dimensions that don’t exist in the tensor: - “raise”: Raise an error if any dimensions don’t exist - “warn”: Warn if any dimensions don’t exist - “ignore”: Silently ignore any dimensions that don’t exist

Returns:

Transposed tensor with reordered dimensions.

Return type:

XTensorVariable

Raises:

ValueError – If missing_dims=”raise” and any dimensions don’t exist. If multiple ellipsis are provided.