dxtb.components.base.ClassicalCache

dxtb.components.base.ClassicalCache#

class dxtb.components.base.ClassicalCache(device=None, dtype=None)[source]#

Bases: ComponentCache

Restart data for individual classical contributions.

Methods

`cpu`	Returns a copy of the `TensorLike` instance on the CPU.
`override_device`	Override the device of the class object.
`override_dtype`	Override the dtype of the class object.
`to`	Returns a copy of the `TensorLike` instance on the specified device.
`type`	Returns a copy of the `TensorLike` instance with specified floating point type.

Attributes

`allowed_dtypes`	Specification of dtypes that the `TensorLike` object can take.
`dd`	Shortcut for device and dtype.
`device`	The device on which the class object resides.
`dtype`	Floating point dtype used by class object.

Parameters:

device (torch.device | None)
dtype (torch.dtype | None)

cpu()#

Returns a copy of the TensorLike instance on the CPU.

This method creates and returns a new copy of the TensorLike instance on the CPU.

Return type:: Self
Returns:: A copy of the TensorLike instance placed on the CPU.
Return type:: TensorLike

override_device(device)#

Override the device of the class object. :rtype: None

Warning

This does not change the device of the underlying tensors. It only changes the device of the class object. Use with caution.

Parameters:: device (torch.device) – Device to override the current device.
Parameters:: device (device)
Return type:: None

override_dtype(dtype)#

Override the dtype of the class object. :rtype: None

Warning

This does not change the dtype of the underlying tensors. It only changes the dtype of the class object. Use with caution.

Parameters:: dtype (torch.dtype) – Floating point dtype to override the current dtype.
Parameters:: dtype (dtype)
Return type:: None

to(device=None, dtype=None)#

Returns a copy of the TensorLike instance on the specified device.

This method creates and returns a new copy of the TensorLike instance on the specified device “device”.

Return type:

Self

Parameters:

device (torch.device) – Device to which all associated tensors should be moved.

Returns:

A copy of the TensorLike instance placed on the specified device.

Return type:

TensorLike

Parameters:

device (device | None)
dtype (dtype | None)

Notes

If the TensorLike instance is already on the desired device self will be returned.

type(dtype)#

Returns a copy of the TensorLike instance with specified floating point type. This method creates and returns a new copy of the TensorLike instance with the specified dtype.

Return type:: Self
Parameters:: dtype (torch.dtype) – Floating point type.
Returns:: A copy of the TensorLike instance with the specified dtype.
Return type:: TensorLike
Parameters:: dtype (dtype)

Notes

If the TensorLike instance has already the desired dtype Self will be returned.

property allowed_dtypes: tuple[dtype, ...]#

Specification of dtypes that the TensorLike object can take. Defaults to float types and must be overridden by subclass if float are not allowed. The IndexHelper is an example that should only allow integers.

Returns:: Collection of allowed dtypes the TensorLike object can take.
Return type:: tuple[torch.dtype, …]

property dd: DD#: Shortcut for device and dtype.

property device: device#: The device on which the class object resides.

property dtype: dtype#: Floating point dtype used by class object.

dxtb.components.base.ClassicalCache

Contents

dxtb.components.base.ClassicalCache#