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Specifications and Common Mistakes

- Specifications and Common Mistakes:

- Misspellings or punctuation mistakes,incorrect formulas, abnormal display.

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mindsponge.common.quat_affine

mindsponge.common.quat_affine(quaternion, translation, rotation=None, normalize=True, unstack_inputs=False, use_numpy=False)

Create quat affine representations based on rots and trans.

Parameters

• quaternion (tensor) – Shape is $(N_{res},4)$.

• translation (tensor) – Shape is $(N_{res},3)$.

• rotation (tensor) – Rots, shape is $(N_{res},9)$. Default: None.

• normalize (bool) – Whether to use normalization. Default: True.

• unstack_inputs (bool) – Whether input is vector(True) of Tensor(False). Default: False.

• use_numpy (bool) – Whether to use numpy. Default: False.

Returns

result after quat affine.

• quaternion, tensor, shape is $(N_{res},4)$ .

• rotation, tuple, $(xx,xy,xz,yx,yy,yz,zx,zy,zz)$, shape of every element is $(N_{res},)$ .

• translation, tensor, shape is $(N_{res},3)$ .

Supported Platforms:

Ascend GPU

Examples

>>> import numpy as np
>>> import mindspore as ms
>>> from mindspore import Tensor
>>> from mindsponge.common.geometry import quat_affine
>>> input_0 = Tensor(np.ones((256, 4)), ms.float32)
>>> input_1 = Tensor(np.ones((256, 3)), ms.float32)
>>> qua, rot, trans = quat_affine(input_0, input_1)
>>> print(qua.shape, len(rot), rot[0].shape, trans.shape)
(256, 4), 9, (256,), (256, 3)