Add test coverage for gnm_common by manumishra12 · Pull Request #25 · google/GNM

manumishra12 · 2026-07-16T15:40:02Z

Adds gnm_common_test.py. gnm_common.py holds the backend-agnostic math
shared by all four GNM backends but had no dedicated test (it was only
exercised indirectly through the per-backend tests).

The new suite (25 tests) covers:

Array helpers: take, eye, reshape_with_batch_dims,
zeros_with_batch_dims.
axis_angle_to_rotation_matrix: zero -> identity, rotation about each
principal axis leaves that axis invariant, the 90 degrees-about-z reference
matrix, orthonormality and unit determinant on random inputs, and batch-shape
preservation.
joint_transforms_world: rest pose places joints at their bind positions,
a global translation shifts the chain, and a root rotation propagates to the
child joint.
linear_blend_skinning: rest pose is the identity, a global translation
translates the vertices, and batch shapes are preserved.
vertex_positions_bind_pose / joint_positions_bind_pose: None
parameters return the template, and identity/expression bases are applied
correctly.
compute_pose_correctives: None inputs and zero rotations produce zero
correctives, and batch shapes are preserved.

Follows the existing absltest style used across the package. All tests pass
locally with the NumPy backend.

Adds gnm_common_test.py covering the backend-agnostic math shared by every GNM backend: array helpers (take, eye, reshape_with_batch_dims, zeros_with_batch_dims), axis_angle_to_rotation_matrix (identity, per-axis invariance, known rotations, orthonormality/determinant, batch shapes), joint_transforms_world forward kinematics, linear_blend_skinning (rest pose, translation, batching), the bind-pose helpers, and compute_pose_correctives. 25 tests, following the existing absltest style.

bednarikjan · 2026-07-22T13:56:30Z

+class ArrayHelpersTest(parameterized.TestCase):
+  """Tests for the backend-agnostic array helpers."""
+
+  def test_take_selects_along_axis(self) -> None:


Please remove the return type annotation from all the test_* functions. This is to stay consistent with our internal codebase.

bednarikjan · 2026-07-22T14:27:52Z

+from gnm.shape import gnm_common
+
+
+class ArrayHelpersTest(parameterized.TestCase):


For all the tests, please use the parameterized to generate a given test for all the backends supported by xnp (NumPy, jax, TF, pytorch).

For the functions which take xnp as an input argument, you can iterate over the backends directly (take, eye), for the other functions you can iterate over input arrays built by the individual backends from which the current xnp is extracted at runtime within the functions under test (reshape_with_batch_dims, zeros_with_batch_dims).

This will help the tests catch any potential bugs specific to a given backend.

bednarikjan · 2026-07-22T14:30:37Z

+    np.testing.assert_array_equal(zeros, np.zeros((4, 4, 4)))
+
+
+class AxisAngleToRotationMatrixTest(parameterized.TestCase):
