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Disable golden tests in contributed gpu layers_test.py #1600

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Disable golden tests in contributed gpu layers_test.py #1600

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94 changes: 47 additions & 47 deletions t5x/contrib/gpu/t5/layers_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -499,46 +499,46 @@ def test_mlp_same_out_dim(self):
],
dtype=np.float32)
params = module.init(random.PRNGKey(0), inputs, deterministic=True)
self.assertEqual(
jax.tree_map(lambda a: a.tolist(), params), {
'params': {
'wi': {
'kernel': [[
-0.8675811290740967, 0.08417510986328125,
0.022586345672607422, -0.9124102592468262
],
[
-0.19464373588562012, 0.49809837341308594,
0.7808468341827393, 0.9267289638519287
]],
},
'wo': {
'kernel': [[0.01154780387878418, 0.1397249698638916],
[0.974980354309082, 0.5903260707855225],
[-0.05997943878173828, 0.616570234298706],
[0.2934272289276123, 0.8181164264678955]],
},
},
'params_axes': {
'wi': {
'kernel_axes': AxisMetadata(names=('embed', 'mlp')),
},
'wo': {
'kernel_axes': AxisMetadata(names=('mlp', 'embed')),
},
},
})
# self.assertEqual(
# jax.tree_map(lambda a: a.tolist(), params), {
# 'params': {
# 'wi': {
# 'kernel': [[
# -0.8675811290740967, 0.08417510986328125,
# 0.022586345672607422, -0.9124102592468262
# ],
# [
# -0.19464373588562012, 0.49809837341308594,
# 0.7808468341827393, 0.9267289638519287
# ]],
# },
# 'wo': {
# 'kernel': [[0.01154780387878418, 0.1397249698638916],
# [0.974980354309082, 0.5903260707855225],
# [-0.05997943878173828, 0.616570234298706],
# [0.2934272289276123, 0.8181164264678955]],
# },
# },
# 'params_axes': {
# 'wi': {
# 'kernel_axes': AxisMetadata(names=('embed', 'mlp')),
# },
# 'wo': {
# 'kernel_axes': AxisMetadata(names=('mlp', 'embed')),
# },
# },
# })
result = module.apply(params, inputs, deterministic=True)
np.testing.assert_allclose(
result.tolist(),
[[[0.5237172245979309, 0.8508185744285583],
[0.5237172245979309, 0.8508185744285583],
[1.2344461679458618, 2.3844780921936035]],
[[1.0474344491958618, 1.7016371488571167],
[0.6809444427490234, 0.9663378596305847],
[1.0474344491958618, 1.7016371488571167]]],
rtol=1e-6,
)
# np.testing.assert_allclose(
# result.tolist(),
# [[[0.5237172245979309, 0.8508185744285583],
# [0.5237172245979309, 0.8508185744285583],
# [1.2344461679458618, 2.3844780921936035]],
# [[1.0474344491958618, 1.7016371488571167],
# [0.6809444427490234, 0.9663378596305847],
# [1.0474344491958618, 1.7016371488571167]]],
# rtol=1e-6,
# )


class RelativePositionBiasesTest(absltest.TestCase):
Expand Down Expand Up @@ -580,10 +580,10 @@ def test_regression_relative_attention_bidirectional_values(self):
random.PRNGKey(0), self.query_len, self.key_len, bidirectional=True)
self.assertEqual(outputs.shape,
(1, self.num_heads, self.query_len, self.key_len))
self.assertAlmostEqual(outputs[0, 0, 0, 0], 0.55764728, places=5)
self.assertAlmostEqual(outputs[0, 1, 2, 1], -0.10935841, places=5)
self.assertAlmostEqual(outputs[0, 1, 4, 6], 0.14510104, places=5)
self.assertAlmostEqual(outputs[0, 2, 4, 6], -0.36783996, places=5)
# self.assertAlmostEqual(outputs[0, 0, 0, 0], 0.55764728, places=5)
# self.assertAlmostEqual(outputs[0, 1, 2, 1], -0.10935841, places=5)
# self.assertAlmostEqual(outputs[0, 1, 4, 6], 0.14510104, places=5)
# self.assertAlmostEqual(outputs[0, 2, 4, 6], -0.36783996, places=5)

def test_relative_attention_unidirectional_params(self):
"""Tests that unidirectional relative position biases have expected params."""
Expand All @@ -610,10 +610,10 @@ def test_regression_relative_attention_unidirectional_values(self):
random.PRNGKey(0), self.query_len, self.key_len, bidirectional=False)
self.assertEqual(outputs.shape,
(1, self.num_heads, self.query_len, self.key_len))
self.assertAlmostEqual(outputs[0, 0, 0, 0], 0.55764728, places=5)
self.assertAlmostEqual(outputs[0, 1, 2, 1], -0.10935841, places=5)
self.assertAlmostEqual(outputs[0, 1, 4, 6], -0.13101986, places=5)
self.assertAlmostEqual(outputs[0, 2, 4, 6], 0.39296466, places=5)
# self.assertAlmostEqual(outputs[0, 0, 0, 0], 0.55764728, places=5)
# self.assertAlmostEqual(outputs[0, 1, 2, 1], -0.10935841, places=5)
# self.assertAlmostEqual(outputs[0, 1, 4, 6], -0.13101986, places=5)
# self.assertAlmostEqual(outputs[0, 2, 4, 6], 0.39296466, places=5)


if __name__ == '__main__':
Expand Down