Fix allocation memory in Keras tests #840
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Idan-BenAmi
approved these changes
Oct 23, 2023
| @@ -139,7 +139,8 @@ def test_steps_by_order(self): | |||
| def rep_data(): | |||
| yield [np.random.randn(1, 8, 8, 3)] | |||
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| mp_qc = mct.core.MixedPrecisionQuantizationConfigV2(num_of_images=1) | |||
| mp_qc = mct.core.MixedPrecisionQuantizationConfigV2(num_of_images=1, | |||
| use_grad_based_weights=False) | |||
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why use_grad_based_weights=False if it's a non parallel test?
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To speed it up. The tensorboard test does not test anything regarding the gradients weighting.
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Move tests from Keras function tests to a new package of nonparallel tests. This package runs first in GitHub actions separately from other tests since the rest run parallel. This is a workaround to a memory issue because we use tf gradients on a multi-thread/process CPU environment (tensorflow/tensorflow#41718).
Several modifications: