Small ops fixes for Torch unit tests #316
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fchollet
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Jun 10, 2023
| @@ -416,6 +416,7 @@ def mish(x): | |||
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| - [Misra, 2019](https://arxiv.org/abs/1908.08681) | |||
| """ | |||
| x = backend.convert_to_tensor(x) | |||
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If this is torch related, can we move it to the torch backend?
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Calling mish in activations.py does x * backend.nn.tanh(backend.nn.softplus(x)) a few lines above this, and this will multiply a numpy array (x) by a Torch tensor, which is not allowed. The conversion to a tensor for x (first arg) must therefore be done here.
keras_core/utils/progbar.py
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| @@ -160,7 +161,9 @@ def update(self, current, values=None, finalize=None): | |||
| info += f" - {k}:" | |||
| if isinstance(self._values[k], list): | |||
| avg = np.mean( | |||
| self._values[k][0] / max(1, self._values[k][1]) | |||
| backend.convert_to_numpy( | |||
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I believe Haifeng has already provided a fix that should make this change unnecessary (earlier today)
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Understood, reverted thanks!
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This PR contains some small ops fixes for Torch unit tests, particularly those relating to incompatibility with numpy ops. Subsequent PRs will contain remaining fixes.