Small ops fixes for Torch unit tests #316
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fchollet
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Jun 10, 2023
| - [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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| 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.