Add a model.check_trainable_weights_consistency #8234
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This will raise a UserWarning when the user modifies model.trainable and tries to print a model summary or launch a fit without having called .compile. Calling .compile() is necessary because trainable weights are collected in compile (model._collected_trainable_weights).
fchollet
previously approved these changes
Oct 24, 2017
keras/engine/training.py
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| if not hasattr(self, '_collected_trainable_weights'): | ||
| return | ||
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| if count_params(self.trainable_weights) != \ |
keras/engine/training.py
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| count_params(self._collected_trainable_weights): | ||
| warnings.warn(UserWarning( | ||
| 'Discrepancy between trainable weights and collected trainable' | ||
| ' weights, did you set model.trainable without calling' |
keras/utils/layer_utils.py
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| @@ -5,6 +5,11 @@ | |||
| import numpy as np | |||
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| def count_params(weights): | |||
| """Count the total number of scalars composing the weights""" | |||
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Docstring formatting: one-line summary should end with a period; the dosctring should include a # Arguments and # Returns section.
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Thanks for the quick review. I think I addressed your comments. |
fchollet
reviewed
Oct 25, 2017
keras/engine/training.py
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| @@ -945,9 +946,25 @@ def handle_metrics(metrics, weights=None): | |||
| trainable_weights = self.trainable_weights | |||
| self._collected_trainable_weights = trainable_weights | |||
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| def check_trainable_weights_consistency(self): | |||
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Please make this method private (underscore) and make the docstring style-compliant.
julienr
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This will raise a UserWarning when the user modifies model.trainable
and tries to print a model summary or launch a fit without having
called .compile.
Calling .compile() is necessary because trainable weights are collected
in compile (model._collected_trainable_weights).
Fixes #8121