Edited docstring, y_pred for SparseCategoricalAcc #37120
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1. The y_pred example was previously given as `[0.1, 0.9, 0.8]`, which is odd given that the probabilities should sum up to one after passing through softmax. Edited to `[0.1, 0.6, 0.3]` to maintain integrity of example while posing a probable result. 2. The docstring for master was not up-to-date with that of Tag 2.1.0. Made changes so that they are even.
tensorflow/python/keras/metrics.py
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| `acc = np.dot(sample_weight, np.equal(y_true, np.argmax(y_pred, axis=1))` | ||
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I would recommend the following
| `acc = np.dot(sample_weight, np.equal(y_true, np.argmax(y_pred, axis=1))` | |
| ```python | |
| acc = np.dot(sample_weight, np.equal(y_true, np.argmax(y_pred, axis=1)) |
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Thank you for the feedback. I have incorporated the changes into the PR.
Co-Authored-By: Mihai Maruseac <mihai.maruseac@gmail.com>
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y_predexample was previously given as[0.1, 0.9, 0.8], which is odd given that the probabilities should sum up to one after passing through softmax. Edited to[0.1, 0.6, 0.3]to maintain integrity of example while posing a probable result.Relates to #36844.