cc0e60c1012b7c72eeb5ea0c41b8a2045177ae5e,keras/backend/tensorflow_backend.py,,sparse_categorical_crossentropy,#Any#Any#Any#,1009

Before Change

    // Note: tf.nn.softmax_cross_entropy_with_logits
    // expects logits, Keras expects probabilities.
    if not from_logits:
        output = tf.clip_by_value(output, tf.cast(_EPSILON, dtype=_FLOATX),
                                  tf.cast(1.-_EPSILON, dtype=_FLOATX))
        output = tf.log(output)

    output_shape = output.get_shape()

After Change

    // Note: tf.nn.softmax_cross_entropy_with_logits
    // expects logits, Keras expects probabilities.
    if not from_logits:
        epsilon = _to_tensor(_EPSILON, output.dtype.base_dtype)
        output = tf.clip_by_value(output, epsilon, 1 - epsilon)
        output = tf.log(output)

    output_shape = output.get_shape()

Instances