7c84229f350b83ce397b8c65e52e333e99b6d19d,keras/backend/tensorflow_backend.py,,truncated_normal,#Any#Any#Any#Any#Any#,4404

Before Change

        dtype = floatx()
    if seed is None:
        seed = np.random.randint(10e6)
    return tf.truncated_normal(shape, mean, stddev, dtype=dtype, seed=seed)


// CTC
// TensorFlow has a native implementation, but it uses sparse tensors

After Change

        dtype = floatx()
    if seed is None:
        seed = np.random.randint(10e6)
    with tf_ops.init_scope():
        return tf_keras_backend.truncated_normal(
            shape, mean=mean, stddev=stddev, dtype=dtype, seed=seed)


// CTC
// TensorFlow has a native implementation, but it uses sparse tensors
// and therefore requires a wrapper for Keras. The functions below convert
// dense to sparse tensors and also wraps up the beam search code that is
// in TensorFlow"s CTC implementation


@tf_graph_op
def ctc_label_dense_to_sparse(labels, label_lengths):
    Converts CTC labels from dense to sparse.

Instances