benderthon/tf_freeze.py
def save_weights_from_checkpoint(input_checkpoint, output_path, conv_var_names=None, conv_transpose_var_names=None):
    """Save the weights of the trainable variables given a checkpoint, each one in a different file in output_path."""
    check_input_checkpoint(input_checkpoint)

    with tf.Session() as sess:
        restore_from_checkpoint(sess, input_checkpoint)
        save_weights(sess, output_path, conv_var_names=conv_var_names,
                     conv_transpose_var_names=conv_transpose_var_names)
def save_weights_from_checkpoint(input_checkpoint, output_path, conv_var_names=None, conv_transpose_var_names=None):
    check_input_checkpoint(input_checkpoint)

    with tf.Session() as sess:
        restore_from_checkpoint(sess, input_checkpoint)
        save_weights(sess, output_path, conv_var_names=conv_var_names,
                     conv_transpose_var_names=conv_transpose_var_names)
def save_weights_from_checkpoint ( input_checkpoint , output_path , conv_var_names = None , conv_transpose_var_names = None ) : check_input_checkpoint ( input_checkpoint ) with tf . Session ( ) as sess : restore_from_checkpoint ( sess , input_checkpoint ) save_weights ( sess , output_path , conv_var_names = conv_var_names , conv_transpose_var_names = conv_transpose_var_names )
Save the weights of the trainable variables given a checkpoint, each one in a different file in output_path.
Save the weights of the trainable variables given a checkpoint each one in a different file in output_path .