benderthon/tf_freeze.py
def save_weights(sess, output_path, conv_var_names=None, conv_transpose_var_names=None):
    """Save the weights of the trainable variables, each one in a different file in output_path."""
    if not conv_var_names:
        conv_var_names = []

    if not conv_transpose_var_names:
        conv_transpose_var_names = []

    for var in tf.trainable_variables():
        filename = '{}-{}'.format(output_path, var.name.replace(':', '-').replace('/', '-'))

        if var.name in conv_var_names:
            var = tf.transpose(var, perm=[3, 0, 1, 2])
        elif var.name in conv_transpose_var_names:
            var = tf.transpose(var, perm=[3, 1, 0, 2])

        value = sess.run(var)

        # noinspection PyTypeChecker
        with open(filename, 'w') as file_:
            value.tofile(file_)
def save_weights(sess, output_path, conv_var_names=None, conv_transpose_var_names=None):
    """Save the weights of the trainable variables, each one in a different file in output_path."""
    if not conv_var_names:
        conv_var_names = []

    if not conv_transpose_var_names:
        conv_transpose_var_names = []

    for var in tf.trainable_variables():
        filename = '{}-{}'.format(output_path, var.name.replace(':', '-').replace('/', '-'))

        if var.name in conv_var_names:
            var = tf.transpose(var, perm=[3, 0, 1, 2])
        elif var.name in conv_transpose_var_names:
            var = tf.transpose(var, perm=[3, 1, 0, 2])

        value = sess.run(var)

        # noinspection PyTypeChecker
        with open(filename, 'w') as file_:
            value.tofile(file_)
def save_weights ( sess , output_path , conv_var_names = None , conv_transpose_var_names = None ) : if not conv_var_names : conv_var_names = [ ] if not conv_transpose_var_names : conv_transpose_var_names = [ ] for var in tf . trainable_variables ( ) : filename = '{}-{}' . format ( output_path , var . name . replace ( ':' , '-' ) . replace ( '/' , '-' ) ) if var . name in conv_var_names : var = tf . transpose ( var , perm = [ 3 , 0 , 1 , 2 ] ) elif var . name in conv_transpose_var_names : var = tf . transpose ( var , perm = [ 3 , 1 , 0 , 2 ] ) value = sess . run ( var ) # noinspection PyTypeChecker with open ( filename , 'w' ) as file_ : value . tofile ( file_ )
Save the weights of the trainable variables, each one in a different file in output_path.
Save the weights of the trainable variables each one in a different file in output_path .