# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#         http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Symbol naming utilities."""

from . import qual_names


class Namer(object):
    """Symbol name generator."""

    def __init__(self, global_namespace):
        self.global_namespace = global_namespace
        self.generated_names = set()

    def new_symbol(self, name_root, reserved_locals):
        """See control_flow.SymbolNamer.new_symbol."""
        # reserved_locals may contain QNs.
        all_reserved_locals = set()
        for s in reserved_locals:
            if isinstance(s, qual_names.QN):
                all_reserved_locals.update(s.qn)
            elif isinstance(s, str):
                all_reserved_locals.add(s)
            else:
                raise ValueError('Unexpected symbol type "%s"' % type(s))

        pieces = name_root.split("_")
        if pieces[-1].isdigit():
            name_root = "_".join(pieces[:-1])
            n = int(pieces[-1])
        else:
            n = 0
        new_name = name_root

        while (
            new_name in self.global_namespace
            or new_name in all_reserved_locals
            or new_name in self.generated_names
        ):
            n += 1
            new_name = "%s_%d" % (name_root, n)

        self.generated_names.add(new_name)
        return new_name
