# Path: dreamer/tools/filter_variables_lib.py
# def filter_variables(include=None, exclude=None):


import tensorflow as tf
from dreamer.tools import filter_variables_lib
# Copyright 2019 The Dreamer 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.

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function




def soft_copy_weights(source_pattern, target_pattern, amount):
  if not (0 < amount <= 0.5 or amount == 1):
    message = 'Copy amount should probably be less than half or everything,'
    message += ' not {}'.format(amount)
    raise ValueError(message)
  source_vars = filter_variables_lib.filter_variables(include=source_pattern)

# Path: dreamer/tools/filter_variables_lib.py
# def filter_variables(include=None, exclude=None):


# Path: dreamer/tools/copy_weights.py
import tensorflow as tf
from dreamer.tools import filter_variables_lib

# Copyright 2019 The Dreamer 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.

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function




def soft_copy_weights(source_pattern, target_pattern, amount):
  if not (0 < amount <= 0.5 or amount == 1):
    message = 'Copy amount should probably be less than half or everything,'
    message += ' not {}'.format(amount)
    raise ValueError(message)
  source_vars = filter_variables_lib.filter_variables(include=source_pattern)

  target_vars = filter_variables_lib.filter_variables(include=target_pattern)