# Path: weakly_supervised_control/disentanglement/tensorsketch/modules/base.py
# def build_with_name_scope(build_parameters):
#     @tf.Module.with_name_scope
#     def build_params_once_with_ns(self, *args):
#         assert not self.built, "{}.built already True".format(self.name)
#         build_parameters(self, *args)
#         self.built = True
#     return build_params_once_with_ns
# 
# Path: weakly_supervised_control/disentanglement/tensorsketch/normalization/base.py
# class KernelNorm(Module):
#     """Abstract class for kernel normalization modules."""
# 
#     NAME = "kernel_norm"
# 
#     @staticmethod
#     def normalize(*inputs):
#         raise NotImplementedError("Implement normalize.")
# 
#     @staticmethod
#     def add(module, kn):
#         assert not hasattr(module, kn.NAME), (
#             "{} already in module attributes".format(kn.NAME))
#         assert kn.NAME not in module.kernel_normalizers, (
#             "{} already in module.kernel_normalizers".format(kn.NAME))
#         setattr(module, kn.NAME, kn)
#         module.kernel_normalizers.update({kn.NAME: kn})
# 
#     @staticmethod
#     def remove(module, kn_name):
#         delattr(module, kn_name)
#         del module.kernel_normalizers[kn_name]


import tensorflow as tf
from weakly_supervised_control.disentanglement.tensorsketch.modules.base import build_with_name_scope
from weakly_supervised_control.disentanglement.tensorsketch.normalization.base import KernelNorm
# 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.
#
#  This file was modified from `https://github.com/google-research/google-research/blob/master/weak_disentangle`.
"""Weight normalization utilities."""




class WeightNorm(KernelNorm):
    """Weight Normalization class."""

    NAME = "weight_norm"

    def __init__(self, scale=True, axis=-1, epsilon=1e-5, name=None):
        super().__init__(name=name)
        self.use_scale = scale
        self.axis = axis
        self.epsilon = epsilon
        self.g = None


# Path: weakly_supervised_control/disentanglement/tensorsketch/modules/base.py
# def build_with_name_scope(build_parameters):
#     @tf.Module.with_name_scope
#     def build_params_once_with_ns(self, *args):
#         assert not self.built, "{}.built already True".format(self.name)
#         build_parameters(self, *args)
#         self.built = True
#     return build_params_once_with_ns
# 
# Path: weakly_supervised_control/disentanglement/tensorsketch/normalization/base.py
# class KernelNorm(Module):
#     """Abstract class for kernel normalization modules."""
# 
#     NAME = "kernel_norm"
# 
#     @staticmethod
#     def normalize(*inputs):
#         raise NotImplementedError("Implement normalize.")
# 
#     @staticmethod
#     def add(module, kn):
#         assert not hasattr(module, kn.NAME), (
#             "{} already in module attributes".format(kn.NAME))
#         assert kn.NAME not in module.kernel_normalizers, (
#             "{} already in module.kernel_normalizers".format(kn.NAME))
#         setattr(module, kn.NAME, kn)
#         module.kernel_normalizers.update({kn.NAME: kn})
# 
#     @staticmethod
#     def remove(module, kn_name):
#         delattr(module, kn_name)
#         del module.kernel_normalizers[kn_name]


# Path: weakly_supervised_control/disentanglement/tensorsketch/normalization/weight_normalization.py
import tensorflow as tf
from weakly_supervised_control.disentanglement.tensorsketch.modules.base import build_with_name_scope
from weakly_supervised_control.disentanglement.tensorsketch.normalization.base import KernelNorm

# 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.
#
#  This file was modified from `https://github.com/google-research/google-research/blob/master/weak_disentangle`.
"""Weight normalization utilities."""




class WeightNorm(KernelNorm):
    """Weight Normalization class."""

    NAME = "weight_norm"

    def __init__(self, scale=True, axis=-1, epsilon=1e-5, name=None):
        super().__init__(name=name)
        self.use_scale = scale
        self.axis = axis
        self.epsilon = epsilon
        self.g = None


    @build_with_name_scope