# -*- coding: utf-8 -*-

# Copyright (C) 2020. Huawei Technologies Co., Ltd. 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.

"""Defined TensorFlow sequential network."""
import tensorflow as tf


class Sequential(object):
    """Sequential network for TensorFlow."""

    def __init__(self, modules):
        """Init Sequential."""
        self.modules = modules

    def __call__(self, inputs, training):
        """Forward function for sequential network."""
        for modules in self.modules:
            inputs = modules(inputs, training)
        return inputs


class Network(object):
    """Base class for tensorflow Network."""

    def __init__(self, desc):
        """Init network."""
        self.fp16 = tf.float16 if desc.get('fp16', False) else tf.float32

    def _custom_dtype_getter(self, getter, name, shape=None, dtype=tf.float16,
                             *args, **kwargs):
        """Create variables in fp32, then casts to fp16 if necessary."""
        if self.fp16 and dtype == tf.float16:
            var = getter(name, shape, tf.float32, *args, **kwargs)
            return tf.cast(var, dtype=dtype, name=name + '_cast')
        else:
            return getter(name, shape, dtype, *args, **kwargs)

    def _model_variable_scope(self, scope_name):
        """Return a variable scope of created model."""
        return tf.variable_scope(scope_name, custom_getter=self._custom_dtype_getter)

# -*- coding: utf-8 -*-

# Copyright (C) 2020. Huawei Technologies Co., Ltd. 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.

"""Defined TensorFlow sequential network."""
import tensorflow as tf


class Sequential(object):
    """Sequential network for TensorFlow."""

    def __init__(self, modules):
        """Init Sequential."""
        self.modules = modules

    def __call__(self, inputs, training):
        """Forward function for sequential network."""
        for modules in self.modules:
            inputs = modules(inputs, training)
        return inputs


class Network(object):
    """Base class for tensorflow Network."""

    def __init__(self, desc):
        """Init network."""
        self.fp16 = tf.float16 if desc.get('fp16', False) else tf.float32

    def _custom_dtype_getter(self, getter, name, shape=None, dtype=tf.float16,
                             *args, **kwargs):
        """Create variables in fp32, then casts to fp16 if necessary."""
        if self.fp16 and dtype == tf.float16:
            var = getter(name, shape, tf.float32, *args, **kwargs)
            return tf.cast(var, dtype=dtype, name=name + '_cast')
        else:
            return getter(name, shape, dtype, *args, **kwargs)

    def _model_variable_scope(self, scope_name):
        """Return a variable scope of created model."""
        return tf.variable_scope(scope_name, custom_getter=self._custom_dtype_getter)

# -*- coding: utf-8 -*- # Copyright (C) 2020. Huawei Technologies Co., Ltd. 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. Defined TensorFlow sequential network. Sequential network for TensorFlow. Init Sequential. Forward function for sequential network. Base class for tensorflow Network. Init network. Create variables in fp32, then casts to fp16 if necessary. Return a variable scope of created model.