import tensorflow as tf
import tensorflow.contrib.slim as slim


class Inception_resnet_v2:

    def __init__(self, num_classes=1001, is_training=True,
        dropout_keep_prob=0.8, reuse=False, scope='InceptionResnetV2'):
        self.num_classes = num_classes
        self.is_training = is_training
        self.dropout_keep_prob = dropout_keep_prob
        self.reuse = reuse
        self.scope = scope

    def encoder(self, x):
        with tf.variable_scope(name_or_scope=self.scope, reuse=self.reuse):
            slim.repeat()

54a0be223797fca3a15cbd830e0b2307160abfff
<mask token>


class Inception_resnet_v2:
    <mask token>
    <mask token>

<mask token>


class Inception_resnet_v2:
    <mask token>

    def encoder(self, x):
        with tf.variable_scope(name_or_scope=self.scope, reuse=self.reuse):
            slim.repeat()

<mask token>


class Inception_resnet_v2:

    def __init__(self, num_classes=1001, is_training=True,
        dropout_keep_prob=0.8, reuse=False, scope='InceptionResnetV2'):
        self.num_classes = num_classes
        self.is_training = is_training
        self.dropout_keep_prob = dropout_keep_prob
        self.reuse = reuse
        self.scope = scope

    def encoder(self, x):
        with tf.variable_scope(name_or_scope=self.scope, reuse=self.reuse):
            slim.repeat()

import tensorflow as tf
import tensorflow.contrib.slim as slim


class Inception_resnet_v2:

    def __init__(self, num_classes=1001, is_training=True,
        dropout_keep_prob=0.8, reuse=False, scope='InceptionResnetV2'):
        self.num_classes = num_classes
        self.is_training = is_training
        self.dropout_keep_prob = dropout_keep_prob
        self.reuse = reuse
        self.scope = scope

    def encoder(self, x):
        with tf.variable_scope(name_or_scope=self.scope, reuse=self.reuse):
            slim.repeat()
