import?warnings
warnings.filterwarnings（‘ignore‘?category=FutureWarning）
import?tensorflow?as?tf
from?tensorflow.examples.tutorials.mnist?import?input_data
slim?=?tf.contrib.slim

#create?weights?for?each?layer
def?get_weights（shape）:
????data?=?tf.truncated_normal（shapestddev=0.1）
????return?tf.Variable（data）

def?get_biases（shape）:
????data?=?tf.constant（0.1shape=shape）
????return?tf.Variable（data）

#2d?convolutional?function
def?convolution_2d（xw）:
????return?tf.nn.conv2d（xwstrides=[1111]padding=‘SAME‘）
#2*2?max?pooling
def?max_pooling（x）:
????return?tf.nn.max_pool（xksize=[1221]strides=[1221]padding=‘SAME‘）


def?combined_static_and_dynamic_shape（tensor）:
????“““Returns?a?list?containing?static?and?dynamic?values?for?the?dimensions.??Returns?a?list?of?static?
????and?dynamic?values?for?shape?dimensions.?This?is??useful?to?preserve?static?shapes?when?available?in?reshape?operation.??
????Args:????tensor:?A?tensor?of?any?type.??
????Returns:????A?list?of?size?tensor.shape.ndims?containing?integers?or?a?scalar?tensor.??“““
????static_tensor_shape?=?tensor.shape.as_list（）
????dynamic_tensor_shape?=?tf.shape（tensor）
????combined_shape?=?[]
????for?index?dim?in?enumerate（static_tensor_shape）:
????????if?dim?is?not?None:
????????????combined_shape.append（dim）
????????else:
????????????combined_shape.append（dynamic_tensor_shape[index]）
????return?combined_shape


def?convolutional_block_attention_module（feature_map?index?reduction_ratio?=?0.5）:
????“““CBAM：convolutional?block?attention?module
????Args:
????????feature_map:input?feature?map
????????index:the?index?of?the?module
????????reduction_ratio:output?units?number?of?first?MLP?layer:reduction_ratio?*?feature?map
????Return:
????????feature?map?with?channel?and?spatial?attention“““

????with?tf.variable_scope（“cbam_%s“?%?（index））:
????????feature_map_shape?=?combined_static_and_dynamic_shape（feature_map）
????????#?channel?attention?module
????????channel_avg_weights?=?tf.nn.avg_pool（value=feature_map
?????????????????????????????????????????????ksize=[1?feature_map_shape[1]?feature_map_shape[2]?1]
?????????????????????????????????????????????strides=[1?1?1?1]
?????????????????????????????????????????????padding=‘VALID‘）??#?global?average?pool
????????channel_max_weights?=?tf.nn.max_pool（value=feature_map
?????????????????????????????????????????????ksize=[1?feature_map_shape[1]?feature_map_shape[2]?1]
?????????????????????????????????????????????strides=[1?1?1?1]
?????????????????????????????????????????????padding=‘VALID‘）
????????channel_avg_reshape?=?tf.reshape（channel_avg_weights
?????????????????????????????????????????[feature_map_shape[0]?1?feature_map_shape[3]]）
????????channel_max_reshape?=?tf.reshape（channel_max_weights
?????????????????????????????????????????[feature_map_shape[0]?1?feature_map_shape[3]]）
????????channel_w_reshape?=?tf.concat（[channel_avg_reshape?channel_max_re