pool_size:2个整数的整数或元组/列表:(pool_height,pool_width),用于指定池窗口的大小.可以是单个整数,以指定所有空间维度的相同值.默认为2x2 strides:2个整数的整数或元组/列表,用于指定池操作的步幅.可以是单个整数,以指定所有空间维度的相同值,移动步长的意思,默认为池化核尺寸,即2。 padding:一个字符串,表示...
pool_size=(2, 2),strides=None,padding='valid',data_format=None )pool_size：2个整数的整数或元组/列表：(pool_height,pool_width),⽤于指定池窗⼝的⼤⼩.可以是单个整数,以指定所有空间维度的相同值.默认为2x2 strides：2个整数的整数或元组/列表,⽤于指定池操作的步幅.可以是单个整数,以指定...
mean pooling是权重为1/num的conv, max pooling 可以看做是只有在最大值的位置权值是1的conv. 所以理...
shape=(1,4,4,3),name="input")avg2d=tf.layers.average_pooling2d(input,pool_size=2,strides=2,padding='valid')## parser parameterwithtf.Session()assess:sess.run(tf.global_variables_initializer())tvars
layers.average_pooling2d(input, pool_size=2, strides=2, padding='valid') ## parser parameter with tf.Session() as sess: sess.run(tf.global_variables_initializer()) tvars = tf.trainable_variables() tvars_vals = sess.run(tvars) graph_val = tf.get_default_graph() graph_def = tf....
filters,3, strides=2, padding="same", kernel_initializer="he_normal") )ifpool: net.add(layers.MaxPool2D(pool_size=(2,2)))ifnorm: net.add(layers.BatchNormalization()) net.add(layers.ReLU())returnnet 开发者ID:intel,项目名称:stacks-usecase,代码行数:16,代码来源:custom_unet.py ...
pooling_layer = tf.keras.layers.MaxPooling2D(pool_size=(2, 2), strides=(2, 2)) output_tensor, indices = pooling_layer(input_tensor) print("Max-pooled result:") print(output_tensor.numpy()) print("Indices of max values:") print(indices.numpy()) ``` 在这个例子中,`output_tensor`是...
defpool2d(x, pool_size, strides=(1,1), border_mode='valid', dim_ordering='th', pool_mode='max'):ifborder_mode =='same':#TODO:add implementation for border_mode="same"raiseException('border_mode="same" not supported with Theano.')elifborder_mode =='valid': ...
nn.avg_pool2d(x, ksize=2, strides=2) assert y.shape == (1, 1, 1, 2) Parameters: input (dragon.Tensor) – The input tensor. ksize (Union[int, Sequence[int]]) – The size of pooling window. strides (Union[int, Sequence[int]]) – The stride of pooling window. padding (Union...
self.pool_size = pool_size self.strides = pool_size if strides is None else strides self.pool_size = argument_validation.standardize_tuple( pool_size, pool_dimensions, "pool_size" ) strides = pool_size if strides is None else strides self.strides = argument_validation.standardize_tuple( str...