-
Notifications
You must be signed in to change notification settings - Fork 1
Network shape
Liam Niehus-Staab edited this page Apr 16, 2019
·
1 revision
_________________________________________________________________ Layer (type) Output Shape Param # ================================================================= conv2d (Conv2D) (None, 256, 256, 64) 3200 _________________________________________________________________ max_pooling2d (MaxPooling2D) (None, 128, 128, 64) 0 _________________________________________________________________ conv2d_1 (Conv2D) (None, 128, 128, 192) 110784 _________________________________________________________________ max_pooling2d_1 (MaxPooling2 (None, 64, 64, 192) 0 _________________________________________________________________ conv2d_2 (Conv2D) (None, 64, 64, 128) 24704 _________________________________________________________________ conv2d_3 (Conv2D) (None, 64, 64, 256) 295168 _________________________________________________________________ conv2d_4 (Conv2D) (None, 64, 64, 256) 65792 _________________________________________________________________ conv2d_5 (Conv2D) (None, 64, 64, 512) 1180160 _________________________________________________________________ max_pooling2d_2 (MaxPooling2 (None, 32, 32, 512) 0 _________________________________________________________________ conv2d_6 (Conv2D) (None, 32, 32, 256) 131328 _________________________________________________________________ conv2d_7 (Conv2D) (None, 32, 32, 512) 1180160 _________________________________________________________________ conv2d_8 (Conv2D) (None, 32, 32, 256) 131328 _________________________________________________________________ conv2d_9 (Conv2D) (None, 32, 32, 512) 1180160 _________________________________________________________________ conv2d_10 (Conv2D) (None, 32, 32, 256) 131328 _________________________________________________________________ conv2d_11 (Conv2D) (None, 32, 32, 512) 1180160 _________________________________________________________________ conv2d_12 (Conv2D) (None, 32, 32, 256) 131328 _________________________________________________________________ conv2d_13 (Conv2D) (None, 32, 32, 512) 1180160 _________________________________________________________________ conv2d_14 (Conv2D) (None, 32, 32, 512) 262656 _________________________________________________________________ conv2d_15 (Conv2D) (None, 32, 32, 1024) 4719616 _________________________________________________________________ max_pooling2d_3 (MaxPooling2 (None, 16, 16, 1024) 0 _________________________________________________________________ conv2d_16 (Conv2D) (None, 16, 16, 512) 524800 _________________________________________________________________ conv2d_17 (Conv2D) (None, 16, 16, 1024) 4719616 _________________________________________________________________ conv2d_18 (Conv2D) (None, 16, 16, 512) 524800 _________________________________________________________________ conv2d_19 (Conv2D) (None, 16, 16, 1024) 4719616 _________________________________________________________________ conv2d_20 (Conv2D) (None, 16, 16, 1024) 9438208 _________________________________________________________________ conv2d_21 (Conv2D) (None, 8, 8, 1024) 9438208 _________________________________________________________________ conv2d_22 (Conv2D) (None, 8, 8, 1024) 9438208 _________________________________________________________________ conv2d_23 (Conv2D) (None, 8, 8, 1024) 9438208 _________________________________________________________________ flatten (Flatten) (None, 65536) 0 _________________________________________________________________ dense (Dense) (None, 1024) 67109888 _________________________________________________________________ dense_1 (Dense) (None, 4096) 4198400 _________________________________________________________________ dense_2 (Dense) (None, 4) 16388 ================================================================= Total params: 131,474,372 Trainable params: 131,474,372 Non-trainable params: 0 _________________________________________________________________