amiralavi / sparsely-connected-keras Goto Github PK
View Code? Open in Web Editor NEWSparsely-connected layers for Keras
License: GNU General Public License v3.0
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hello how can i use this on 2D img conv?
Block 1
x = Conv2D(64, (3, 3), activation='relu', padding='same', name='block1_conv1')(img_input)
x = Conv2D(64, (3, 3), activation='relu', padding='same', name='block1_conv2')(x)
x = MaxPooling2D((2, 2), strides=(2, 2), name='block1_pool')(x)
# Block 2
x = Conv2D(128, (3, 3), activation='relu', padding='same', name='block2_conv1')(x)
x = Conv2D(128, (3, 3), activation='relu', padding='same', name='block2_conv2')(x)
x = MaxPooling2D((2, 2), strides=(2, 2), name='block2_pool')(x)
# Block 3
x = Conv2D(256, (3, 3), activation='relu', padding='same', name='block3_conv1')(x)
x = Conv2D(256, (3, 3), activation='relu', padding='same', name='block3_conv2')(x)
x = Conv2D(256, (3, 3), activation='relu', padding='same', name='block3_conv3')(x)
x = MaxPooling2D((2, 2), strides=(2, 2), name='block3_pool')(x)
# Block 4
x = Conv2D(512, (3, 3), activation='relu', padding='same', name='block4_conv1')(x)
x = Conv2D(512, (3, 3), activation='relu', padding='same', name='block4_conv2')(x)
x = Conv2D(512, (3, 3), activation='relu', padding='same', name='block4_conv3')(x)
x = MaxPooling2D((2, 2), strides=(2, 2), name='block4_pool')(x)
# Block 5
x = Conv2D(512, (3, 3), activation='relu', padding='same', name='block5_conv1')(x)
x = Conv2D(512, (3, 3), activation='relu', padding='same', name='block5_conv2')(x)
x = Conv2D(512, (3, 3), activation='relu', padding='same', name='block5_conv3')(x)
-------------------------------------------------------------------------------------------
standard vgg16 out 7*7*512
------------------------------------------------------------------------------------------
out = Flatten(name='flatten'))(x)
out = Dense(4096, activation='relu', name='fc1'))(out)
out =Dropout(0.5))(out)
out = Dense(4096, activation='relu', name='fc2'))(out)
out = Dropout(0.5))(out)
out_class = Dense(nb_classes, activation='softmax' )(out)
'''
New TF version
Hello everyone,
this package doesn´t work with the new version of tf, because the import command for keras changed. I fixed it locally in the sparse_layer.py file by adding 'tensorflow' before every '.keras' (please note that InputSpec can no longer be imported from keras.engine):
import numpy as np
from tensorflow.keras import backend as K
#from tensorflow.keras.engine import InputSpec
from tensorflow.keras.initializers import Constant
from tensorflow.keras.layers import Dense
from tensorflow.keras.layers import Layer, InputSpec
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