MicroKeras is a minimal implementation of the Sequential Class from the Keras deep-learning library, built from scratch using Python and NumPy. It provides a simple and intuitive API for building, training, and
model=ks.models.Sequential() model.add(Dense(16,input_dim=41)) model.add(Activation('relu')) model.add(Dense(128)) model.add(Activation('relu')) model.add(Dense(64)) model.add(Activation('relu')) model.add(Dense(32)) model.add(Activation('relu')) ...
.keras.applications.vgg16.VGG16(include_top=False, 117 weights="imagenet", 118 input_shape=(180,180,3)) 119 convbase.trainable=False#冻结卷积基 120 convbase.summary() 121 122 #模型 123 data_augmentation=tf.keras.Sequential([ 124 tf.keras.layers.RandomFlip("horizontal"), 125 tf.keras....
model=ks.models.Sequential() model.add(Dense(16,input_dim=41)) model.add(Activation('relu')) model.add(Dense(128)) model.add(Activation('relu')) model.add(Dense(64)) model.add(Activation('relu')) model.add(Dense(32)) model.add(Activation('relu')) ...