The following Keras codes show a deep learning network. Please draw the network structure from input...

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The following Keras codes show a deep learning network. Please draw the network structure from input to the output to explicitly show network components and parameters: 1. Please draw diagram of the designed network [0.5 pt] 2. Show input, output sizes, and number of weight values of each convolution layer [0.5 pt]. 3. Show input and output size of each pooling layer [0.5 pt]. 4. Show input, output sizes, and number of weight values of each dense layer [0.5 pt]. network Sequential() model.add(Conv2D(32, (3, 3), activation="relu",input_shape=c(28,28,3)) model.add(MaxPooling2D((2,2)) model.add(Conv2D(64,(3,3), activation="relu")) model.add(MaxPooling2D((2,2)) model.add(Flatten()) model.add(Dense(64,activation='relu')) model.add(Dense(10,activation='softmax')) The following Keras codes show a deep learning network. Please draw the network structure from input to the output to explicitly show network components and parameters: 1. Please draw diagram of the designed network [0.5 pt] 2. Show input, output sizes, and number of weight values of each convolution layer [0.5 pt]. 3. Show input and output size of each pooling layer [0.5 pt]. 4. Show input, output sizes, and number of weight values of each dense layer [0.5 pt]. network Sequential() model.add(Conv2D(32, (3, 3), activation="relu",input_shape=c(28,28,3)) model.add(MaxPooling2D((2,2)) model.add(Conv2D(64,(3,3), activation="relu")) model.add(MaxPooling2D((2,2)) model.add(Flatten()) model.add(Dense(64,activation='relu')) model.add(Dense(10,activation='softmax'))

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