MobileNetConvBlock.md

from tensorflow import keras
import numpy as np
from pyradox import modules

inputs = keras.Input(shape=(28, 28, 1))
x = modules.MobileNetConvBlock(filters=3, alpha=1.0)(inputs)
x = keras.layers.GlobalAvgPool2D()(x)
outputs = keras.layers.Dense(10, activation="softmax")(x)

model = keras.models.Model(inputs=inputs, outputs=outputs) 

model.summary()
keras.utils.plot_model(model, show_shapes=True, expand_nested=True)

Model: "model"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
input_1 (InputLayer)         [(None, 28, 28, 1)]       0         
_________________________________________________________________
conv2d (Conv2D)              (None, 28, 28, 3)         27        
_________________________________________________________________
batch_normalization (BatchNo (None, 28, 28, 3)         12        
_________________________________________________________________
activation (Activation)      (None, 28, 28, 3)         0         
_________________________________________________________________
global_average_pooling2d (Gl (None, 3)                 0         
_________________________________________________________________
dense (Dense)                (None, 10)                40        
=================================================================
Total params: 79
Trainable params: 73
Non-trainable params: 6
_________________________________________________________________