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

inputs = keras.Input(shape=(28, 28, 1))
x = modules.Convolution2D(padding='same', activation='relu', batch_normalization=True, dropout=0.2)(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, 32)        320
_________________________________________________________________
batch_normalization (BatchNo (None, 28, 28, 32)        128
_________________________________________________________________
dropout (Dropout)            (None, 28, 28, 32)        0
_________________________________________________________________
global_average_pooling2d (Gl (None, 32)                0
_________________________________________________________________
dense (Dense)                (None, 10)                330
=================================================================
Total params: 778
Trainable params: 714
Non-trainable params: 64
_________________________________________________________________

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