InceptionResNetBlock-2.md

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

inputs = keras.Input(shape=(28, 28, 1))
x = modules.InceptionResNetBlock(1.0, 'block17')(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 #     Connected to                     
==================================================================================================
input_1 (InputLayer)            [(None, 28, 28, 1)]  0                                            
__________________________________________________________________________________________________
conv2d_1 (Conv2D)               (None, 28, 28, 128)  128         input_1[0][0]                    
__________________________________________________________________________________________________
batch_normalization_1 (BatchNor (None, 28, 28, 128)  384         conv2d_1[0][0]                   
__________________________________________________________________________________________________
activation_1 (Activation)       (None, 28, 28, 128)  0           batch_normalization_1[0][0]      
__________________________________________________________________________________________________
conv2d_2 (Conv2D)               (None, 28, 28, 160)  143360      activation_1[0][0]               
__________________________________________________________________________________________________
batch_normalization_2 (BatchNor (None, 28, 28, 160)  480         conv2d_2[0][0]                   
__________________________________________________________________________________________________
activation_2 (Activation)       (None, 28, 28, 160)  0           batch_normalization_2[0][0]      
__________________________________________________________________________________________________
conv2d (Conv2D)                 (None, 28, 28, 192)  192         input_1[0][0]                    
__________________________________________________________________________________________________
conv2d_3 (Conv2D)               (None, 28, 28, 192)  215040      activation_2[0][0]               
__________________________________________________________________________________________________
batch_normalization (BatchNorma (None, 28, 28, 192)  576         conv2d[0][0]                     
__________________________________________________________________________________________________
batch_normalization_3 (BatchNor (None, 28, 28, 192)  576         conv2d_3[0][0]                   
__________________________________________________________________________________________________
activation (Activation)         (None, 28, 28, 192)  0           batch_normalization[0][0]        
__________________________________________________________________________________________________
activation_3 (Activation)       (None, 28, 28, 192)  0           batch_normalization_3[0][0]      
__________________________________________________________________________________________________
concatenate (Concatenate)       (None, 28, 28, 384)  0           activation[0][0]                 
                                                                 activation_3[0][0]               
__________________________________________________________________________________________________
conv2d_4 (Conv2D)               (None, 28, 28, 1)    385         concatenate[0][0]                
__________________________________________________________________________________________________
lambda (Lambda)                 (None, 28, 28, 1)    0           input_1[0][0]                    
                                                                 conv2d_4[0][0]                   
__________________________________________________________________________________________________
activation_4 (Activation)       (None, 28, 28, 1)    0           lambda[0][0]                     
__________________________________________________________________________________________________
global_average_pooling2d (Globa (None, 1)            0           activation_4[0][0]               
__________________________________________________________________________________________________
dense (Dense)                   (None, 10)           20          global_average_pooling2d[0][0]   
==================================================================================================
Total params: 361,141
Trainable params: 359,797
Non-trainable params: 1,344
__________________________________________________________________________________________________