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GitHub Repository: amanchadha/coursera-deep-learning-specialization
 Path: blob/master/C4 - Convolutional Neural Networks/Week 3/Image Segmentation Unet/outputs.py
Views: 4818
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unet_model_output = [['InputLayer', [(None, 96, 128, 3)], 0],

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['Conv2D', (None, 96, 128, 32), 896, 'same', 'relu', 'HeNormal'],

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['Conv2D', (None, 96, 128, 32), 9248, 'same', 'relu', 'HeNormal'],

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['MaxPooling2D', (None, 48, 64, 32), 0, (2, 2)],

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['Conv2D', (None, 48, 64, 64), 18496, 'same', 'relu', 'HeNormal'],

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['Conv2D', (None, 48, 64, 64), 36928, 'same', 'relu', 'HeNormal'],

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['MaxPooling2D', (None, 24, 32, 64), 0, (2, 2)],

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['Conv2D', (None, 24, 32, 128), 73856, 'same', 'relu', 'HeNormal'],

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['Conv2D', (None, 24, 32, 128), 147584, 'same', 'relu', 'HeNormal'],

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['MaxPooling2D', (None, 12, 16, 128), 0, (2, 2)],

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['Conv2D', (None, 12, 16, 256), 295168, 'same', 'relu', 'HeNormal'],

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['Conv2D', (None, 12, 16, 256), 590080, 'same', 'relu', 'HeNormal'],

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['Dropout', (None, 12, 16, 256), 0, 0.3],

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['MaxPooling2D', (None, 6, 8, 256), 0, (2, 2)],

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['Conv2D', (None, 6, 8, 512), 1180160, 'same', 'relu', 'HeNormal'],

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['Conv2D', (None, 6, 8, 512), 2359808, 'same', 'relu', 'HeNormal'],

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['Dropout', (None, 6, 8, 512), 0, 0.3],

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['Conv2DTranspose', (None, 12, 16, 256), 1179904],

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['Concatenate', (None, 12, 16, 512), 0],

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['Conv2D', (None, 12, 16, 256), 1179904, 'same', 'relu', 'HeNormal'],

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['Conv2D', (None, 12, 16, 256), 590080, 'same', 'relu', 'HeNormal'],

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['Conv2DTranspose', (None, 24, 32, 128), 295040],

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['Concatenate', (None, 24, 32, 256), 0],

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['Conv2D', (None, 24, 32, 128), 295040, 'same', 'relu', 'HeNormal'],

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['Conv2D', (None, 24, 32, 128), 147584, 'same', 'relu', 'HeNormal'],

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['Conv2DTranspose', (None, 48, 64, 64), 73792],

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['Concatenate', (None, 48, 64, 128), 0],

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['Conv2D', (None, 48, 64, 64), 73792, 'same', 'relu', 'HeNormal'],

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['Conv2D', (None, 48, 64, 64), 36928, 'same', 'relu', 'HeNormal'],

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['Conv2DTranspose', (None, 96, 128, 32), 18464],

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['Concatenate', (None, 96, 128, 64), 0],

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['Conv2D', (None, 96, 128, 32), 18464, 'same', 'relu', 'HeNormal'],

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['Conv2D', (None, 96, 128, 32), 9248, 'same', 'relu', 'HeNormal'],

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['Conv2D', (None, 96, 128, 32), 9248, 'same', 'relu', 'HeNormal'],

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['Conv2D', (None, 96, 128, 23), 759, 'same', 'linear', 'GlorotUniform']]

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