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Talles L
Talles L

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Visualizing a Keras model

#keras

This:

my_model.summary()
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Gives you something like this on the terminal:

Model: "fashion_mnist" ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓ ┃ Layer (type) ┃ Output Shape ┃ Param # ┃ ┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩ │ scale_to_0_1_range (Rescaling) │ (None, 784) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ hidden_1 (Dense) │ (None, 300) │ 235,500 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ hidden_2 (Dense) │ (None, 100) │ 30,100 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ output (Dense) │ (None, 10) │ 1,010 │ └─────────────────────────────────┴────────────────────────┴───────────────┘ Total params: 266,610 (1.02 MB) Trainable params: 266,610 (1.02 MB) Non-trainable params: 0 (0.00 B)
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If you prefer a .png:

keras.utils.plot_model(my_model, to_file='model.png', show_shapes=True, show_dtype=True, show_layer_names=True, show_layer_activations=True)
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Saves an image like this:

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