visualkeras Spam Dense example#

An example showing the visualkeras function used by a tf.keras.Model model.

# Authors: The scikit-plots developers
# SPDX-License-Identifier: BSD-3-Clause

# Force garbage collection
import gc; gc.collect()
import tensorflow.python as tf_python
# Clear the GPU memory cache
tf_python.keras.backend.clear_session()

model = tf_python.keras.models.Sequential()
model.add(tf_python.keras.layers.InputLayer(input_shape=(100,)))

# Add Dense layers
model.add(tf_python.keras.layers.Dense(64, activation='relu'))  # input_shape=(100,)
model.add(tf_python.keras.layers.Dense(32, activation='relu'))
model.add(tf_python.keras.layers.Dense(1, activation='sigmoid'))

# Compile the model
model.compile(optimizer='rmsprop', loss='binary_crossentropy', metrics=['accuracy'])

from scikitplot import visualkeras

img_spam = visualkeras.layered_view(
  model,
  to_file='../result_images/spam_dense.png',
  min_xy=10, min_z=10, scale_xy=10, scale_z=10,
  one_dim_orientation='x',
)
try:
    import matplotlib.pyplot as plt
    plt.imshow(img_spam)
    plt.axis('off')
    plt.show()
except:
    pass