Commit be8c48de authored by Jean Ibarz's avatar Jean Ibarz
Browse files

Added parameters in default_model_creator() for on-line data augmentation,...

Added parameters in default_model_creator() for on-line data augmentation, random scale and random shift.
parent 8153fe20
import tensorflow as tf import tensorflow as tf
import tensorflow.keras.layers as tkl
from core.layers import RandomShift2DLayer, RandomScale2DLayer from core.layers import RandomShift2DLayer, RandomScale2DLayer
def default_model_creator(): def default_model_creator(model_config):
model = tf.keras.Sequential([ model = tf.keras.Sequential([
RandomScale2DLayer(minval=-10, maxval=10), RandomScale2DLayer(minval=model_config['random_scale']['minval'],
RandomShift2DLayer(minval=0, maxval=100, axis=1), maxval=model_config['random_scale']['maxval']),
tf.keras.layers.Flatten(), RandomShift2DLayer(minval=model_config['random_shift']['minval'],
tf.keras.layers.Dense(units=320, activation='relu'), maxval=model_config['random_shift']['maxval'],
tf.keras.layers.Dropout(rate=0.05), axis=1),
tf.keras.layers.Dense(units=160, activation='relu'), tkl.Flatten(),
tf.keras.layers.Dropout(rate=0.05), tkl.Dense(units=320, activation='relu'),
tf.keras.layers.Dense(units=80, activation='relu'), tkl.Dropout(rate=0.05),
tf.keras.layers.Dropout(rate=0.05), tkl.Dense(units=160, activation='relu'),
tf.keras.layers.Dense(units=40, activation='relu'), tkl.Dropout(rate=0.05),
tf.keras.layers.Dropout(rate=0.0), tkl.Dense(units=80, activation='relu'),
tf.keras.layers.Dense(units=10, activation='relu'), tkl.Dropout(rate=0.05),
tf.keras.layers.Dense(units=10, activation='relu'), tkl.Dense(units=40, activation='relu'),
tf.keras.layers.Dense(units=10, activation='relu'), tkl.Dropout(rate=0.0),
tf.keras.layers.Dense(units=10, activation='relu'), tkl.Dense(units=10, activation='relu'),
tf.keras.layers.Dense(units=10, activation='relu'), tkl.Dense(units=10, activation='relu'),
tf.keras.layers.Dense(units=1, activation='sigmoid'), tkl.Dense(units=10, activation='relu'),
tf.keras.layers.experimental.preprocessing.Rescaling(scale=360, offset=0.0) tkl.Dense(units=10, activation='relu'),
tkl.Dense(units=10, activation='relu'),
tkl.Dense(units=1, activation='sigmoid'),
tkl.experimental.preprocessing.Rescaling(scale=360, offset=0.0)
]) ])
return model return model
Supports Markdown
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment