Merge pull request #9 from IvanKuchin/development

Enhancement: inroduce config parameter TRAIN_PASSES_PER_VALIDATION

config.py

@@ -1,4 +1,5 @@
 EPOCHS = 1000
+TRAIN_PASSES_PER_VALIDATION = 2
 
 NUMBER_OF_CONV_IN_LAYER = 2
 

tools/categorical_metrics.py

@@ -34,13 +34,13 @@ def update_state(self, y_true, y_pred, sample_weight=None):
  subj = tf.argmax(y_pred, axis = -1)
 
  if self.reduce == "max":
- self.m.assign(tf.reduce_max(subj))
+ self.m.assign(tf.reduce_max(tf.cast(subj, dtype=tf.float32)))
  elif self.reduce == "min":
- self.m.assign(tf.reduce_min(subj))
+ self.m.assign(tf.reduce_min(tf.cast(subj, dtype=tf.float32)))
  elif self.reduce == "mean":
- self.m.assign(tf.reduce_mean(subj))
+ self.m.assign(tf.reduce_mean(tf.cast(subj, dtype=tf.float32)))
  elif self.reduce == "sum":
- self.m.assign(tf.reduce_sum(subj))
+ self.m.assign(tf.reduce_sum(tf.cast(subj, dtype=tf.float32)))
 
  def result(self):
  return self.m

train_segmentation.py

@@ -49,7 +49,7 @@ def main():
  ds_train = craft_datasets(os.path.join(config.TFRECORD_FOLDER, "train"))
  ds_valid = craft_datasets(os.path.join(config.TFRECORD_FOLDER, "valid"))
 
- ds_train = ds_train.prefetch(1).repeat(2)
+ ds_train = ds_train.prefetch(1).repeat(config.TRAIN_PASSES_PER_VALIDATION)
 
  model = craft_network(config.MODEL_CHECKPOINT)
  # predict_on_random_data(model)
@@ -97,7 +97,7 @@ def main():
  tensorboard_cb,
  reduce_lr_on_plateau,
  csv_logger,
- # early_stopping,
+ early_stopping,
  tf.keras.callbacks.TerminateOnNaN()],
  verbose = 1,
  # workers = 2