flipping and scaling data augmentation

configs/train.json

@@ -3,7 +3,8 @@
 
  "data" : {
  "path" : "/deep/group/med/alivecor/training2017",
- "seed" : 2016
+ "seed" : 2016,
+ "augment" : true
  },
 
  "optimizer" : {

loader.py

@@ -28,13 +28,15 @@ class Loader:
  """
 
  def __init__(self, data_path, batch_size,
- val_frac=0.2, seed=None):
+ val_frac=0.2, seed=None,
+ augment=False):
  """
  :param data_path: path to the training and validation files
  :param batch_size: size of the minibatches to train on
  :param val_frac: fraction of the dataset to use for validation
  (held out by record)
  :param seed: seed the rng for shuffling data
+ :param augment: set to true to augment the training data
  """
  if not os.path.exists(data_path):
  msg = "Non-existent data path: {}".format(data_path)
@@ -44,6 +46,7 @@ def __init__(self, data_path, batch_size,
  random.seed(seed)
 
  self.batch_size = batch_size
+ self.augment = augment
 
  self._train, self._val = load_all_data(data_path, val_frac)
  logger.debug("Training set has " + str(len(self._train)) + " samples")
@@ -122,7 +125,10 @@ def output_dim(self):
  @property
  def train(self):
  """ Returns the raw training set. """
- return self._train
+ for ecgs, labels in self._train:
+ if self.augment:
+ ecgs = [transform(ecg) for ecg in ecgs]
+ yield (ecgs, labels)
 
  @property
  def val(self):
@@ -157,6 +163,11 @@ def __setstate__(self, state):
  self._class_to_int = state[3]
  self.class_counts = state[4]
 
+def transform(ecg):
+ scale = random.uniform(0.1, 5.0)
+ flip = random.choice([-1.0, 1.0])
+ return ecg * flip * scale
+
 def load_all_data(data_path, val_frac):
  """
  Returns tuple of training and validation sets. Each set

train.py

@@ -24,6 +24,7 @@ def run_epoch(model, data_loader, session, summarizer):
  for batch in data_loader.train:
  ops = [model.train_op, model.avg_loss,
  model.avg_acc, model.it, summary_op]
+
  res = session.run(ops, feed_dict=model.feed_dict(*batch))
  _, loss, acc, it, summary = res
  summarizer.add_summary(summary, global_step=it)
@@ -89,8 +90,9 @@ def main(argv=None):
  random.seed(config['seed'])
  epochs = config['optimizer']['epochs']
  data_loader = loader.Loader(config['data']['path'],
- config['model']['batch_size'],
- seed=config['data']['seed'])
+ config['model']['batch_size'],
+ seed=config['data']['seed'],
+ augment=config['data'].get('augment', False))
 
  model = network.Network(is_verbose)