Iterating Through TF Dataset

TFDataset-Take.py

# if dataset is not batched
# this will take 1 example
with (ambient, target), label in dataset.take(1):
  print("ambient shape", ambient.shape)
  print("target shape", target.shape)
  print("label shape", label.shape)
  ambient_array = ambient.numpy()
  target_array = target.numpy()
  label_array = label.numpy()
  
# if dataset is batched
# this will take 1 batch
with features, labels in dataset.take(1):
  # features is a tuple of tensors
  ambients = features[0]
  targets = features[1]
  # get a single example (the first in the batch)
  ambient = ambients[0] # tensors can be sliced
  target = targets[0] # still a tensor until .numpy() is called
  print("ambient shape", ambient.shape)
  print("target shape", target.shape)
  print("label shape", label.shape)
  ambient_array = ambient.numpy()
  target_array = target.numpy()
  label_array = label.numpy()