tf.contrib.tpu.while_loop

Builds a training loop for TPUs.

tf.contrib.tpu.while_loop(
    condition, body, inputs=None, infeed_queue=None, name=None
)

The set of loop-carried tensors corresponds to inputs. Both condition and body take the current value of the loop-carried tensors. 'body' additionally takes a tuple of infeed from infeed_queue if infeed_queue is not None. condition must return a single boolean value that determines whether iteration continues. body must return an updated list of values for the loop-carried tensors.

Args
condition	a Python function that builds the loop condition.
body	a Python function that builds the loop body.
inputs	a list of initial values passed into the training loop, or None (equivalent to an empty list).
infeed_queue	if not None, the infeed queue from which to append a tuple of arguments as inputs to condition.
name	(Deprecated) Does nothing.

Returns
The final values of the loop-carried tensors.

Raises
TypeError	if body or condition has the wrong signature.