experiments/STT-tensorflow
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Disables logging and summaries of steps, steps/s, loss etc. when RunConfig.log_step_count_steps is None.

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This is already how Estimator works (as one can see in line 2136 where we explicitly replace log_step_count_steps as None).  It should be backward compatible as current code would have crashed if log_step_count_steps is None.

PiperOrigin-RevId: 217019985
This commit is contained in:
A. Unique TensorFlower 2018-10-13 20:16:31 -07:00 committed by TensorFlower Gardener
parent 47b04fdb3e
commit 109a0c1b15
1 changed files with 23 additions and 19 deletions
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42
tensorflow/contrib/tpu/python/tpu/tpu_estimator.py
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@ -2480,17 +2480,19 @@ class TPUEstimator(estimator_lib.Estimator):
# examples_hook is added to training_hooks for both CPU and TPU
# execution.
examples_hook = ExamplesPerSecondHook(
ctx.global_batch_size,
output_dir=self.model_dir,
every_n_steps=self._log_every_n_steps)
if self._log_every_n_steps is not None:
examples_hook = ExamplesPerSecondHook(
ctx.global_batch_size,
output_dir=self.model_dir,
every_n_steps=self._log_every_n_steps)
if ctx.is_running_on_cpu(is_export_mode=is_export_mode):
logging.info('Running %s on CPU', mode)
estimator_spec = model_fn_wrapper.call_without_tpu(
features, labels, is_export_mode=is_export_mode)
estimator_spec = estimator_spec._replace(
training_hooks=estimator_spec.training_hooks + (examples_hook,))
if self._log_every_n_steps is not None:
estimator_spec = estimator_spec._replace(
training_hooks=estimator_spec.training_hooks + (examples_hook,))
return estimator_spec
assert labels is None, '`labels` passed to `model_fn` must be `None`.'
@ -2540,10 +2542,6 @@ class TPUEstimator(estimator_lib.Estimator):
with ops.control_dependencies([loss]):
global_step = array_ops.identity(training.get_global_step())
hooks = input_hooks + shutdown_hooks
logging_hook_frequency = ( # Divide and round up
(self._log_every_n_steps +
self._config.tpu_config.iterations_per_loop - 1) //
self._config.tpu_config.iterations_per_loop)
hooks.extend([
TPUInfeedOutfeedSessionHook(
ctx,
@ -2553,16 +2551,22 @@ class TPUEstimator(estimator_lib.Estimator):
run_infeed_loop_on_coordinator),
rendezvous=self._rendezvous[mode],
),
InstallSignalHandlerHook(),
training.LoggingTensorHook({
'loss': array_ops.identity(loss),
'step': global_step,
},
every_n_iter=logging_hook_frequency)
InstallSignalHandlerHook()
])
examples_hook._set_steps_per_run( # pylint: disable=protected-access
self._config.tpu_config.iterations_per_loop)
hooks.append(examples_hook)
if self._log_every_n_steps is not None:
logging_hook_frequency = ( # Divide and round up
(self._log_every_n_steps +
self._config.tpu_config.iterations_per_loop - 1) //
self._config.tpu_config.iterations_per_loop)
hooks.append(
training.LoggingTensorHook({
'loss': array_ops.identity(loss),
'step': global_step,
},
every_n_iter=logging_hook_frequency))
examples_hook._set_steps_per_run( # pylint: disable=protected-access
self._config.tpu_config.iterations_per_loop)
hooks.append(examples_hook)
if training_hooks:
hooks.extend(training_hooks)