def test_invalid_eval_spec(self):
estimator = estimator_lib.Estimator(model_fn=lambda features: features)
train_spec = training.TrainSpec(input_fn=lambda: 1)
invalid_eval_spec = object()
with self.assertRaisesRegexp(TypeError, _INVALID_EVAL_SPEC_MSG):
training._TrainingExecutor(estimator, train_spec, invalid_eval_spec)
def test_invalid_estimator(self):
invalid_estimator = object()
train_spec = training.TrainSpec(input_fn=lambda: 1)
eval_spec = training.EvalSpec(input_fn=lambda: 1)
with self.assertRaisesRegexp(TypeError, _INVALID_ESTIMATOR_MSG):
training._TrainingExecutor(invalid_estimator, train_spec, eval_spec)
def test_invalid_eval_spec(self):
estimator = estimator_lib.Estimator(model_fn=lambda features: features)
train_spec = training.TrainSpec(input_fn=lambda: 1)
invalid_eval_spec = object()
with self.assertRaisesRegexp(TypeError, _INVALID_EVAL_SPEC_MSG):
training._TrainingExecutor(estimator, train_spec, invalid_eval_spec)
def test_invalid_estimator(self):
invalid_estimator = object()
train_spec = training.TrainSpec(input_fn=lambda: 1)
eval_spec = training.EvalSpec(input_fn=lambda: 1)
with self.assertRaisesRegexp(TypeError, _INVALID_ESTIMATOR_MSG):
training._TrainingExecutor(invalid_estimator, train_spec, eval_spec)
def test_fail_with_none_task_id(self):
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
mock_train_spec = test.mock.Mock(spec=training.TrainSpec)
mock_eval_spec = test.mock.Mock(spec=training.EvalSpec)
mock_est.config = test.mock.PropertyMock(spec=run_config_lib.RunConfig)
mock_est.config.cluster_spec = {'gs': 'dummy'}
mock_est.config.master = 'grpc://...'
mock_est.config.task_type = 'gs'
mock_est.config.task_id = None
with self.assertRaisesRegexp(RuntimeError,
_INVALID_CONFIG_FOR_STD_SERVER_MSG):
training._TrainingExecutor(mock_est, mock_train_spec,
mock_eval_spec).run_ps()
def test_fail_with_empty_task_type(self):
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
mock_train_spec = test.mock.Mock(spec=training.TrainSpec)
mock_eval_spec = test.mock.Mock(spec=training.EvalSpec)
mock_est.config = test.mock.PropertyMock(spec=run_config_lib.RunConfig)
mock_est.config.cluster_spec = {'gs': 'dummy'}
mock_est.config.master = 'grpc://...'
mock_est.config.task_type = ''
mock_est.config.task_id = 2
with self.assertRaisesRegexp(RuntimeError,
_INVALID_CONFIG_FOR_STD_SERVER_MSG):
training._TrainingExecutor(mock_est, mock_train_spec,
mock_eval_spec).run_ps()
def test_evaluate_with_evaluate_spec(self, mock_latest_ckpt):
latest_ckpt_path = mock_latest_ckpt.return_value
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
mock_train_spec = test.mock.Mock(spec=training.TrainSpec)
self._set_up_mock_est_to_train_and_evaluate_once(
mock_est, mock_train_spec)
eval_spec = training.EvalSpec(input_fn=lambda: 1,
steps=2,
hooks=[_FakeHook()],
name='cont_eval',
delay_secs=0,
throttle_secs=0)
executor = training._TrainingExecutor(mock_est, mock_train_spec,
eval_spec)
executor.run_evaluator()
mock_est.evaluate.assert_called_with(name='cont_eval',
input_fn=eval_spec.input_fn,
steps=eval_spec.steps,
checkpoint_path=latest_ckpt_path,
hooks=eval_spec.hooks)
self.assertFalse(mock_est.train.called)
def test_that_export_fn_is_called_with_run_local(self):
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
mock_train_spec = test.mock.Mock(spec=training.TrainSpec)
mock_train_spec.max_steps = 200
mock_est.evaluate.return_value = {
_GLOBAL_STEP_KEY: mock_train_spec.max_steps
}
# _validate_hooks would have made sure that train_spec.hooks is [], when
# None were passed.
mock_train_spec.hooks = []
def export_fn(estimator, *args, **kwargs):
del args, kwargs
estimator.export_fn_was_called = True
export_strategy = export_strategy_lib.ExportStrategy(
name='see_whether_export_fn_is_called', export_fn=export_fn)
eval_spec = training.EvalSpec(input_fn=lambda: 1,
steps=2,
delay_secs=0,
throttle_secs=213,
export_strategies=export_strategy)
executor = training._TrainingExecutor(mock_est, mock_train_spec,
eval_spec)
executor.run_local()
self.assertTrue(mock_est.export_fn_was_called)
def test_runs_in_a_loop_until_max_steps(self):
mock_est = test.mock.Mock(spec=estimator_lib.Estimator, model_dir='path/')
mock_est.latest_checkpoint = self.unique_checkpoint_every_time_fn
mock_est.times_export_fn_was_called = 0
def export_fn(estimator, *args, **kwargs):
del args, kwargs
estimator.times_export_fn_was_called += 1
export_strategy = export_strategy_lib.ExportStrategy(
name='see_whether_export_fn_is_called', export_fn=export_fn)
train_spec = training.TrainSpec(
input_fn=lambda: 1, max_steps=300, hooks=[_FakeHook()])
eval_spec = training.EvalSpec(
input_fn=lambda: 1,
hooks=[_FakeHook()],
throttle_secs=100,
export_strategies=export_strategy)
# should be called 3 times.
mock_est.evaluate.side_effect = [{
_GLOBAL_STEP_KEY: train_spec.max_steps - 100
}, {
_GLOBAL_STEP_KEY: train_spec.max_steps - 50
}, {
_GLOBAL_STEP_KEY: train_spec.max_steps
}]
executor = training._TrainingExecutor(mock_est, train_spec, eval_spec)
executor.run_local()
self.assertEqual(3, mock_est.train.call_count)
self.assertEqual(3, mock_est.evaluate.call_count)
self.assertEqual(3, mock_est.times_export_fn_was_called)
def test_skip_evaluation_due_to_ckpt(self, mock_latest_ckpt):
training_max_step = 200
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
mock_est.evaluate.side_effect = [{
_GLOBAL_STEP_KEY:
training_max_step // 2
}, {
_GLOBAL_STEP_KEY: training_max_step
}]
mock_train_spec = test.mock.Mock(spec=training.TrainSpec)
mock_train_spec.max_steps = training_max_step
self._set_up_mock_est_to_train_and_evaluate_once(
mock_est, mock_train_spec)
# First two items are invalid, next two items are same.
mock_latest_ckpt.side_effect = [None, '', 'same', 'same', 'path_2']
eval_spec = training.EvalSpec(input_fn=lambda: 1,
delay_secs=0,
throttle_secs=0)
executor = training._TrainingExecutor(mock_est, mock_train_spec,
eval_spec)
with test.mock.patch.object(logging, 'warning') as mock_log:
executor.run_evaluator()
# Three checkpoint paths are invalid.
self.assertEqual(5, mock_latest_ckpt.call_count)
self.assertEqual(2, mock_est.evaluate.call_count)
# Two warning logs are expected (last warning time is reset after a
# successuful evaluation)
self.assertEqual(2, mock_log.call_count)
def test_that_export_fn_is_called(self):
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
mock_train_spec = test.mock.Mock(spec=training.TrainSpec)
self._set_up_mock_est_to_train_and_evaluate_once(
mock_est, mock_train_spec)
def export_fn(estimator, *args, **kwargs):
del args, kwargs
estimator.export_fn_was_called = True
export_strategy = export_strategy_lib.ExportStrategy(
name='see_whether_export_fn_is_called', export_fn=export_fn)
eval_spec = training.EvalSpec(input_fn=lambda: 1,
steps=2,
delay_secs=0,
throttle_secs=0,
export_strategies=export_strategy)
executor = training._TrainingExecutor(mock_est, mock_train_spec,
eval_spec)
executor.run_evaluator()
# Verify that export_fn was called on the right estimator.
self.assertTrue(mock_est.export_fn_was_called)
def test_that_export_is_called_with_run_local(self):
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
mock_train_spec = test.mock.Mock(spec=training.TrainSpec)
mock_train_spec.max_steps = 200
mock_est.evaluate.return_value = {
_GLOBAL_STEP_KEY: mock_train_spec.max_steps
}
# _validate_hooks would have made sure that train_spec.hooks is [], when
# None were passed.
mock_train_spec.hooks = []
def export(estimator, *args, **kwargs):
del args, kwargs
estimator.export_was_called = True
exporter = test.mock.PropertyMock(spec=exporter_lib.Exporter)
exporter.name = 'see_whether_export_is_called'
exporter.export = export
eval_spec = training.EvalSpec(
input_fn=lambda: 1,
steps=2,
start_delay_secs=0,
throttle_secs=213,
exporters=exporter)
executor = training._TrainingExecutor(mock_est, mock_train_spec, eval_spec)
executor.run_local()
self.assertTrue(mock_est.export_was_called)
def test_evaluate_multiple_times(self):
training_max_step = 200
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
mock_est.model_dir = compat.as_bytes(test.get_temp_dir())
mock_est.evaluate.side_effect = [
{_GLOBAL_STEP_KEY: training_max_step // 2},
{_GLOBAL_STEP_KEY: training_max_step}
]
mock_est.latest_checkpoint.side_effect = ['path_1', 'path_2']
mock_train_spec = test.mock.Mock(spec=training.TrainSpec)
mock_train_spec.max_steps = training_max_step
exporter = test.mock.PropertyMock(spec=exporter_lib.Exporter)
exporter.name = 'see_how_many_times_export_is_called'
eval_spec = training.EvalSpec(
input_fn=lambda: 1,
start_delay_secs=0,
throttle_secs=0,
exporters=exporter)
executor = training._TrainingExecutor(mock_est, mock_train_spec, eval_spec)
executor.run_evaluator()
self.assertEqual(2, mock_est.evaluate.call_count)
self.assertEqual(2, exporter.export.call_count)
def test_evaluate_multiple_times(self):
training_max_step = 200
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
mock_est.model_dir = compat.as_bytes(test.get_temp_dir())
mock_est.evaluate.side_effect = [
{_GLOBAL_STEP_KEY: training_max_step // 2},
{_GLOBAL_STEP_KEY: training_max_step}
]
mock_est.latest_checkpoint.side_effect = ['path_1', 'path_2']
mock_train_spec = test.mock.Mock(spec=training.TrainSpec)
mock_train_spec.max_steps = training_max_step
mock_est.times_export_fn_was_called = 0
def export_fn(estimator, *args, **kwargs):
del args, kwargs
estimator.times_export_fn_was_called += 1
export_strategy = export_strategy_lib.ExportStrategy(
name='see_whether_export_fn_is_called', export_fn=export_fn)
eval_spec = training.EvalSpec(
input_fn=lambda: 1,
delay_secs=0,
throttle_secs=0,
export_strategies=export_strategy)
executor = training._TrainingExecutor(mock_est, mock_train_spec, eval_spec)
executor.run_evaluator()
self.assertEqual(2, mock_est.evaluate.call_count)
self.assertEqual(2, mock_est.times_export_fn_was_called)
def test_train_and_evaluate_args(self):
mock_est = test.mock.Mock(spec=estimator_lib.Estimator,
model_dir='path/')
mock_est.latest_checkpoint.return_value = 'checkpoint_path/'
train_spec = training.TrainSpec(input_fn=lambda: 1,
max_steps=300,
hooks=[_FakeHook()])
eval_spec = training.EvalSpec(input_fn=lambda: 1,
steps=2,
hooks=[_FakeHook()],
name='local_eval')
mock_est.evaluate.return_value = {
_GLOBAL_STEP_KEY: train_spec.max_steps
}
executor = training._TrainingExecutor(mock_est, train_spec, eval_spec)
executor.run_local()
mock_est.evaluate.assert_called_with(
name=eval_spec.name,
input_fn=eval_spec.input_fn,
steps=eval_spec.steps,
checkpoint_path='checkpoint_path/',
hooks=eval_spec.hooks)
train_args = mock_est.train.call_args[1]
self.assertEqual(list(train_spec.hooks),
list(train_args['hooks'][:-1]))
self.assertEqual(train_spec.input_fn, train_args['input_fn'])
self.assertEqual(train_spec.max_steps, train_args['max_steps'])
def testRequiredArgumentsSet(self):
estimator = estimator_lib.Estimator(model_fn=lambda features: features)
train_spec = training.TrainSpec(input_fn=lambda: 1)
eval_spec = training.EvalSpec(input_fn=lambda: 1)
executor = training._TrainingExecutor(estimator, train_spec, eval_spec)
self.assertEqual(estimator, executor.estimator)
def testRequiredArgumentsSet(self):
estimator = estimator_lib.Estimator(model_fn=lambda features: features)
train_spec = training.TrainSpec(input_fn=lambda: 1)
eval_spec = training.EvalSpec(input_fn=lambda: 1)
executor = training._TrainingExecutor(estimator, train_spec, eval_spec)
self.assertEqual(estimator, executor.estimator)
def test_skip_evaluation_due_to_ckpt(self):
training_max_step = 200
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
mock_est.evaluate.side_effect = [
{_GLOBAL_STEP_KEY: training_max_step // 2},
{_GLOBAL_STEP_KEY: training_max_step}
]
mock_train_spec = test.mock.Mock(spec=training.TrainSpec)
mock_train_spec.max_steps = training_max_step
self._set_up_mock_est_to_train_and_evaluate_once(mock_est, mock_train_spec)
# First two items are invalid, next two items are same.
mock_est.latest_checkpoint.side_effect = [
None, '', 'same', 'same', 'path_2'
]
eval_spec = training.EvalSpec(
input_fn=lambda: 1, start_delay_secs=0, throttle_secs=0)
executor = training._TrainingExecutor(mock_est, mock_train_spec, eval_spec)
with test.mock.patch.object(logging, 'warning') as mock_log:
executor.run_evaluator()
# Three checkpoint paths are invalid.
self.assertEqual(5, mock_est.latest_checkpoint.call_count)
self.assertEqual(2, mock_est.evaluate.call_count)
# Two warning logs are expected (last warning time is reset after a
# successuful evaluation)
self.assertEqual(2, mock_log.call_count)
def test_that_export_is_called(self):
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
mock_train_spec = test.mock.Mock(spec=training.TrainSpec)
self._set_up_mock_est_to_train_and_evaluate_once(mock_est, mock_train_spec)
def export(estimator, *args, **kwargs):
del args, kwargs
estimator.export_was_called = True
exporter = test.mock.PropertyMock(spec=exporter_lib.Exporter)
exporter.name = 'see_whether_export_is_called'
exporter.export = export
eval_spec = training.EvalSpec(
input_fn=lambda: 1,
steps=2,
start_delay_secs=0,
throttle_secs=0,
exporters=exporter)
executor = training._TrainingExecutor(mock_est, mock_train_spec, eval_spec)
executor.run_evaluator()
# Verify that export was called on the right estimator.
self.assertTrue(mock_est.export_was_called)
def test_train_with_train_spec(self, mock_server, unused_mock_sleep):
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
mock_est.config = self._run_config
train_spec = training.TrainSpec(input_fn=lambda: 1,
max_steps=2,
hooks=[_FakeHook()])
mock_eval_spec = test.mock.Mock(spec=training.EvalSpec)
mock_server_instance = mock_server.return_value
executor = training._TrainingExecutor(mock_est, train_spec,
mock_eval_spec)
self._run_task(executor)
mock_server.assert_called_with(mock_est.config.cluster_spec,
job_name=mock_est.config.task_type,
task_index=mock_est.config.task_id,
config=test.mock.ANY,
start=False)
self.assertTrue(mock_server_instance.start.called)
mock_est.train.assert_called_with(input_fn=train_spec.input_fn,
max_steps=train_spec.max_steps,
hooks=train_spec.hooks)
mock_est.evaluate.assert_not_called()
mock_est.export_savedmodel.assert_not_called()
def test_runs_in_a_loop_until_max_steps(self):
mock_est = test.mock.Mock(spec=estimator_lib.Estimator, model_dir='path/')
mock_est.latest_checkpoint = self.unique_checkpoint_every_time_fn
mock_est.times_export_was_called = 0
def export(estimator, *args, **kwargs):
del args, kwargs
estimator.times_export_was_called += 1
exporter = test.mock.PropertyMock(spec=exporter_lib.Exporter)
exporter.name = 'see_how_many_times_export_is_called'
exporter.export = export
train_spec = training.TrainSpec(
input_fn=lambda: 1, max_steps=300, hooks=[_FakeHook()])
eval_spec = training.EvalSpec(
input_fn=lambda: 1,
hooks=[_FakeHook()],
throttle_secs=100,
exporters=exporter)
# should be called 3 times.
mock_est.evaluate.side_effect = [{
_GLOBAL_STEP_KEY: train_spec.max_steps - 100
}, {
_GLOBAL_STEP_KEY: train_spec.max_steps - 50
}, {
_GLOBAL_STEP_KEY: train_spec.max_steps
}]
executor = training._TrainingExecutor(mock_est, train_spec, eval_spec)
executor.run_local()
self.assertEqual(3, mock_est.train.call_count)
self.assertEqual(3, mock_est.evaluate.call_count)
self.assertEqual(3, mock_est.times_export_was_called)
def test_train_with_train_spec(self, mock_server, unused_mock_sleep):
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
mock_est.config = self._run_config
train_spec = training.TrainSpec(
input_fn=lambda: 1, max_steps=2, hooks=[_FakeHook()])
mock_eval_spec = test.mock.Mock(spec=training.EvalSpec)
mock_server_instance = mock_server.return_value
executor = training._TrainingExecutor(mock_est, train_spec, mock_eval_spec)
self._run_task(executor)
mock_server.assert_called_with(
mock_est.config.cluster_spec,
job_name=mock_est.config.task_type,
task_index=mock_est.config.task_id,
config=test.mock.ANY,
start=False)
self.assertTrue(mock_server_instance.start.called)
mock_est.train.assert_called_with(input_fn=train_spec.input_fn,
max_steps=train_spec.max_steps,
hooks=train_spec.hooks,
saving_listeners=test.mock.ANY)
mock_est.evaluate.assert_not_called()
mock_est.export_savedmodel.assert_not_called()
def test_evaluate_multiple_times(self):
training_max_step = 200
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
mock_est.model_dir = compat.as_bytes(test.get_temp_dir())
mock_est.evaluate.side_effect = [
{_GLOBAL_STEP_KEY: training_max_step // 2},
{_GLOBAL_STEP_KEY: training_max_step}
]
mock_est.latest_checkpoint.side_effect = ['path_1', 'path_2']
mock_train_spec = test.mock.Mock(spec=training.TrainSpec)
mock_train_spec.max_steps = training_max_step
mock_est.times_export_fn_was_called = 0
def export_fn(estimator, *args, **kwargs):
del args, kwargs
estimator.times_export_fn_was_called += 1
export_strategy = export_strategy_lib.ExportStrategy(
name='see_whether_export_fn_is_called', export_fn=export_fn)
eval_spec = training.EvalSpec(
input_fn=lambda: 1,
delay_secs=0,
throttle_secs=0,
export_strategies=export_strategy)
executor = training._TrainingExecutor(mock_est, mock_train_spec, eval_spec)
executor.run_evaluator()
self.assertEqual(2, mock_est.evaluate.call_count)
self.assertEqual(2, mock_est.times_export_fn_was_called)
def test_errors_out_if_throttle_secs_is_zero(self):
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
train_spec = training.TrainSpec(input_fn=lambda: 1)
eval_spec = training.EvalSpec(input_fn=lambda: 1, throttle_secs=0)
executor = training._TrainingExecutor(mock_est, train_spec, eval_spec)
with self.assertRaisesRegexp(ValueError, 'throttle_secs'):
executor.run_local()
def test_errors_out_if_throttle_secs_is_zero(self):
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
train_spec = training.TrainSpec(input_fn=lambda: 1)
eval_spec = training.EvalSpec(input_fn=lambda: 1, throttle_secs=0)
executor = training._TrainingExecutor(mock_est, train_spec, eval_spec)
with self.assertRaisesRegexp(ValueError, 'throttle_secs'):
executor.run_local()
def test_errors_out_if_evaluate_returns_non_dict(self):
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
train_spec = training.TrainSpec(input_fn=lambda: 1)
eval_spec = training.EvalSpec(input_fn=(lambda: 1), throttle_secs=123)
mock_est.evaluate.return_value = 123
executor = training._TrainingExecutor(mock_est, train_spec, eval_spec)
with self.assertRaisesRegexp(TypeError, _INVALID_EVAL_RESULT_TYPE_ERR):
executor.run_local()
def test_errors_out_if_evaluate_returns_empty_dict(self):
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
train_spec = training.TrainSpec(input_fn=lambda: 1)
eval_spec = training.EvalSpec(input_fn=(lambda: 1),
start_delay_secs=0, throttle_secs=0)
mock_est.evaluate.return_value = {}
executor = training._TrainingExecutor(mock_est, train_spec, eval_spec)
with self.assertRaisesRegexp(RuntimeError, _INVALID_EMPTY_EVAL_RESULT_ERR):
executor.run_evaluator()
def test_errors_out_if_evaluate_returns_dict_without_global_step(self):
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
train_spec = training.TrainSpec(input_fn=lambda: 1)
eval_spec = training.EvalSpec(input_fn=(lambda: 1), throttle_secs=123)
mock_est.evaluate.return_value = {'loss': 123}
executor = training._TrainingExecutor(mock_est, train_spec, eval_spec)
with self.assertRaisesRegexp(RuntimeError,
_MISSING_GLOBAL_STEP_IN_EVAL_RESULT_ERR):
executor.run_local()
def test_no_delay_for_master(self, _):
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
mock_est.config = self._run_config
mock_train_spec = test.mock.Mock(spec=training.TrainSpec)
mock_eval_spec = test.mock.Mock(spec=training.EvalSpec)
executor = training._TrainingExecutor(mock_est, mock_train_spec,
mock_eval_spec)
with test.mock.patch.object(time, 'sleep') as mock_sleep:
self._run_task(executor)
mock_sleep.assert_not_called()
def test_no_server_startup_in_google(self, mock_server, unused_mock_sleep):
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
mock_est.config = self._run_config
mock_train_spec = test.mock.Mock(spec=training.TrainSpec)
mock_eval_spec = test.mock.Mock(spec=training.EvalSpec)
executor = training._TrainingExecutor(mock_est, mock_train_spec,
mock_eval_spec)
tf_config = {'TF_CONFIG': json.dumps(_TF_CONFIG_FOR_GOOGLE)}
with test.mock.patch.dict('os.environ', tf_config):
self._run_task(executor)
mock_server.assert_not_called()
def test_no_delay_for_master(self, _):
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
mock_est.config = self._run_config
mock_train_spec = test.mock.Mock(spec=training.TrainSpec)
mock_eval_spec = test.mock.Mock(spec=training.EvalSpec)
executor = training._TrainingExecutor(mock_est, mock_train_spec,
mock_eval_spec)
with test.mock.patch.object(time, 'sleep') as mock_sleep:
self._run_task(executor)
mock_sleep.assert_not_called()
def test_no_server_startup_in_google(self, mock_server, unused_mock_sleep):
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
mock_est.config = self._run_config
mock_train_spec = test.mock.Mock(spec=training.TrainSpec)
mock_eval_spec = test.mock.Mock(spec=training.EvalSpec)
executor = training._TrainingExecutor(mock_est, mock_train_spec,
mock_eval_spec)
tf_config = {'TF_CONFIG': json.dumps(_TF_CONFIG_FOR_GOOGLE)}
with test.mock.patch.dict('os.environ', tf_config):
self._run_task(executor)
mock_server.assert_not_called()
def test_send_stop_at_secs_to_train(self):
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
train_spec = training.TrainSpec(
input_fn=lambda: 1, max_steps=2, hooks=[_FakeHook()])
eval_spec = training.EvalSpec(
input_fn=lambda: 1, hooks=[_FakeHook()], throttle_secs=100)
mock_est.evaluate.return_value = {_GLOBAL_STEP_KEY: train_spec.max_steps}
executor = training._TrainingExecutor(mock_est, train_spec, eval_spec)
executor.run_local()
stop_hook = mock_est.train.call_args[1]['hooks'][-1]
self.assertIsInstance(stop_hook, training._StopAtSecsHook)
self.assertEqual(eval_spec.throttle_secs, stop_hook._stop_after_secs)
def test_delay_for_worker(self, _):
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
mock_est.config = self._run_config
mock_train_spec = test.mock.Mock(spec=training.TrainSpec)
mock_eval_spec = test.mock.Mock(spec=training.EvalSpec)
executor = training._TrainingExecutor(mock_est, mock_train_spec,
mock_eval_spec)
expected_secs = (self._run_config.task_id + 1) * _DELAY_SECS_PER_WORKER
with test.mock.patch.object(time, 'sleep') as mock_sleep:
mock_sleep.side_effect = lambda s: self.assertEqual(expected_secs, s)
self._run_task(executor)
self.assertTrue(mock_sleep.called)
def test_delay_for_worker(self, _):
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
mock_est.config = self._run_config
mock_train_spec = test.mock.Mock(spec=training.TrainSpec)
mock_eval_spec = test.mock.Mock(spec=training.EvalSpec)
executor = training._TrainingExecutor(mock_est, mock_train_spec,
mock_eval_spec)
expected_secs = (self._run_config.task_id + 1) * _DELAY_SECS_PER_WORKER
with test.mock.patch.object(time, 'sleep') as mock_sleep:
mock_sleep.side_effect = lambda s: self.assertEqual(expected_secs, s)
self._run_task(executor)
self.assertTrue(mock_sleep.called)
def test_send_stop_at_secs_to_train(self):
mock_est = test.mock.Mock(spec=estimator_lib.Estimator, model_dir='path/')
mock_est.latest_checkpoint = self.unique_checkpoint_every_time_fn
train_spec = training.TrainSpec(
input_fn=lambda: 1, max_steps=2, hooks=[_FakeHook()])
eval_spec = training.EvalSpec(
input_fn=lambda: 1, hooks=[_FakeHook()], throttle_secs=100)
mock_est.evaluate.return_value = {_GLOBAL_STEP_KEY: train_spec.max_steps}
executor = training._TrainingExecutor(mock_est, train_spec, eval_spec)
executor.run_local()
stop_hook = mock_est.train.call_args[1]['hooks'][-1]
self.assertIsInstance(stop_hook, training._StopAtSecsHook)
self.assertEqual(eval_spec.throttle_secs, stop_hook._stop_after_secs)
def test_fail_with_empty_master(self):
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
mock_train_spec = test.mock.Mock(spec=training.TrainSpec)
mock_eval_spec = test.mock.Mock(spec=training.EvalSpec)
mock_est.config = test.mock.PropertyMock(spec=run_config_lib.RunConfig)
mock_est.config.cluster_spec = {'worker': 'dummy'}
mock_est.config.master = ''
mock_est.config.task_type = 'worker'
mock_est.config.task_id = 2
with self.assertRaisesRegexp(RuntimeError,
_INVALID_CONFIG_FOR_STD_SERVER_MSG):
self._run_task(training._TrainingExecutor(mock_est, mock_train_spec,
mock_eval_spec))
def test_sleep_delay_secs(self):
training_max_step = 200
delay_secs = 123
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
mock_est.evaluate.return_value = {_GLOBAL_STEP_KEY: training_max_step}
mock_train_spec = test.mock.Mock(spec=training.TrainSpec)
mock_train_spec.max_steps = training_max_step
eval_spec = training.EvalSpec(
input_fn=lambda: 1, steps=2, hooks=[_FakeHook()], name='cont_eval',
delay_secs=delay_secs, throttle_secs=0)
executor = training._TrainingExecutor(mock_est, mock_train_spec, eval_spec)
with test.mock.patch.object(time, 'sleep') as mock_sleep:
executor.run_evaluator()
mock_sleep.assert_called_with(delay_secs)
self.assertTrue(mock_est.evaluate.called)
def test_evaluate_multiple_times(self):
training_max_step = 200
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
mock_est.evaluate.side_effect = [
{_GLOBAL_STEP_KEY: training_max_step // 2},
{_GLOBAL_STEP_KEY: training_max_step}
]
mock_est.latest_checkpoint.side_effect = ['path_1', 'path_2']
mock_train_spec = test.mock.Mock(spec=training.TrainSpec)
mock_train_spec.max_steps = training_max_step
eval_spec = training.EvalSpec(
input_fn=lambda: 1, delay_secs=0, throttle_secs=0)
executor = training._TrainingExecutor(mock_est, mock_train_spec, eval_spec)
executor.run_evaluator()
self.assertEqual(2, mock_est.evaluate.call_count)
def test_throttle_secs(self, mock_sleep, mock_time):
throttle_secs = 123
operation_secs = 12
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
mock_train_spec = test.mock.Mock(spec=training.TrainSpec)
self._set_up_mock_est_to_train_and_evaluate_once(mock_est, mock_train_spec)
eval_spec = training.EvalSpec(
input_fn=lambda: 1, delay_secs=0, throttle_secs=throttle_secs)
mock_time.side_effect = [921, 921 + operation_secs]
executor = training._TrainingExecutor(mock_est, mock_train_spec, eval_spec)
# Disable logging as it calls time.time also.
with test.mock.patch.object(logging, 'info'):
executor.run_evaluator()
mock_sleep.assert_called_with(throttle_secs - operation_secs)
self.assertTrue(mock_est.evaluate.called)
def test_throttle_secs(self, mock_sleep, mock_time):
throttle_secs = 123
operation_secs = 12
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
mock_train_spec = test.mock.Mock(spec=training.TrainSpec)
self._set_up_mock_est_to_train_and_evaluate_once(mock_est, mock_train_spec)
eval_spec = training.EvalSpec(
input_fn=lambda: 1, start_delay_secs=0, throttle_secs=throttle_secs)
mock_time.side_effect = [921, 921 + operation_secs]
executor = training._TrainingExecutor(mock_est, mock_train_spec, eval_spec)
# Disable logging as it calls time.time also.
with test.mock.patch.object(logging, 'info'):
executor.run_evaluator()
mock_sleep.assert_called_with(throttle_secs - operation_secs)
self.assertTrue(mock_est.evaluate.called)
def test_sleep_delay_secs(self):
training_max_step = 200
delay_secs = 123
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
mock_est.evaluate.return_value = {_GLOBAL_STEP_KEY: training_max_step}
mock_est.model_dir = compat.as_bytes(test.get_temp_dir())
mock_train_spec = test.mock.Mock(spec=training.TrainSpec)
mock_train_spec.max_steps = training_max_step
eval_spec = training.EvalSpec(
input_fn=lambda: 1, steps=2, hooks=[_FakeHook()], name='cont_eval',
delay_secs=delay_secs, throttle_secs=0)
executor = training._TrainingExecutor(mock_est, mock_train_spec, eval_spec)
with test.mock.patch.object(time, 'sleep') as mock_sleep:
executor.run_evaluator()
mock_sleep.assert_called_with(delay_secs)
self.assertTrue(mock_est.evaluate.called)
def test_handles_no_new_checkpoint_found(self):
mock_est = test.mock.Mock(spec=estimator_lib.Estimator, model_dir='path/')
mock_est.latest_checkpoint.return_value = (
'no_new_checkpoints_after_the_first_train_step')
train_spec = training.TrainSpec(
input_fn=lambda: 1, max_steps=300, hooks=[_FakeHook()])
eval_spec = training.EvalSpec(
input_fn=lambda: 1, hooks=[_FakeHook()], throttle_secs=100)
# It was going to be called 3 times.
mock_est.evaluate.side_effect = [{
_GLOBAL_STEP_KEY: train_spec.max_steps - 100
}, {
_GLOBAL_STEP_KEY: train_spec.max_steps - 50
}, {
_GLOBAL_STEP_KEY: train_spec.max_steps
}]
executor = training._TrainingExecutor(mock_est, train_spec, eval_spec)
with self.assertRaisesRegexp(RuntimeError, _STALE_CHECKPOINT_MSG):
executor.run_local()
def test_runs_in_a_loop_until_max_steps(self):
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
train_spec = training.TrainSpec(
input_fn=lambda: 1, max_steps=300, hooks=[_FakeHook()])
eval_spec = training.EvalSpec(
input_fn=lambda: 1, hooks=[_FakeHook()], throttle_secs=100)
# should be called 3 times.
mock_est.evaluate.side_effect = [{
_GLOBAL_STEP_KEY: train_spec.max_steps - 100
}, {
_GLOBAL_STEP_KEY: train_spec.max_steps - 50
}, {
_GLOBAL_STEP_KEY: train_spec.max_steps
}]
executor = training._TrainingExecutor(mock_est, train_spec, eval_spec)
executor.run_local()
self.assertEqual(3, mock_est.train.call_count)
self.assertEqual(3, mock_est.evaluate.call_count)
def test_evaluate_with_evaluate_spec(self):
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
mock_est.latest_checkpoint.return_value = 'latest_it_is'
mock_train_spec = test.mock.Mock(spec=training.TrainSpec)
self._set_up_mock_est_to_train_and_evaluate_once(mock_est, mock_train_spec)
eval_spec = training.EvalSpec(
input_fn=lambda: 1, steps=2, hooks=[_FakeHook()], name='cont_eval',
start_delay_secs=0, throttle_secs=0)
executor = training._TrainingExecutor(mock_est, mock_train_spec, eval_spec)
executor.run_evaluator()
mock_est.evaluate.assert_called_with(
name='cont_eval',
input_fn=eval_spec.input_fn,
steps=eval_spec.steps,
checkpoint_path='latest_it_is',
hooks=eval_spec.hooks)
self.assertFalse(mock_est.train.called)
def test_train_and_evaluate_args(self):
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
train_spec = training.TrainSpec(
input_fn=lambda: 1, max_steps=300, hooks=[_FakeHook()])
eval_spec = training.EvalSpec(
input_fn=lambda: 1, steps=2, hooks=[_FakeHook()], name='local_eval')
mock_est.evaluate.return_value = {_GLOBAL_STEP_KEY: train_spec.max_steps}
executor = training._TrainingExecutor(mock_est, train_spec, eval_spec)
executor.run_local()
mock_est.evaluate.assert_called_with(
name=eval_spec.name,
input_fn=eval_spec.input_fn,
steps=eval_spec.steps,
hooks=eval_spec.hooks)
train_args = mock_est.train.call_args[1]
self.assertEqual(list(train_spec.hooks), list(train_args['hooks'][:-1]))
self.assertEqual(train_spec.input_fn, train_args['input_fn'])
self.assertEqual(train_spec.max_steps, train_args['max_steps'])
def test_std_server(self, mock_server):
mock_server_instance = test.mock.Mock()
mock_server.return_value = mock_server_instance
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
mock_est.config = _create_run_config_with_cluster_spec(
_TF_CONFIG_FOR_PS)
mock_train_spec = test.mock.Mock(spec=training.TrainSpec)
mock_eval_spec = test.mock.Mock(spec=training.EvalSpec)
executor = training._TrainingExecutor(mock_est, mock_train_spec,
mock_eval_spec)
executor.run_ps()
mock_server.assert_called_with(mock_est.config.cluster_spec,
job_name=mock_est.config.task_type,
task_index=mock_est.config.task_id,
config=test.mock.ANY,
start=False)
self.assertTrue(mock_server_instance.start.called)
self.assertTrue(mock_server_instance.join.called)
def test_std_server(self, mock_server):
mock_server_instance = test.mock.Mock()
mock_server.return_value = mock_server_instance
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
mock_est.config = _create_run_config_with_cluster_spec(_TF_CONFIG_FOR_PS)
mock_train_spec = test.mock.Mock(spec=training.TrainSpec)
mock_eval_spec = test.mock.Mock(spec=training.EvalSpec)
executor = training._TrainingExecutor(mock_est, mock_train_spec,
mock_eval_spec)
executor.run_ps()
mock_server.assert_called_with(
mock_est.config.cluster_spec,
job_name=mock_est.config.task_type,
task_index=mock_est.config.task_id,
config=test.mock.ANY,
start=False)
self.assertTrue(mock_server_instance.start.called)
self.assertTrue(mock_server_instance.join.called)
def test_evaluate_multiple_times(self, mock_latest_ckpt):
training_max_step = 200
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
mock_est.evaluate.side_effect = [{
_GLOBAL_STEP_KEY:
training_max_step // 2
}, {
_GLOBAL_STEP_KEY: training_max_step
}]
mock_latest_ckpt.side_effect = ['path_1', 'path_2']
mock_train_spec = test.mock.Mock(spec=training.TrainSpec)
mock_train_spec.max_steps = training_max_step
eval_spec = training.EvalSpec(input_fn=lambda: 1,
delay_secs=0,
throttle_secs=0)
executor = training._TrainingExecutor(mock_est, mock_train_spec,
eval_spec)
executor.run_evaluator()
self.assertEqual(2, mock_est.evaluate.call_count)
def test_run_master_triggers_evaluate(self, _):
def estimator_train(saving_listeners, *args, **kwargs):
# There shalt be a saving_listener. Estimator is going to call
# `after_save`.
del args, kwargs
saving_listeners[0].after_save(session=None, global_step_value=None)
mock_est = test.mock.Mock(
spec=estimator_lib.Estimator, model_dir='path/', train=estimator_train)
mock_est.latest_checkpoint.return_value = 'checkpoint_path/'
mock_est.config = self._run_config
def export(estimator, *args, **kwargs):
del args, kwargs
estimator.export_was_called = True
exporter = test.mock.PropertyMock(spec=exporter_lib.Exporter)
exporter.name = 'see_whether_export_is_called'
exporter.export = export
train_spec = training.TrainSpec(input_fn=lambda: 1, max_steps=300)
eval_spec = training.EvalSpec(
input_fn=lambda: 1, steps=2, exporters=exporter)
mock_est.evaluate.return_value = {_GLOBAL_STEP_KEY: train_spec.max_steps}
executor = training._TrainingExecutor(mock_est, train_spec, eval_spec)
executor.run_master()
mock_est.evaluate.assert_called_with(
name=eval_spec.name,
input_fn=eval_spec.input_fn,
steps=eval_spec.steps,
checkpoint_path='checkpoint_path/',
hooks=eval_spec.hooks)
self.assertTrue(mock_est.export_was_called)
def test_runs_in_a_loop_until_max_steps(self):
mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
train_spec = training.TrainSpec(input_fn=lambda: 1,
max_steps=300,
hooks=[_FakeHook()])
eval_spec = training.EvalSpec(input_fn=lambda: 1,
hooks=[_FakeHook()],
throttle_secs=100)
# should be called 3 times.
mock_est.evaluate.side_effect = [{
_GLOBAL_STEP_KEY:
train_spec.max_steps - 100
}, {
_GLOBAL_STEP_KEY:
train_spec.max_steps - 50
}, {
_GLOBAL_STEP_KEY: train_spec.max_steps
}]
executor = training._TrainingExecutor(mock_est, train_spec, eval_spec)
executor.run_local()
self.assertEqual(3, mock_est.train.call_count)
self.assertEqual(3, mock_est.evaluate.call_count)
