def _GetSimpleTestConfig(self):
model_name = 'image.mnist.LeNet5'
cfg = model_registry.GetParams(model_name, 'Train')
cfg.cluster.task = 0
cfg.cluster.mode = 'sync'
cfg.cluster.job = 'trainer_client'
cfg.cluster.worker.name = '/job:localhost'
cfg.cluster.worker.replicas = 1
cfg.cluster.worker.gpus_per_replica = 0
cfg.cluster.ps.name = '/job:localhost'
cfg.cluster.ps.replicas = 1
cfg.cluster.ps.gpus_per_replica = 0
cfg.cluster.reporting_job = FLAGS.vizier_reporting_job
# Generate 2 inputs.
cfg.input.ckpt = FakeMnistData(self.get_temp_dir(),
train_size=2,
test_size=2)
cfg.input.num_samples = 2
cfg.input.batch_size = 2
cfg.train.max_steps = 2
ema_decay = 0.9999
cfg.task.train.ema_decay = ema_decay
cfg.train.ema_decay = ema_decay
return cfg
def _GetTestConfig(self):
model_name = 'image.mnist.LeNet5'
cfg = model_registry.GetParams(model_name, 'Dev')
cfg.cluster.task = 0
cfg.cluster.mode = 'sync'
cfg.cluster.job = 'trainer_client'
cfg.cluster.worker.name = '/job:local'
cfg.cluster.worker.replicas = 1
cfg.cluster.worker.gpus_per_replica = 0
cfg.cluster.ps.name = '/job:local'
cfg.cluster.ps.replicas = 1
cfg.cluster.ps.gpus_per_replica = 0
# Generate 2 inputs.
self._tmpdir, cfg.input.ckpt = FakeMnistData(train_size=0, test_size=2)
cfg.input.num_samples = 2
cfg.train.max_steps = 2
cfg.train.ema_decay = 0.9999
return cfg
def testRunLocally(self):
logdir = os.path.join(tf.test.get_temp_dir(),
'run_locally_test' + str(random.random()))
FLAGS.logdir = logdir
FLAGS.run_locally = 'cpu'
FLAGS.mode = 'sync'
FLAGS.model = 'image.mnist.LeNet5'
FLAGS.model_params_override = (
'train.max_steps: 2; input.num_samples: 2; input.ckpt: %s' %
FakeMnistData(self.get_temp_dir(), train_size=2, test_size=2))
trainer.main(None)
train_files = tf.io.gfile.glob(logdir + '/train/*')
self.assertTrue(self._HasFile(train_files, 'ckpt'))
self.assertTrue(self._HasFile(train_files, 'tfevents'))
control_files = tf.io.gfile.glob(logdir + '/control/*')
self.assertTrue(self._HasFile(control_files, 'params.txt'))
self.assertTrue(self._HasFile(control_files, 'model_analysis.txt'))
self.assertTrue(self._HasFile(control_files, 'tfevents'))
def _GetTestConfig(self):
model_name = 'image.mnist.LeNet5'
# So this is how particular parameters are obtained
cfg = model_registry.GetParams(model_name, 'Train')
cfg.cluster.task = 0
cfg.cluster.mode = 'sync'
cfg.cluster.job = 'trainer_client'
cfg.cluster.worker.name = '/job:localhost'
cfg.cluster.worker.replicas = 1
cfg.cluster.worker.gpus_per_replica = 0
cfg.cluster.ps.name = '/job:localhost'
cfg.cluster.ps.replicas = 1
cfg.cluster.ps.gpus_per_replica = 0
# Generate 2 inputs.
cfg.input.ckpt = FakeMnistData(self.get_temp_dir(),
train_size=2,
test_size=2)
cfg.input.num_samples = 2
cfg.input.batch_size = 2
cfg.train.max_steps = 2
cfg.train.ema_decay = 0.9999
return cfg