def prepare_tensorboard(
env: det.EnvContext,
container_path: Optional[str] = None,
) -> Tuple[tensorboard.TensorboardManager, tensorboard.BatchMetricWriter]:
tensorboard_mgr = tensorboard.build(
env.det_cluster_id,
env.det_experiment_id,
env.det_trial_id,
env.experiment_config["checkpoint_storage"],
container_path,
)
try:
from determined.tensorboard.metric_writers import tensorflow
writer: tensorboard.MetricWriter = tensorflow.TFWriter()
except ModuleNotFoundError:
logging.warning("Tensorflow writer not found")
from determined.tensorboard.metric_writers import pytorch
writer = pytorch.TorchWriter()
return (
tensorboard_mgr,
tensorboard.BatchMetricWriter(writer),
)
def get_metric_writer() -> tensorboard.BatchMetricWriter:
try:
from determined.tensorboard.metric_writers import tensorflow
writer: tensorboard.MetricWriter = tensorflow.TFWriter()
except ModuleNotFoundError:
logging.warning("TensorFlow writer not found")
from determined.tensorboard.metric_writers import pytorch
writer = pytorch.TorchWriter()
return tensorboard.BatchMetricWriter(writer)
def prepare_tensorboard(
env: det.EnvContext,
) -> Tuple[tensorboard.TensorboardManager, tensorboard.BatchMetricWriter]:
tensorboard_mgr = tensorboard.build(env, env.experiment_config["checkpoint_storage"])
try:
from determined.tensorboard.metric_writers import pytorch
writer: tensorboard.MetricWriter = pytorch.TorchWriter()
except ImportError:
print("PYTORCH WRITER NOT FOUND")
from determined.tensorboard.metric_writers import tensorflow
writer = tensorflow.TFWriter()
return (
tensorboard_mgr,
tensorboard.BatchMetricWriter(writer, env.experiment_config.batches_per_step()),
)
def create_metric_writer(
cls: Type["TFKerasTrialController"],
) -> tensorboard.BatchMetricWriter:
writer = tensorflow.TFWriter()
return tensorboard.BatchMetricWriter(writer)