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Hi, I really wish I could use TensorBoardOutputConfig when my SageMaker Estimator instance type is local or local_gpu.
This could be accomplished by either or both of:
Enabling streaming to s3 when running local mode jobs
Enabling a local output path instead of an s3 output path, for example:
fromsagemaker.debuggerimportTensorBoardOutputConfiginstance_type='local_gpu'tb_output_path="file:///local/path/to/stream/tensorboard/files/to"tensorboard_output_config=TensorBoardOutputConfig(
# and rename s3_output_path to output_path?output_path=tb_output_path,
container_local_output_path='/tensorboard'
)
This would make it possible to perform local debugging of tensorboard logging code within my sagemaker scripts. Without local debugging, writing tensorboard logging code for sagemaker jobs can be a very slow process.
The text was updated successfully, but these errors were encountered:
Hi, I really wish I could use
TensorBoardOutputConfig
when my SageMaker Estimator instance type islocal
orlocal_gpu
.This could be accomplished by either or both of:
This would make it possible to perform local debugging of tensorboard logging code within my sagemaker scripts. Without local debugging, writing tensorboard logging code for sagemaker jobs can be a very slow process.
The text was updated successfully, but these errors were encountered: