aws / aws/amazon-sagemaker-examples

tf-resnet-profiling-multi-gpu-multi-node-boto3.ipynb failed CI

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Dominant language
Jupyter Notebook
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Merged PRs (30d)
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Description

Link to the notebook:
https://github.com/aws/amazon-sagemaker-examples/blob/master/sagemaker-debugger/tensorflow_profiling/tf-resnet-profiling-multi-gpu-multi-node-boto3.ipynb

Error:

---------------------------------------------------------------------------
Exception encountered at "In [8]":
---------------------------------------------------------------------------
ModuleNotFoundError Traceback (most recent call last)
in
----> 1 from smdebug.profiler.analysis.notebook_utils.training_job import TrainingJob
2 tj = TrainingJob(training_job_name, region)
3 tj.wait_for_sys_profiling_data_to_be_available()

/usr/local/lib/python3.7/site-packages/smdebug/profiler/analysis/notebook_utils/__init__.py in
1 # Local
----> 2 from .metrics_histogram import MetricsHistogram
3 from .step_histogram import StepHistogram
4 from .training_job import TrainingJob

/usr/local/lib/python3.7/site-packages/smdebug/profiler/analysis/notebook_utils/metrics_histogram.py in
4 # Third Party
5 import numpy as np
----> 6 from bokeh.io import out

[...]

ModuleNotFoundError: No module named 'bokeh'

Contributor guide

Open the contributing guide

Research direction

Open tf-resnet-profiling-multi-gpu-multi-node-boto3.ipynb and inspect cell In [8], beginning by reproducing the TrainingJob import in CI. Done means the notebook runs past that cell without the reported bokeh ModuleNotFoundError.

Written by the indexing model from the issue text.

Assessment

Tech stack
aws, jupyter-notebook, python
Domain
ci-cd, machine-learning
Issue type
Bug
Difficulty
2/5
Estimated time
1-3 hours
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
25/100

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