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Make code_location to be S3 URI instead of bucket in training_config() - #501
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Nov 19, 2018
Codecov Report
@@ Coverage Diff @@## master #501 +/- ##
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+ Coverage 94.29% 94.29% +<.01%
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Files 59 59 Lines 4610 4613 +3 ==========================================
+ Hits 4347 4350 +3
Misses 263 263
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jesterhazy
suggested changes
Nov 19, 2018
| code_location (str): Name of the S3 bucket where custom code is uploaded (default: None). | ||
| code_location (str): The S3 URI where custom code is uploaded (default: None). | ||
| If not specified, default bucket created by ``sagemaker.session.Session`` is used. | ||
| The default S3 path is default_bucket/job-name/source/. |
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including s3 protocol makes this clearer (s3://default_bucket/...)
| container_log_level (int): Log level to use within the container (default: logging.INFO). | ||
| Valid values are defined in the Python logging module. | ||
| code_location (str): Name of the S3 bucket where custom code is uploaded (default: None). | ||
| code_location (str): The S3 URI where custom code is uploaded (default: None). |
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let's fix this to make it clear we expect a prefix and will append /source/sourcedir.tar.gz
jesterhazy
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Nov 19, 2018
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Evan-W-ang added a commit
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Jun 8, 2026
aws#501) * Make code_location to be S3 URI instead of bucket in training_config()
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Jun 8, 2026
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Issue #, if available:
Description of changes:
The docstring for code_location is not correct. code_location can be a S3 URI, not just a bucket. And I need to change related Airflow API because it treats code_location as a bucket.
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