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4 changes: 2 additions & 2 deletions custom_tensorflow_keras_nlp/Headline Classifier Local.ipynb
Original file line number Diff line number Diff line change
Expand Up @@ -56,7 +56,7 @@
"\n",
"role = get_execution_role()\n",
"print(role)\n",
"sess = sagemaker.Session()\n"
"sess = sagemaker.Session()"
]
},
{
Expand All @@ -77,7 +77,7 @@
"%%time\n",
"import util.preprocessing\n",
"\n",
"util.preprocessing.download_dataset()\n"
"util.preprocessing.download_dataset()"
]
},
{
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11 changes: 7 additions & 4 deletions custom_tensorflow_keras_nlp/Headline Classifier SageMaker.ipynb
Original file line number Diff line number Diff line change
Expand Up @@ -56,7 +56,7 @@
"\n",
"role = get_execution_role()\n",
"print(role)\n",
"sess = sagemaker.Session()\n"
"sess = sagemaker.Session()"
]
},
{
Expand All @@ -77,7 +77,7 @@
"%%time\n",
"import util.preprocessing\n",
"\n",
"util.preprocessing.download_dataset()\n"
"util.preprocessing.download_dataset()"
]
},
{
Expand Down Expand Up @@ -490,8 +490,8 @@
" ],\n",
" base_job_name=\"news-keras\",\n",
" max_run=20*60, # Maximum allowed active runtime\n",
" use_spot_instances=True, # Use spot instances to reduce cost\n",
" max_wait=30*60, # Maximum clock time (including spot delays)\n",
" #use_spot_instances=True, # Use spot instances to reduce cost\n",
" #max_wait=30*60, # Maximum clock time (including spot delays)\n",
")\n",
"\n",
"estimator.fit(inputs)\n"
Expand Down Expand Up @@ -773,6 +773,9 @@
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.10"
},
"test": {
"dependsOn": "Headline Classifier Local.ipynb"
}
},
"nbformat": 4,
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Original file line number Diff line number Diff line change
Expand Up @@ -56,7 +56,7 @@
"%%time\n",
"import util.preprocessing\n",
"\n",
"util.preprocessing.download_dataset()\n"
"util.preprocessing.download_dataset()"
]
},
{
Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -128,7 +128,7 @@
"# make the category classes more readable\n",
"mapping = {1: 'World', 2: 'Sports', 3: 'Business', 4: 'Sci/Tech'}\n",
"df = df.replace({'CATEGORY': mapping})\n",
"df.head()\n"
"df.head()"
]
},
{
Expand Down Expand Up @@ -497,8 +497,8 @@
" ],\n",
" base_job_name=\"news-pytorch\",\n",
" max_run=20*60, # Maximum allowed active runtime\n",
" use_spot_instances=True, # Use spot instances to reduce cost\n",
" max_wait=30*60, # Maximum clock time (including spot delays)\n",
" #use_spot_instances=True, # Use spot instances to reduce cost\n",
" #max_wait=30*60, # Maximum clock time (including spot delays)\n",
")\n",
"\n",
"estimator.fit(inputs)"
Expand Down Expand Up @@ -795,6 +795,11 @@
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.13"
},
"test": {
"dependsOn": [
"/pytorch_alternatives/custom_pytorch_nlp/Headline Classifier Local.ipynb"
]
}
},
"nbformat": 4,
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Original file line number Diff line number Diff line change
Expand Up @@ -418,6 +418,9 @@
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.13"
},
"test": {
"skip": true
}
},
"nbformat": 4,
Expand Down
8 changes: 8 additions & 0 deletions testspec.yml
Original file line number Diff line number Diff line change
@@ -1,2 +1,10 @@
# Test specifications for the workshop's automated test runner
# TODO: Confirm structure
version: 0.1

tree:
custom_tensorflow_keras_nlp:
contents:
Headline Classifier SageMaker.ipynb:
dependsOn:
- Headline Classifier Local.ipynb