Merge branch 'master' into master

Author: aaronmarkham

.github/ISSUE_TEMPLATE/bug_report.md

@@ -0,0 +1,32 @@
+---
+name: Bug report
+about: File a report to help us reproduce and fix the problem
+title: ''
+labels: 'bug'
+assignees: ''
+
+---
+
+**Describe the bug**
+A clear and concise description of what the bug is.
+
+**To reproduce**
+A clear, step-by-step set of instructions to reproduce the bug.
+
+**Expected behavior**
+A clear and concise description of what you expected to happen.
+
+**Screenshots or logs**
+If applicable, add screenshots or logs to help explain your problem.
+
+**System information**
+A description of your system. Please provide:
+- **SageMaker Python SDK version**:
+- **Framework name (eg. PyTorch) or algorithm (eg. KMeans)**:
+- **Framework version**:
+- **Python version**:
+- **CPU or GPU**:
+- **Custom Docker image (Y/N)**:
+
+**Additional context**
+Add any other context about the problem here.

.github/ISSUE_TEMPLATE/config.yml

@@ -0,0 +1,5 @@
+blank_issues_enabled: false
+contact_links:
+  - name: Ask a question
+    url: https://stackoverflow.com/questions/tagged/amazon-sagemaker
+    about: Use Stack Overflow to ask and answer questions

.github/ISSUE_TEMPLATE/documentation-request.md

@@ -0,0 +1,17 @@
+---
+name: Documentation request
+about: Request improved documentation
+title: ''
+labels: 'doc update'
+assignees: ''
+
+---
+
+**What did you find confusing? Please describe.**
+A clear and concise description of what you found confusing. Ex. I tried to [...] but I didn't understand how to [...]
+
+**Describe how documentation can be improved**
+A clear and concise description of where documentation was lacking and how it can be improved.
+
+**Additional context**
+Add any other context or screenshots about the documentation request here.

.github/ISSUE_TEMPLATE/feature_request.md

@@ -0,0 +1,20 @@
+---
+name: Feature request
+about: Suggest an improvement for this library
+title: ''
+labels: 'feature request'
+assignees: ''
+
+---
+
+**Is your feature request related to a problem? Please describe.**
+A clear and concise description of what the problem is. Ex. I'm always frustrated when [...]
+
+**Describe the solution you'd like**
+A clear and concise description of what you want to happen.
+
+**Describe alternatives you've considered**
+A clear and concise description of any alternative solutions or features you've considered.
+
+**Additional context**
+Add any other context or screenshots about the feature request here.

.github/issue_template.md

@@ -312,6 +312,15 @@ For more information on the runtime environment, including specific package vers
 If there are other packages you want to use with your script, you can include a ``requirements.txt`` file in the same directory as your training script to install other dependencies at runtime.
 Both ``requirements.txt`` and your training script should be put in the same folder.
 You must specify this folder in ``source_dir`` argument when creating an MXNet estimator.
+
+The function of installing packages using ``requirements.txt`` is supported for all MXNet versions during training.
+When serving an MXNet model, support for this function varies with MXNet versions.
+For MXNet 1.6.0 or newer, ``requirements.txt`` must be under folder ``code``.
+The SageMaker MXNet Estimator will automatically save ``code`` in ``model.tar.gz`` after training (assuming you set up your script and ``requirements.txt`` correctly as stipulated in the previous paragraph).
+In the case of bringing your own trained model for deployment, you must save ``requirements.txt`` under folder ``code`` in ``model.tar.gz`` yourself or specify it through ``dependencies``.
+For MXNet 1.4.1, ``requirements.txt`` is not supported for inference.
+For MXNet 0.12.1-1.3.0, ``requirements.txt`` must be in ``source_dir``.
+
 A ``requirements.txt`` file is a text file that contains a list of items that are installed by using ``pip install``.
 You can also specify the version of an item to install.
 For information about the format of a ``requirements.txt`` file, see `Requirements Files <https://pip.pypa.io/en/stable/user_guide/#requirements-files>`__ in the pip documentation.

doc/using_mxnet.rst

@@ -127,7 +127,7 @@ For more information on the runtime environment, including specific package vers
 
 If there are other packages you want to use with your script, you can include a ``requirements.txt`` file in the same directory as your training script to install other dependencies at runtime. Both ``requirements.txt`` and your training script should be put in the same folder. You must specify this folder in ``source_dir`` argument when creating PyTorch estimator.
 
-The function of installing packages using ``requirements.txt`` is supported for all PyTorch versions during training. When serving a PyTorch model, support for this function varies with PyTorch Versions. For PyTorch 1.3.1 or newer, ``requirements.txt`` must be under folder ``code``. SageMaker PyTorch Estimator will automatically save ``code`` in ``model.tar.gz`` after training (assuming you set up your script and ``requirements.txt`` correctly as stipulated in the previous paragraph). In the case of bringing your own trained model for deployment, you must save ``requirements.txt`` under folder ``code`` in ``model.tar.gz`` yourself. For PyTorch 1.2.0, ``requirements.txt`` is not supported for inference. For PyTorch 0.4.0 to 1.1.0, ``requirements.txt`` must be in ``source_dir``.
+The function of installing packages using ``requirements.txt`` is supported for all PyTorch versions during training. When serving a PyTorch model, support for this function varies with PyTorch versions. For PyTorch 1.3.1 or newer, ``requirements.txt`` must be under folder ``code``. The SageMaker PyTorch Estimator will automatically save ``code`` in ``model.tar.gz`` after training (assuming you set up your script and ``requirements.txt`` correctly as stipulated in the previous paragraph). In the case of bringing your own trained model for deployment, you must save ``requirements.txt`` under folder ``code`` in ``model.tar.gz`` yourself or specify it through ``dependencies``. For PyTorch 1.2.0, ``requirements.txt`` is not supported for inference. For PyTorch 0.4.0 to 1.1.0, ``requirements.txt`` must be in ``source_dir``.
 
 A ``requirements.txt`` file is a text file that contains a list of items that are installed by using ``pip install``. You can also specify the version of an item to install. For information about the format of a ``requirements.txt`` file, see `Requirements Files <https://pip.pypa.io/en/stable/user_guide/#requirements-files>`__ in the pip documentation.
 

doc/using_pytorch.rst

@@ -796,7 +796,7 @@ def delete_endpoint(self):
         """Delete an Amazon SageMaker ``Endpoint``.
 
         Raises:
-            ValueError: If the endpoint does not exist.
+            botocore.exceptions.ClientError: If the endpoint does not exist.
         """
         self._ensure_latest_training_job(error_message="Endpoint was not created yet")
         self.sagemaker_session.delete_endpoint(self.latest_training_job.name)

src/sagemaker/estimator.py

@@ -15,8 +15,7 @@
 
 PYTORCH_VERSION = "0.4"
 """Default PyTorch version for when the framework version is not specified.
-The latest PyTorch version is 1.1.0, but the default version is no longer updated so as to not
-break existing workflows.
+The default version is no longer updated so as to not break existing workflows.
 """
 
 LATEST_VERSION = "1.3.1"