Rebased and added new link in TV tutorial.

Author: brianjo

.jenkins/build.sh

@@ -14,7 +14,6 @@ sudo apt-get install -y --no-install-recommends unzip p7zip-full sox libsox-dev
 export PATH=/opt/conda/bin:$PATH
 rm -rf src
 pip install -r $DIR/../requirements.txt
-pip uninstall -y torchvision || true
 
 export PATH=/opt/conda/bin:$PATH
 conda install -y sphinx==1.8.2 pandas
@@ -25,12 +24,6 @@ pip install -e git+git://github.com/pytorch/pytorch_sphinx_theme.git#egg=pytorch
 # this is a workaround to the issue.
 pip install sphinx-gallery tqdm matplotlib ipython pillow==4.1.1
 
-# Install torchvision from source
-git clone https://github.com/pytorch/vision --quiet
-pushd vision
-pip install . --no-deps  # We don't want it to install the stock PyTorch version from pip
-popd
-
 # Install torchaudio from source
 git clone https://github.com/pytorch/audio --quiet
 pushd audio
@@ -39,17 +32,6 @@ popd
 
 aws configure set default.s3.multipart_threshold 5120MB
 
-if [[ $(pip show torch) ]]; then
-  # Clean up previous PyTorch installations
-  pip uninstall -y torch || true
-  pip uninstall -y torch || true
-fi
-
-# Install a nightly build of pytorch
-
-# GPU, requires CUDA version 9.0
-pip install cython torch_nightly -f https://download.pytorch.org/whl/nightly/cu90/torch_nightly.html
-
 # Decide whether to parallelize tutorial builds, based on $JOB_BASE_NAME
 export NUM_WORKERS=20
 if [[ "${JOB_BASE_NAME}" == *worker_* ]]; then

advanced_source/torch_script_custom_ops.rst

@@ -27,13 +27,6 @@ convert them to third party tensor formats (in this case, OpenCV ``Mat``s), how
 to register your operator with the TorchScript runtime and finally how to
 compile the operator and use it in Python and C++.
 
-This tutorial assumes you have the *preview release* of PyTorch 1.0 installed
-via ``pip`` or `conda`. See https://pytorch.org/get-started/locally for
-instructions on grabbing the latest release of PyTorch 1.0. Alternatively, you
-can compile PyTorch from source. The documentation in `this file
-<https://github.com/pytorch/pytorch/blob/master/CONTRIBUTING.md>`_ will assist
-you with this.
-
 Implementing the Custom Operator in C++
 ---------------------------------------
 

intermediate_source/torchvision_tutorial.rst

@@ -3,7 +3,7 @@ TorchVision 0.3 Object Detection Finetuning Tutorial
 
 .. tip::
    To get the most of this tutorial, we suggest using this 
-   `Colab Version <https://colab.research.google.com/github/pytorch/tutorials/_static/torchvision_finetuning_instance_segmentation.ipynb>`__. 
+   `Colab Version <https://colab.research.google.com/github/pytorch/vision/blob/temp-tutorial/tutorials/torchvision_finetuning_instance_segmentation.ipynb>`__. 
    This will allow you to experiment with the information presented below. 
 
 For this tutorial, we will be finetuning a pre-trained `Mask

requirements.txt

@@ -5,7 +5,8 @@ sphinx-gallery
 tqdm
 numpy
 matplotlib
-torchvision==0.3
+torch
+torchvision
 PyHamcrest
 bs4
 awscli==1.16.35