CI code cleaning (#7615)

Author: carmocca

.azure-pipelines/gpu-tests.yml

@@ -55,13 +55,9 @@ jobs:
       displayName: 'Image info & NVIDIA'
 
     - bash: |
-        export GIT_TERMINAL_PROMPT=1
-        #sudo apt-get install -y cmake
-        # python -m pip install "pip==20.1"
-        pip install --requirement requirements.txt
         python -c "fname = 'requirements/extra.txt' ; lines = [line for line in open(fname).readlines() if 'horovod' not in line] ; open(fname, 'w').writelines(lines)"
-        pip install --requirement ./requirements/devel.txt --upgrade-strategy only-if-needed
-        pip install fairscale>=0.3.4 --upgrade-strategy only-if-needed
+        pip install fairscale>=0.3.4
+        pip install . --requirement requirements/devel.txt
         pip list
       displayName: 'Install dependencies'
 
@@ -114,15 +110,9 @@ jobs:
 
     - script: |
         set -e
-        python setup.py install --user
-        rm -rf pytorch_lightning
-        pip list
         python -m pytest pl_examples -v --maxfail=2 --durations=0
         bash pl_examples/run_examples-args.sh --trainer.gpus 1 --trainer.max_epochs 1 --data.batch_size 64 --trainer.limit_train_batches 5 --trainer.limit_val_batches 3
         bash pl_examples/run_ddp-examples.sh --trainer.max_epochs 1 --data.batch_size 32 --trainer.limit_train_batches 2 --trainer.limit_val_batches 2
-        # cd pl_examples/basic_examples
-        # bash submit_ddp_job.sh
-        # bash submit_ddp2_job.sh
       env:
         PL_USE_MOCKED_MNIST: "1"
       displayName: 'Examples'

.github/workflows/ci_pkg-install.yml

@@ -15,8 +15,7 @@ jobs:
       fail-fast: false
       # max-parallel: 6
       matrix:
-        # PyTorch 1.5 is failing on Win and bolts requires torchvision>=0.5
-        os: [ubuntu-20.04, macOS-10.15 , windows-2019]  #
+        os: [ubuntu-20.04, macOS-10.15, windows-2019]
         python-version: [3.6, 3.9]
 
     steps:

pl_examples/basic_examples/README.md

@@ -58,16 +58,3 @@ To run this demo do the following:
 1. Log into the jumphost node of your SLURM-managed cluster.
 2. Create a conda environment with Lightning and a GPU PyTorch version.
 3. Choose a script to submit
-
-#### DDP
-Submit this job to run with DistributedDataParallel (2 nodes, 2 gpus each)
-```bash
-sbatch submit_ddp_job.sh YourEnv
-```
-
-#### DDP2
-Submit this job to run with a different implementation of DistributedDataParallel.
-In this version, each node acts like DataParallel but syncs across nodes like DDP.
-```bash
-sbatch submit_ddp2_job.sh YourEnv
-```