update installation scripts for testing

Makefile

@@ -11,7 +11,7 @@ torch-env-cpu: env-files/torch/generic_torch.sh
 	env ENV_NAME=.venv-pytorch \
 		NO_CUDA=1 \
 		bash -c 'bash env-files/torch/generic_torch.sh'
-	.venv-pytorch/bin/horovodrun --check-build 
+	# .venv-pytorch/bin/horovodrun --check-build 
 
 # Install TensorFlow env (GPU support)
 tensorflow-env: env-files/tensorflow/generic_tf.sh
@@ -44,7 +44,7 @@ tf-env-vega: env-files/tensorflow/createEnvVegaTF.sh env-files/tensorflow/generi
 
 
 test:
-	PYTORCH_ENABLE_MPS_FALLBACK=1 .venv/bin/pytest -v tests/ -m "not slurm"
+	PYTORCH_ENABLE_MPS_FALLBACK=1 .venv/bin/pytest -v tests/
 
 test-jsc: tests/run_on_jsc.sh
 	bash tests/run_on_jsc.sh

docs/uv-tutorial.md

@@ -63,7 +63,7 @@ particular, if you are a developer you would use one of the following two comman
 you are on HPC with cuda, you would use:
 
 ```bash
-uv sync --extra torch --extra dev --extra tf \
+uv sync --extra dev --extra nvidia --extra torch --extra tf \
     --no-cache \
     --index https://download.pytorch.org/whl/cu121
 ```

env-files/tensorflow/generic_tf.sh

@@ -9,89 +9,87 @@ if [ -z "$ENV_NAME" ]; then
   ENV_NAME=".venv-tf"
 fi
 
-if [ -z "$NO_CUDA" ]; then
-  echo "Installing itwinai and its dependencies in '$ENV_NAME' virtual env (CUDA enabled)"
-else
-  echo "Installing itwinai and its dependencies in '$ENV_NAME' virtual env (CUDA disabled)"
-fi
-
-# get python version
-pver="$(python --version 2>&1 | awk '{print $2}' | cut -f1-2 -d.)"
-
-# use pyenv if exist
-if [ -d "$HOME/.pyenv" ];then
-  export PYENV_ROOT="$HOME/.pyenv"
-  export PATH="$PYENV_ROOT/bin:$PATH"
-fi
-
+# if [ -z "$NO_CUDA" ]; then
+#   echo "Installing itwinai and its dependencies in '$ENV_NAME' virtual env (CUDA enabled)"
+# else
+#   echo "Installing itwinai and its dependencies in '$ENV_NAME' virtual env (CUDA disabled)"
+# fi
+#
+# # get python version
+# pver="$(python --version 2>&1 | awk '{print $2}' | cut -f1-2 -d.)"
+#
+# # use pyenv if exist
+# if [ -d "$HOME/.pyenv" ];then
+#   export PYENV_ROOT="$HOME/.pyenv"
+#   export PATH="$PYENV_ROOT/bin:$PATH"
+# fi
+#
 # set dir
 cDir=$PWD
 
 # create environment
 if [ -d "${cDir}/$ENV_NAME" ];then
   echo "env $ENV_NAME already exists"
-
-  source $ENV_NAME/bin/activate
 else
   python3 -m venv $ENV_NAME
-
-  # activate env
-  source $ENV_NAME/bin/activate
-
   echo "$ENV_NAME environment is created in ${cDir}"
 fi
 
-pip3 install --no-cache-dir  --upgrade pip
-
-# get wheel -- setuptools extension
-pip3 install --no-cache-dir wheel
-
-# install TF 
-if [ -f "${cDir}/$ENV_NAME/bin/tensorboard" ]; then
-  echo 'TF already installed'
-  echo
-else
-  if [ -z "$NO_CUDA" ]; then
-    pip3 install tensorflow[and-cuda]==2.16.* --no-cache-dir
-  else
-    # CPU only installation
-    pip3 install tensorflow==2.16.* --no-cache-dir
-  fi
-fi
-
-# CURRENTLY, horovod is not used with TF. Skipped.
-# # install horovod
-# if [ -f "${cDir}/$ENV_NAME/bin/horovodrun" ]; then
-#   echo 'Horovod already installed'
+source $ENV_NAME/bin/activate
+pip install --no-cache-dir -e ".[dev,nvidia,tf]"
+
+# pip3 install --no-cache-dir  --upgrade pip
+#
+# # get wheel -- setuptools extension
+# pip3 install --no-cache-dir wheel
+#
+# # install TF 
+# if [ -f "${cDir}/$ENV_NAME/bin/tensorboard" ]; then
+#   echo 'TF already installed'
 #   echo
 # else
 #   if [ -z "$NO_CUDA" ]; then
-#     export HOROVOD_GPU=CUDA
-#     export HOROVOD_GPU_OPERATIONS=NCCL
-#     export HOROVOD_WITH_TENSORFLOW=1
-#     # export TMPDIR=${cDir}
+#     pip3 install tensorflow[and-cuda]==2.16.* --no-cache-dir
 #   else
 #     # CPU only installation
-#     export HOROVOD_WITH_TENSORFLOW=1
-#     # export TMPDIR=${cDir}
+#     pip3 install tensorflow==2.16.* --no-cache-dir
 #   fi
-
-#   pip3 install --no-cache-dir horovod[tensorflow,keras] # --ignore-installed
 # fi
-
-# WHEN USING TF >= 2.16:
-# install legacy version of keras (2.16)
-# Since TF 2.16, keras updated to 3.3,
-# which leads to an error when more than 1 node is used
-# https://keras.io/getting_started/
-pip3 install --no-cache-dir  tf_keras==2.16.*
-
-# Install Pov4ML
-if [[ "$OSTYPE" =~ ^darwin ]] ; then
-  pip install "prov4ml[apple,nvidia]@git+https://github.com/matbun/ProvML@new-main" || exit 1
-else
-  pip install "prov4ml[nvidia]@git+https://github.com/matbun/ProvML@new-main" || exit 1
-fi
-
-# Install itwinai: MUST be last line of the script for the user installation script to work!
-pip3 install --no-cache-dir  -e .[dev]
+#
+# # CURRENTLY, horovod is not used with TF. Skipped.
+# # # install horovod
+# # if [ -f "${cDir}/$ENV_NAME/bin/horovodrun" ]; then
+# #   echo 'Horovod already installed'
+# #   echo
+# # else
+# #   if [ -z "$NO_CUDA" ]; then
+# #     export HOROVOD_GPU=CUDA
+# #     export HOROVOD_GPU_OPERATIONS=NCCL
+# #     export HOROVOD_WITH_TENSORFLOW=1
+# #     # export TMPDIR=${cDir}
+# #   else
+# #     # CPU only installation
+# #     export HOROVOD_WITH_TENSORFLOW=1
+# #     # export TMPDIR=${cDir}
+# #   fi
+#
+# #   pip3 install --no-cache-dir horovod[tensorflow,keras] # --ignore-installed
+# # fi
+#
+# # WHEN USING TF >= 2.16:
+# # install legacy version of keras (2.16)
+# # Since TF 2.16, keras updated to 3.3,
+# # which leads to an error when more than 1 node is used
+# # https://keras.io/getting_started/
+# pip3 install --no-cache-dir  tf_keras==2.16.*
+#
+# # Install Pov4ML
+# if [[ "$OSTYPE" =~ ^darwin ]] ; then
+#   pip install "prov4ml[apple,nvidia]@git+https://github.com/matbun/ProvML@new-main" || exit 1
+# else
+#   pip install "prov4ml[nvidia]@git+https://github.com/matbun/ProvML@new-main" || exit 1
+# fi
+#
+#
+# # Install itwinai: MUST be last line of the script for the user installation script to work!
+# pip3 install --no-cache-dir  -e .[dev]