Fix nova script (pytorch#2033)

Summary:
- Fix a syntax issue with bash associative arrays that caused the Nova build scripts to fail

Pull Request resolved: pytorch#2033

Reviewed By: spcyppt

Differential Revision: D49529109

Pulled By: q10

fbshipit-source-id: d2e1ac49e3490bc89b266c7596a19117efa0caa8

Author: q10

.github/scripts/fbgemm_gpu_build.bash

@@ -290,7 +290,7 @@ build_fbgemm_gpu_package () {
   fbgemm_variant="$3"
   fbgemm_variant_targets="$4"
   if [ "$fbgemm_variant" == "" ]; then
-    echo "Usage: ${FUNCNAME[0]} ENV_NAME PACKAGE_NAME VARIANT [TARGETS]"
+    echo "Usage: ${FUNCNAME[0]} ENV_NAME RELEASE_TYPE VARIANT [VARIANT_TARGETS]"
     echo "Example(s):"
     echo "    ${FUNCNAME[0]} build_env nightly cpu                           # Nightly CPU-only variant"
     echo "    ${FUNCNAME[0]} build_env nightly cuda                          # Nightly CUDA variant for default target(s)"

.github/scripts/fbgemm_gpu_test.bash

@@ -129,13 +129,14 @@ run_fbgemm_gpu_tests () {
 ################################################################################
 
 test_setup_conda_environment () {
-  local python_version="$1"
-  local pytorch_installer="$2"
-  local pytorch_version="$3"
-  local pytorch_variant_type="$4"
-  local pytorch_variant_version="$5"
+  local env_name="$1"
+  local python_version="$2"
+  local pytorch_installer="$3"
+  local pytorch_version="$4"
+  local pytorch_variant_type="$5"
+  local pytorch_variant_version="$6"
   if [ "$pytorch_variant_type" == "" ]; then
-    echo "Usage: ${FUNCNAME[0]} PYTHON_VERSION PYTORCH_INSTALLER PYTORCH_VERSION PYTORCH_VARIANT_TYPE [PYTORCH_VARIANT_VERSION]"
+    echo "Usage: ${FUNCNAME[0]} ENV_NAME PYTHON_VERSION PYTORCH_INSTALLER PYTORCH_VERSION PYTORCH_VARIANT_TYPE [PYTORCH_VARIANT_VERSION]"
     echo "Example(s):"
     echo "    ${FUNCNAME[0]} build_env 3.8 pip test cuda 11.8.0       # Setup environment with pytorch-test for Python 3.8 + CUDA 11.8.0"
     return 1
@@ -148,9 +149,11 @@ test_setup_conda_environment () {
     echo ""
   fi
 
-  local env_name="test_py${python_version}_${pytorch_installer}_pytorch_${pytorch_version}_${pytorch_variant_type}"
-  if [ "$pytorch_variant_version" != "" ]; then
-    local env_name="${env_name}_${pytorch_variant_version}"
+  if [ "$env_name" == "" ]; then
+    local env_name="test_py${python_version}_${pytorch_installer}_pytorch_${pytorch_version}_${pytorch_variant_type}"
+    if [ "$pytorch_variant_version" != "" ]; then
+      local env_name="${env_name}_${pytorch_variant_version}"
+    fi
   fi
 
   echo "Creating the Build Environment: ${env_name} ..."

.github/scripts/nova_prescript.bash

@@ -57,15 +57,15 @@ if [[ $CU_VERSION = cu* ]]; then
   echo "[NOVA] ------------------------------------------"
 
   echo "[NOVA] Building the CUDA variant of FBGEMM_GPU ..."
-  fbgemm_variant="cuda"
+  export fbgemm_variant="cuda"
 
 elif [[ $CU_VERSION = rocm* ]]; then
   echo "[NOVA] Building the ROCm variant of FBGEMM_GPU ..."
-  fbgemm_variant="rocm"
+  export fbgemm_variant="rocm"
 
 else
   echo "[NOVA] Building the CPU variant of FBGEMM_GPU ..."
-  fbgemm_variant="cpu"
+  export fbgemm_variant="cpu"
 fi
 
 # Install the necessary Python eggs for building
@@ -78,7 +78,7 @@ export BUILD_FROM_NOVA
 
 # Build FBGEMM_GPU nightly by default
 if [[ ${CHANNEL} == "" ]]; then
-  CHANNEL="nightly"
+  export CHANNEL="nightly"
 fi
 
 # Build the wheel

.github/scripts/test_torchrec.bash

@@ -11,49 +11,17 @@ set -e
 # shellcheck source=/dev/null
 . "$(dirname "$(realpath -s "$0")")/setup_env.bash"
 
-create_conda_pytorch_environment () {
-  local env_name="$1"
-  local python_version="$2"
-  local pytorch_channel_name="$3"
-  local cuda_version="$4"
-  if [ "$python_version" == "" ]; then
-    echo "Usage: ${FUNCNAME[0]} ENV_NAME PYTHON_VERSION PYTORCH_CHANNEL_NAME CUDA_VERSION"
-    echo "Example:"
-    echo "    ${FUNCNAME[0]} build_env 3.10 pytorch-nightly 11.7.1"
-    return 1
-  fi
-
-  # Create the Conda environment
-  create_conda_environment "${env_name}" "${python_version}"
-
-  # Convert the channels to versions
-  if [ "${pytorch_channel_name}" == "pytorch-nightly" ]; then
-    pytorch_version="nightly"
-  elif [ "${pytorch_channel_name}" == "pytorch-test" ]; then
-    pytorch_version="test"
-  else
-    pytorch_version="latest"
-  fi
-
-  if [ "${cuda_version}" == "" ]; then
-    # Install the CPU variant of PyTorch
-    install_pytorch_conda "${env_name}" "${pytorch_version}" cpu
-  else
-    # Install CUDA and the GPU variant of PyTorch
-    install_cuda "${env_name}" "${cuda_version}"
-    install_pytorch_conda "${env_name}" "${pytorch_version}"
-  fi
-}
-
 verbose=0
+env_name=test_binary
 torchrec_package_name=""
 python_version=""
 cuda_version="x"
 fbgemm_wheel_path="x"
 miniconda_prefix="${HOME}/miniconda"
 
 usage () {
-  echo "Usage: bash test_torchrec.bash -o PACKAGE_NAME -p PYTHON_VERSION -P PYTORCH_CHANNEL_NAME -c CUDA_VERSION -w FBGEMM_WHEEL_PATH [-m MINICONDA_PREFIX] [-v] [-h]"
+  # shellcheck disable=SC2086
+  echo "Usage: bash $(basename ${BASH_SOURCE[0]}) -o PACKAGE_NAME -p PYTHON_VERSION -P PYTORCH_CHANNEL_NAME -c CUDA_VERSION -w FBGEMM_WHEEL_PATH [-m MINICONDA_PREFIX] [-v] [-h]"
   echo "-v                  : verbose"
   echo "-h                  : help"
   echo "PACKAGE_NAME        : output package name of TorchRec (e.g., torchrec_nightly)"
@@ -65,7 +33,8 @@ usage () {
   echo "FBGEMM_WHEEL_PATH   : path to FBGEMM_GPU's wheel file"
   echo "MINICONDA_PREFIX    : path to install Miniconda (default: \$HOME/miniconda)"
   echo "Example: Python 3.10 + PyTorch nightly (CUDA 11.7), install miniconda at \$HOME/miniconda, using dist/fbgemm_gpu_nightly.whl"
-  echo "       bash test_torchrec.bash -v -o torchrec_nightly -p 3.10 -P pytorch-nightly -c 11.7 -w dist/fbgemm_gpu_nightly.whl"
+  # shellcheck disable=SC2086
+  echo "       bash $(basename ${BASH_SOURCE[0]}) -v -o torchrec_nightly -p 3.10 -P pytorch-nightly -c 11.7 -w dist/fbgemm_gpu_nightly.whl"
 }
 
 while getopts vho:p:P:c:m:w: flag
@@ -112,30 +81,37 @@ echo "## 1. Set up Miniconda"
 setup_miniconda "$miniconda_prefix"
 
 ################################################################################
-echo "## 2. Create test_binary environment"
+echo "## 2. Create Conda environment"
 ################################################################################
 
-create_conda_pytorch_environment test_binary "$python_version" "$pytorch_channel_name" "$cuda_version"
+if [ "${cuda_version}" == "" ]; then
+  pytorch_variant="cuda ${cuda_version}"
+else
+  pytorch_variant="cpu"
+fi
+
+# shellcheck disable=SC2086
+test_setup_conda_environment "$env_name" "$python_version" pip "$pytorch_channel_name" $pytorch_variant
 
 # Comment out FBGEMM_GPU since we will install it from "$fbgemm_wheel_path"
 sed -i 's/fbgemm-gpu/#fbgemm-gpu/g' requirements.txt
-conda run -n test_binary python -m pip install -r requirements.txt
+conda run -n "$env_name" python -m pip install -r requirements.txt
 # Install FBGEMM_GPU from a local wheel file.
-conda run -n test_binary python -m pip install "$fbgemm_wheel_path"
-conda run -n test_binary python -c "import fbgemm_gpu"
+conda run -n "$env_name" python -m pip install "$fbgemm_wheel_path"
+conda run -n "$env_name" python -c "import fbgemm_gpu"
 
 ################################################################################
 echo "## 3. Build TorchRec"
 ################################################################################
 
 rm -rf dist
-conda run -n test_binary python setup.py bdist_wheel --package_name "${torchrec_package_name}" --python-tag="py${python_tag}"
+conda run -n "$env_name" python setup.py bdist_wheel --package_name "${torchrec_package_name}" --python-tag="py${python_tag}"
 
 ################################################################################
 echo "## 4. Import TorchRec"
 ################################################################################
 
-conda run -n test_binary python -m pip install dist/"${torchrec_package_name}"*.whl
-conda run -n test_binary python -c "import torchrec"
+conda run -n "$env_name" python -m pip install dist/"${torchrec_package_name}"*.whl
+conda run -n "$env_name" python -c "import torchrec"
 
 echo "Test succeeded"

.github/scripts/utils_cuda.bash

@@ -102,7 +102,7 @@ install_cudnn () {
 
   # Install cuDNN manually
   # Based on install script in https://github.com/pytorch/builder/blob/main/common/install_cuda.sh
-  local cudnn_packages=(
+  declare -A cudnn_packages=(
     ["115"]="https://developer.download.nvidia.com/compute/redist/cudnn/v8.3.2/local_installers/11.5/cudnn-${PLATFORM_NAME_LC}-8.3.2.44_cuda11.5-archive.tar.xz"
     ["116"]="https://developer.download.nvidia.com/compute/redist/cudnn/v8.3.2/local_installers/11.5/cudnn-${PLATFORM_NAME_LC}-8.3.2.44_cuda11.5-archive.tar.xz"
     ["117"]="https://ossci-linux.s3.amazonaws.com/cudnn-${PLATFORM_NAME_LC}-8.5.0.96_cuda11-archive.tar.xz"