Add build and run Resnet50 and VGG16 actions

to the tartan CI job.

.github/actions/build_vgg_resnet_action/action.yml

@@ -0,0 +1,75 @@
+name: Setup and build networks; VGG16, Resnet50
+description: Build and run VV16 and Resnet50 with oneAPI base toolkit and oneAPI-Construction-Kit
+
+inputs:
+  workspace:
+    description: 'Main workflow workspace'
+    default: ${{ github.workspace }}
+
+runs:
+  # We don't want a new docker just a list of steps, so mark as composite
+  using: "composite"
+  steps:
+    - name: setup python
+      uses: actions/setup-python@v4
+      with:
+        python-version: '3.8'
+
+    - name: Install Python libraries and system dependencies
+      shell: bash
+      run: |
+        pip install requests numpy h5py Pillow
+        sudo add-apt-repository universe
+        sudo apt-get update
+        sudo apt-get install -y libblas-dev libopenblas64-dev libopenblas-dev libpthread-stubs0-dev libboost-all-dev
+
+    - name: Clone portDNN
+      shell: bash
+      run: git clone --recursive --depth 1 --single-branch https://github.com/codeplaysoftware/portDNN.git
+
+    - name: Download Daily Release
+      shell: bash
+      run: |
+        wget "https://github.com/intel/llvm/releases/download/nightly-2023-12-18/sycl_linux.tar.gz"
+        mkdir linux_nightly_release
+        tar -xzf sycl_linux.tar.gz -C linux_nightly_release
+
+    - name: Set up environment and build networks
+      shell: bash
+      run: |
+        export LD_LIBRARY_PATH=${{ inputs.workspace }}/build/lib:${{ inputs.workspace }}/linux_nightly_release/lib/libsycl.so:${{ inputs.workspace }}/linux_nightly_release/lib:$LD_LIBRARY_PATH
+        export CMAKE_CXX_COMPILER=${{ inputs.workspace }}/linux_nightly_release/bin/clang++
+        export CMAKE_C_COMPILER=${{ inputs.workspace }}/linux_nightly_release/bin/clang
+        export CA_HAL_DEBUG=1
+        export CA_PROFILE_LEVEL=3
+        export ONEAPI_DEVICE_SELECTOR=opencl:acc
+        export OCL_ICD_FILENAMES=${{ inputs.workspace }}/build/lib/libCL.so
+        # As the oneAPI basetoolkit release has a whitelist of devices, it filters out RefSi.
+        # To override it, as a temporary solution we can point SYCL_CONFIG_FILE_NAME to ``.
+        # This way it doesn't set the default sycl.conf.
+        export SYCL_CONFIG_FILE_NAME=""
+        export portDNN_source=$(pwd)/portDNN
+        export OCL_ICD_VENDORS=/dev/null
+
+        # VGG16
+        mkdir vdata
+        cd vdata
+        wget --no-verbose https://storage.googleapis.com/tensorflow/keras-applications/vgg16/vgg16_weights_tf_dim_ordering_tf_kernels.h5
+        python $portDNN_source/samples/networks/vgg/h5toBin.py vgg16_weights_tf_dim_ordering_tf_kernels.h5
+        cd ..
+
+        # Resnet50
+        mkdir rdata
+        cd rdata
+        wget --no-verbose https://storage.googleapis.com/tensorflow/keras-applications/resnet/resnet50_weights_tf_dim_ordering_tf_kernels.h5
+        python $portDNN_source/samples/networks/resnet50/h5toBin.py resnet50_weights_tf_dim_ordering_tf_kernels.h5
+        cd ..
+
+        # Preparing an image
+        python $portDNN_source/samples/networks/img2bin.py ${{ inputs.workspace }}/examples/technical_blogs/tartan_blog/Simple.jpg
+
+        # Testing on image for VGG16
+        CA_HAL_DEBUG=1 CA_PROFILE_LEVEL=3 OCL_ICD_FILENAMES=${{ inputs.workspace }}/build/lib/libCL.so ONEAPI_DEVICE_SELECTOR=opencl:acc SYCL_CONFIG_FILE_NAME=  ${{ inputs.workspace }}/portDNN_build_dir/samples/networks/vgg/vgg vdata/ ${{ inputs.workspace }}/examples/technical_blogs/tartan_blog/Simple.jpg.bin
+
+        # Testing on image for Resnet50
+        CA_HAL_DEBUG=1 CA_PROFILE_LEVEL=3 OCL_ICD_FILENAMES=${{ inputs.workspace }}/build/lib/libCL.so ONEAPI_DEVICE_SELECTOR=opencl:acc SYCL_CONFIG_FILE_NAME=  ${{ inputs.workspace }}/portDNN_build_dir/samples/networks/resnet50/resnet50 rdata/ ${{ inputs.workspace }}/examples/technical_blogs/tartan_blog/Simple.jpg.bin

.github/workflows/run_tartan.yml

@@ -34,7 +34,7 @@ jobs:
 
       - name: Install Python libraries and system dependencies
         run: |
-          pip install requests numpy h5py Pillow
+          pip install --user requests numpy h5py Pillow
           sudo add-apt-repository universe
           sudo apt-get update
           sudo apt-get install -y libblas-dev libopenblas64-dev libopenblas-dev libpthread-stubs0-dev libboost-all-dev
@@ -47,7 +47,6 @@ jobs:
           wget "https://github.com/intel/llvm/releases/download/nightly-2023-11-22/sycl_linux.tar.gz"
           mkdir linux_nightly_release
           tar -xzf sycl_linux.tar.gz -C linux_nightly_release
-          ls
 
       - name: Build portBLAS
         uses: ./.github/actions/build_portBLAS_action
@@ -56,5 +55,38 @@ jobs:
 
       - name: Build portDNN
         uses: ./.github/actions/build_portDNN_action
+        with:
+          workspace: ${{ github.workspace }}
+
+      - name: Package Tartan Artifacts
+        run: |
+          ls
+          tar -cvzf new_tartan.tar.gz build portDNN_build_dir portBLAS_build_dir
+
+      - name: Upload Artifacts
+        uses: actions/upload-artifact@v2
+        with:
+          name: tartan-build
+          path: new_tartan.tar.gz
+
+  build_and_run_networks:
+    runs-on: ubuntu-22.04
+    needs: run_riscv_m1_tartan
+    steps:
+      - name: Checkout repo
+        uses: actions/checkout@v3
+
+      - name: Download artifacts
+        uses: actions/download-artifact@v2
+        with:
+          name: tartan-build
+
+      - name: Untar artifacts
+        run: |
+          tar -xvzf new_tartan.tar.gz
+          ls
+
+      - name: Build vgg and resnet
+        uses: ./.github/actions/build_vgg_resnet_action
         with:
           workspace: ${{ github.workspace }}