Adopt rc2 wheels (#4756)

Author: sramakintel

docker/Dockerfile.prebuilt

@@ -58,22 +58,7 @@ RUN apt-get update && \
     apt-get clean && \
     rm -rf  /var/lib/apt/lists/*
 
-RUN wget -O- https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB \
-   | gpg --dearmor | tee /usr/share/keyrings/oneapi-archive-keyring.gpg > /dev/null && \
-   echo "deb [signed-by=/usr/share/keyrings/oneapi-archive-keyring.gpg] https://apt.repos.intel.com/oneapi all main" \
-   | tee /etc/apt/sources.list.d/oneAPI.list
-
-ARG DPCPP_VER
-ARG MKL_VER
-ARG CCL_VER
-
-RUN apt-get update && \
-    apt-get install -y --no-install-recommends \
-        intel-oneapi-runtime-dpcpp-cpp=${DPCPP_VER} \
-        intel-oneapi-runtime-mkl=${MKL_VER} \
-        intel-oneapi-runtime-ccl=${CCL_VER} && \
-    apt-get clean && \
-    rm -rf  /var/lib/apt/lists/*
+ENV OCL_ICD_VENDORS=/etc/OpenCL/vendors 
 
 ARG PYTHON
 RUN apt-get update && apt install -y software-properties-common 

docker/README.md

@@ -33,18 +33,20 @@ Alternatively, `./build.sh` script has docker build command to install prebuilt
 To pull docker images use the following command:
 
 ```bash
-docker pull intel/intel-extension-for-pytorch:xpu
+docker pull intel/intel-extension-for-pytorch:2.3.110-xpu
 ```
+
 ### Running container:
 
 Run the following commands to start Intel® Extension for PyTorch\* GPU container. You can use `-v` option to mount your
 local directory into the container. The `-v` argument can be omitted if you do not need
 access to a local directory in the container. Pass the video and render groups to your
 docker container so that the GPU is accessible.
 
+```bash
+IMAGE_NAME=intel/intel-extension-for-pytorch:2.3.110-xpu
 ```
-IMAGE_NAME=intel/intel-extension-for-pytorch:xpu
-```
+
 ```bash
 docker run --rm \
     -v <your-local-dir>:/workspace \
@@ -58,44 +60,57 @@ docker run --rm \
 
 #### Verify if XPU is accessible from PyTorch:
 You are inside the container now. Run the following command to verify XPU is visible to PyTorch:
+
 ```bash
 python -c "import torch;print(torch.device('xpu'))"
 ```
+
 Sample output looks like below:
-```
+
+```bash
 xpu
 ```
+
 Then, verify that the XPU device is available to Intel® Extension for PyTorch\*:
+
 ```bash
-python -c "import intel_extension_for_pytorch as ipex;print(ipex.xpu.is_available())"
+python -c "import torch;import intel_extension_for_pytorch as ipex;print(torch.xpu.has_xpu())"
 ```
+
 Sample output looks like below:
-```
+
+```bash
 True
 ```
+
 Use the following command to check whether MKL is enabled as default:
+
 ```bash
-python -c "import intel_extension_for_pytorch as ipex;print(ipex.xpu.has_onemkl())"
+python -c "import torch;import intel_extension_for_pytorch as ipex;print(torch.xpu.has_onemkl())"
 ```
+
 Sample output looks like below:
-```
+
+```bash
 True
 ```
+
 Finally, use the following command to show detailed info of detected device:
+
 ```bash
-python -c "import torch; import intel_extension_for_pytorch as ipex; print(torch.__version__); print(ipex.__version__); [print(f'[{i}]: {ipex.xpu.get_device_properties(i)}') for i in range(ipex.xpu.device_count())];"
+python -c "import torch; import intel_extension_for_pytorch as ipex; print(torch.__version__); print(ipex.__version__); [print(f'[{i}]: {torch.xpu.get_device_properties(i)}') for i in range(torch.xpu.device_count())];"
 ```
 
 Sample output looks like below:
+
+```bash
+2.3.1+cxx11.abi
+2.3.110+xpu
+[0]: _XpuDeviceProperties(name='Intel(R) Data Center GPU Max 1550', platform_name='Intel(R) Level-Zero', type='gpu', driver_version='1.3.30049', total_memory=65536MB, max_compute_units=448, gpu_eu_count=448, gpu_subslice_count=56, max_work_group_size=1024, max_num_sub_groups=64, sub_group_sizes=[16 32], has_fp16=1, has_fp64=1, has_atomic64=1)
+[1]: _XpuDeviceProperties(name='Intel(R) Data Center GPU Max 1550', platform_name='Intel(R) Level-Zero', type='gpu', driver_version='1.3.30049', total_memory=65536MB, max_compute_units=448, gpu_eu_count=448, gpu_subslice_count=56, max_work_group_size=1024, max_num_sub_groups=64, sub_group_sizes=[16 32], has_fp16=1, has_fp64=1, has_atomic64=1)
 ```
-2.1.0.post2+cxx11.abi
-2.1.30+xpu
-[0]: _DeviceProperties(name='Intel(R) Data Center GPU Max 1550', platform_name='Intel(R) Level-Zero', dev_type='gpu', driver_version='1.3.27642', has_fp64=1, total_memory=65536MB, max_compute_units=448, gpu_eu_count=448)
-[1]: _DeviceProperties(name='Intel(R) Data Center GPU Max 1550', platform_name='Intel(R) Level-Zero', dev_type='gpu', driver_version='1.3.27642', has_fp64=1, total_memory=65536MB, max_compute_units=448, gpu_eu_count=448)
-```
+
 #### Running your own script
 
 Now you are inside container with Python 3.10, PyTorch, and Intel® Extension for PyTorch\* preinstalled. You can run your own script
 to run on Intel GPU.
-
-

docker/build.sh

@@ -12,9 +12,6 @@ if [[ ${IMAGE_TYPE} = "xpu" ]]; then
                  --build-arg LEVEL_ZERO_GPU_VER=1.3.30049.10-950~22.04 \
                  --build-arg LEVEL_ZERO_VER=1.17.6-950~22.04 \
                  --build-arg LEVEL_ZERO_DEV_VER=1.17.6-950~22.04 \
-                 --build-arg DPCPP_VER=2024.1.0-963 \
-                 --build-arg MKL_VER=2024.1.0-691 \
-                 --build-arg CCL_VER=2021.12.0-309 \
                  --build-arg TORCH_VERSION=2.3.1+cxx11.abi  \
                  --build-arg IPEX_VERSION=2.3.110+xpu \
                  --build-arg TORCHVISION_VERSION=0.18.1+cxx11 \