update doc for release 2.6.10 (#5352)

* update llm readme for release 2.6

* update doc torch compile

* explain intel compiler compatible error case while installing ipex

Author: ZhaoqiongZ

docs/tutorials/features/torch_compile_gpu.md

@@ -9,20 +9,10 @@ Intel® Extension for PyTorch\* now empowers users to seamlessly harness graph c
 # Required Dependencies
 
 **Verified version**:
-- `torch` : v2.5
-- `intel_extension_for_pytorch` : v2.5
-- `triton` : v3.1.0+91b14bf559
+- `torch` : v2.6
+- `intel_extension_for_pytorch` : v2.6
 
-
-Install [Intel® oneAPI DPC++/C++ Compiler 2025.0.4](https://www.intel.com/content/www/us/en/developer/tools/oneapi/dpc-compiler-download.html).
-
-Follow [Intel® Extension for PyTorch\* Installation](https://intel.github.io/intel-extension-for-pytorch/xpu/latest/) to install `torch` and `intel_extension_for_pytorch` firstly.
-
-Triton could be directly installed using the following command:
-
-```Bash
-pip install --pre pytorch-triton-xpu==3.1.0+91b14bf559 --index-url https://download.pytorch.org/whl/nightly/xpu
-```
+Follow [ https://pytorch-extension.intel.com/installation?platform=gpu&version=v2.6.10%2Bxpu) to install `torch` and `intel_extension_for_pytorch`. Triton is installed along with torch.
 
 The cached files would be generated if you had run `torch.compile` with a previous version of triton, but they are generally conflicting with the new version.
 So, if the folder `~/.triton` exists before your first running of the `torch.compile` script in the current environment, please delete it.
@@ -32,17 +22,8 @@ So, if the folder `~/.triton` exists before your first running of the `torch.com
 rm -rf ~/.triton
 ```
 
-Remember to activate the oneAPI DPC++/C++ Compiler by following commands.
-
-```bash
-# {dpcpproot} is the location for dpcpp ROOT path and it is where you installed oneAPI DPCPP, usually it is /opt/intel/oneapi/compiler/latest or ~/intel/oneapi/compiler/latest
-source {dpcpproot}/env/vars.sh
-```
-
-
 # Example Usage
 
-
 ## Inferenece with torch.compile
 
 ```python

docs/tutorials/known_issues.md

@@ -117,6 +117,15 @@ Troubleshooting
     pip install --pre pytorch-triton-xpu==3.1.0+91b14bf559  --index-url https://download.pytorch.org/whl/nightly/xpu
     ```
 
+- **Problem**: ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
+                torch 2.6.0+xpu requires intel-cmplr-lib-rt==2025.0.2, but you have intel-cmplr-lib-rt 2025.0.4 which is incompatible.
+                torch 2.6.0+xpu requires intel-cmplr-lib-ur==2025.0.2, but you have intel-cmplr-lib-ur 2025.0.4 which is incompatible.
+                torch 2.6.0+xpu requires intel-cmplr-lic-rt==2025.0.2, but you have intel-cmplr-lic-rt 2025.0.4 which is incompatible.
+                torch 2.6.0+xpu requires intel-sycl-rt==2025.0.2, but you have intel-sycl-rt 2025.0.4 which is incompatible.
+  - **Cause**: The intel-extension-for-pytorch v2.6.10+xpu uses Intel Compiler 2025.0.4 for a distributed feature fix, while torch v2.6.0+xpu is pinned with 2025.0.2.
+  - **Solution**: Ignore the Error since actually torch v2.6.0+xpu is compatible with Intel Compiler 2025.0.4.
+
+
 ## Performance Issue
 
 - **Problem**: Extended durations for data transfers from the host system to the device (H2D) and from the device back to the host system (D2H).

examples/gpu/llm/README.md

@@ -8,21 +8,70 @@ Here you can find benchmarking scripts for large language models (LLM) text gene
 
 ## Environment Setup
 
-### [Recommended] Docker-based environment setup with compilation from source
+### [Recommended] Docker-based environment setup with prebuilt wheel files
 
 ```bash
 # Get the Intel® Extension for PyTorch* source code
 git clone https://github.com/intel/intel-extension-for-pytorch.git
 cd intel-extension-for-pytorch
-git checkout xpu-main
+git checkout release/xpu/2.6.10
+git submodule sync
+git submodule update --init --recursive
+
+# Build an image with the provided Dockerfile by installing Intel® Extension for PyTorch* with prebuilt wheels
+docker build -f examples/gpu/llm/Dockerfile -t ipex-llm:26010 .
+
+# Run the container with command below
+docker run -it --rm --privileged -v /dev/dri/by-path:/dev/dri/by-path ipex-llm:26010 bash
+
+# When the command prompt shows inside the docker container, enter llm examples directory
+cd llm
+
+# Activate environment variables
+source ./tools/env_activate.sh [inference|fine-tuning]
+```
+
+### Conda-based environment setup with prebuilt wheel files
+
+Make sure the driver packages are installed. Refer to [Installation Guide](https://intel.github.io/intel-extension-for-pytorch/#installation?platform=gpu&version=v2.6.10%2Bxpu&os=linux%2Fwsl2&package=pip).
+
+```bash
+
+# Get the Intel® Extension for PyTorch* source code
+git clone https://github.com/intel/intel-extension-for-pytorch.git
+cd intel-extension-for-pytorch
+git checkout release/xpu/2.6.10
+git submodule sync
+git submodule update --init --recursive
+
+# Make sure you have GCC >= 11 is installed on your system.
+# Create a conda environment
+conda create -n llm python=3.10 -y
+conda activate llm
+# Setup the environment with the provided script
+cd examples/gpu/llm
+# If you want to install Intel® Extension for PyTorch\* with prebuilt wheels, use the commands below:
+bash ./tools/env_setup.sh 0x07
+conda deactivate
+conda activate llm
+source ./tools/env_activate.sh [inference|fine-tuning]
+```
+
+### Docker-based environment setup with compilation from source
+
+```bash
+# Get the Intel® Extension for PyTorch* source code
+git clone https://github.com/intel/intel-extension-for-pytorch.git
+cd intel-extension-for-pytorch
+git checkout release/xpu/2.6.10
 git submodule sync
 git submodule update --init --recursive
 
 # Build an image with the provided Dockerfile by compiling Intel® Extension for PyTorch* from source
-docker build -f examples/gpu/llm/Dockerfile --build-arg COMPILE=ON -t ipex-llm:xpu-main .
+docker build -f examples/gpu/llm/Dockerfile --build-arg COMPILE=ON -t ipex-llm:26010 .
 
 # Run the container with command below
-docker run -it --rm --privileged -v /dev/dri/by-path:/dev/dri/by-path ipex-llm:xpu-main bash
+docker run -it --rm --privileged -v /dev/dri/by-path:/dev/dri/by-path ipex-llm:26010 bash
 
 # When the command prompt shows inside the docker container, enter llm examples directory
 cd llm
@@ -33,14 +82,14 @@ source ./tools/env_activate.sh [inference|fine-tuning]
 
 ### Conda-based environment setup with compilation from source
 
-Make sure the driver and Base Toolkit are installed. Refer to [Installation Guide](https://intel.github.io/intel-extension-for-pytorch/#installation?platform=gpu&version=v2.3.110%2Bxpu&os=linux%2Fwsl2&package=source).
+Make sure the driver and Base Toolkit are installed. Refer to [Installation Guide](https://intel.github.io/intel-extension-for-pytorch/#installation?platform=gpu&version=v2.6.10%2Bxpu&os=linux%2Fwsl2&package=source).
 
 ```bash
 
 # Get the Intel® Extension for PyTorch* source code
 git clone https://github.com/intel/intel-extension-for-pytorch.git
 cd intel-extension-for-pytorch
-git checkout xpu-main
+git checkout release/xpu/2.6.10
 git submodule sync
 git submodule update --init --recursive
 
@@ -51,7 +100,8 @@ conda activate llm
 # Setup the environment with the provided script
 cd examples/gpu/llm
 # If you want to install Intel® Extension for PyTorch\* from source, use the commands below:
-# e.g. bash ./tools/env_setup.sh 3 /opt/intel/oneapi pvc
+
+# e.g. bash ./tools/env_setup.sh 0x03 /opt/intel/oneapi/ pvc
 bash ./tools/env_setup.sh 3 <ONEAPI_ROOT_DIR> <AOT>
 
 conda deactivate