Jingxu10/docstring 112 (#1004)

* fix docs bugs

highlight installation of pytorch+cpu

* update version number to 1.12.100

Author: jingxu10

docs/tutorials/installation.md

@@ -5,7 +5,7 @@ Installation Guide
 
 |Category|Content|
 |--|--|
-|Compiler|Recommend using GCC newer than 11.2|
+|Compiler|Recommend using GCC 10|
 |Operating System|CentOS 7, RHEL 8, Rocky Linux 8.5, Ubuntu newer than 18.04|
 |Python|See prebuilt wheel files availability matrix below|
 
@@ -26,7 +26,7 @@ Make sure PyTorch is installed so that the extension will work properly. For eac
 |[v1.5.0-rc3](https://github.com/pytorch/pytorch/tree/v1.5.0-rc3 "v1.5.0-rc3")|[v1.0.1](https://github.com/intel/intel-extension-for-pytorch/tree/v1.0.1)|
 |[v1.5.0-rc3](https://github.com/pytorch/pytorch/tree/v1.5.0-rc3 "v1.5.0-rc3")|[v1.0.0](https://github.com/intel/intel-extension-for-pytorch/tree/v1.0.0)|
 
-Here is an example showing how to install PyTorch. For more details, refer to [pytorch.org](https://pytorch.org/get-started/locally/).
+Please install CPU version of PyTorch through its official channel. For more details, refer to [pytorch.org](https://pytorch.org/get-started/locally/).
 
 ---
 

docs/tutorials/performance_tuning/known_issues.md

@@ -1,6 +1,8 @@
 Known Issues
 ============
 
+- Compiling with gcc 11 might result in `illegal instruction` error.
+
 - `RuntimeError: Overflow when unpacking long` when a tensor's min max value exceeds int range while performing int8 calibration. Please customize QConfig to use min-max calibration method.
 
 - For models with dynamic control flow, please try dynamic quantization. Users are likely to get performance gain for GEMM models.

intel_extension_for_pytorch/cpu/runtime/multi_stream.py

@@ -8,24 +8,25 @@
 import warnings
 
 class MultiStreamModuleHint(object):
+    r"""
+    MultiStreamModuleHint is a hint to MultiStreamModule about how to split the inputs
+    or concat the output. Each argument should be None, with type of int or a container
+    which containes int or None such as: (0, None, ...) or [0, None, ...]. If the argument
+    is None, it means this argument will not be split or concat. If the argument is with
+    type int, its value means along which dim this argument will be split or concat.
+
+    Args:
+        *args: Variable length argument list.
+        **kwargs: Arbitrary keyword arguments.
+
+    Returns:
+        intel_extension_for_pytorch.cpu.runtime.MultiStreamModuleHint: Generated
+        intel_extension_for_pytorch.cpu.runtime.MultiStreamModuleHint object.
+
+    :meta public:
+    """
+
     def __init__(self, *args, **kwargs):
-        r"""
-        MultiStreamModuleHint is a hint to MultiStreamModule about how to split the inputs
-        or concat the output. Each argument should be None, with type of int or a container
-        which containes int or None such as: (0, None, ...) or [0, None, ...]. If the argument
-        is None, it means this argument will not be split or concat. If the argument is with
-        type int, its value means along which dim this argument will be split or concat.
-
-        Args:
-            *args: Variable length argument list.
-            **kwargs: Arbitrary keyword arguments.
-
-        Returns:
-            intel_extension_for_pytorch.cpu.runtime.MultiStreamModuleHint: Generated
-            intel_extension_for_pytorch.cpu.runtime.MultiStreamModuleHint object.
-
-        :meta public:
-        """
         self.args = list(args)
         self.kwargs = kwargs
         self.args_len = args.__len__()

setup.py

@@ -74,7 +74,7 @@
 #TORCH_VERSION = '1.13.0'
 #TORCH_VERSION = os.getenv('TORCH_VERSION', TORCH_VERSION)
 
-TORCH_IPEX_VERSION = '1.12.0+cpu'
+TORCH_IPEX_VERSION = '1.12.100+cpu'
 PYTHON_VERSION = sys.version_info
 
 package_name = "intel_extension_for_pytorch"