Update naming and dropping Intel specifics (backport #2355) (#2378)

* Update naming and dropping Intel specifics (#2355)

* Dropping Intel specific naming

* Fix conda related naming

* updating doc config with naming

* Renaming IntelEstomator to ExtensionEstimator

* Replacing oneDAL with sustitution reference

* Fixing linting on incremental_ridge

* remplacing substitute name

* removing reg

* update copyright/author

* adding onedal substitution

* fix spacing

(cherry picked from commit f89c9e2)

# Conflicts:
#	doc/sources/oneapi-gpu.rst
#	doc/sources/quick-start.rst

* Update oneapi-gpu.rst

* Update quick-start.rst

---------

Co-authored-by: Nikolay Petrov <[email protected]>

Author: mergify[bot]

CONTRIBUTING.md

@@ -17,12 +17,12 @@
 
 # How to Contribute
 
-As an open source project, we welcome community contributions to Intel(R) Extension for Scikit-learn. 
+As an open source project, we welcome community contributions to Extension for Scikit-learn. 
 This document explains how to participate in project conversations, log bugs and enhancement requests, and submit code patches.
 
 ## Licensing 
 
-Intel(R) Extension for Scikit-learn uses the [Apache 2.0 License](https://github.com/uxlfoundation/scikit-learn-intelex/blob/main/LICENSE). 
+Extension for Scikit-learn uses the [Apache 2.0 License](https://github.com/uxlfoundation/scikit-learn-intelex/blob/main/LICENSE). 
 By contributing to the project, you agree to the license and copyright terms and release your own contributions under these terms. 
 
 ## Pull Requests 

INSTALL.md

@@ -18,25 +18,23 @@
 
 # Installation  <!-- omit in toc -->
 
-To install Intel(R) Extension for Scikit-learn*, use one of the following scenarios:
+To install Extension for Scikit-learn*, use one of the following scenarios:
 
 - [Before You Begin](#before-you-begin)
 - [Install via PIP](#install-via-pip)
   - [Install from PyPI Channel (recommended by default)](#install-from-pypi-channel-recommended-by-default)
-- [Install from Anaconda Cloud](#install-from-anaconda-cloud)
-  - [Install via Anaconda Cloud from Conda-Forge Channel](#install-via-anaconda-cloud-from-conda-forge-channel)
-  - [Install via Anaconda Cloud from Intel Channel](#install-via-anaconda-cloud-from-intel-channel)
+- [Install via conda](#install-via-conda)
+  - [Install from Conda-Forge Channel](#install-from-conda-forge-channel)
+  - [Install from Intel conda Channel](#install-from-intel-conda-channel)
 - [Build from Sources](#build-from-sources)
   - [Prerequisites](#prerequisites)
   - [Configure the Build with Environment Variables](#configure-the-build-with-environment-variables)
-  - [Build Intel(R) Extension for Scikit-learn](#build-intelr-extension-for-scikit-learn)
+  - [Build Extension for Scikit-learn](#build-intelr-extension-for-scikit-learn)
 - [Build from Sources with `conda-build`](#build-from-sources-with-conda-build)
   - [Prerequisites for `conda-build`](#prerequisites-for-conda-build)
-  - [Build Intel(R) Extension for Scikit-learn with `conda-build`](#build-intelr-extension-for-scikit-learn-with-conda-build)
+  - [Build Extension for Scikit-learn with `conda-build`](#build-intelr-extension-for-scikit-learn-with-conda-build)
 - [Next Steps](#next-steps)
 
-> **_NOTE:_** Intel(R) Extension for Scikit-learn* is also available as a part of [Intel® AI Tools](https://www.intel.com/content/www/us/en/developer/tools/oneapi/ai-analytics-toolkit.html). If you already have it installed, you do not need to separately install the extension.
-
 
 ## Before You Begin
 
@@ -49,8 +47,8 @@ Check [System](https://uxlfoundation.github.io/scikit-learn-intelex/latest/syste
 * Devices: CPU, GPU
 * Distribution channels:
   * PyPI
-  * Anaconda Cloud from Conda-Forge Channel
-  * Anaconda Cloud from Intel Channel (https://software.repos.intel.com/python/conda/)
+  * Conda-Forge Channel
+  * Intel conda Channel (https://software.repos.intel.com/python/conda/)
 
 ## Install via PIP
 
@@ -78,11 +76,11 @@ Install `scikit-learn-intelex`:
    pip install scikit-learn-intelex
    ```
 
-## Install from Anaconda Cloud
+## Install via conda
 
 To prevent version conflicts, we recommend to create and activate a new environment. 
 
-### Install via Anaconda Cloud from Conda-Forge Channel
+### Install from Conda-Forge Channel
 
 - Install into a newly created environment (recommended):
 
@@ -102,7 +100,7 @@ To prevent version conflicts, we recommend to create and activate a new environm
   conda install scikit-learn-intelex
   ```
 
-### Install via Anaconda Cloud from Intel Channel
+### Install Intel conda Channel
 
 We recommend this installation for the users of Intel® Distribution for Python.
 
@@ -133,7 +131,7 @@ We recommend this installation for the users of Intel® Distribution for Python.
   ```
 
 ## Build from Sources
-Intel(R) Extension for Scikit-learn* is easily built from the sources with the majority of the necessary prerequisites available with conda or pip. 
+Extension for Scikit-learn* is easily built from the sources with the majority of the necessary prerequisites available with conda or pip. 
 
 The package is available for Windows* OS, Linux* OS, and macOS*.
 
@@ -153,7 +151,7 @@ The build-process (using setup.py) happens in 4 stages:
 * cmake and pybind11
 * A C++ compiler with C++11 support
 * Clang-Format version >=14
-* [Intel® oneAPI Data Analytics Library (oneDAL)](https://github.com/uxlfoundation/oneDAL) version 2021.1 or later, but be mindful that **the oneDAL version must be <= than that of scikit-learn-intelex** (it's backwards compatible but not forwards compatible).
+* [oneAPI Data Analytics Library (oneDAL)](https://github.com/uxlfoundation/oneDAL) version 2021.1 or later, but be mindful that **the oneDAL version must be <= than that of scikit-learn-intelex** (it's backwards compatible but not forwards compatible).
   * You can use the pre-built `dal-devel` conda package from conda-forge channel
 * MPI (optional, needed for distributed mode)
   * You can use the pre-built `impi_rt` and `impi-devel` conda packages from conda-forge channel
@@ -173,7 +171,7 @@ The build-process (using setup.py) happens in 4 stages:
 **Note:** The `-j` flag in the ``MAKEFLAGS`` environment variable is superseded in `setup.py` modes which support the ``--parallel`` and `-j` command line flags.
 
 
-### Build Intel(R) Extension for Scikit-learn
+### Build Extension for Scikit-learn
 
 - To install the package:
 
@@ -202,7 +200,7 @@ The build-process (using setup.py) happens in 4 stages:
 
 Where: 
 
-* Keys `--single-version-externally-managed` and `--no-deps` are required to not download daal4py after the installation of Intel(R) Extension for Scikit-learn. 
+* Keys `--single-version-externally-managed` and `--no-deps` are required to not download daal4py after the installation of Extension for Scikit-learn. 
 * The `develop` mode does not install the package but creates a `.egg-link` in the deployment directory
 back to the project source-code directory. That way, you can edit the source code and see the changes
 without reinstalling the package after a small change.
@@ -227,7 +225,7 @@ python setup.py build --abs-rpath
 
 ## Build from Sources with `conda-build`
 
-Intel(R) Extension for Scikit-learn* is easily built from the sources using only one command and `conda-build` utility. 
+Extension for Scikit-learn* is easily built from the sources using only one command and `conda-build` utility. 
 
 ### Prerequisites for `conda-build`
 
@@ -241,7 +239,7 @@ Intel(R) Extension for Scikit-learn* is easily built from the sources using only
 In order to enable DPC++ interfaces support on Windows, you need to set `DPCPPROOT` environment variable pointing to DPC++/C++ Compiler distribution.
 Conda-forge distribution of DPC++ compiler is used by default on Linux, but you still can set your own distribution via `DPCPPROOT` variable.
 
-### Build Intel(R) Extension for Scikit-learn with `conda-build`
+### Build Extension for Scikit-learn with `conda-build`
 
 Create and verify `scikit-learn-intelex` conda package with next command executed from root of sklearnex repo:
 

README.md

@@ -17,9 +17,9 @@
 <div align="center">
 
 
-# Intel(R) Extension for Scikit-learn*
+# Extension for Scikit-learn*
 
-<h3> Speed up your scikit-learn applications for Intel(R) CPUs and GPUs across single- and multi-node configurations
+<h3> Speed up your scikit-learn applications for CPUs and GPUs across single- and multi-node configurations
 
 [Releases](https://github.com/uxlfoundation/scikit-learn-intelex/releases)&nbsp;&nbsp;&nbsp;|&nbsp;&nbsp;&nbsp;[Documentation](https://uxlfoundation.github.io/scikit-learn-intelex/)&nbsp;&nbsp;&nbsp;|&nbsp;&nbsp;&nbsp;[Examples](https://github.com/uxlfoundation/scikit-learn-intelex/tree/master/examples/notebooks)&nbsp;&nbsp;&nbsp;|&nbsp;&nbsp;&nbsp;[Support]()&nbsp;&nbsp;&nbsp;|&nbsp;&nbsp;[License](https://github.com/uxlfoundation/scikit-learn-intelex/blob/master/LICENSE)&nbsp;&nbsp;&nbsp;
 
@@ -39,29 +39,27 @@
 
 ## Overview
 
-Intel(R) Extension for Scikit-learn is a **free software AI accelerator** designed to deliver over **10-100X** acceleration to your existing scikit-learn code.
-The software acceleration is achieved with vector instructions, AI hardware-specific memory optimizations, threading, and optimizations for all upcoming Intel(R) platforms at launch time.
+Extension for Scikit-learn is a **free software AI accelerator** designed to deliver over **10-100X** acceleration to your existing scikit-learn code.
+The software acceleration is achieved with vector instructions, AI hardware-specific memory optimizations, threading, and optimizations.
 
 
-With Intel(R) Extension for Scikit-learn, you can:
+With Extension for Scikit-learn, you can:
 
 * Speed up training and inference by up to 100x with equivalent mathematical accuracy
-* Benefit from performance improvements across different Intel(R) hardware configurations, including GPUs and multi-GPU configurations
+* Benefit from performance improvements across different CPU hardware configurations, including GPUs and multi-GPU configurations
 * Integrate the extension into your existing Scikit-learn applications without code modifications
 * Continue to use the open-source scikit-learn API
 * Enable and disable the extension with a couple of lines of code or at the command line
 
-Intel(R) Extension for Scikit-learn is also a part of [Intel(R) AI Tools](https://www.intel.com/content/www/us/en/developer/tools/oneapi/ai-analytics-toolkit.html).
-
 ## Acceleration
 
 ![](https://raw.githubusercontent.com/uxlfoundation/scikit-learn-intelex/master/doc/sources/_static/scikit-learn-acceleration.PNG)
 
 [Benchmarks code](https://github.com/IntelPython/scikit-learn_bench)
 
-## Intel(R) Optimizations
+## Optimizations
 
-- **Enable Intel(R) CPU optimizations**
+- **Enable CPU optimizations**
 
     ```py
     import numpy as np
@@ -75,7 +73,7 @@ Intel(R) Extension for Scikit-learn is also a part of [Intel(R) AI Tools](https:
     clustering = DBSCAN(eps=3, min_samples=2).fit(X)
     ```
 
-- **Enable Intel(R) GPU optimizations**
+- **Enable GPU optimizations**
 
     _Note: executing on GPU has [additional system software requirements](https://www.intel.com/content/www/us/en/developer/articles/system-requirements/intel-oneapi-dpcpp-system-requirements.html) - see [details](https://uxlfoundation.github.io/scikit-learn-intelex/latest/oneapi-gpu.html)._
 
@@ -96,7 +94,7 @@ Intel(R) Extension for Scikit-learn is also a part of [Intel(R) AI Tools](https:
 
 ## Installation
 
-To install Intel(R) Extension for Scikit-learn, run:
+To install Extension for Scikit-learn, run:
 
 ```
 pip install scikit-learn-intelex
@@ -136,8 +134,8 @@ To patch scikit-learn, you can:
 
 ### daal4py and oneDAL
 
-The acceleration is achieved through the use of the Intel(R) oneAPI Data Analytics Library (oneDAL). Learn more:
-- [About Intel(R) oneAPI Data Analytics Library](https://github.com/uxlfoundation/oneDAL)
+The acceleration is achieved through the use of the oneAPI Data Analytics Library (oneDAL). Learn more:
+- [About oneAPI Data Analytics Library](https://github.com/uxlfoundation/oneDAL)
 - [About daal4py](https://github.com/uxlfoundation/scikit-learn-intelex/tree/main/daal4py)
 
 ## Samples & Examples

SECURITY.md

@@ -19,13 +19,13 @@
 
 As an open-source project, we understand the importance of and responsibility
 for security. This Security Policy outlines our guidelines and procedures to
-ensure the highest level of security and trust for Intel(R) Extension for Scikit-learn* users. 
+ensure the highest level of security and trust for Extension for Scikit-learn* users. 
 
 ## Supported Versions
 
 Security vulnerabilities are fixed in the [latest version][1]
 and delivered as a patch release. We don't guarantee security fixes to be
-back-ported to older Intel(R) Extension for Scikit-learn* versions.
+back-ported to older Extension for Scikit-learn* versions.
 
 ## Report a Vulnerability
 
@@ -52,24 +52,24 @@ Along with the report, provide the following info:
 
 ### When Should I Report a Vulnerability?
 
-* You think you discovered a potential security vulnerability in Intel(R) Extension for Scikit-learn*.
-* You are unsure how the potential vulnerability affects Intel(R) Extension for Scikit-learn*.
+* You think you discovered a potential security vulnerability in Extension for Scikit-learn*.
+* You are unsure how the potential vulnerability affects Extension for Scikit-learn*.
 * You think you discovered a vulnerability in another project or 3rd party
-component on which Intel(R) Extension for Scikit-learn* depends. If the issue is not fixed in the 3rd party
+component on which Extension for Scikit-learn* depends. If the issue is not fixed in the 3rd party
 component, try to report directly there first.
 
 ### When Should I NOT Report a Vulnerability?
 
 * You got an automated scan hit and are unable to provide details.
-* You need help using Intel(R) Extension for Scikit-learn* for security.
+* You need help using Extension for Scikit-learn* for security.
 * You need help applying security-related updates.
 * Your issue is not security-related.
 
 ## Security Reports Review Process
 
 We aim to respond quickly to your inquiry and coordinate a fix and
 disclosure with you. All confirmed security vulnerabilities will be addressed
-according to severity level and impact on Intel(R) Extension for Scikit-learn*. Normally, security issues
+according to severity level and impact on Extension for Scikit-learn*. Normally, security issues
 are fixed in the next planned release.
 
 ## Disclosure Policy

SUPPORT.md

@@ -15,9 +15,9 @@
 * limitations under the License.
 *******************************************************************************/-->
 
-# Intel(R) Extension for Scikit-learn Support
+# Extension for Scikit-learn Support
 
-We are committed to providing support and assistance to help you make the most out of Intel(R) Extension for Scikit-learn. 
+We are committed to providing support and assistance to help you make the most out of Extension for Scikit-learn. 
 Use the following methods if you face any challenges. 
 
 
@@ -34,7 +34,7 @@ Visit the [GitHub Discussions](https://github.com/uxlfoundation/scikit-learn-int
 
 ## Forum 
 
-Ask questions about Intel(R) Extension for Scikit-learn on our [Forum](https://community.intel.com/t5/Intel-Distribution-for-Python/bd-p/distribution-python).
+Ask questions about Extension for Scikit-learn on our [Forum](https://community.intel.com/t5/Intel-Distribution-for-Python/bd-p/distribution-python).
 Make sure to provide all relevant details, so we could help you as soon as possible. 
 
 ## Email

conda-recipe/meta.yaml

@@ -104,7 +104,7 @@ about:
   license_file:
     - LICENSE
     - doc/third-party-programs-sklearnex.txt
-  summary: Intel(R) Extension for Scikit-learn* is a seamless way to speed up your Scikit-learn application.
+  summary: Extension for Scikit-learn* is a seamless way to speed up your Scikit-learn application.
   description: |
     <strong>LEGAL NOTICE: Use of this software package is subject to the
     software license agreement (as set forth above, in the license section of

daal4py/README.md

@@ -14,7 +14,7 @@
   ~ limitations under the License.
 -->
 
-# daal4py - A Convenient Python API to the Intel(R) oneAPI Data Analytics Library
+# daal4py - A Convenient Python API to the oneAPI Data Analytics Library
 [![Build Status](https://dev.azure.com/daal/daal4py/_apis/build/status/CI?branchName=main)](https://dev.azure.com/daal/daal4py/_build/latest?definitionId=9&branchName=main)
 [![Coverity Scan Build Status](https://scan.coverity.com/projects/21716/badge.svg)](https://scan.coverity.com/projects/daal4py)
 [![Join the community on GitHub Discussions](https://badgen.net/badge/join%20the%20discussion/on%20github/black?icon=github)](https://github.com/IntelPython/daal4py/discussions)
@@ -23,9 +23,9 @@
 
 **IMPORTANT NOTICE**: `daal4py` has been merged into `scikit-learn-intelex`. As of version 2025.0, it is distributed as an additional importable module within the package `scikit-learn-intelex` instead of being a separate package. The last standalone release of `daal4py` was version 2024.7, and this standalone package will not receive further updates.
 
-A simplified API to Intel(R) oneAPI Data Analytics Library that allows for fast usage of the framework suited for Data Scientists or Machine Learning users.  Built to help provide an abstraction to Intel(R) oneAPI Data Analytics Library for either direct usage or integration into one's own framework.
+A simplified API to oneAPI Data Analytics Library that allows for fast usage of the framework suited for Data Scientists or Machine Learning users.  Built to help provide an abstraction to oneAPI Data Analytics Library for either direct usage or integration into one's own framework.
 
-Note: For the most part, `daal4py` is used as an internal backend within the Intel(R) Scikit-Learn extension, and it is highly recommended to use `sklearnex` instead. Nevertheless, some functionalities from `daal4py` can still be of use, and the module can still be imported directly (`import daal4py`) after installing `scikit-learn-intelex`.
+Note: For the most part, `daal4py` is used as an internal backend within the Scikit-Learn extension, and it is highly recommended to use `sklearnex` instead. Nevertheless, some functionalities from `daal4py` can still be of use, and the module can still be imported directly (`import daal4py`) after installing `scikit-learn-intelex`.
 
 ## 👀 Follow us on Medium
 
@@ -43,7 +43,7 @@ We publish blogs on Medium, so [follow us](https://medium.com/intel-analytics-so
 - [Documentation](https://intelpython.github.io/daal4py/)
 - [scikit-learn API and patching](https://intelpython.github.io/daal4py/sklearn.html#sklearn)
 - [Building from Sources](https://github.com/uxlfoundation/scikit-learn-intelex/blob/main/daal4py/INSTALL.md)
-- [About Intel(R) oneAPI Data Analytics Library](https://github.com/uxlfoundation/oneDAL)
+- [About oneAPI Data Analytics Library](https://github.com/uxlfoundation/oneDAL)
 
 ## 💬 Support
 
@@ -78,12 +78,12 @@ pip install -U mpi4py impi_rt
 ```
 
 ```shell
-# Anaconda Cloud for dpcpp
+# conda for dpcpp
 conda install dpcpp_cpp_rt dpctl -c https://software.repos.intel.com/python/conda/
 ```
 
 ```shell
-# Anaconda Cloud for MPI
+# conda for MPI
 conda install mpi4py impi_rt -c https://software.repos.intel.com/python/conda/
 ```
 
@@ -92,4 +92,4 @@ conda install mpi4py impi_rt -c https://software.repos.intel.com/python/conda/
 
 # ⚠️ Scikit-learn patching
 
-Scikit-learn patching functionality in daal4py was deprecated and moved to a separate package - [Intel(R) Extension for Scikit-learn*](https://github.com/uxlfoundation/scikit-learn-intelex). All future updates for the patching will be available in Intel(R) Extension for Scikit-learn only. Please use the package instead of daal4py for the Scikit-learn acceleration.
+Scikit-learn patching functionality in daal4py was deprecated and moved to a separate package - [Extension for Scikit-learn*](https://github.com/uxlfoundation/scikit-learn-intelex). All future updates for the patching will be available in Extension for Scikit-learn only. Please use the package instead of daal4py for the Scikit-learn acceleration.

daal4py/__main__.py

@@ -27,7 +27,7 @@ def _main():
         description="""
             Run your Python script with Intel(R) Distribution for
             Python* patches of scikit-learn, optimizing solvers of
-            scikit-learn with Intel(R) oneAPI Data Analytics Library.
+            scikit-learn with oneAPI Data Analytics Library.
             """,
         formatter_class=argparse.ArgumentDefaultsHelpFormatter,
     )

daal4py/sklearn/_n_jobs_support.py

@@ -82,7 +82,7 @@ def n_jobs_wrapper(self, *args, **kwargs):
         if not isinstance(threading.current_thread(), threading._MainThread):
             warn(
                 "'Threading' parallel backend is not supported by "
-                "Intel(R) Extension for Scikit-learn*. "
+                "Extension for Scikit-learn*. "
                 "Falling back to usage of all available threads."
             )
             result = method(self, *args, **kwargs)