Merge branch 'unifyai:main' into max_pool3d

.devcontainer/build_multiversion/devcontainer.json

@@ -9,7 +9,7 @@
 		"dockerfile": "../../docker/DockerfileMultiversion",
 		"context": "../..",
       "args": {
-    "fw": ["numpy/1.24.2  tensorflow/2.11.0 tensorflow/2.12.0 jax/0.4.10 jax/0.4.8"]
+    "fw": ["numpy/1.24.2 tensorflow/2.11.0 tensorflow/2.12.0 jax/0.4.10 jax/0.4.8"]
 
   }
 	},

.pre-commit-config.yaml

@@ -26,6 +26,6 @@ repos:
         # Exclude everything in frontends except __init__.py, and func_wrapper.py
         exclude: 'ivy/functional/(frontends|backends)/(?!.*/func_wrapper\.py$).*(?!__init__\.py$)'
   - repo: https://github.com/unifyai/lint-hook
-    rev: 27646397c5390f644a645f439535b1061b9c0105
+    rev: 2ea80bc854c7f74b09620151028579083ff92ec2
     hooks:
       - id: ivy-lint

docker/DockerfileMultiversion

@@ -1,9 +1,6 @@
 FROM debian:buster
 WORKDIR /ivy
 
-
-
-
 ARG fw
 ARG pycon=3.8.10
 # Install miniconda
@@ -29,6 +26,7 @@ RUN apt-get update && \
     apt-get install -y rsync && \
     apt-get install -y libusb-1.0-0 && \
     apt-get install -y libglib2.0-0 && \
+    pip3 install pip-autoremove && \
     pip3 install --upgrade pip && \
     pip3 install setuptools==58.5.3
 
@@ -42,10 +40,15 @@ RUN git clone --progress --recurse-submodules https://github.com/unifyai/ivy --d
 
 COPY /docker/multiversion_framework_directory.py .
 COPY /docker/requirement_mappings_multiversion.json .
+COPY /docker/multiversion_testing_requirements.txt .
 
 # requirement mappings directs which dependency to be installed and where
 SHELL ["/bin/bash", "-c"]
-RUN python3 multiversion_framework_directory.py  $fw
+RUN python3 multiversion_framework_directory.py  $fw && \
+    pip install -r multiversion_testing_requirements.txt && \
+    pip-autoremove torch -y && \
+    pip-autoremove tensorflow -y && \
+    pip-autoremove jax -y
 
 
 ENV PATH=/opt/miniconda/envs/multienv/bin:$PATH

docker/multiversion_framework_directory.py

@@ -46,9 +46,7 @@ def install_deps(pkgs, path_to_json, base="/opt/fw/"):
         # check to see if this pkg has specific version dependencies
         with open(path_to_json, "r") as file:
             json_data = json.load(file)
-            print(json_data.keys())
             for keys in json_data[fw]:
-                print(keys, "here")
                 # check if key is dict
                 if isinstance(keys, dict):
                     # this is a dep with just one key
@@ -70,7 +68,8 @@ def install_deps(pkgs, path_to_json, base="/opt/fw/"):
                         )
                 else:
                     subprocess.run(
-                        f"pip3 install  {keys} --target"
+                        "pip3 install "
+                        f" {keys} {f'-f https://data.pyg.org/whl/torch-{ver}%2Bcpu.html' if keys=='torch-scatter' else ''} --target"
                         f" {path} --default-timeout=100   --no-cache-dir",
                         shell=True,
                     )
@@ -79,8 +78,9 @@ def install_deps(pkgs, path_to_json, base="/opt/fw/"):
 if __name__ == "__main__":
     arg_lis = sys.argv
 
-    json_path = (  # path to the json file storing version specific deps
-        "requirement_mappings_multiversion.json"
+    json_path = os.path.join(  # path to the json file storing version specific deps
+        os.path.dirname(os.path.realpath(sys.argv[0])),
+        "requirement_mappings_multiversion.json",
     )
 
     directory_generator(arg_lis[1:])

docker/multiversion_testing_requirements.txt

@@ -6,10 +6,7 @@ pymongo==4.3.3
 redis==4.3.4
 matplotlib==3.5.2
 opencv-python==4.6.0.66 # mod_name=cv2
-tensorflow-probability==0.17.0 # mod_name=tensorflow_probability
-functorch==0.1.1
 scipy==1.8.1
-dm-haiku==0.0.6 # mod_name=haiku
 pydriller
 tqdm
 coverage
@@ -20,4 +17,16 @@ colorama
 packaging
 nvidia-ml-py<=11.495.46 # mod_name=pynvml
 paddle-bfloat
-jsonpickle
+jsonpickle
+ml_dtypes
+diskcache
+google-auth # mod_name=google.auth
+requests
+pyvis
+dill
+scikit-learn # mod_name=sklearn
+pandas
+pyspark
+autoflake # for backend generation
+snakeviz # for profiling
+cryptography

docker/requirement_mappings_multiversion.json

@@ -1,7 +1,7 @@
 
 {
     "tensorflow": [
-        "tensorflow-probability"
+        {"tensorflow-probability":{"2.12.0":"0.20.0","2.11.0":"0.19.0"}}
     ],
     "jax": ["dm-haiku", "flax",{"jaxlib": {"0.4.10": "0.4.10","0.4.8": "0.4.7"}}],
     "numpy": ["numpy"],

docs/index.rst

@@ -20,7 +20,6 @@
   :caption: Users
 
   overview/background.rst
-  overview/design.rst
   overview/related_work.rst
   overview/extensions.rst
 
@@ -30,8 +29,9 @@
   :maxdepth: -1
   :caption: Contributors
 
-  overview/deep_dive.rst
+  overview/design.rst
   overview/contributing.rst
+  overview/deep_dive.rst
 
 
 .. toctree::

docs/overview/contributing/the_basics.rst

@@ -67,7 +67,7 @@ c. Comment on the ToDo list issue with a reference to your new issue like so:
    At some point after your comment is made, your issue will automatically be added to the ToDo list and the comment will be deleted.
    No need to wait for this to happen before progressing to the next stage. Don’t comment anything else on these ToDo issues, which should be kept clean with comments only as described above.
 
-d. Start working on the task, and create a PR as soon as you have a full or partial solution, and then directly reference the issue in the pull request by adding the following content to the description of the PR:
+d. Start working on the task, and open a PR as soon as you have a full or partial solution, when you open the PR make sure to follow the `conventional commits format <https://www.conventionalcommits.org/en/v1.0.0/>`_, and then directly reference the issue in the pull request by adding the following content to the description of the PR:
 
    :code:`Close #Issue_number`
 
@@ -532,7 +532,7 @@ with PyCharm
         1. Click the gutter at the executable line of code where you want to set the breakpoint or place the caret at the line and press :code:`Ctrl+F8`
 
         .. image:: https://github.com/unifyai/unifyai.github.io/blob/main/img/externally_linked/contributing/the_basics/getting_most_out_of_IDE/adding_breakpoint.png?raw=true
-           :aligh: center
+           :align: center
 
     2. Enter into the debug mode:
         1. Click on Run icon and Select **Debug test** or press :code:`Shift+F9`.
@@ -577,10 +577,11 @@ with PyCharm
             1. Select the breakpoint-fragment of code, press :code:`Alt+shift+E` Start debugging!
 
             .. image:: https://github.com/unifyai/unifyai.github.io/blob/main/img/externally_linked/contributing/the_basics/getting_most_out_of_IDE/console_coding.png?raw=true
-               :aligh: center
+               :align: center
+
 
     5. Using **try-except**:
-        1. PyChram is great at pointing the lines of code which are causing tests to fail.
+        1. PyCharm is great at pointing the lines of code which are causing tests to fail.
            Navigating to that line, you can add Try-Except block with breakpoints to get in depth understanding of the errors.
 
         .. image:: https://github.com/unifyai/unifyai.github.io/blob/main/img/externally_linked/contributing/the_basics/getting_most_out_of_IDE/try_except.png?raw=true

docs/overview/deep_dive/array_api_tests.rst

@@ -35,10 +35,10 @@ Instead, the change must be made to the array-api repository directly and then o
         # to initialise local config file and fetch + checkout submodule (not needed everytime)
         git submodule update --init --recursive
 
-        # pulls changes from upstream remote repo and merges them
+        # pulls changes from the upstream remote repo and merges them
         git submodule update --recursive --remote --merge
 
-Sometimes you will face strange behaviour when staging changes from Ivy main repo which includes submodule updates.
+Sometimes you will face strange behaviour when staging changes from Ivy's main repo which includes submodule updates.
 And this is being caused by your submodule being out of date because we update the submodule iteratively. You can get around this by running the following command:
 
 .. code-block:: none
@@ -71,7 +71,7 @@ Using the terminal, you can run all array-api tests in a given file for a certai
         # /ivy
         /bin/bash -e ./run_tests_CLI/test_array_api.sh jax test_linalg
 
-You can change the argument with any of our supported frameworks - tensorflow, numpy, torch or jax - and the individual test function categories in :code:`ivy/ivy_tests/array_api_testing/test_array_api/array_api_tests`, e.g. *test_set_functions*, *test_signatures* etc.
+You can change the argument with any of our supported frameworks - tensorflow, numpy, torch, or jax - and the individual test function categories in :code:`ivy/ivy_tests/array_api_testing/test_array_api/array_api_tests`, e.g. *test_set_functions*, *test_signatures* etc.
 
 You can also run a specific test, as often running *all* tests in a file is excessive.
 To make this work, you should set the backend explicitly in the `_array_module.py` file, which you can find in the `array_api_tests` submodule.
@@ -160,7 +160,7 @@ You may also need to include the hypothesis import of `reproduce_failure` as sho
 
 The test should then include the inputs which led to the previous failure and recreate it.
 If you are taking the :code:`@reproduce_failure` decorator from a CI stack trace and trying to reproduce it locally, you may find that sometimes the local test unexpectedly passes.
-This is usually caused by a discrepancy in your local source code and ivy-main, so try pulling from main to sync the behaviour.
+This is usually caused by a discrepancy in your local source code and ivy-main, so try pulling from the main to sync the behaviour.
 
 Test Skipping
 -------------

docs/overview/deep_dive/arrays.rst

@@ -25,7 +25,7 @@ Arrays
 .. _`wrapped logic`: https://github.com/unifyai/ivy/blob/6a729004c5e0db966412b00aa2fce174482da7dd/ivy/func_wrapper.py#L95
 .. _`NumPy's`: https://numpy.org/doc/stable/user/basics.dispatch.html#basics-dispatch
 .. _`PyTorch's`: https://pytorch.org/docs/stable/notes/extending.html#extending-torch
-There are two types of array in Ivy, there is the :class:`ivy.NativeArray` and also the :class:`ivy.Array`.
+There are two types of arrays in Ivy, there is the :class:`ivy.NativeArray` and also the :class:`ivy.Array`.
 
 Native Array
 ------------
@@ -44,7 +44,7 @@ All functions in the Ivy functional API which accept *at least one array argumen
 The only exceptions to this are functions in the `nest <https://github.com/unifyai/ivy/blob/906ddebd9b371e7ae414cdd9b4bf174fd860efc0/ivy/functional/ivy/nest.py>`_ module and the `meta <https://github.com/unifyai/ivy/blob/906ddebd9b371e7ae414cdd9b4bf174fd860efc0/ivy/functional/ivy/meta.py>`_ module, which have no instance method implementations.
 
 The organization of these instance methods follows the same organizational structure as the files in the functional API.
-The :class:`ivy.Array` class `inherits`_ from many category-specific array classes, such as `ArrayWithElementwise`_, each of which implement the category-specific instance methods.
+The :class:`ivy.Array` class `inherits`_ from many category-specific array classes, such as `ArrayWithElementwise`_, each of which implements the category-specific instance methods.
 
 Each instance method simply calls the functional API function internally, but passes in :code:`self._data` as the first *array* argument.
 `ivy.Array.add`_ is a good example.

docs/overview/deep_dive/backend_setting.rst

@@ -51,7 +51,7 @@ It's helpful to look at an example:
 
 In the last example above, the moment any backend is set, it will be used over the `implicit_backend`_.
 However when the current backend is set to the previous using the :func:`ivy.previous_backend`, the `implicit_backend`_ will be used as a fallback, which will assume the backend from the last run.
-While the `implicit_backend`_ functionality gives more freedom to the user, the recommended way of doing things would be set the backend explicitly.
+While the `implicit_backend`_ functionality gives more freedom to the user, the recommended way of doing things would be to set the backend explicitly.
 In addition, all the previously set backends can be cleared by calling :func:`ivy.unset_backend`.
 
 Dynamic Backend Setting

docs/overview/deep_dive/building_the_docs_pipline.rst

@@ -84,7 +84,7 @@ To build the docs through docker you use this command:
 
     docker run -v /path/to/project:/project unifyai/doc-builder
 
-You can as well add options described in the :ref:`The convenience script` section.
+You can also add options described in the :ref:`The convenience script` section.
 
 .. code-block:: bash
     
@@ -94,7 +94,7 @@ How Ivy's docs is structured
 -----------------------------
 
 Looking at `Ivy docs <https://github.com/unifyai/ivy/tree/main/docs>`_, we can see
-that it structured like this:
+that it is structured like this:
 
 .. code-block:: bash
 
@@ -148,7 +148,7 @@ Here is a segment of the file:
 
 You can see here different reStructuredText directives. The first one is ``include``,
 which simply includes the main README file of the project, this is a good place if you
-want to make the rendered docs looks different from the README, or simply include it as
+want to make the rendered docs look different from the README, or simply include it as
 is.
 
 The second directive is ``toctree``, which is used to create a table of contents. The
@@ -167,15 +167,15 @@ The last directive is ``autosummary``, which is used to automatically generate a
 of contents for a module, as well as the documentation itself automatically by
 discovering the docstrings of the module. This is a custom directive, built on the original
 `autosummary`_
-extension. We will explain in details how did we change it, in :ref:`Custom Extensions`.
+extension. We will explain in detail how did we change it, in :ref:`Custom Extensions`.
 
 ``partial_conf.py``
 ~~~~~~~~~~~~~~~~~~~
 
 This is a partial `Sphinx configuration file`_. Which is being imported in the 
 `conf.py <https://github.com/unifyai/doc-builder/blob/main/docs/conf.py#L150>`_,
 it's used to customize options that are specific to the project being documented.
-While importing common configuration such as the theme, the extensions, etc in the 
+While importing common configurations such as the theme, the extensions, etc in the 
 original ``conf.py``.
 
 This is a part of ``partial_conf.py``:
@@ -202,7 +202,7 @@ customize the title of the table of contents for each module.
 This is an optional file, which is executed before the docs are built. This is useful
 if you need to install some dependencies for the docs to build. In Ivy's case, we 
 install ``torch`` then ``torch-scatter`` sequentially to avoid a bug in 
-``torch-scatter``'s setup. And if we want to do any changes to the docker container
+``torch-scatter``'s setup. And if we want to make any changes to the docker container
 before building the docs.
 
 Custom Extensions
@@ -222,7 +222,7 @@ This extension is a modified version of the original `autosummary`_, which is us
 discover and automatically document the docstrings of a module. This is done by
 generating "stub" rst files for each module listed in the ``autosummary`` directive,
 you can add a template for these stub files using the ``:template:`` option. Which can
-inturn include the ``autosummary`` directive again, recursing on the whole module.
+in turn include the ``autosummary`` directive again, recursing on the whole module.
 
 Unfortunately, the original ``autosummary`` extension is very limited, forcing you to
 have a table of contents for each modules.
@@ -233,9 +233,9 @@ We'll go through each option or configuration value added to the original ``auto
 """"""""""""""""
 
 As the name suggests, the original behavior of ``autosummary`` is to generate a table
-of contents for each module. And it generate stub files only if ``:toctree:`` option is
+of contents for each module. And it generates stub files only if the ``:toctree:`` option is
 specified. As we only need the ``toctree`` this option hides the table of contents, but
-it require the ``:toctree:`` option to be specified.
+it requires the ``:toctree:`` option to be specified.
 
 ``discussion_linker``
 ~~~~~~~~~~~~~~~~~~~~~
@@ -250,7 +250,7 @@ The directive is included like this:
     .. discussion-links:: module.foo
 
 
-First it will look for ``discussion_channel_map`` configuration, in Ivy it looks like 
+First it will look for the ``discussion_channel_map`` configuration, in Ivy it looks like 
 this:
 
 .. code-block:: python
@@ -264,7 +264,7 @@ this:
 
 The key is the module name, if it's not found the ``discussion-link`` directive will
 render an empty node. The first and only value in the list is the channel id of the 
-module, it is in a list as we used to have forums as will but they are removed now.
+module, it is in a list as we used to have forums as well but they are removed now.
 
 The output string is generated by a series of replaces on template strings, which are
 customizable using the config. To understand how it works, let's look at the default
@@ -350,8 +350,8 @@ in ``ivy.functional.ivy``, it will replace the module to ``ivy.`` instead of
 
 It's used instead of simply using ``ivy.<data atribute>`` because data attributes have
 no ``__doc__`` atribute, instead docs are discovered by parsing the source code itself.
-So for Sphinx to find the required docs, it need to be supplied the full module name,
-then using ``autoivydata`` directive will replace the module name to ``ivy.``.
+So for Sphinx to find the required docs, it needs to be supplied the full module name,
+then using the ``autoivydata`` directive will replace the module name to ``ivy.``.
 
 Please refer to the `auto documenter guide in sphinx documentation 
 <https://www.sphinx-doc.org/en/master/development/tutorials/autodoc_ext.html>`_ for more