move to extras

Author: makslevental

.github/workflows/sdist.yml

@@ -103,6 +103,8 @@ jobs:
     steps:
       - name: Checkout
         uses: actions/checkout@v2
+        with:
+          sparse-checkout: examples/mlir_python_extras.ipynb
 
       - name: Setup Python
         uses: actions/setup-python@v4
@@ -116,7 +118,7 @@ jobs:
           pip install jupyter
           sed -i.bak 's/OUTPUT_TIMEOUT = 10/OUTPUT_TIMEOUT = 100/g' \
             $(python -c 'import site; print(site.getsitepackages()[0])')/jupyter_client/runapp.py
-          BRANCH=${{ github.ref_name }} jupyter run examples/mlir_python_utils.ipynb
+          BRANCH=${{ github.ref_name }} jupyter run examples/mlir_python_extras.ipynb
 
   mlir-bindings-aarch64:
 

.github/workflows/test.yml

@@ -22,7 +22,7 @@ jobs:
 
       - uses: actions/upload-artifact@v3
         with:
-          path: ./wheelhouse/mlir_python_utils*.whl
+          path: ./wheelhouse/mlir_python_extras*.whl
 
   build_sdist:
     name: Build source distribution

.github/workflows/test_pypi.yml

@@ -1,4 +1,4 @@
-# mlir-python-utils
+# mlir-python-extras
 
 The missing pieces (as far as boilerplate reduction goes) of the MLIR python bindings.
 
@@ -77,7 +77,7 @@ The few main features/affordances:
 1. `region_op`s (like `@func` above)
    \
     
-   1. These are decorators around ops (bindings for MLIR operations) that have regions (e.g., [in_parallel](https://github.com/makslevental/mlir-python-utils/blob/a9885db18096a610d29a26293396d860d40ad213/mlir_utils/dialects/ext/scf.py#L185)). 
+   1. These are decorators around ops (bindings for MLIR operations) that have regions (e.g., [in_parallel](https://github.com/makslevental/mlir-python-extras/blob/a9885db18096a610d29a26293396d860d40ad213/mlir_extras/dialects/ext/scf.py#L185)). 
    They turn decorated functions, by executing them "eagerly", into an instance of such an op, e.g., 
       ```python
       @func
@@ -87,7 +87,7 @@ The few main features/affordances:
       becomes `func.func @foo(%arg0: i32) { }`; if the region carrying op produces a result, the identifier for the python function (`foo`) becomes the corresponding `ir.Value` of the result (if the op doesn't produce a result then the identifier becomes the corresponding `ir.OpView`).
       \
       \
-      See [mlir_utils.util.op_region_builder](https://github.com/makslevental/mlir-python-utils/blob/a9885db18096a610d29a26293396d860d40ad213/mlir_utils/util.py#L123) for details.
+      See [mlir_extras.util.op_region_builder](https://github.com/makslevental/mlir-python-extras/blob/a9885db18096a610d29a26293396d860d40ad213/mlir_extras/util.py#L123) for details.
       \
        
 2. `@canonicalize` (like `@canonicalize(using=scf)` above)
@@ -96,16 +96,16 @@ The few main features/affordances:
    1. These are decorators that **rewrite the python AST**. They transform a select few forms (basically only `if`s) into a more "canonical" form, in order to more easily map to MLIR. If that scares you, fear not; they are not essential and all target MLIR can still be mapped to without using them (by using the slightly more verbose `region_op`).
       \
       \
-      See [mlir_utils.ast.canonicalize](https://github.com/makslevental/mlir-python-utils/blob/a9885db18096a610d29a26293396d860d40ad213/mlir_utils/ast/canonicalize.py) for details.
+      See [mlir_extras.ast.canonicalize](https://github.com/makslevental/mlir-python-extras/blob/a9885db18096a610d29a26293396d860d40ad213/mlir_extras/ast/canonicalize.py) for details.
       \
        
-3. `mlir_utils.types` (like `T.memref(K, K, T.i64)` above)
+3. `mlir_extras.types` (like `T.memref(K, K, T.i64)` above)
    \
     
-   1. These are just convenient wrappers around upstream type constructors. Note, because MLIR types are uniqued to a `ir.Context`, these are all actually functions that return the type (yes, even `T.i64`, which uses [`__getattr__` on the module](https://github.com/makslevental/mlir-python-utils/blob/2ca62e9c1540b1624c302bc9efb4666ff5d1c133/mlir_utils/types.py#L98)).
+   1. These are just convenient wrappers around upstream type constructors. Note, because MLIR types are uniqued to a `ir.Context`, these are all actually functions that return the type (yes, even `T.i64`, which uses [`__getattr__` on the module](https://github.com/makslevental/mlir-python-extras/blob/2ca62e9c1540b1624c302bc9efb4666ff5d1c133/mlir_extras/types.py#L98)).
       \
       \
-      See [mlir_utils.types](https://github.com/makslevental/mlir-python-utils/blob/a9885db18096a610d29a26293396d860d40ad213/mlir_utils/types.py) for details.
+      See [mlir_extras.types](https://github.com/makslevental/mlir-python-extras/blob/a9885db18096a610d29a26293396d860d40ad213/mlir_extras/types.py) for details.
       \
        
 4. `Pipeline()`
@@ -114,8 +114,8 @@ The few main features/affordances:
    1. This is just a (generated) wrapper around available **upstream** passes; it can be used to build pass pipelines (by `str(Pipeline())`). It is mainly convenient with IDEs/editors that will tab-complete the available methods on the `Pipeline` class (which correspond to passes), Note, if your host bindings don't register some upstream passes, then this will generate "illegal" pass pipelines.
       \
       \
-      See [mlir_utils._configuration.generate_pass_pipeline.py](https://github.com/makslevental/mlir-python-utils/blob/a9885db18096a610d29a26293396d860d40ad213/mlir_utils/_configuration/generate_pass_pipeline.py) for details on generation
-      [mlir_utils.runtime.passes.py](https://github.com/makslevental/mlir-python-utils/blob/a9885db18096a610d29a26293396d860d40ad213/mlir_utils/runtime/passes.py#L80) for the passes themselves.
+      See [mlir_extras._configuration.generate_pass_pipeline.py](https://github.com/makslevental/mlir-python-extras/blob/a9885db18096a610d29a26293396d860d40ad213/mlir_extras/_configuration/generate_pass_pipeline.py) for details on generation
+      [mlir_extras.runtime.passes.py](https://github.com/makslevental/mlir-python-extras/blob/a9885db18096a610d29a26293396d860d40ad213/mlir_extras/runtime/passes.py#L80) for the passes themselves.
       \
        
 
@@ -133,7 +133,7 @@ Practically speaking that means you need to have *some* package installed that i
 So
 
 ```shell
-$ YOUR_HOST_MLIR_PYTHON_PACKAGE_PREFIX=<YOUR_HOST_MLIR_PYTHON_PACKAGE_PREFIX> pip install git+https://github.com/makslevental/mlir-python-utils
+$ YOUR_HOST_MLIR_PYTHON_PACKAGE_PREFIX=<YOUR_HOST_MLIR_PYTHON_PACKAGE_PREFIX> pip install git+https://github.com/makslevental/mlir-python-extras
 ```
 
 where `YOUR_HOST_MLIR_PYTHON_PACKAGE_PREFIX` is (as it says) the package prefix for your chosen host bindings.
@@ -148,7 +148,7 @@ $ pip install mlir-python-bindings -f https://makslevental.github.io/wheels/
 and then
 
 ```shell
-$ pip install git+https://github.com/makslevental/mlir-python-utils
+$ pip install git+https://github.com/makslevental/mlir-python-extras
 ```
 
 ## Examples/Demo