Update docs and samples to use latest iree-turbine. (iree-org#19054)

This adapts docs and samples to
https://github.com/iree-org/iree-turbine/releases/tag/v2.5.0.

* Switched from `import shark_turbine.aot as aot` to `import
iree.turbine.aot as aot` (see also
iree-org/iree-turbine#28).
* Redirected notes from `/RELEASING.md` to
https://github.com/iree-org/iree-turbine/blob/main/docs/releasing.md.
The release process is changing now with
iree-org#18938 and I'll want to fold the
notes there in to
https://iree.dev/developers/general/release-management/ instead.
* Re-ran some Colab notebooks and adapted to the latest changes across
projects. Note that the
https://github.com/iree-org/iree/tree/main/samples/dynamic_shapes sample
still has code using `@aot.jittable`, so I have re-opened
iree-org#18564 to migrate it. I spent
some time trying to update it but wasn't sure how to demonstrate dynamic
shapes using the "modern canonical usage" effectively.
* This fixes the recent test failures:
https://github.com/iree-org/iree/actions/runs/11697207429/job/32575551934.
Test run:
https://github.com/ScottTodd/iree/actions/runs/11713816651/job/32627295562

Signed-off-by: Giacomo Serafini <179146510+giacs-epic@users.noreply.github.com>

RELEASING.md

@@ -85,8 +85,6 @@ release process:
 * https://pypi.org/project/iree-compiler/
 * https://pypi.org/project/iree-runtime/
 * https://pypi.org/project/iree-turbine/
-* https://pypi.org/project/shark-turbine/ (transitional until switched to
-  iree-turbine)
 * https://pypi.org/project/iree-tools-tf/
 * https://pypi.org/project/iree-tools-tflite/
 
@@ -101,109 +99,7 @@ Deprecated projects no longer updated:
 
 There are presently two build promotion processes documented:
 
-* Old one focused purely on releasing IREE core packages:
-https://iree.dev/developers/general/release-management/
-* New one driven by the Torch frontend and documented below.
-
-The versioning scheme for
-[iree-turbine](https://github.com/iree-org/iree-turbine) is rooted on the
-then-current PyTorch released version, with optional date-based dev/pre-release
-suffixes (i.e. `rcYYYYMMDD` or `devYYYYMMDD`) or intra PyTorch releases
-(i.e. `postVVVV`).
-
-This process is being trialed to correspond with the 2.3.0 release of PyTorch.
-In this scenario, the pinned nightly build of IREE is considered current and
-promoted as part of the Turbine release to PyPI (and the release is marked as
-not pre-release on the GitHub releases page).
-
-Promotions are done roughly monthly or at need. The schedule is shifted to
-account for extra factors as needed.
-
-In the future, we would like to adopt a real versioning scheme (beyond the
-nightly calver+build number scheme) and manage promotion and pinning of the
-core IREE dep more explicitly and in alignment with how downstreams are using
-it.
-
-### Steps to Promote
-
-There are multiple release artifacts that are deployed from this project:
-
-* shark-turbine wheel (transitional while switching to iree-turbine)
-* iree-turbine wheel
-* iree-compiler wheels
-* iree-runtime wheels
-
-Typically we deploy IREE compiler and runtime wheels along with a turbine
-release, effectively promoting a nightly.
-
-#### Building Artifacts
-
-Start with a clean clone of iree-turbine:
-
-```
-cd scratch
-git clone git@github.com:iree-org/iree-turbine.git
-cd iree-turbine
-```
-
-Build a pre-release:
-
-```
-./build_tools/build_release.py --core-version 2.3.0 --core-pre-version=rcYYYYMMDD
-```
-
-Build an official release:
-
-```
-./build_tools/build_release.py --core-version 2.3.0
-```
-
-This will download all deps, including wheels for all supported platforms and
-Python versions for iree-compiler and iree-runtime. All wheels will be placed
-in the `wheelhouse/` directory.
-
-
-#### Testing
-
-TODO: Write a script for this.
-
-```
-python -m venv wheelhouse/test.venv
-source wheelhouse/test.venv/bin/activate
-pip install -f wheelhouse iree-turbine[testing]
-# Temp: tests require torchvision.
-pip install -f wheelhouse torchvision
-pytest core/tests
-```
-
-#### Push
-
-From the testing venv, verify that everything is sane:
-
-```
-pip freeze
-```
-
-Push IREE deps (if needed/updated):
-
-```
-twine upload wheelhouse/iree_compiler-* wheelhouse/iree_runtime-*
-```
-
-Push built wheels:
-
-```
-twine upload wheelhouse/iree_turbine-* wheelhouse/shark_turbine-*
-```
-
-#### Install from PyPI and Sanity Check
-
-TODO: Script this
-
-From the testing venv:
-
-```
-pip uninstall -y shark-turbine iree-turbine iree-compiler iree-runtime
-pip install iree-turbine
-pytest core/tests
-```
+* Releasing IREE core packages:
+  https://iree.dev/developers/general/release-management/
+* Releasing iree-turbine packages:
+  https://github.com/iree-org/iree-turbine/blob/main/docs/releasing.md

docs/website/docs/guides/ml-frameworks/pytorch.md

@@ -22,8 +22,8 @@ status: new
 
 ## :octicons-book-16: Overview
 
-[iree-turbine](https://pypi.org/project/iree-turbine/) (rebrand pending from
-"shark-turbine") offers a tight integration between compatible versions of IREE,
+[iree-turbine](https://pypi.org/project/iree-turbine/) offers a tight
+integration between compatible versions of IREE,
 [torch-mlir](https://github.com/llvm/torch-mlir), and
 [PyTorch](https://pytorch.org/).
 
@@ -193,7 +193,7 @@ graph LR
 ```python
 import iree.runtime as ireert
 import numpy as np
-import shark_turbine.aot as aot
+import iree.turbine.aot as aot
 import torch
 
 # Define the `nn.Module` to export.
@@ -264,15 +264,15 @@ graph LR
 ```
 
 Advanced export workflows can use the
-[`aot.CompiledModule`](https://github.com/iree-org/iree-turbine/tree/main/shark_turbine/aot/compiled_module.py)
+[`aot.CompiledModule`](https://github.com/iree-org/iree-turbine/blob/main/iree/turbine/aot/compiled_module.py)
 class to define and constrain the structure of a program prior to compiling it.
 
 <!-- TODO(scotttodd): API reference pages for aot.CompiledModule etc.?
                       https://github.com/iree-org/iree-turbine/issues/77
 -->
 
 ```python
-import shark_turbine.aot as aot
+import iree.turbine.aot as aot
 
 # A minimal program, with no functions or variables.
 class BasicModule(aot.CompiledModule):
@@ -339,7 +339,7 @@ models parameters on disk, so that they can be loaded later during runtime.
 import torch
 from safetensors.torch import save_file
 import numpy as np
-import shark_turbine.aot as aot
+import iree.turbine.aot as aot
 
 class LinearModule(torch.nn.Module):
     def __init__(self, in_features, out_features):