[ENH] Make deep clustering consisting with other deep learning submodules in terms of saving/loading #6524

	name: PR Examples

	on:
	push:
	branches:
	- main
	pull_request:
	branches:
	- main
	paths:
	- "examples/**"
	- "aeon/**"
	- ".github/workflows/**"
	- "pyproject.toml"

	concurrency:
	group: ${{ github.workflow }}-${{ github.head_ref \|\| github.ref }}
	cancel-in-progress: true

	jobs:
	run-notebook-examples:
	runs-on: ubuntu-22.04

	steps:
	- name: Checkout
	uses: actions/checkout@v4

	- name: Setup Python 3.10
	uses: actions/setup-python@v5
	with:
	python-version: "3.10"

	- if: ${{ github.event_name == 'pull_request' && !contains(github.event.pull_request.labels.*.name, 'no numba cache') }}
	name: Restore numba cache
	uses: ./.github/actions/numba_cache
	with:
	cache_name: "run-notebook-examples"
	runner_os: ${{ runner.os }}
	python_version: "3.10"

	- name: Install aeon and dependencies
	uses: nick-fields/retry@v3
	with:
	timeout_minutes: 30
	max_attempts: 3
	command: python -m pip install .[all_extras,binder,dev]

	- name: Run example notebooks
	run: .github/utilities/run_examples.sh ${{ github.event_name != 'pull_request' \|\| !contains(github.event.pull_request.labels.*.name, 'full examples run') }}
	shell: bash

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