add learnablefakequantize to pt2e flow #3825

	name: Run 1xL4 Tests

	on:
	push:
	branches:
	- main
	- 'gh/**'
	pull_request:
	branches:
	- main
	- 'gh/**'

	concurrency:
	group: 1xL4_tests-${{ github.workflow }}-${{ github.ref == 'refs/heads/main' && github.run_number \|\| github.ref }}
	cancel-in-progress: true

	env:
	HF_TOKEN: ${{ secrets.HF_TOKEN }}

	jobs:
	test:
	strategy:
	fail-fast: false
	matrix:
	include:
	- name: SM-89
	runs-on: linux.g6.4xlarge.experimental.nvidia.gpu
	torch-spec: '--pre torch --index-url https://download.pytorch.org/whl/nightly/cu126'
	gpu-arch-type: "cuda"
	gpu-arch-version: "12.6"
	permissions:
	id-token: write
	contents: read
	uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
	with:
	timeout: 60
	runner: ${{ matrix.runs-on }}
	gpu-arch-type: ${{ matrix.gpu-arch-type }}
	gpu-arch-version: ${{ matrix.gpu-arch-version }}
	submodules: recursive
	script: \|
	conda create -n venv python=3.10 -y
	conda activate venv
	export PATH=/opt/rh/devtoolset-10/root/usr/bin/:$PATH
	python -m pip install --upgrade pip
	pip install uv
	pip install ${{ matrix.torch-spec }}
	uv pip install -r dev-requirements.txt
	pip install .
	pytest test/integration --verbose -s
	pytest test/dtypes/test_affine_quantized_float.py --verbose -s
	./test/float8/test_everything_single_gpu.sh
	python test/quantization/quantize_/workflows/float8/test_float8_tensor.py

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