feat: add support for int8 quantization on linear layers

[pommedeterresautee]

Fix #288

• add int8 matmul + scalers support
• update PyTorch to last available (post branch cut)
• update triton to 2.0 (requires to rework some kernels)

test pass

================================================== warnings summary ==================================================
test/test_model_optimization.py: 1 warning
test/test_torchdynamo.py: 79 warnings
  /home/geantvert/.local/share/virtualenvs/kernl/lib/python3.9/site-packages/torch/cuda/graphs.py:79: UserWarning: The CUDA Graph is empty. This ususally means that the graph was attempted to be captured on wrong device or stream. (Triggered internally at ../aten/src/ATen/cuda/CUDAGraph.cpp:191.)
    super().capture_end()

test/debugger/test_memory.py::test_load_is_in_different_memory
  /mnt/workspace/kernl/test/debugger/test_memory.py:58: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly.  To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()
    assert t.storage().data_ptr() != a.storage().data_ptr()

-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
============================= 2885 passed, 3 skipped, 81 warnings in 10684.37s (2:58:04) =============================