Prepare for an update to the XNNPACK submodule (#72642)

Summary:
- Target Sha1: ae108ef49aa5623b896fc93d4298c49d1750d9ba
- Make USE_XNNPACK a dependent option on cmake minimum version 3.12
- Print USE_XNNPACK under cmake options summary, and print the
  availability from collet_env.py
- Skip XNNPACK based tests when XNNPACK is not available
    - Add SkipIfNoXNNPACK wrapper to skip tests
- Update cmake version for xenial-py3.7-gcc5.4 image to 3.12.4
    - This is required for the backwards compatibility test.
      The PyTorch op schema is XNNPACK dependent. See,
      aten/src/ATen/native/xnnpack/RegisterOpContextClass.cpp for
      example. The nightly version is assumed to have USE_XNNPACK=ON,
      so with this change we ensure that the test build can also
      have XNNPACK.
- HACK: skipping test_xnnpack_integration tests on ROCM

Pull Request resolved: https://github.com/pytorch/pytorch/pull/72642

Reviewed By: kimishpatel

Differential Revision: D34456794

Pulled By: digantdesai

fbshipit-source-id: 85dbfe0211de7846d8a84321b14fdb061cd6c037
(cherry picked from commit 6cf48e7b64d6979962d701b5d493998262cc8bfa)

test/test_xnnpack_integration.py

@@ -53,7 +53,6 @@ class TestXNNPACKOps(TestCase):
         output_linearprepacked = torch.ops.prepacked.linear_clamp_run(input_data, packed_weight_bias)
         torch.testing.assert_close(ref_result, output_linearprepacked, rtol=1e-2, atol=1e-3)
 
-
     @given(batch_size=st.integers(0, 3),
            input_channels_per_group=st.integers(1, 32),
            height=st.integers(5, 64),