[AARCH64] Fall back to GEMM if mkldnn_matmul fails

[malfet]

• Add call to at::globalContext().userEnabledMkldnn() to apply_mkldnn_matmul_heur
• Surround calls to mkldnn_matmul with try {} catch {}
• Print warning and fall back to BLAS (by calling at::globalContext().setUserEnabledMkldnn()) if mkldnn_matmul() fails

Test plan: On Linux arm run:

$ sudo chmod 400 /sys; python -c "import torch;m=torch.nn.Linear(1, 32);print(torch.__version__);print(m(torch.rand(32, 1)))"
Error in cpuinfo: failed to parse the list of possible processors in /sys/devices/system/cpu/possible
Error in cpuinfo: failed to parse the list of present processors in /sys/devices/system/cpu/present
Error in cpuinfo: failed to parse both lists of possible and present processors
2.3.0.dev20231215
bad err=11 in Xbyak::Error
bad err=11 in Xbyak::Error
/home/ubuntu/miniconda3/envs/py311/lib/python3.11/site-packages/torch/nn/modules/linear.py:116: UserWarning: mkldnn_matmul failed, switching to BLAS gemm:internal error (Triggered internally at /pytorch/aten/src/ATen/native/LinearAlgebra.cpp:1509.)
  return F.linear(input, self.weight, self.bias)
tensor([[-0.5183,  0.2279, -0.4035,  ..., -0.3446,  0.0938, -0.2113],
        [-0.5111,  0.2362, -0.3821,  ..., -0.3536,  0.1011, -0.2159],
        [-0.6387,  0.0894, -0.7619,  ..., -0.1939, -0.0282, -0.1344],
        ...,
        [-0.6352,  0.0934, -0.7516,  ..., -0.1983, -0.0247, -0.1366],
        [-0.4790,  0.2733, -0.2862,  ..., -0.3939,  0.1338, -0.2365],
        [-0.5702,  0.1682, -0.5580,  ..., -0.2796,  0.0412, -0.1782]],
       grad_fn=<AddmmBackward0>)

Fixes #114750

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✅ You can merge normally! (1 Unrelated Failure)

As of commit 4a3390c with merge base 4ea7430 ():

FLAKY - The following job failed but was likely due to flakiness present on trunk:

• pull / linux-focal-py3.8-clang10 / test (dynamo, 2, 7, linux.2xlarge) (gh)
  test_linalg.py::TestLinalgCPU::test_ldl_factor_cpu_complex64

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[lezcano]

Do we test this in CI? If so, can we add a regression test?

[malfet]

@lezcano we can only test it in nightlies, but I will add it later (and do some manual testing right now)

[malfet]

@pytorchbot merge

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[malfet]

@jgong5 FYI, is it safe to assume that mkldnn_matmul should never raise an exception and if it does, it safe to fallback to BLAS GEMM? Also, would be nice to check perf impact (should be near zero as try which do not raise are generally safe)