Repository: pytorch
Issue: ONNX export: Unsupported FX nodes: {'call_function': ['aten._sample_dirichlet.default', 
Labels: module: onnx,triaged,oncall: pt2,module: dynamic shapes,module: dynamo,oncall: export

### 🐛 Describe the bug

Hi,
I tried to export a model with a PowerSpherical distribution (the https://github.com/nicola-decao/power_spherical/blob/master/power_spherical/distributions.py) and would be delighted to receive your support.

```
import torch
from distributions import HypersphericalUniform, MarginalTDistribution, PowerSpherical

class PowerModel(torch.nn.Module):
    def __init__(self):
        super().__init__()
        batch_size = 32
        cloc = torch.randn(batch_size, 3)
        cscale = torch.ones(batch_size)
        self.psher = PowerSpherical(loc=cloc, scale=cscale)

    def forward(self):
        return self.psher.rsample()



exported_program = torch.export.export(PowerModel() , args=())


print(exported_program)

_ = torch.onnx.dynamo_export( exported_program, )
```

I got the following error message
```


(lightning_py310) user1@pc1:/local_data/user1$ python export_pow.py 
Traceback (most recent call last):
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/utils.py", line 1397, in run_node
    return node.target(*args, **kwargs)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/utils/_stats.py", line 20, in wrapper
    return fn(*args, **kwargs)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_subclasses/fake_tensor.py", line 1250, in __torch_dispatch__
    return self.dispatch(func, types, args, kwargs)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_subclasses/fake_tensor.py", line 1487, in dispatch
    op_impl_out = op_impl(self, func, *args, **kwargs)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_subclasses/fake_tensor.py", line 422, in constructors
    r = func(*args, **new_kwargs)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_ops.py", line 448, in __call__
    return self._op(*args, **kwargs or {})
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/fx/experimental/symbolic_shapes.py", line 954, in guard_bool
    r = self.shape_env.evaluate_expr(self.expr, self.hint, fx_node=self.fx_node)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/fx/experimental/symbolic_shapes.py", line 3453, in evaluate_expr
    concrete_val = self.size_hint(orig_expr)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/fx/experimental/symbolic_shapes.py", line 3251, in size_hint
    raise self._make_data_dependent_error(result_expr, expr)
torch.fx.experimental.symbolic_shapes.GuardOnDataDependentSymNode: It appears that you're trying to get a value out of symbolic int/float whose value is data-dependent (and thus we do not know the true value.)  The expression we were trying to evaluate is Eq(32*i0, 0) (unhinted: Eq(32*i0, 0)).  Scroll up to see where each of these data-dependent accesses originally occurred.

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/utils.py", line 1337, in get_fake_value
    return wrap_fake_exception(
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/utils.py", line 916, in wrap_fake_exception
    return fn()
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/utils.py", line 1338, in <lambda>
    lambda: run_node(tx.output, node, args, kwargs, nnmodule)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/utils.py", line 1410, in run_node
    raise RuntimeError(fn_str + str(e)).with_traceback(e.__traceback__) from e
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/utils.py", line 1397, in run_node
    return node.target(*args, **kwargs)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/utils/_stats.py", line 20, in wrapper
    return fn(*args, **kwargs)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_subclasses/fake_tensor.py", line 1250, in __torch_dispatch__
    return self.dispatch(func, types, args, kwargs)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_subclasses/fake_tensor.py", line 1487, in dispatch
    op_impl_out = op_impl(self, func, *args, **kwargs)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_subclasses/fake_tensor.py", line 422, in constructors
    r = func(*args, **new_kwargs)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_ops.py", line 448, in __call__
    return self._op(*args, **kwargs or {})
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/fx/experimental/symbolic_shapes.py", line 954, in guard_bool
    r = self.shape_env.evaluate_expr(self.expr, self.hint, fx_node=self.fx_node)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/fx/experimental/symbolic_shapes.py", line 3453, in evaluate_expr
    concrete_val = self.size_hint(orig_expr)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/fx/experimental/symbolic_shapes.py", line 3251, in size_hint
    raise self._make_data_dependent_error(result_expr, expr)
RuntimeError: Failed running call_function <built-in method empty of type object at 0x7f7a03469a40>(*((32, FakeTensor(..., size=(), dtype=torch.int64)),), **{'device': device(type='cpu'), 'dtype': torch.float32}):
It appears that you're trying to get a value out of symbolic int/float whose value is data-dependent (and thus we do not know the true value.)  The expression we were trying to evaluate is Eq(32*i0, 0) (unhinted: Eq(32*i0, 0)).  Scroll up to see where each of these data-dependent accesses originally occurred.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/local_data/user1/export_pow.py", line 64, in <module>
    exported_program = torch.export.export(PowerModel() , args=())
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/export/__init__.py", line 1018, in export
    return export(f, args, kwargs, constraints)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_export/__init__.py", line 270, in export
    gm_torch_level, _ = torch._dynamo.export(
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py", line 1140, in inner
    result_traced = opt_f(*args, **kwargs)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1527, in _call_impl
    return forward_call(*args, **kwargs)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py", line 328, in _fn
    return fn(*args, **kwargs)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1527, in _call_impl
    return forward_call(*args, **kwargs)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py", line 490, in catch_errors
    return callback(frame, cache_entry, hooks, frame_state)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 133, in _fn
    return fn(*args, **kwargs)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 389, in _convert_frame_assert
    return _compile(
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 569, in _compile
    guarded_code = compile_inner(code, one_graph, hooks, transform)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/utils.py", line 189, in time_wrapper
    r = func(*args, **kwargs)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 491, in compile_inner
    out_code = transform_code_object(code, transform)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/bytecode_transformation.py", line 1028, in transform_code_object
    transformations(instructions, code_options)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 458, in transform
    tracer.run()
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 2069, in run
    super().run()
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 719, in run
    and self.step()
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 683, in step
    getattr(self, inst.opname)(inst)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 392, in wrapper
    return inner_fn(self, inst)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 1110, in CALL_FUNCTION
    self.call_function(fn, args, {})
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 557, in call_function
    self.push(fn.call_function(self, args, kwargs))
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/variables/functions.py", line 307, in call_function
    return super().call_function(tx, args, kwargs)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/variables/functions.py", line 261, in call_function
    return super().call_function(tx, args, kwargs)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/variables/functions.py", line 90, in call_function
    return tx.inline_user_function_return(
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 593, in inline_user_function_return
    result = InliningInstructionTranslator.inline_call(self, fn, args, kwargs)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 2174, in inline_call
    return cls.inline_call_(parent, func, args, kwargs)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 2281, in inline_call_
    tracer.run()
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 719, in run
    and self.step()
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 683, in step
    getattr(self, inst.opname)(inst)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 392, in wrapper
    return inner_fn(self, inst)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 1110, in CALL_FUNCTION
    self.call_function(fn, args, {})
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 557, in call_function
    self.push(fn.call_function(self, args, kwargs))
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/variables/functions.py", line 307, in call_function
    return super().call_function(tx, args, kwargs)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/variables/functions.py", line 261, in call_function
    return super().call_function(tx, args, kwargs)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/variables/functions.py", line 90, in call_function
    return tx.inline_user_function_return(
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 593, in inline_user_function_return
    result = InliningInstructionTranslator.inline_call(self, fn, args, kwargs)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 2174, in inline_call
    return cls.inline_call_(parent, func, args, kwargs)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 2281, in inline_call_
    tracer.run()
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 719, in run
    and self.step()
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 683, in step
    getattr(self, inst.opname)(inst)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 392, in wrapper
    return inner_fn(self, inst)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 1110, in CALL_FUNCTION
    self.call_function(fn, args, {})
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 557, in call_function
    self.push(fn.call_function(self, args, kwargs))
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/variables/functions.py", line 307, in call_function
    return super().call_function(tx, args, kwargs)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/variables/functions.py", line 261, in call_function
    return super().call_function(tx, args, kwargs)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/variables/functions.py", line 90, in call_function
    return tx.inline_user_function_return(
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 593, in inline_user_function_return
    result = InliningInstructionTranslator.inline_call(self, fn, args, kwargs)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 2174, in inline_call
    return cls.inline_call_(parent, func, args, kwargs)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 2281, in inline_call_
    tracer.run()
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 719, in run
    and self.step()
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 683, in step
    getattr(self, inst.opname)(inst)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 392, in wrapper
    return inner_fn(self, inst)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 1162, in CALL_FUNCTION_KW
    self.call_function(fn, args, kwargs)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 557, in call_function
    self.push(fn.call_function(self, args, kwargs))
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/variables/torch.py", line 729, in call_function
    tensor_variable = wrap_fx_proxy(
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/variables/builder.py", line 1191, in wrap_fx_proxy
    return wrap_fx_proxy_cls(
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/variables/builder.py", line 1278, in wrap_fx_proxy_cls
    example_value = get_fake_value(proxy.node, tx)
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/_dynamo/utils.py", line 1366, in get_fake_value
    raise UserError(
torch._dynamo.exc.UserError: Tried to use data-dependent value in the subsequent computation. This can happen when we encounter unbounded dynamic value that is unknown during tracing time.You will need to explicitly give hint to the compiler. Please take a look at constrain_as_value OR constrain_as_size APIs

from user code:
   File "/local_data/user1/export_pow.py", line 55, in forward
    return self.psher.rsample()
  File "/local_data/user1/miniforge3/envs/lightning_py310/lib/python3.10/site-packages/torch/distributions/transformed_distribution.py", line 152, in rsample
    x = self.base_dist.rsample(sample_shape)
  File "/local_data/user1/distributions2.py", line 134, in rsample
    self.marginal_s.rsample(sample_shape + self.marginal_t.scale.shape),
  File "/local_data/user1/distributions2.py", line 66, in rsample
    v = torch.empty(

Set TORCH_LOGS="+dynamo" and TORCHDYNAMO_VERBOSE=1 for more information


```


### Versions

```
(lightning_py310) user@pc1:/local_data/user1$ python collect_env.py 
Collecting environment information...
PyTorch version: 2.1.2+cu121
Is debug build: False
CUDA used to build PyTorch: 12.1
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.3 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: Could not collect
CMake version: version 3.22.1
Libc version: glibc-2.35

Python version: 3.10.13 | packaged by conda-forge | (main, Oct 26 2023, 18:07:37) [GCC 12.3.0] (64-bit runtime)
Python platform: Linux-6.2.0-37-generic-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: 12.2.128
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: 
GPU 0: NVIDIA A40
GPU 1: NVIDIA A40
GPU 2: NVIDIA A40
GPU 3: NVIDIA A40

Nvidia driver version: 535.86.10
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Architecture:                       x86_64
CPU op-mode(s):                     32-bit, 64-bit
Address sizes:                      46 bits physical, 57 bits virtual
Byte Order:                         Little Endian
CPU(s):                             112
On-line CPU(s) list:                0-111
Vendor ID:                          GenuineIntel
Model name:                         Intel(R) Xeon(R) Gold 6330 CPU @ 2.00GHz
CPU family:                         6
Model:                              106
Thread(s) per core:                 2
Core(s) per socket:                 28
Socket(s):                          2
Stepping:                           6
BogoMIPS:                           4000.00
Flags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 invpcid_single intel_ppin ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb intel_pt avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local split_lock_detect wbnoinvd dtherm ida arat pln pts avx512vbmi umip pku ospke avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg tme avx512_vpopcntdq la57 rdpid fsrm md_clear pconfig flush_l1d arch_capabilities
Virtualization:                     VT-x
L1d cache:                          2.6 MiB (56 instances)
L1i cache:                          1.8 MiB (56 instances)
L2 cache:                           70 MiB (56 instances)
L3 cache:                           84 MiB (2 instances)
NUMA node(s):                       2
NUMA node0 CPU(s):                  0,2,4,6,8,10,12,14,16,18,20,22,24,26,28,30,32,34,36,38,40,42,44,46,48,50,52,54,56,58,60,62,64,66,68,70,72,74,76,78,80,82,84,86,88,90,92,94,96,98,100,102,104,106,108,110
NUMA node1 CPU(s):                  1,3,5,7,9,11,13,15,17,19,21,23,25,27,29,31,33,35,37,39,41,43,45,47,49,51,53,55,57,59,61,63,65,67,69,71,73,75,77,79,81,83,85,87,89,91,93,95,97,99,101,103,105,107,109,111
Vulnerability Gather data sampling: Mitigation; Microcode
Vulnerability Itlb multihit:        Not affected
Vulnerability L1tf:                 Not affected
Vulnerability Mds:                  Not affected
Vulnerability Meltdown:             Not affected
Vulnerability Mmio stale data:      Mitigation; Clear CPU buffers; SMT vulnerable
Vulnerability Retbleed:             Not affected
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:           Mitigation; Enhanced IBRS, IBPB conditional, RSB filling, PBRSB-eIBRS SW sequence
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Not affected

Versions of relevant libraries:
[pip3] flake8==6.1.0
[pip3] mypy-extensions==1.0.0
[pip3] numpy==1.26.2
[pip3] onnx==1.15.0
[pip3] onnxconverter-common==1.14.0
[pip3] onnxmltools==1.10.0
[pip3] onnxruntime==1.16.3
[pip3] onnxscript==0.1.0.dev20231213
[pip3] pytorch-lightning==2.1.3
[pip3] pytorch-triton==2.1.0+bcad9dabe1
[pip3] skl2onnx==1.15.0
[pip3] torch==2.1.2
[pip3] torchaudio==2.2.0.dev20231210+cu121
[pip3] torchmetrics==1.2.1
[pip3] torchvision==0.16.2
[pip3] triton==2.1.0
[conda] numpy                     1.26.2                   pypi_0    pypi
[conda] pytorch-lightning         2.1.3                    pypi_0    pypi
[conda] pytorch-triton            2.1.0+bcad9dabe1          pypi_0    pypi
[conda] torch                     2.1.2                    pypi_0    pypi
[conda] torchaudio                2.2.0.dev20231210+cu121          pypi_0    pypi
[conda] torchfix                  0.2.1                    pypi_0    pypi
[conda] torchmetrics              1.2.1                    pypi_0    pypi
[conda] torchvision               0.16.2                   pypi_0    pypi
[conda] triton                    2.1.0                    pypi_0    pypi
```

cc @ezyang @msaroufim @wconstab @bdhirsh @anijain2305 @zou3519 @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @aakhundov @kadeng @avikchaudhuri @gmagogsfm @zhxchen17 @tugsbayasgalan @angelayi @suo @ydwu4