test_bernoulli_self_cuda_bool: RuntimeError: "check_uniform_bounds" not implemented for 'Bool'

[desertfire]

Repro:

PYTORCH_TEST_WITH_INDUCTOR=1 python test/test_torch.py -k test_bernoulli_self_cuda_bool

Error:

======================================================================
ERROR: test_bernoulli_self_cuda_bool (__main__.TestTorchDeviceTypeCUDA)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/fsx/users/binbao/pytorch/torch/testing/_internal/common_utils.py", line 2001, in wrapper
    method(*args, **kwargs)
  File "/fsx/users/binbao/pytorch/torch/testing/_internal/common_utils.py", line 2001, in wrapper
    method(*args, **kwargs)
  File "/fsx/users/binbao/pytorch/torch/testing/_internal/common_device_type.py", line 394, in instantiated_test
    raise rte
  File "/fsx/users/binbao/pytorch/torch/testing/_internal/common_device_type.py", line 381, in instantiated_test
    result = test(self, **param_kwargs)
  File "/fsx/users/binbao/pytorch/test/test_torch.py", line 1833, in test_bernoulli_self
    @dtypes(*floating_types())
  File "/fsx/users/binbao/pytorch/torch/_dynamo/eval_frame.py", line 157, in _fn
    return fn(*args, **kwargs)
  File "/fsx/users/binbao/pytorch/functorch/_src/aot_autograd.py", line 870, in forward
    return compiled_f(
  File "/fsx/users/binbao/pytorch/functorch/_src/aot_autograd.py", line 856, in new_func
    compiled_fn = create_aot_dispatcher_function(
  File "/fsx/users/binbao/torchdynamo-tip/torchdynamo/utils.py", line 86, in time_wrapper
    r = func(*args, **kwargs)
  File "/fsx/users/binbao/pytorch/functorch/_src/aot_autograd.py", line 579, in create_aot_dispatcher_function
    return aot_dispatch_base(flat_fn, fake_flat_tensor_args, aot_config)
  File "/fsx/users/binbao/pytorch/functorch/_src/aot_autograd.py", line 285, in aot_dispatch_base
    fw_module = make_fx(flat_fn, aot_config.decompositions)(*flat_args)
  File "/fsx/users/binbao/pytorch/torch/fx/experimental/proxy_tensor.py", line 657, in wrapped
    t = dispatch_trace(wrap_key(func, args, fx_tracer), tracer=fx_tracer, concrete_args=tuple(phs))
  File "/fsx/users/binbao/pytorch/torch/_dynamo/eval_frame.py", line 157, in _fn
    return fn(*args, **kwargs)
  File "/fsx/users/binbao/pytorch/torch/fx/experimental/proxy_tensor.py", line 413, in dispatch_trace
    graph = tracer.trace(root, concrete_args)
  File "/fsx/users/binbao/pytorch/torch/_dynamo/eval_frame.py", line 157, in _fn
    return fn(*args, **kwargs)
  File "/fsx/users/binbao/pytorch/torch/fx/_symbolic_trace.py", line 739, in trace
    (self.create_arg(fn(*args)),),
  File "/fsx/users/binbao/pytorch/torch/fx/experimental/proxy_tensor.py", line 427, in wrapped
    out = f(*tensors)
  File "<string>", line 1, in <lambda>
  File "/fsx/users/binbao/pytorch/functorch/_src/aot_autograd.py", line 818, in functional_call
    out = Interpreter(mod).run(*args[params_len:], **kwargs)
  File "/fsx/users/binbao/pytorch/torch/fx/interpreter.py", line 130, in run
    self.env[node] = self.run_node(node)
  File "/fsx/users/binbao/pytorch/torch/fx/interpreter.py", line 171, in run_node
    return getattr(self, n.op)(n.target, args, kwargs)
  File "/fsx/users/binbao/pytorch/torch/fx/interpreter.py", line 265, in call_method
    return getattr(self_obj, target)(*args_tail, **kwargs)
  File "/fsx/users/binbao/pytorch/torch/fx/experimental/proxy_tensor.py", line 453, in __torch_dispatch__
    return self.inner_torch_dispatch(func, types, args, kwargs)
  File "/fsx/users/binbao/pytorch/torch/fx/experimental/proxy_tensor.py", line 478, in inner_torch_dispatch
    out = proxy_call(self, func, args, kwargs)
  File "/fsx/users/binbao/pytorch/torch/fx/experimental/proxy_tensor.py", line 226, in proxy_call
    r = CURRENT_DECOMPOSITION_TABLE[func](*args, **kwargs)
  File "/fsx/users/binbao/pytorch/torch/_inductor/decomposition.py", line 326, in bernoulli_
    return self.copy_(torch.rand_like(self) < p)
  File "/fsx/users/binbao/pytorch/torch/fx/experimental/proxy_tensor.py", line 453, in __torch_dispatch__
    return self.inner_torch_dispatch(func, types, args, kwargs)
  File "/fsx/users/binbao/pytorch/torch/fx/experimental/proxy_tensor.py", line 478, in inner_torch_dispatch
    out = proxy_call(self, func, args, kwargs)
  File "/fsx/users/binbao/pytorch/torch/fx/experimental/proxy_tensor.py", line 317, in proxy_call
    out = func(*args, **kwargs)
  File "/fsx/users/binbao/pytorch/torch/_ops.py", line 257, in __call__
    return self._op(*args, **kwargs or {})
  File "/fsx/users/binbao/pytorch/torch/_subclasses/fake_tensor.py", line 814, in __torch_dispatch__
    op_impl_out = op_impl(self, func, *args, **kwargs)
  File "/fsx/users/binbao/pytorch/torch/_subclasses/fake_tensor.py", line 307, in constructors
    r = func(*args, **new_kwargs)
  File "/fsx/users/binbao/pytorch/torch/_ops.py", line 257, in __call__
    return self._op(*args, **kwargs or {})
RuntimeError: "check_uniform_bounds" not implemented for 'Bool'

While executing %bernoulli_ : [#users=0] = call_method[target=bernoulli_](args = (%empty, 0.5), kwargs = {})
Original traceback:
Module stack: {}
  File "/fsx/users/binbao/pytorch/test/test_torch.py", line 1844, in test_bernoulli_self
    t.bernoulli_(0.5)

[desertfire]

cc @eellison