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/data/users/dberard/scripts/oncall/112502.py:7: UserWarning: An output with one or more elements was resized since it had shape [9, 10], which does not match the required output shape [9]. This behavior is deprecated, and in a future PyTorch release outputs will not be resized unless they have zero elements. You can explicitly reuse an out tensor t by resizing it, inplace, to zero elements with t.resize_(0). (Triggered internally at ../aten/src/ATen/native/Resize.cpp:28.) | |
x = torch.diag(input=x, diagonal=0,out=torch.rand([9, 10], dtype=torch.float32).to('cpu')) | |
build succeded | |
/data/users/dberard/pytorch/torch/_prims_common/wrappers.py:159: UserWarning: An output with one or more elements was resized since it had shape torch.Size([9, 10]) which does not match the required output shape {str(shape)}. This behavior is deprecated, and in a future PyTorch release outputs will not be resized unless they have zero elements. You can explicitly reuse an out tensor t by resizing it, inplace, to zero elements with t.resize_(0). | |
warnings.warn(msg) | |
Traceback (most recent call last): | |
File "/data/users/dberard/scripts/oncall/112502.py", line 13, in <module> | |
op_info = torch.compile(forward, mode='max-autotune',fullgraph=False,dynamic=True)(cuda_tensor, 'cuda') | |
File "/data/users/dberard/pytorch/torch/_dynamo/eval_frame.py", line 411, in _fn | |
return fn(*args, **kwargs) | |
File "/data/users/dberard/pytorch/torch/_dynamo/eval_frame.py", line 559, in catch_errors | |
return callback(frame, cache_entry, hooks, frame_state) | |
File "/data/users/dberard/pytorch/torch/_dynamo/convert_frame.py", line 687, in _convert_frame | |
result = inner_convert(frame, cache_entry, hooks, frame_state) | |
File "/data/users/dberard/pytorch/torch/_dynamo/convert_frame.py", line 148, in _fn | |
return fn(*args, **kwargs) | |
File "/data/users/dberard/pytorch/torch/_dynamo/convert_frame.py", line 406, in _convert_frame_assert | |
return _compile( | |
File "/data/users/dberard/pytorch/torch/_dynamo/convert_frame.py", line 614, in _compile | |
guarded_code = compile_inner(code, one_graph, hooks, transform) | |
File "/data/users/dberard/pytorch/torch/_dynamo/utils.py", line 221, in time_wrapper | |
r = func(*args, **kwargs) | |
File "/data/users/dberard/pytorch/torch/_dynamo/convert_frame.py", line 531, in compile_inner | |
out_code = transform_code_object(code, transform) | |
File "/data/users/dberard/pytorch/torch/_dynamo/bytecode_transformation.py", line 1028, in transform_code_object | |
transformations(instructions, code_options) | |
File "/data/users/dberard/pytorch/torch/_dynamo/convert_frame.py", line 501, in transform | |
tracer.run() | |
File "/data/users/dberard/pytorch/torch/_dynamo/symbolic_convert.py", line 2119, in run | |
super().run() | |
File "/data/users/dberard/pytorch/torch/_dynamo/symbolic_convert.py", line 752, in run | |
and self.step() | |
File "/data/users/dberard/pytorch/torch/_dynamo/symbolic_convert.py", line 715, in step | |
getattr(self, inst.opname)(inst) | |
File "/data/users/dberard/pytorch/torch/_dynamo/symbolic_convert.py", line 405, in wrapper | |
return inner_fn(self, inst) | |
File "/data/users/dberard/pytorch/torch/_dynamo/symbolic_convert.py", line 1200, in CALL_FUNCTION_KW | |
self.call_function(fn, args, kwargs) | |
File "/data/users/dberard/pytorch/torch/_dynamo/symbolic_convert.py", line 586, in call_function | |
self.push(fn.call_function(self, args, kwargs)) | |
File "/data/users/dberard/pytorch/torch/_dynamo/variables/torch.py", line 722, in call_function | |
tensor_variable = wrap_fx_proxy( | |
File "/data/users/dberard/pytorch/torch/_dynamo/variables/builder.py", line 1341, in wrap_fx_proxy | |
return wrap_fx_proxy_cls( | |
File "/data/users/dberard/pytorch/torch/_dynamo/variables/builder.py", line 1431, in wrap_fx_proxy_cls | |
example_value = get_fake_value(proxy.node, tx, allow_non_graph_fake=True) | |
File "/data/users/dberard/pytorch/torch/_dynamo/utils.py", line 1483, in get_fake_value | |
raise TorchRuntimeError(str(e)).with_traceback(e.__traceback__) from None | |
File "/data/users/dberard/pytorch/torch/_dynamo/utils.py", line 1444, in get_fake_value | |
ret_val = wrap_fake_exception( | |
File "/data/users/dberard/pytorch/torch/_dynamo/utils.py", line 993, in wrap_fake_exception | |
return fn() | |
File "/data/users/dberard/pytorch/torch/_dynamo/utils.py", line 1445, in <lambda> | |
lambda: run_node(tx.output, node, args, kwargs, nnmodule) | |
File "/data/users/dberard/pytorch/torch/_dynamo/utils.py", line 1548, in run_node | |
raise RuntimeError(fn_str + str(e)).with_traceback(e.__traceback__) from e | |
File "/data/users/dberard/pytorch/torch/_dynamo/utils.py", line 1527, in run_node | |
return node.target(*args, **kwargs) | |
File "/data/users/dberard/pytorch/torch/utils/_stats.py", line 20, in wrapper | |
return fn(*args, **kwargs) | |
File "/data/users/dberard/pytorch/torch/_subclasses/fake_tensor.py", line 1378, in __torch_dispatch__ | |
return self.dispatch(func, types, args, kwargs) | |
File "/data/users/dberard/pytorch/torch/_subclasses/fake_tensor.py", line 1680, in dispatch | |
return self.wrap_meta_outputs_with_default_device_logic(r, func, args, kwargs) | |
File "/data/users/dberard/pytorch/torch/_subclasses/fake_tensor.py", line 1746, in wrap_meta_outputs_with_default_device_logic | |
return tree_map(partial(wrap), r) | |
File "/data/users/dberard/pytorch/torch/utils/_pytree.py", line 425, in tree_map | |
return tree_unflatten([fn(i) for i in flat_args], spec) | |
File "/data/users/dberard/pytorch/torch/utils/_pytree.py", line 425, in <listcomp> | |
return tree_unflatten([fn(i) for i in flat_args], spec) | |
File "/data/users/dberard/pytorch/torch/_subclasses/fake_tensor.py", line 1763, in wrap | |
) = FakeTensor._find_common_device(func, args, kwargs) | |
File "/data/users/dberard/pytorch/torch/_subclasses/fake_tensor.py", line 1257, in _find_common_device | |
pytree.tree_map_(merge_devices, kwargs) | |
File "/data/users/dberard/pytorch/torch/utils/_pytree.py", line 430, in tree_map_ | |
deque(map(fn, flat_args), maxlen=0) # consume and exhaust the iterable | |
File "/data/users/dberard/pytorch/torch/_subclasses/fake_tensor.py", line 1252, in merge_devices | |
raise RuntimeError( | |
torch._dynamo.exc.TorchRuntimeError: Failed running call_function <built-in method diag of type object at 0x7fd1cebeaf40>(*(), **{'input': FakeTensor(..., device='cuda:0', size=(s0, s1)), 'diagonal': 0, 'out': FakeTensor(..., size=(s0,))}): | |
Unhandled FakeTensor Device Propagation for aten.diagonal_copy.out, found two different devices cuda:0, cpu | |
from user code: | |
File "/data/users/dberard/scripts/oncall/112502.py", line 7, in forward | |
x = torch.diag(input=x, diagonal=0,out=torch.rand([9, 10], dtype=torch.float32).to('cpu')) | |
Set TORCH_LOGS="+dynamo" and TORCHDYNAMO_VERBOSE=1 for more information | |
You can suppress this exception and fall back to eager by setting: | |
import torch._dynamo | |
torch._dynamo.config.suppress_errors = True | |
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