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August 13, 2022 00:06
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| ## Logs | |
| ``` | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 629, in CALL_FUNCTION | |
| self.call_function(fn, args, {}) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 226, in call_function | |
| self.push(fn.call_function(self, args, kwargs)) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/misc.py", line 531, in call_function | |
| return self.obj.call_method(tx, self.name, args, kwargs).add_options(self) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/user_defined.py", line 76, in call_method | |
| return super().call_method(tx, args, kwargs) | |
| TypeError: call_method() missing 1 required positional argument: 'kwargs' | |
| ========== Exception (above) while processing ========== | |
| File "penny-quantum-torch.py", line 33, in <module> | |
| opt.step(closure) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context | |
| return func(*args, **kwargs) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/optim/adam.py", line 105, in step | |
| @torch.no_grad() | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/optim/adam.py", line 118, in step | |
| loss = closure() | |
| File "penny-quantum-torch.py", line 27, in closure | |
| loss = cost(phi, theta) | |
| File "penny-quantum-torch.py", line 15, in cost | |
| def cost(phi, theta): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 588, in __call__ | |
| def __call__(self, *args, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 588, in __call__ | |
| def __call__(self, *args, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 619, in __call__ | |
| res = qml.execute( | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 197, in execute | |
| def execute( | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 197, in execute | |
| def execute( | |
| ========== End debug info ========== | |
| ERROR FROM offset=12 filename /home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/operation.py 350 KeyError | |
| ERROR FROM offset=24 filename /home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/operation.py 350 KeyError | |
| ERROR FROM offset=38 filename /home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/operation.py 534 KeyError | |
| ERROR FROM offset=8 filename /home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/tape/tape.py 1574 KeyError | |
| ERROR FROM offset=20 filename /home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/tape/tape.py 1574 KeyError | |
| ERROR FROM offset=94 filename /home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py 117 KeyError | |
| ========== TorchDynamo Stack Trace ========== | |
| Traceback (most recent call last): | |
| File "/home/ubuntu/torchdynamo/torchdynamo/convert_frame.py", line 288, in _convert_frame_assert | |
| code = transform_code_object(frame.f_code, transform) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/bytecode_transformation.py", line 338, in transform_code_object | |
| transformations(instructions, code_options) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/convert_frame.py", line 264, in transform | |
| tracer.run() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 312, in run | |
| and self.step() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 290, in step | |
| getattr(self, inst.opname)(inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 694, in LOAD_ATTR | |
| result = BuiltinVariable(getattr).call_function( | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/builtin.py", line 335, in call_function | |
| result = handler(tx, *args, **kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/builtin.py", line 678, in call_getattr | |
| obj.var_getattr(tx, name).clone(source=source).add_options(options) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/user_defined.py", line 298, in var_getattr | |
| return variables.UserMethodVariable( | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/functions.py", line 200, in call_function | |
| return super().call_function(tx, args, kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/functions.py", line 64, in call_function | |
| return tx.inline_user_function_return( | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 261, in inline_user_function_return | |
| result = InliningInstructionTranslator.inline_call(self, fn, args, kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 1352, in inline_call | |
| return cls.inline_call_(parent, func, args, kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 1398, in inline_call_ | |
| tracer.run() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 312, in run | |
| and self.step() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 290, in step | |
| getattr(self, inst.opname)(inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 151, in wrapper | |
| return inner_fn(self, inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 629, in CALL_FUNCTION | |
| self.call_function(fn, args, {}) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 226, in call_function | |
| self.push(fn.call_function(self, args, kwargs)) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/functions.py", line 64, in call_function | |
| return tx.inline_user_function_return( | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 261, in inline_user_function_return | |
| result = InliningInstructionTranslator.inline_call(self, fn, args, kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 1352, in inline_call | |
| return cls.inline_call_(parent, func, args, kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 1398, in inline_call_ | |
| tracer.run() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 312, in run | |
| and self.step() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 290, in step | |
| getattr(self, inst.opname)(inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 694, in LOAD_ATTR | |
| result = BuiltinVariable(getattr).call_function( | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/builtin.py", line 335, in call_function | |
| result = handler(tx, *args, **kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/builtin.py", line 678, in call_getattr | |
| obj.var_getattr(tx, name).clone(source=source).add_options(options) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/user_defined.py", line 298, in var_getattr | |
| return variables.UserMethodVariable( | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/functions.py", line 200, in call_function | |
| return super().call_function(tx, args, kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/functions.py", line 64, in call_function | |
| return tx.inline_user_function_return( | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 261, in inline_user_function_return | |
| result = InliningInstructionTranslator.inline_call(self, fn, args, kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 1352, in inline_call | |
| return cls.inline_call_(parent, func, args, kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 1398, in inline_call_ | |
| tracer.run() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 312, in run | |
| and self.step() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 290, in step | |
| getattr(self, inst.opname)(inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 151, in wrapper | |
| return inner_fn(self, inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 629, in CALL_FUNCTION | |
| self.call_function(fn, args, {}) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 226, in call_function | |
| self.push(fn.call_function(self, args, kwargs)) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/functions.py", line 64, in call_function | |
| return tx.inline_user_function_return( | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 261, in inline_user_function_return | |
| result = InliningInstructionTranslator.inline_call(self, fn, args, kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 1352, in inline_call | |
| return cls.inline_call_(parent, func, args, kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 1398, in inline_call_ | |
| tracer.run() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 312, in run | |
| and self.step() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 290, in step | |
| getattr(self, inst.opname)(inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 151, in wrapper | |
| return inner_fn(self, inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 629, in CALL_FUNCTION | |
| self.call_function(fn, args, {}) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 226, in call_function | |
| self.push(fn.call_function(self, args, kwargs)) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/functions.py", line 64, in call_function | |
| return tx.inline_user_function_return( | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 261, in inline_user_function_return | |
| result = InliningInstructionTranslator.inline_call(self, fn, args, kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 1352, in inline_call | |
| return cls.inline_call_(parent, func, args, kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 1398, in inline_call_ | |
| tracer.run() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 312, in run | |
| and self.step() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 290, in step | |
| getattr(self, inst.opname)(inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 694, in LOAD_ATTR | |
| result = BuiltinVariable(getattr).call_function( | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/builtin.py", line 335, in call_function | |
| result = handler(tx, *args, **kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/builtin.py", line 691, in call_getattr | |
| member = obj.value.__dict__[name] | |
| KeyError: 'round' | |
| ========== Exception (above) while processing ========== | |
| File "penny-quantum-torch.py", line 33, in <module> | |
| opt.step(closure) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context | |
| return func(*args, **kwargs) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/optim/adam.py", line 105, in step | |
| @torch.no_grad() | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/optim/adam.py", line 118, in step | |
| loss = closure() | |
| File "penny-quantum-torch.py", line 27, in closure | |
| loss = cost(phi, theta) | |
| File "penny-quantum-torch.py", line 15, in cost | |
| def cost(phi, theta): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 588, in __call__ | |
| def __call__(self, *args, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 588, in __call__ | |
| def __call__(self, *args, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 619, in __call__ | |
| res = qml.execute( | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 197, in execute | |
| def execute( | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 344, in execute | |
| qml.interfaces.cache_execute( | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 99, in wrapper | |
| @wraps(fn) | |
| ========== End debug info ========== | |
| ERROR FROM offset=12 filename /home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/operation.py 350 KeyError | |
| ERROR FROM offset=24 filename /home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/operation.py 350 KeyError | |
| ERROR FROM offset=38 filename /home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/operation.py 534 KeyError | |
| ERROR FROM offset=8 filename /home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/tape/tape.py 1574 KeyError | |
| ERROR FROM offset=20 filename /home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/tape/tape.py 1574 KeyError | |
| ========== TorchDynamo Stack Trace ========== | |
| Traceback (most recent call last): | |
| File "/home/ubuntu/torchdynamo/torchdynamo/convert_frame.py", line 288, in _convert_frame_assert | |
| code = transform_code_object(frame.f_code, transform) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/bytecode_transformation.py", line 338, in transform_code_object | |
| transformations(instructions, code_options) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/convert_frame.py", line 264, in transform | |
| tracer.run() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 312, in run | |
| and self.step() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 290, in step | |
| getattr(self, inst.opname)(inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 151, in wrapper | |
| return inner_fn(self, inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 629, in CALL_FUNCTION | |
| self.call_function(fn, args, {}) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 226, in call_function | |
| self.push(fn.call_function(self, args, kwargs)) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/functions.py", line 64, in call_function | |
| return tx.inline_user_function_return( | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 261, in inline_user_function_return | |
| result = InliningInstructionTranslator.inline_call(self, fn, args, kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 1352, in inline_call | |
| return cls.inline_call_(parent, func, args, kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 1398, in inline_call_ | |
| tracer.run() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 312, in run | |
| and self.step() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 290, in step | |
| getattr(self, inst.opname)(inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 694, in LOAD_ATTR | |
| result = BuiltinVariable(getattr).call_function( | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/builtin.py", line 335, in call_function | |
| result = handler(tx, *args, **kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/builtin.py", line 678, in call_getattr | |
| obj.var_getattr(tx, name).clone(source=source).add_options(options) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/user_defined.py", line 298, in var_getattr | |
| return variables.UserMethodVariable( | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/functions.py", line 200, in call_function | |
| return super().call_function(tx, args, kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/functions.py", line 64, in call_function | |
| return tx.inline_user_function_return( | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 261, in inline_user_function_return | |
| result = InliningInstructionTranslator.inline_call(self, fn, args, kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 1352, in inline_call | |
| return cls.inline_call_(parent, func, args, kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 1398, in inline_call_ | |
| tracer.run() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 312, in run | |
| and self.step() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 290, in step | |
| getattr(self, inst.opname)(inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 151, in wrapper | |
| return inner_fn(self, inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 629, in CALL_FUNCTION | |
| self.call_function(fn, args, {}) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 226, in call_function | |
| self.push(fn.call_function(self, args, kwargs)) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/functions.py", line 64, in call_function | |
| return tx.inline_user_function_return( | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 261, in inline_user_function_return | |
| result = InliningInstructionTranslator.inline_call(self, fn, args, kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 1352, in inline_call | |
| return cls.inline_call_(parent, func, args, kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 1398, in inline_call_ | |
| tracer.run() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 312, in run | |
| and self.step() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 290, in step | |
| getattr(self, inst.opname)(inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 151, in wrapper | |
| return inner_fn(self, inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 629, in CALL_FUNCTION | |
| self.call_function(fn, args, {}) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 226, in call_function | |
| self.push(fn.call_function(self, args, kwargs)) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/functions.py", line 64, in call_function | |
| return tx.inline_user_function_return( | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 261, in inline_user_function_return | |
| result = InliningInstructionTranslator.inline_call(self, fn, args, kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 1352, in inline_call | |
| return cls.inline_call_(parent, func, args, kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 1398, in inline_call_ | |
| tracer.run() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 312, in run | |
| and self.step() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 290, in step | |
| getattr(self, inst.opname)(inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 694, in LOAD_ATTR | |
| result = BuiltinVariable(getattr).call_function( | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/builtin.py", line 335, in call_function | |
| result = handler(tx, *args, **kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/builtin.py", line 691, in call_getattr | |
| member = obj.value.__dict__[name] | |
| KeyError: 'round' | |
| ========== Exception (above) while processing ========== | |
| File "penny-quantum-torch.py", line 33, in <module> | |
| opt.step(closure) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context | |
| return func(*args, **kwargs) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/optim/adam.py", line 105, in step | |
| @torch.no_grad() | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/optim/adam.py", line 118, in step | |
| loss = closure() | |
| File "penny-quantum-torch.py", line 27, in closure | |
| loss = cost(phi, theta) | |
| File "penny-quantum-torch.py", line 15, in cost | |
| def cost(phi, theta): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 588, in __call__ | |
| def __call__(self, *args, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 588, in __call__ | |
| def __call__(self, *args, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 619, in __call__ | |
| res = qml.execute( | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 197, in execute | |
| def execute( | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 344, in execute | |
| qml.interfaces.cache_execute( | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 117, in wrapper | |
| h = tape.hash | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/tape/tape.py", line 1570, in hash | |
| @property | |
| ========== End debug info ========== | |
| ERROR FROM offset=12 filename /home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/operation.py 350 KeyError | |
| ERROR FROM offset=24 filename /home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/operation.py 350 KeyError | |
| ERROR FROM offset=38 filename /home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/operation.py 534 KeyError | |
| ========== TorchDynamo Stack Trace ========== | |
| Traceback (most recent call last): | |
| File "/home/ubuntu/torchdynamo/torchdynamo/convert_frame.py", line 288, in _convert_frame_assert | |
| code = transform_code_object(frame.f_code, transform) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/bytecode_transformation.py", line 338, in transform_code_object | |
| transformations(instructions, code_options) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/convert_frame.py", line 264, in transform | |
| tracer.run() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 312, in run | |
| and self.step() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 290, in step | |
| getattr(self, inst.opname)(inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 151, in wrapper | |
| return inner_fn(self, inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 629, in CALL_FUNCTION | |
| self.call_function(fn, args, {}) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 226, in call_function | |
| self.push(fn.call_function(self, args, kwargs)) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/functions.py", line 64, in call_function | |
| return tx.inline_user_function_return( | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 261, in inline_user_function_return | |
| result = InliningInstructionTranslator.inline_call(self, fn, args, kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 1352, in inline_call | |
| return cls.inline_call_(parent, func, args, kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 1398, in inline_call_ | |
| tracer.run() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 312, in run | |
| and self.step() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 290, in step | |
| getattr(self, inst.opname)(inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 151, in wrapper | |
| return inner_fn(self, inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 629, in CALL_FUNCTION | |
| self.call_function(fn, args, {}) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 226, in call_function | |
| self.push(fn.call_function(self, args, kwargs)) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/functions.py", line 64, in call_function | |
| return tx.inline_user_function_return( | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 261, in inline_user_function_return | |
| result = InliningInstructionTranslator.inline_call(self, fn, args, kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 1352, in inline_call | |
| return cls.inline_call_(parent, func, args, kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 1398, in inline_call_ | |
| tracer.run() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 312, in run | |
| and self.step() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 290, in step | |
| getattr(self, inst.opname)(inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 694, in LOAD_ATTR | |
| result = BuiltinVariable(getattr).call_function( | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/builtin.py", line 335, in call_function | |
| result = handler(tx, *args, **kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/builtin.py", line 691, in call_getattr | |
| member = obj.value.__dict__[name] | |
| KeyError: 'round' | |
| ========== Exception (above) while processing ========== | |
| File "penny-quantum-torch.py", line 33, in <module> | |
| opt.step(closure) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context | |
| return func(*args, **kwargs) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/optim/adam.py", line 105, in step | |
| @torch.no_grad() | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/optim/adam.py", line 118, in step | |
| loss = closure() | |
| File "penny-quantum-torch.py", line 27, in closure | |
| loss = cost(phi, theta) | |
| File "penny-quantum-torch.py", line 15, in cost | |
| def cost(phi, theta): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 588, in __call__ | |
| def __call__(self, *args, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 588, in __call__ | |
| def __call__(self, *args, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 619, in __call__ | |
| res = qml.execute( | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 197, in execute | |
| def execute( | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 344, in execute | |
| qml.interfaces.cache_execute( | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 117, in wrapper | |
| h = tape.hash | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/tape/tape.py", line 1574, in hash | |
| fingerprint.extend(op.hash for op in self.operations) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/tape/tape.py", line 1574, in <genexpr> | |
| fingerprint.extend(op.hash for op in self.operations) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/operation.py", line 526, in hash | |
| @property | |
| ========== End debug info ========== | |
| ERROR FROM offset=12 filename /home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/operation.py 350 KeyError | |
| ERROR FROM offset=24 filename /home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/operation.py 350 KeyError | |
| ========== TorchDynamo Stack Trace ========== | |
| Traceback (most recent call last): | |
| File "/home/ubuntu/torchdynamo/torchdynamo/convert_frame.py", line 288, in _convert_frame_assert | |
| code = transform_code_object(frame.f_code, transform) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/bytecode_transformation.py", line 338, in transform_code_object | |
| transformations(instructions, code_options) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/convert_frame.py", line 264, in transform | |
| tracer.run() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 312, in run | |
| and self.step() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 290, in step | |
| getattr(self, inst.opname)(inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 151, in wrapper | |
| return inner_fn(self, inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 629, in CALL_FUNCTION | |
| self.call_function(fn, args, {}) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 226, in call_function | |
| self.push(fn.call_function(self, args, kwargs)) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/functions.py", line 64, in call_function | |
| return tx.inline_user_function_return( | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 261, in inline_user_function_return | |
| result = InliningInstructionTranslator.inline_call(self, fn, args, kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 1352, in inline_call | |
| return cls.inline_call_(parent, func, args, kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 1398, in inline_call_ | |
| tracer.run() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 312, in run | |
| and self.step() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 290, in step | |
| getattr(self, inst.opname)(inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 694, in LOAD_ATTR | |
| result = BuiltinVariable(getattr).call_function( | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/builtin.py", line 335, in call_function | |
| result = handler(tx, *args, **kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/builtin.py", line 691, in call_getattr | |
| member = obj.value.__dict__[name] | |
| KeyError: 'round' | |
| ========== Exception (above) while processing ========== | |
| File "penny-quantum-torch.py", line 33, in <module> | |
| opt.step(closure) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context | |
| return func(*args, **kwargs) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/optim/adam.py", line 105, in step | |
| @torch.no_grad() | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/optim/adam.py", line 118, in step | |
| loss = closure() | |
| File "penny-quantum-torch.py", line 27, in closure | |
| loss = cost(phi, theta) | |
| File "penny-quantum-torch.py", line 15, in cost | |
| def cost(phi, theta): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 588, in __call__ | |
| def __call__(self, *args, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 588, in __call__ | |
| def __call__(self, *args, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 619, in __call__ | |
| res = qml.execute( | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 197, in execute | |
| def execute( | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 344, in execute | |
| qml.interfaces.cache_execute( | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 117, in wrapper | |
| h = tape.hash | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/tape/tape.py", line 1574, in hash | |
| fingerprint.extend(op.hash for op in self.operations) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/tape/tape.py", line 1574, in <genexpr> | |
| fingerprint.extend(op.hash for op in self.operations) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/operation.py", line 534, in hash | |
| _process_data(self), | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/operation.py", line 344, in _process_data | |
| def _process_data(op): | |
| ========== End debug info ========== | |
| ERROR FROM offset=6 filename /home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/autoray/autoray.py 1148 AssertionError | |
| ERROR FROM offset=6 filename /home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/devices/default_qubit_torch.py 236 NotImplementedError | |
| ERROR FROM offset=44 filename /home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/devices/default_qubit.py 596 NotImplementedError | |
| ========== TorchDynamo Stack Trace ========== | |
| Traceback (most recent call last): | |
| File "/home/ubuntu/torchdynamo/torchdynamo/convert_frame.py", line 288, in _convert_frame_assert | |
| code = transform_code_object(frame.f_code, transform) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/bytecode_transformation.py", line 338, in transform_code_object | |
| transformations(instructions, code_options) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/convert_frame.py", line 264, in transform | |
| tracer.run() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 312, in run | |
| and self.step() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 290, in step | |
| getattr(self, inst.opname)(inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 151, in wrapper | |
| return inner_fn(self, inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 678, in CALL_FUNCTION_KW | |
| self.call_function(fn, args, kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 226, in call_function | |
| self.push(fn.call_function(self, args, kwargs)) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/misc.py", line 531, in call_function | |
| return self.obj.call_method(tx, self.name, args, kwargs).add_options(self) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/user_defined.py", line 211, in call_method | |
| return UserMethodVariable(method, self, **options).call_function( | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/functions.py", line 200, in call_function | |
| return super().call_function(tx, args, kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/functions.py", line 64, in call_function | |
| return tx.inline_user_function_return( | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 261, in inline_user_function_return | |
| result = InliningInstructionTranslator.inline_call(self, fn, args, kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 1352, in inline_call | |
| return cls.inline_call_(parent, func, args, kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 1398, in inline_call_ | |
| tracer.run() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 312, in run | |
| and self.step() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 290, in step | |
| getattr(self, inst.opname)(inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 151, in wrapper | |
| return inner_fn(self, inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 629, in CALL_FUNCTION | |
| self.call_function(fn, args, {}) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 226, in call_function | |
| self.push(fn.call_function(self, args, kwargs)) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/builtin.py", line 335, in call_function | |
| result = handler(tx, *args, **kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/builtin.py", line 539, in call_isinstance | |
| arg_type = arg.python_type() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/base.py", line 140, in python_type | |
| raise NotImplementedError(f"{self} has no type") | |
| NotImplementedError: NumpyVariable() has no type | |
| ========== Exception (above) while processing ========== | |
| File "penny-quantum-torch.py", line 33, in <module> | |
| opt.step(closure) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context | |
| return func(*args, **kwargs) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/optim/adam.py", line 105, in step | |
| @torch.no_grad() | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/optim/adam.py", line 118, in step | |
| loss = closure() | |
| File "penny-quantum-torch.py", line 27, in closure | |
| loss = cost(phi, theta) | |
| File "penny-quantum-torch.py", line 15, in cost | |
| def cost(phi, theta): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 588, in __call__ | |
| def __call__(self, *args, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 588, in __call__ | |
| def __call__(self, *args, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 619, in __call__ | |
| res = qml.execute( | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 197, in execute | |
| def execute( | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 344, in execute | |
| qml.interfaces.cache_execute( | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 172, in wrapper | |
| res = fn(execution_tapes.values(), **kwargs) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 97, in fn | |
| return original_fn(tapes, **kwargs) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/contextlib.py", line 75, in inner | |
| return func(*args, **kwds) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/_qubit_device.py", line 331, in batch_execute | |
| def batch_execute(self, circuits): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/devices/default_qubit.py", line 765, in reset | |
| def reset(self): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/devices/default_qubit.py", line 584, in _create_basis_state | |
| def _create_basis_state(self, index): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/devices/default_qubit.py", line 584, in _create_basis_state | |
| def _create_basis_state(self, index): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/devices/default_qubit.py", line 584, in _create_basis_state | |
| def _create_basis_state(self, index): | |
| ========== End debug info ========== | |
| ERROR FROM offset=6 filename /home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/devices/default_qubit_torch.py 236 NotImplementedError | |
| ========== TorchDynamo Stack Trace ========== | |
| Traceback (most recent call last): | |
| File "/home/ubuntu/torchdynamo/torchdynamo/convert_frame.py", line 288, in _convert_frame_assert | |
| code = transform_code_object(frame.f_code, transform) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/bytecode_transformation.py", line 338, in transform_code_object | |
| transformations(instructions, code_options) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/convert_frame.py", line 264, in transform | |
| tracer.run() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 312, in run | |
| and self.step() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 290, in step | |
| getattr(self, inst.opname)(inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 151, in wrapper | |
| return inner_fn(self, inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 629, in CALL_FUNCTION | |
| self.call_function(fn, args, {}) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 226, in call_function | |
| self.push(fn.call_function(self, args, kwargs)) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/builtin.py", line 335, in call_function | |
| result = handler(tx, *args, **kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/builtin.py", line 539, in call_isinstance | |
| arg_type = arg.python_type() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/base.py", line 140, in python_type | |
| raise NotImplementedError(f"{self} has no type") | |
| NotImplementedError: NumpyVariable() has no type | |
| ========== Exception (above) while processing ========== | |
| File "penny-quantum-torch.py", line 33, in <module> | |
| opt.step(closure) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context | |
| return func(*args, **kwargs) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/optim/adam.py", line 105, in step | |
| @torch.no_grad() | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/optim/adam.py", line 118, in step | |
| loss = closure() | |
| File "penny-quantum-torch.py", line 27, in closure | |
| loss = cost(phi, theta) | |
| File "penny-quantum-torch.py", line 15, in cost | |
| def cost(phi, theta): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 588, in __call__ | |
| def __call__(self, *args, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 588, in __call__ | |
| def __call__(self, *args, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 619, in __call__ | |
| res = qml.execute( | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 197, in execute | |
| def execute( | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 344, in execute | |
| qml.interfaces.cache_execute( | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 172, in wrapper | |
| res = fn(execution_tapes.values(), **kwargs) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 97, in fn | |
| return original_fn(tapes, **kwargs) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/contextlib.py", line 75, in inner | |
| return func(*args, **kwds) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/_qubit_device.py", line 331, in batch_execute | |
| def batch_execute(self, circuits): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/devices/default_qubit.py", line 765, in reset | |
| def reset(self): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/devices/default_qubit.py", line 584, in _create_basis_state | |
| def _create_basis_state(self, index): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/devices/default_qubit.py", line 584, in _create_basis_state | |
| def _create_basis_state(self, index): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/devices/default_qubit.py", line 596, in _create_basis_state | |
| state = self._asarray(state, dtype=self.C_DTYPE) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/devices/default_qubit_torch.py", line 235, in _asarray | |
| def _asarray(self, a, dtype=None): | |
| ========== End debug info ========== | |
| ERROR FROM offset=4 filename /home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/ops/qubit/parametric_ops.py 99 KeyError | |
| ========== TorchDynamo Stack Trace ========== | |
| Traceback (most recent call last): | |
| File "/home/ubuntu/torchdynamo/torchdynamo/convert_frame.py", line 288, in _convert_frame_assert | |
| code = transform_code_object(frame.f_code, transform) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/bytecode_transformation.py", line 338, in transform_code_object | |
| transformations(instructions, code_options) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/convert_frame.py", line 264, in transform | |
| tracer.run() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 312, in run | |
| and self.step() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 290, in step | |
| getattr(self, inst.opname)(inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 694, in LOAD_ATTR | |
| result = BuiltinVariable(getattr).call_function( | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/builtin.py", line 335, in call_function | |
| result = handler(tx, *args, **kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/builtin.py", line 691, in call_getattr | |
| member = obj.value.__dict__[name] | |
| KeyError: 'cos' | |
| ========== Exception (above) while processing ========== | |
| File "penny-quantum-torch.py", line 33, in <module> | |
| opt.step(closure) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context | |
| return func(*args, **kwargs) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/optim/adam.py", line 105, in step | |
| @torch.no_grad() | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/optim/adam.py", line 118, in step | |
| loss = closure() | |
| File "penny-quantum-torch.py", line 27, in closure | |
| loss = cost(phi, theta) | |
| File "penny-quantum-torch.py", line 15, in cost | |
| def cost(phi, theta): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 588, in __call__ | |
| def __call__(self, *args, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 588, in __call__ | |
| def __call__(self, *args, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 619, in __call__ | |
| res = qml.execute( | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 197, in execute | |
| def execute( | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 344, in execute | |
| qml.interfaces.cache_execute( | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 172, in wrapper | |
| res = fn(execution_tapes.values(), **kwargs) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 97, in fn | |
| return original_fn(tapes, **kwargs) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/contextlib.py", line 75, in inner | |
| return func(*args, **kwds) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/_qubit_device.py", line 331, in batch_execute | |
| def batch_execute(self, circuits): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/_qubit_device.py", line 331, in batch_execute | |
| def batch_execute(self, circuits): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/devices/default_qubit_torch.py", line 205, in execute | |
| def execute(self, circuit, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/devices/default_qubit_torch.py", line 205, in execute | |
| def execute(self, circuit, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/_qubit_device.py", line 228, in execute | |
| def execute(self, circuit, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/_qubit_device.py", line 257, in execute | |
| self.apply(circuit.operations, rotations=circuit.diagonalizing_gates, **kwargs) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/devices/default_qubit.py", line 207, in apply | |
| def apply(self, operations, rotations=None, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/devices/default_qubit.py", line 240, in _apply_operation | |
| def _apply_operation(self, state, operation): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/devices/default_qubit_torch.py", line 305, in _get_unitary_matrix | |
| return self._asarray(unitary.matrix(), dtype=self.C_DTYPE) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/operation.py", line 1414, in matrix | |
| canonical_matrix = self.compute_matrix(*self.parameters, **self.hyperparameters) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/ops/qubit/parametric_ops.py", line 78, in compute_matrix | |
| @staticmethod | |
| ========== End debug info ========== | |
| ERROR FROM offset=10 filename /home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/autoray/autoray.py 260 KeyError | |
| ERROR FROM offset=56 filename /home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/autoray/autoray.py 85 KeyError | |
| ========== TorchDynamo Stack Trace ========== | |
| Traceback (most recent call last): | |
| File "/home/ubuntu/torchdynamo/torchdynamo/convert_frame.py", line 288, in _convert_frame_assert | |
| code = transform_code_object(frame.f_code, transform) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/bytecode_transformation.py", line 338, in transform_code_object | |
| transformations(instructions, code_options) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/convert_frame.py", line 264, in transform | |
| tracer.run() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 312, in run | |
| and self.step() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 290, in step | |
| getattr(self, inst.opname)(inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 151, in wrapper | |
| return inner_fn(self, inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 629, in CALL_FUNCTION | |
| self.call_function(fn, args, {}) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 226, in call_function | |
| self.push(fn.call_function(self, args, kwargs)) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/functions.py", line 64, in call_function | |
| return tx.inline_user_function_return( | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 261, in inline_user_function_return | |
| result = InliningInstructionTranslator.inline_call(self, fn, args, kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 1352, in inline_call | |
| return cls.inline_call_(parent, func, args, kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 1398, in inline_call_ | |
| tracer.run() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 312, in run | |
| and self.step() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 290, in step | |
| getattr(self, inst.opname)(inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 151, in wrapper | |
| return inner_fn(self, inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 105, in impl | |
| self.push(fn_var.call_function(self, self.popn(nargs), {})) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/builtin.py", line 335, in call_function | |
| result = handler(tx, *args, **kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/builtin.py", line 536, in call_getitem | |
| return args[0].call_method(tx, "__getitem__", args[1:], kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/dicts.py", line 67, in call_method | |
| return self.getitem_const(args[0]) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/dicts.py", line 51, in getitem_const | |
| return self.items[ConstDictVariable.get_key(arg)].add_options(self, arg) | |
| KeyError: ('torch', 'stack') | |
| ========== Exception (above) while processing ========== | |
| File "penny-quantum-torch.py", line 33, in <module> | |
| opt.step(closure) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context | |
| return func(*args, **kwargs) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/optim/adam.py", line 105, in step | |
| @torch.no_grad() | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/optim/adam.py", line 118, in step | |
| loss = closure() | |
| File "penny-quantum-torch.py", line 27, in closure | |
| loss = cost(phi, theta) | |
| File "penny-quantum-torch.py", line 15, in cost | |
| def cost(phi, theta): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 588, in __call__ | |
| def __call__(self, *args, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 588, in __call__ | |
| def __call__(self, *args, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 619, in __call__ | |
| res = qml.execute( | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 197, in execute | |
| def execute( | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 344, in execute | |
| qml.interfaces.cache_execute( | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 172, in wrapper | |
| res = fn(execution_tapes.values(), **kwargs) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 97, in fn | |
| return original_fn(tapes, **kwargs) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/contextlib.py", line 75, in inner | |
| return func(*args, **kwds) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/_qubit_device.py", line 331, in batch_execute | |
| def batch_execute(self, circuits): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/_qubit_device.py", line 331, in batch_execute | |
| def batch_execute(self, circuits): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/devices/default_qubit_torch.py", line 205, in execute | |
| def execute(self, circuit, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/devices/default_qubit_torch.py", line 205, in execute | |
| def execute(self, circuit, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/_qubit_device.py", line 228, in execute | |
| def execute(self, circuit, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/_qubit_device.py", line 257, in execute | |
| self.apply(circuit.operations, rotations=circuit.diagonalizing_gates, **kwargs) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/devices/default_qubit.py", line 207, in apply | |
| def apply(self, operations, rotations=None, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/devices/default_qubit.py", line 240, in _apply_operation | |
| def _apply_operation(self, state, operation): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/devices/default_qubit_torch.py", line 305, in _get_unitary_matrix | |
| return self._asarray(unitary.matrix(), dtype=self.C_DTYPE) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/operation.py", line 1414, in matrix | |
| canonical_matrix = self.compute_matrix(*self.parameters, **self.hyperparameters) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/ops/qubit/parametric_ops.py", line 109, in compute_matrix | |
| return qml.math.stack([stack_last([c, js]), stack_last([js, c])], axis=-2) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/math/multi_dispatch.py", line 154, in wrapper | |
| @functools.wraps(fn) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/math/multi_dispatch.py", line 154, in wrapper | |
| @functools.wraps(fn) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/math/multi_dispatch.py", line 507, in stack | |
| return np.stack(values, axis=axis, like=like) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/autoray/autoray.py", line 29, in do | |
| def do(fn, *args, like=None, **kwargs): | |
| ========== End debug info ========== | |
| ERROR FROM offset=38 filename /home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/ops/qubit/parametric_ops.py 315 KeyError | |
| ========== TorchDynamo Stack Trace ========== | |
| Traceback (most recent call last): | |
| File "/home/ubuntu/torchdynamo/torchdynamo/convert_frame.py", line 288, in _convert_frame_assert | |
| code = transform_code_object(frame.f_code, transform) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/bytecode_transformation.py", line 338, in transform_code_object | |
| transformations(instructions, code_options) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/convert_frame.py", line 264, in transform | |
| tracer.run() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 312, in run | |
| and self.step() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 290, in step | |
| getattr(self, inst.opname)(inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 694, in LOAD_ATTR | |
| result = BuiltinVariable(getattr).call_function( | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/builtin.py", line 335, in call_function | |
| result = handler(tx, *args, **kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/builtin.py", line 691, in call_getattr | |
| member = obj.value.__dict__[name] | |
| KeyError: 'exp' | |
| ========== Exception (above) while processing ========== | |
| File "penny-quantum-torch.py", line 33, in <module> | |
| opt.step(closure) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context | |
| return func(*args, **kwargs) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/optim/adam.py", line 105, in step | |
| @torch.no_grad() | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/optim/adam.py", line 118, in step | |
| loss = closure() | |
| File "penny-quantum-torch.py", line 27, in closure | |
| loss = cost(phi, theta) | |
| File "penny-quantum-torch.py", line 15, in cost | |
| def cost(phi, theta): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 588, in __call__ | |
| def __call__(self, *args, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 588, in __call__ | |
| def __call__(self, *args, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 619, in __call__ | |
| res = qml.execute( | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 197, in execute | |
| def execute( | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 344, in execute | |
| qml.interfaces.cache_execute( | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 172, in wrapper | |
| res = fn(execution_tapes.values(), **kwargs) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 97, in fn | |
| return original_fn(tapes, **kwargs) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/contextlib.py", line 75, in inner | |
| return func(*args, **kwds) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/_qubit_device.py", line 331, in batch_execute | |
| def batch_execute(self, circuits): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/_qubit_device.py", line 331, in batch_execute | |
| def batch_execute(self, circuits): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/devices/default_qubit_torch.py", line 205, in execute | |
| def execute(self, circuit, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/devices/default_qubit_torch.py", line 205, in execute | |
| def execute(self, circuit, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/_qubit_device.py", line 228, in execute | |
| def execute(self, circuit, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/_qubit_device.py", line 257, in execute | |
| self.apply(circuit.operations, rotations=circuit.diagonalizing_gates, **kwargs) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/devices/default_qubit.py", line 207, in apply | |
| def apply(self, operations, rotations=None, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/devices/default_qubit.py", line 207, in apply | |
| def apply(self, operations, rotations=None, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/devices/default_qubit.py", line 240, in _apply_operation | |
| def _apply_operation(self, state, operation): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/devices/default_qubit_torch.py", line 304, in _get_unitary_matrix | |
| return self._asarray(unitary.eigvals(), dtype=self.C_DTYPE) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/operation.py", line 1424, in eigvals | |
| def eigvals(self): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/operation.py", line 689, in eigvals | |
| return self.compute_eigvals(*self.parameters, **self.hyperparameters) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/ops/qubit/parametric_ops.py", line 284, in compute_eigvals | |
| @staticmethod | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/ops/qubit/parametric_ops.py", line 284, in compute_eigvals | |
| @staticmethod | |
| ========== End debug info ========== | |
| ERROR FROM offset=12 filename /home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/devices/default_qubit_torch.py 141 AssertionError | |
| ERROR FROM offset=4 filename /home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py 319 KeyError | |
| ERROR FROM offset=12 filename /home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/cachetools/__init__.py 74 KeyError | |
| ========== TorchDynamo Stack Trace ========== | |
| Traceback (most recent call last): | |
| File "/home/ubuntu/torchdynamo/torchdynamo/convert_frame.py", line 288, in _convert_frame_assert | |
| code = transform_code_object(frame.f_code, transform) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/bytecode_transformation.py", line 338, in transform_code_object | |
| transformations(instructions, code_options) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/convert_frame.py", line 264, in transform | |
| tracer.run() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 312, in run | |
| and self.step() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 290, in step | |
| getattr(self, inst.opname)(inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 151, in wrapper | |
| return inner_fn(self, inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 629, in CALL_FUNCTION | |
| self.call_function(fn, args, {}) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 226, in call_function | |
| self.push(fn.call_function(self, args, kwargs)) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/functions.py", line 64, in call_function | |
| return tx.inline_user_function_return( | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 261, in inline_user_function_return | |
| result = InliningInstructionTranslator.inline_call(self, fn, args, kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 1352, in inline_call | |
| return cls.inline_call_(parent, func, args, kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 1398, in inline_call_ | |
| tracer.run() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 312, in run | |
| and self.step() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 290, in step | |
| getattr(self, inst.opname)(inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 694, in LOAD_ATTR | |
| result = BuiltinVariable(getattr).call_function( | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/builtin.py", line 335, in call_function | |
| result = handler(tx, *args, **kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/builtin.py", line 691, in call_getattr | |
| member = obj.value.__dict__[name] | |
| KeyError: 'shape' | |
| ========== Exception (above) while processing ========== | |
| File "penny-quantum-torch.py", line 33, in <module> | |
| opt.step(closure) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context | |
| return func(*args, **kwargs) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/optim/adam.py", line 105, in step | |
| @torch.no_grad() | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/optim/adam.py", line 118, in step | |
| loss = closure() | |
| File "penny-quantum-torch.py", line 27, in closure | |
| loss = cost(phi, theta) | |
| File "penny-quantum-torch.py", line 15, in cost | |
| def cost(phi, theta): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 588, in __call__ | |
| def __call__(self, *args, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 588, in __call__ | |
| def __call__(self, *args, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 619, in __call__ | |
| res = qml.execute( | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 197, in execute | |
| def execute( | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 344, in execute | |
| qml.interfaces.cache_execute( | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 189, in wrapper | |
| cache[hashes[i]] = r | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/cachetools/__init__.py", line 216, in __setitem__ | |
| def __setitem__(self, key, value, cache_setitem=Cache.__setitem__): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/cachetools/__init__.py", line 72, in __setitem__ | |
| def __setitem__(self, key, value): | |
| ========== End debug info ========== | |
| ERROR FROM offset=4 filename /home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py 319 KeyError | |
| ========== TorchDynamo Stack Trace ========== | |
| Traceback (most recent call last): | |
| File "/home/ubuntu/torchdynamo/torchdynamo/convert_frame.py", line 288, in _convert_frame_assert | |
| code = transform_code_object(frame.f_code, transform) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/bytecode_transformation.py", line 338, in transform_code_object | |
| transformations(instructions, code_options) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/convert_frame.py", line 264, in transform | |
| tracer.run() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 312, in run | |
| and self.step() | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 290, in step | |
| getattr(self, inst.opname)(inst) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/symbolic_convert.py", line 694, in LOAD_ATTR | |
| result = BuiltinVariable(getattr).call_function( | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/builtin.py", line 335, in call_function | |
| result = handler(tx, *args, **kwargs) | |
| File "/home/ubuntu/torchdynamo/torchdynamo/variables/builtin.py", line 691, in call_getattr | |
| member = obj.value.__dict__[name] | |
| KeyError: 'shape' | |
| ========== Exception (above) while processing ========== | |
| File "penny-quantum-torch.py", line 33, in <module> | |
| opt.step(closure) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context | |
| return func(*args, **kwargs) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/optim/adam.py", line 105, in step | |
| @torch.no_grad() | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/optim/adam.py", line 118, in step | |
| loss = closure() | |
| File "penny-quantum-torch.py", line 27, in closure | |
| loss = cost(phi, theta) | |
| File "penny-quantum-torch.py", line 15, in cost | |
| def cost(phi, theta): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 588, in __call__ | |
| def __call__(self, *args, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 588, in __call__ | |
| def __call__(self, *args, **kwargs): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/qnode.py", line 619, in __call__ | |
| res = qml.execute( | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 197, in execute | |
| def execute( | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 344, in execute | |
| qml.interfaces.cache_execute( | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 189, in wrapper | |
| cache[hashes[i]] = r | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/cachetools/__init__.py", line 216, in __setitem__ | |
| def __setitem__(self, key, value, cache_setitem=Cache.__setitem__): | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/cachetools/__init__.py", line 74, in __setitem__ | |
| size = self.getsizeof(value) | |
| File "/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/pennylane/interfaces/execution.py", line 319, in <lambda> | |
| cache = LRUCache(maxsize=cachesize, getsizeof=lambda x: qml.math.shape(x)[0]) | |
| ========== End debug info ========== | |
| WARNING torchdynamo.convert_frame: torchdynamo hit config.cache_size_limit (64) | |
| function: '__setitem__' (/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/cachetools/__init__.py:216) | |
| reasons: ['key == 6899054623475161868'] | |
| to diagnose recompilation issues, see https://github.com/pytorch/torchdynamo/blob/main/TROUBLESHOOTING.md. | |
| WARNING torchdynamo.convert_frame: torchdynamo hit config.cache_size_limit (64) | |
| function: '_single_tensor_adam' (/home/ubuntu/anaconda3/envs/quantum/lib/python3.8/site-packages/torch/optim/adam.py:229) | |
| reasons: ['___stack1 == 1.0'] | |
| to diagnose recompilation issues, see https://github.com/pytorch/torchdynamo/blob/main/TROUBLESHOOTING.md. | |
| ``` |
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