Hi
I am trying to run the map_trainer example, got following error:
--------------------------------------------------------------------------- RayTaskError(TypeError) Traceback (most recent call last) Cell In[1], line 18 15 return -fidelity(s, target) 17 # Use case 0: Calculate the cost of a randomly initialized circuit 5 times without optimizing it. —> 18 results_0 = map_trainer( 19 cost_fn=cost_fn, 20 tasks=5, 21 ) 23 # Use case 1: Run circuit optimization 5 times on randomly initialized circuits. 24 results_1 = map_trainer( 25 cost_fn=cost_fn, 26 device_factory=make_circ, (…) 29 symplectic_lr=0.05, 30 ) File ~/Photonic Neural Network/MrMustard/mrmustard/training/trainer.py:379, in map_trainer(trainer, tasks, pbar, unblock, num_cpus, **kwargs) 376 if not unblock: 377 # blocks and wait till all tasks complete to return the end results. 378 if pbar: → 379 results = list( 380 track( 381 _iter_futures(promises), 382 description=f"{len(promises)} tasks running…", 383 total=len(promises), 384 ) 385 ) 386 else: 387 results = ray.get(promises) File ~/anaconda3/envs/Xanadu/lib/python3.11/site-packages/rich/progress.py:175, in track(sequence, description, total, completed, auto_refresh, console, transient, get_time, refresh_per_second, style, complete_style, finished_style, pulse_style, update_period, disable, show_speed) 164 progress = Progress( 165 *columns, 166 auto_refresh=auto_refresh, (…) 171 disable=disable, 172 ) 174 with progress: → 175 yield from progress.track( 176 sequence, 177 total=total, 178 completed=completed, 179 description=description, 180 update_period=update_period, 181 ) File ~/anaconda3/envs/Xanadu/lib/python3.11/site-packages/rich/progress.py:1225, in Progress.track(self, sequence, total, completed, task_id, description, update_period) 1223 if self.live.auto_refresh: 1224 with _TrackThread(self, task_id, update_period) as track_thread: → 1225 for value in sequence: 1226 yield value 1227 track_thread.completed += 1 File ~/Photonic Neural Network/MrMustard/mrmustard/training/trainer.py:215, in _iter_futures(futures) 213 while futures: 214 done, futures = ray.wait(futures) → 215 yield ray.get(done[0]) File ~/anaconda3/envs/Xanadu/lib/python3.11/site-packages/ray/_private/auto_init_hook.py:21, in wrap_auto_init..auto_init_wrapper(*args, **kwargs) 18 @wraps(fn) 19 def auto_init_wrapper(*args, **kwargs): 20 auto_init_ray() —> 21 return fn(*args, **kwargs) File ~/anaconda3/envs/Xanadu/lib/python3.11/site-packages/ray/_private/client_mode_hook.py:103, in client_mode_hook..wrapper(*args, **kwargs) 101 if func.name != “init” or is_client_mode_enabled_by_default: 102 return getattr(ray, func.name)(*args, **kwargs) → 103 return func(*args, **kwargs) File ~/anaconda3/envs/Xanadu/lib/python3.11/site-packages/ray/_private/worker.py:2755, in get(object_refs, timeout) 2749 raise ValueError( 2750 f"Invalid type of object refs, {type(object_refs)}, is given. " 2751 "‘object_refs’ must either be an ObjectRef or a list of ObjectRefs. " 2752 ) 2754 # TODO(ujvl): Consider how to allow user to retrieve the ready objects. → 2755 values, debugger_breakpoint = worker.get_objects(object_refs, timeout=timeout) 2756 for i, value in enumerate(values): 2757 if isinstance(value, RayError): File ~/anaconda3/envs/Xanadu/lib/python3.11/site-packages/ray/_private/worker.py:906, in Worker.get_objects(self, object_refs, timeout, return_exceptions) 904 global_worker.core_worker.dump_object_store_memory_usage() 905 if isinstance(value, RayTaskError): → 906 raise value.as_instanceof_cause() 907 else: 908 raise value RayTaskError(TypeError): ray::train_device() (pid=3643480, ip=128.111.58.29) File “/home/rahul/Photonic Neural Network/MrMustard/mrmustard/training/trainer.py”, line 181, in train_device final_cost = cost_fn() ^^^^^^^^^ File “/tmp/ipykernel_3641918/1782703836.py”, line 14, in cost_fn File “/home/rahul/Photonic Neural Network/MrMustard/mrmustard/lab/abstract/state.py”, line 616, in rshift return other.primal(self) ^^^^^^^^^^^^^^^^^^ File “/home/rahul/Photonic Neural Network/MrMustard/mrmustard/lab/circuit.py”, line 63, in primal state = op.primal(state) ^^^^^^^^^^^^^^^^ File “/home/rahul/Photonic Neural Network/MrMustard/mrmustard/lab/abstract/transformation.py”, line 85, in primal new_state = self._transform_gaussian(state, dual=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File “/home/rahul/Photonic Neural Network/MrMustard/mrmustard/lab/abstract/transformation.py”, line 115, in _transform_gaussian X, Y, d = self.XYd(allow_none=False) if not dual else self.XYd_dual(allow_none=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^ File “/home/rahul/Photonic Neural Network/MrMustard/mrmustard/lab/abstract/transformation.py”, line 235, in XYd Y = math.zeros_like(X) if self.Y_matrix is None else self.Y_matrix ^^^^^^^^^^^^^^^^^^ File “/home/rahul/Photonic Neural Network/MrMustard/mrmustard/math/backend_manager.py”, line 1224, in zeros_like return self._apply(“zeros_like”, (array,)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File “/home/rahul/Photonic Neural Network/MrMustard/mrmustard/math/backend_manager.py”, line 111, in _apply return attr(*args) ^^^^^^^^^^^ File “/home/rahul/Photonic Neural Network/MrMustard/mrmustard/math/backend_numpy.py”, line 382, in zeros_like return np.zeros(np.array(array).shape, dtype=array.dtype) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ TypeError: Cannot interpret ‘tf.float64’ as a data type
. I’ve forwarded your question to the MrMustard developers. Note that they may take a few days to get back to you because of the holidays next week.