File Not Found error in Jupyter Notebook when i use auto.assign_causal_mechnism
bernddude opened this issue · comments
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my model is working fine, however when i try to use the auto assignment feature
i get a stubborn File Not found error
Expected behavior
The same code ran fine before, is there any system variable setting required
This is a new notebook
Version information:
- DoWhy version [e.g. 0.7]
Additional context
None
Hi,
can you post the error stack?
Thank you so much for your quick response .... is this what you were looking for ?
FileNotFoundError Traceback (most recent call last)
Cell In[258], line 25
23 print('use auto')
24 q = gcm.auto.AssignmentQuality(Quality)
---> 25 gcm.auto.assign_causal_mechanisms(Icausal_model,based_on = dfOutS[list(nodesG)],quality=q,override_models=True)
27 # 2. Fitting the PCM to the data:
28 if classification:
File ~/anaconda3/envs/loki/lib/python3.9/site-packages/dowhy/gcm/auto.py:294, in assign_causal_mechanisms(causal_model, based_on, quality, override_models)
291 validate_causal_model_assignment(causal_model.graph, node)
292 continue
--> 294 model_performances = assign_causal_mechanism_node(causal_model, node, based_on, quality)
296 if is_root_node(causal_model.graph, node):
297 auto_assignment_summary.add_node_log_message(
298 node,
299 "Node %s is a root node. Therefore, assigning '%s' to the node representing the marginal distribution."
300 % (node, causal_model.causal_mechanism(node)),
301 )
File ~/anaconda3/envs/loki/lib/python3.9/site-packages/dowhy/gcm/auto.py:362, in assign_causal_mechanism_node(causal_model, node, based_on, quality)
359 else:
360 node_data = based_on[node].to_numpy()
--> 362 best_model, model_performances = select_model(
363 based_on[get_ordered_predecessors(causal_model.graph, node)].to_numpy(),
...
69 )
71 # Send sys_path and make sure the current directory will not be changed
72 d["sys_path"] = [p if p != "" else process.ORIGINAL_DIR for p in sys.path]
Overall Error stack
"name": "FileNotFoundError",
"message": "[Errno 2] No such file or directory",
"stack": "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)\nCell \u001b[0;32mIn[258], line 25\u001b[0m\n\u001b[1;32m 23\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124muse auto\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m 24\u001b[0m q \u001b[38;5;241m=\u001b[39m gcm\u001b[38;5;241m.\u001b[39mauto\u001b[38;5;241m.\u001b[39mAssignmentQuality(Quality)\n\u001b[0;32m---> 25\u001b[0m \u001b[43mgcm\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mauto\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43massign_causal_mechanisms\u001b[49m\u001b[43m(\u001b[49m\u001b[43mIcausal_model\u001b[49m\u001b[43m,\u001b[49m\u001b[43mbased_on\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mdfOutS\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;28;43mlist\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mnodesG\u001b[49m\u001b[43m)\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43mquality\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mq\u001b[49m\u001b[43m,\u001b[49m\u001b[43moverride_models\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[1;32m 27\u001b[0m \u001b[38;5;66;03m# 2. Fitting the PCM to the data:\u001b[39;00m\n\u001b[1;32m 28\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m classification: \n\nFile \u001b[0;32m~/anaconda3/envs/loki/lib/python3.9/site-packages/dowhy/gcm/auto.py:294\u001b[0m, in \u001b[0;36massign_causal_mechanisms\u001b[0;34m(causal_model, based_on, quality, override_models)\u001b[0m\n\u001b[1;32m 291\u001b[0m validate_causal_model_assignment(causal_model\u001b[38;5;241m.\u001b[39mgraph, node)\n\u001b[1;32m 292\u001b[0m \u001b[38;5;28;01mcontinue\u001b[39;00m\n\u001b[0;32m--> 294\u001b[0m model_performances \u001b[38;5;241m=\u001b[39m \u001b[43massign_causal_mechanism_node\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcausal_model\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnode\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbased_on\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mquality\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 296\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m is_root_node(causal_model\u001b[38;5;241m.\u001b[39mgraph, node):\n\u001b[1;32m 297\u001b[0m auto_assignment_summary\u001b[38;5;241m.\u001b[39madd_node_log_message(\n\u001b[1;32m 298\u001b[0m node,\n\u001b[1;32m 299\u001b[0m \u001b[38;5;124m"\u001b[39m\u001b[38;5;124mNode \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m is a root node. Therefore, assigning \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m to the node representing the marginal distribution.\u001b[39m\u001b[38;5;124m"\u001b[39m\n\u001b[1;32m 300\u001b[0m \u001b[38;5;241m%\u001b[39m (node, causal_model\u001b[38;5;241m.\u001b[39mcausal_mechanism(node)),\n\u001b[1;32m 301\u001b[0m )\n\nFile \u001b[0;32m~/anaconda3/envs/loki/lib/python3.9/site-packages/dowhy/gcm/auto.py:362\u001b[0m, in \u001b[0;36massign_causal_mechanism_node\u001b[0;34m(causal_model, node, based_on, quality)\u001b[0m\n\u001b[1;32m 359\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 360\u001b[0m node_data \u001b[38;5;241m=\u001b[39m based_on[node]\u001b[38;5;241m.\u001b[39mto_numpy()\n\u001b[0;32m--> 362\u001b[0m best_model, model_performances \u001b[38;5;241m=\u001b[39m \u001b[43mselect_model\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 363\u001b[0m \u001b[43m \u001b[49m\u001b[43mbased_on\u001b[49m\u001b[43m[\u001b[49m\u001b[43mget_ordered_predecessors\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcausal_model\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgraph\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnode\u001b[49m\u001b[43m)\u001b[49m\u001b[43m]\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mto_numpy\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 364\u001b[0m \u001b[43m \u001b[49m\u001b[43mnode_data\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 365\u001b[0m \u001b[43m \u001b[49m\u001b[43mquality\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 366\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 368\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(best_model, ClassificationModel):\n\u001b[1;32m 369\u001b[0m causal_model\u001b[38;5;241m.\u001b[39mset_causal_mechanism(node, ClassifierFCM(best_model))\n\nFile \u001b[0;32m~/anaconda3/envs/loki/lib/python3.9/site-packages/dowhy/gcm/auto.py:417\u001b[0m, in \u001b[0;36mselect_model\u001b[0;34m(X, Y, model_selection_quality)\u001b[0m\n\u001b[1;32m 415\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m best_model(), model_performances\n\u001b[1;32m 416\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 417\u001b[0m best_model, model_performances \u001b[38;5;241m=\u001b[39m \u001b[43mfind_best_model\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 418\u001b[0m \u001b[43m \u001b[49m\u001b[43mlist_of_regressor\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mX\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mY\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmodel_selection_splits\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmodel_selection_splits\u001b[49m\n\u001b[1;32m 419\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 420\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m best_model(), model_performances\n\nFile \u001b[0;32m~/anaconda3/envs/loki/lib/python3.9/site-packages/dowhy/gcm/auto.py:543\u001b[0m, in \u001b[0;36mfind_best_model\u001b[0;34m(prediction_model_factories, X, Y, metric, max_samples_per_split, model_selection_splits, n_jobs)\u001b[0m\n\u001b[1;32m 540\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mfloat\u001b[39m(np\u001b[38;5;241m.\u001b[39mmean(average_result))\n\u001b[1;32m 542\u001b[0m random_seeds \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mrandom\u001b[38;5;241m.\u001b[39mrandint(np\u001b[38;5;241m.\u001b[39miinfo(np\u001b[38;5;241m.\u001b[39mint32)\u001b[38;5;241m.\u001b[39mmax, size\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mlen\u001b[39m(prediction_model_factories))\n\u001b[0;32m--> 543\u001b[0m average_metric_scores \u001b[38;5;241m=\u001b[39m \u001b[43mParallel\u001b[49m\u001b[43m(\u001b[49m\u001b[43mn_jobs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mn_jobs\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 544\u001b[0m \u001b[43m \u001b[49m\u001b[43mdelayed\u001b[49m\u001b[43m(\u001b[49m\u001b[43mestimate_average_score\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\u001b[43mprediction_model_factory\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mint\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mrandom_seed\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 545\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mprediction_model_factory\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrandom_seed\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mzip\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mprediction_model_factories\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrandom_seeds\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 546\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 547\u001b[0m sorted_results \u001b[38;5;241m=\u001b[39m \u001b[38;5;28msorted\u001b[39m(\n\u001b[1;32m 548\u001b[0m \u001b[38;5;28mzip\u001b[39m(prediction_model_factories, average_metric_scores, [metric_name] \u001b[38;5;241m*\u001b[39m \u001b[38;5;28mlen\u001b[39m(prediction_model_factories)),\n\u001b[1;32m 549\u001b[0m key\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mlambda\u001b[39;00m x: x[\u001b[38;5;241m1\u001b[39m],\n\u001b[1;32m 550\u001b[0m )\n\u001b[1;32m 552\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m sorted_results[\u001b[38;5;241m0\u001b[39m][\u001b[38;5;241m0\u001b[39m], sorted_results\n\nFile \u001b[0;32m~/anaconda3/envs/loki/lib/python3.9/site-packages/joblib/parallel.py:1950\u001b[0m, in \u001b[0;36mParallel.call\u001b[0;34m(self, iterable)\u001b[0m\n\u001b[1;32m 1944\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_call_ref \u001b[38;5;241m=\u001b[39m weakref\u001b[38;5;241m.\u001b[39mref(output)\n\u001b[1;32m 1946\u001b[0m \u001b[38;5;66;03m# The first item from the output is blank, but it makes the interpreter\u001b[39;00m\n\u001b[1;32m 1947\u001b[0m \u001b[38;5;66;03m# progress until it enters the Try/Except block of the generator and\u001b[39;00m\n\u001b[1;32m 1948\u001b[0m \u001b[38;5;66;03m# reach the first yield statement. This starts the aynchronous\u001b[39;00m\n\u001b[1;32m 1949\u001b[0m \u001b[38;5;66;03m# dispatch of the tasks to the workers.\u001b[39;00m\n\u001b[0;32m-> 1950\u001b[0m \u001b[38;5;28;43mnext\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43moutput\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1952\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m output \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mreturn_generator \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28mlist\u001b[39m(output)\n\nFile \u001b[0;32m~/anaconda3/envs/loki/lib/python3.9/site-packages/joblib/parallel.py:1588\u001b[0m, in \u001b[0;36mParallel._get_outputs\u001b[0;34m(self, iterator, pre_dispatch)\u001b[0m\n\u001b[1;32m 1586\u001b[0m detach_generator_exit \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[1;32m 1587\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 1588\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_start\u001b[49m\u001b[43m(\u001b[49m\u001b[43miterator\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpre_dispatch\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1589\u001b[0m \u001b[38;5;66;03m# first yield returns None, for internal use only. This ensures\u001b[39;00m\n\u001b[1;32m 1590\u001b[0m \u001b[38;5;66;03m# that we enter the try/except block and start dispatching the\u001b[39;00m\n\u001b[1;32m 1591\u001b[0m \u001b[38;5;66;03m# tasks.\u001b[39;00m\n\u001b[1;32m 1592\u001b[0m \u001b[38;5;28;01myield\u001b[39;00m\n\nFile \u001b[0;32m~/anaconda3/envs/loki/lib/python3.9/site-packages/joblib/parallel.py:1571\u001b[0m, in \u001b[0;36mParallel._start\u001b[0;34m(self, iterator, pre_dispatch)\u001b[0m\n\u001b[1;32m 1562\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_start\u001b[39m(\u001b[38;5;28mself\u001b[39m, iterator, pre_dispatch):\n\u001b[1;32m 1563\u001b[0m \u001b[38;5;66;03m# Only set self._iterating to True if at least a batch\u001b[39;00m\n\u001b[1;32m 1564\u001b[0m \u001b[38;5;66;03m# was dispatched. In particular this covers the edge\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 1568\u001b[0m \u001b[38;5;66;03m# was very quick and its callback already dispatched all the\u001b[39;00m\n\u001b[1;32m 1569\u001b[0m \u001b[38;5;66;03m# remaining jobs.\u001b[39;00m\n\u001b[1;32m 1570\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_iterating \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[0;32m-> 1571\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdispatch_one_batch\u001b[49m\u001b[43m(\u001b[49m\u001b[43miterator\u001b[49m\u001b[43m)\u001b[49m:\n\u001b[1;32m 1572\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_iterating \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_original_iterator \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 1574\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdispatch_one_batch(iterator):\n\nFile \u001b[0;32m~/anaconda3/envs/loki/lib/python3.9/site-packages/joblib/parallel.py:1462\u001b[0m, in \u001b[0;36mParallel.dispatch_one_batch\u001b[0;34m(self, iterator)\u001b[0m\n\u001b[1;32m 1460\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[1;32m 1461\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1462\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_dispatch\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtasks\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1463\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m\n\nFile \u001b[0;32m~/anaconda3/envs/loki/lib/python3.9/site-packages/joblib/parallel.py:1384\u001b[0m, in \u001b[0;36mParallel._dispatch\u001b[0;34m(self, batch)\u001b[0m\n\u001b[1;32m 1379\u001b[0m batch_tracker \u001b[38;5;241m=\u001b[39m BatchCompletionCallBack(\n\u001b[1;32m 1380\u001b[0m dispatch_timestamp, batch_size, \u001b[38;5;28mself\u001b[39m\n\u001b[1;32m 1381\u001b[0m )\n\u001b[1;32m 1382\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_jobs\u001b[38;5;241m.\u001b[39mappend(batch_tracker)\n\u001b[0;32m-> 1384\u001b[0m job \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_backend\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mapply_async\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbatch\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcallback\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbatch_tracker\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1385\u001b[0m batch_tracker\u001b[38;5;241m.\u001b[39mregister_job(job)\n\nFile \u001b[0;32m~/anaconda3/envs/loki/lib/python3.9/site-packages/joblib/_parallel_backends.py:600\u001b[0m, in \u001b[0;36mLokyBackend.apply_async\u001b[0;34m(self, func, callback)\u001b[0m\n\u001b[1;32m 598\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mapply_async\u001b[39m(\u001b[38;5;28mself\u001b[39m, func, callback\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m):\n\u001b[1;32m 599\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m"""Schedule a func to be run"""\u001b[39;00m\n\u001b[0;32m--> 600\u001b[0m future \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_workers\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msubmit\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfunc\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 601\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m callback \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 602\u001b[0m future\u001b[38;5;241m.\u001b[39madd_done_callback(callback)\n\nFile \u001b[0;32m~/anaconda3/envs/loki/lib/python3.9/site-packages/joblib/externals/loky/reusable_executor.py:225\u001b[0m, in \u001b[0;36m_ReusablePoolExecutor.submit\u001b[0;34m(self, fn, args, kwargs)\u001b[0m\n\u001b[1;32m 223\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21msubmit\u001b[39m(\u001b[38;5;28mself\u001b[39m, fn, \u001b[38;5;241m\u001b[39margs, \u001b[38;5;241m\u001b[39m\u001b[38;5;241m\u001b[39mkwargs):\n\u001b[1;32m 224\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_submit_resize_lock:\n\u001b[0;32m--> 225\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msubmit\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfn\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\nFile \u001b[0;32m~/anaconda3/envs/loki/lib/python3.9/site-packages/joblib/externals/loky/process_executor.py:1248\u001b[0m, in \u001b[0;36mProcessPoolExecutor.submit\u001b[0;34m(self, fn, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1245\u001b[0m \u001b[38;5;66;03m# Wake up queue management thread\u001b[39;00m\n\u001b[1;32m 1246\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_executor_manager_thread_wakeup\u001b[38;5;241m.\u001b[39mwakeup()\n\u001b[0;32m-> 1248\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_ensure_executor_running\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1249\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m f\n\nFile \u001b[0;32m~/anaconda3/envs/loki/lib/python3.9/site-packages/joblib/externals/loky/process_executor.py:1220\u001b[0m, in \u001b[0;36mProcessPoolExecutor._ensure_executor_running\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1218\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_processes_management_lock:\n\u001b[1;32m 1219\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_processes) \u001b[38;5;241m!=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_max_workers:\n\u001b[0;32m-> 1220\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_adjust_process_count\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1221\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_start_executor_manager_thread()\n\nFile \u001b[0;32m~/anaconda3/envs/loki/lib/python3.9/site-packages/joblib/externals/loky/process_executor.py:1209\u001b[0m, in \u001b[0;36mProcessPoolExecutor._adjust_process_count\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1207\u001b[0m p \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_context\u001b[38;5;241m.\u001b[39mProcess(target\u001b[38;5;241m=\u001b[39m_process_worker, args\u001b[38;5;241m=\u001b[39margs)\n\u001b[1;32m 1208\u001b[0m p\u001b[38;5;241m.\u001b[39m_worker_exit_lock \u001b[38;5;241m=\u001b[39m worker_exit_lock\n\u001b[0;32m-> 1209\u001b[0m \u001b[43mp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstart\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1210\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_processes[p\u001b[38;5;241m.\u001b[39mpid] \u001b[38;5;241m=\u001b[39m p\n\u001b[1;32m 1211\u001b[0m mp\u001b[38;5;241m.\u001b[39mutil\u001b[38;5;241m.\u001b[39mdebug(\n\u001b[1;32m 1212\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m"\u001b[39m\u001b[38;5;124mAdjusted process count to \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_max_workers\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m: \u001b[39m\u001b[38;5;124m"\u001b[39m\n\u001b[1;32m 1213\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00m[(p\u001b[38;5;241m.\u001b[39mname,\u001b[38;5;250m \u001b[39mpid)\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mfor\u001b[39;00m\u001b[38;5;250m \u001b[39mpid,\u001b[38;5;250m \u001b[39mp\u001b[38;5;250m \u001b[39m\u001b[38;5;129;01min\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_processes\u001b[38;5;241m.\u001b[39mitems()]\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m"\u001b[39m\n\u001b[1;32m 1214\u001b[0m )\n\nFile \u001b[0;32m~/anaconda3/envs/loki/lib/python3.9/multiprocessing/process.py:121\u001b[0m, in \u001b[0;36mBaseProcess.start\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 118\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m _current_process\u001b[38;5;241m.\u001b[39m_config\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdaemon\u001b[39m\u001b[38;5;124m'\u001b[39m), [\\n\u001b1;32m 119\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdaemonic processes are not allowed to have children\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 120\u001b[0m _cleanup()\n\u001b[0;32m--> 121\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_popen \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_Popen\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 122\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_sentinel \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_popen\u001b[38;5;241m.\u001b[39msentinel\n\u001b[1;32m 123\u001b[0m \u001b[38;5;66;03m# Avoid a refcycle if the target function holds an indirect\u001b[39;00m\n\u001b[1;32m 124\u001b[0m \u001b[38;5;66;03m# reference to the process object (see bpo-30775)\u001b[39;00m\n\nFile \u001b[0;32m~/anaconda3/envs/loki/lib/python3.9/site-packages/joblib/externals/loky/backend/process.py:45\u001b[0m, in \u001b[0;36mLokyProcess._Popen\u001b[0;34m(process_obj)\u001b[0m\n\u001b[1;32m 43\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 44\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mpopen_loky_posix\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m Popen\n\u001b[0;32m---> 45\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mPopen\u001b[49m\u001b[43m(\u001b[49m\u001b[43mprocess_obj\u001b[49m\u001b[43m)\u001b[49m\n\nFile \u001b[0;32m~/anaconda3/envs/loki/lib/python3.9/site-packages/joblib/externals/loky/backend/popen_loky_posix.py:48\u001b[0m, in \u001b[0;36mPopen.init\u001b[0;34m(self, process_obj)\u001b[0m\n\u001b[1;32m 46\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mreturncode \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 47\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_fds \u001b[38;5;241m=\u001b[39m []\n\u001b[0;32m---> 48\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_launch\u001b[49m\u001b[43m(\u001b[49m\u001b[43mprocess_obj\u001b[49m\u001b[43m)\u001b[49m\n\nFile \u001b[0;32m~/anaconda3/envs/loki/lib/python3.9/site-packages/joblib/externals/loky/backend/popen_loky_posix.py:99\u001b[0m, in \u001b[0;36mPopen._launch\u001b[0;34m(self, process_obj)\u001b[0m\n\u001b[1;32m 97\u001b[0m set_spawning_popen(\u001b[38;5;28mself\u001b[39m)\n\u001b[1;32m 98\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m---> 99\u001b[0m prep_data \u001b[38;5;241m=\u001b[39m 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\u001b[0;32m~/anaconda3/envs/loki/lib/python3.9/site-packages/joblib/externals/loky/backend/spawn.py:68\u001b[0m, in \u001b[0;36mget_preparation_data\u001b[0;34m(name, init_main_module)\u001b[0m\n\u001b[1;32m 60\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m"""Return info about parent needed by child to unpickle process object."""\u001b[39;00m\n\u001b[1;32m 61\u001b[0m _check_not_importing_main()\n\u001b[1;32m 62\u001b[0m d \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mdict\u001b[39m(\n\u001b[1;32m 63\u001b[0m log_to_stderr\u001b[38;5;241m=\u001b[39mutil\u001b[38;5;241m.\u001b[39m_log_to_stderr,\n\u001b[1;32m 64\u001b[0m authkey\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mbytes\u001b[39m(process\u001b[38;5;241m.\u001b[39mcurrent_process()\u001b[38;5;241m.\u001b[39mauthkey),\n\u001b[1;32m 65\u001b[0m name\u001b[38;5;241m=\u001b[39mname,\n\u001b[1;32m 66\u001b[0m sys_argv\u001b[38;5;241m=\u001b[39msys\u001b[38;5;241m.\u001b[39margv,\n\u001b[1;32m 67\u001b[0m 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}
That is weird. Did you make sure to have the newest version installed (0.11.1)? And is it only happening when you call assign_causal_mechnism?
Otherwise, if you can provide a short executable code snippet to reproduce this, I can take a look (you can simply use some dummy data).
Thank you so much for your continued help. Yes i install the code yesterday (on this machine).
and so far the only problem i have is this specific error. All the rest of my code which i used on other machines before runs just fine (actually i am positive surprised about that) :)
To be totally honest i was expecting that its just some issue with global settings on my side, i was just wondering / hoping that somebody might have run into the same issue before ?
pls don't worry to much , its not the biggest issue.
i will likely poke around a bit more 9on the machine) , just have to finish some other work right and .
i will leave a message here in case i find the cause & a solution
Hello Patrick, i found out what was the issue . The problem was that my Jupyter environment was referring to a non existing current directory . I am assuming that might be b/c i was running the code on a network drive.
I solved the issue by explicitly assigning a working directory and it all worked fine.
The clue that gave it away was that when i ran os.getcwd() i got the same error
i just had a hunch that its something like that , which is why i checked on the working directory
Once i got that error , i was pretty sure what's the issue and how to solve it
thx again for your help and i hope this might help the next guy :)
Great, glad to hear it is working now! :)
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