The code below is triggering a AttributeError: can't set attribute. I'm still new to programming so am having a difficult time figuring out why this error is occurring. Any help is appreciated.
import cimcb_lite as cb
cv = cb.cross_val.kfold(model=cb.model.PLS_SIMPLS,X=XTknn,
Y=Ytrain,
param_dict={'n_components': [1,2,3,4,5]},
folds=5,
bootnum=100)
cv.run()
seeing this error
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
/var/folders/rs/f6nsd1894354_821jj157jnr0000gn/T/ipykernel_30013/1292624611.py in <module>
8
9 # run the cross validation
---> 10 cv.run()
11
/opt/anaconda3/lib/python3.9/site-packages/cimcb_lite/cross_val/kfold.py in run(self)
82 def run(self):
83 """Runs all functions prior to plot."""
---> 84 self.calc_ypred()
85 self.calc_stats()
86 if self.bootnum > 1:
/opt/anaconda3/lib/python3.9/site-packages/cimcb_lite/cross_val/kfold.py in calc_ypred(self)
55 model_i = self.model(**params_i)
56 # Full
---> 57 model_i.train(self.X, self.Y)
58 ypred_full_i = model_i.test(self.X)
59 self.ypred_full.append(ypred_full_i)
/opt/anaconda3/lib/python3.9/site-packages/cimcb_lite/model/PLS_SIMPLS.py in train(self, X, Y)
77 # Calculates and store attributes of PLS SIMPLS
78 Xscores, Yscores, Xloadings, Yloadings, Weights, Beta = self.pls_simpls(X, Y, ncomp=self.n_component)
---> 79 self.model.x_scores_ = Xscores
80 self.model.y_scores_ = Yscores
81 self.model.x_loadings_ = Xloadings
AttributeError: can't set attribute
Related
I am trying to get the shap values for the masked language modeling task using transformer. I get the error KeyError: 'label' for the code where I input a single data sample to get the explanation. My complete code and error trace are as follows:
import transformers
import shap
from transformers import RobertaTokenizer, RobertaForMaskedLM, pipeline
import torch
model = RobertaForMaskedLM.from_pretrained('microsoft/codebert-base-mlm')
tokenizer = RobertaTokenizer.from_pretrained('microsoft/codebert-base-mlm')
code_example = "if (x <mask> 10)"
fill_mask = pipeline('fill-mask', model=model, tokenizer=tokenizer)
explainer = shap.Explainer(fill_mask)
shap_values = explainer(['x {tokenizer.mask_token} 10'])
Following is the error trace
KeyError Traceback (most recent call last)
[<ipython-input-12-bb3832d1772d>](https://localhost:8080/#) in <module>
6 # explain the model on two sample inputs
7 explainer = shap.Explainer(fill_mask)
----> 8 shap_values = explainer(['x {tokenizer.mask_token} 10'])
9 print(shap_values)
10 # visualize the first prediction's explanation for the POSITIVE output class
5 frames
[/usr/local/lib/python3.7/dist-packages/shap/explainers/_partition.py](https://localhost:8080/#) in __call__(self, max_evals, fixed_context, main_effects, error_bounds, batch_size, outputs, silent, *args)
136 return super().__call__(
137 *args, max_evals=max_evals, fixed_context=fixed_context, main_effects=main_effects, error_bounds=error_bounds, batch_size=batch_size,
--> 138 outputs=outputs, silent=silent
139 )
140
[/usr/local/lib/python3.7/dist-packages/shap/explainers/_explainer.py](https://localhost:8080/#) in __call__(self, max_evals, main_effects, error_bounds, batch_size, outputs, silent, *args, **kwargs)
266 row_result = self.explain_row(
267 *row_args, max_evals=max_evals, main_effects=main_effects, error_bounds=error_bounds,
--> 268 batch_size=batch_size, outputs=outputs, silent=silent, **kwargs
269 )
270 values.append(row_result.get("values", None))
[/usr/local/lib/python3.7/dist-packages/shap/explainers/_partition.py](https://localhost:8080/#) in explain_row(self, max_evals, main_effects, error_bounds, batch_size, outputs, silent, fixed_context, *row_args)
159 # if not fixed background or no base value assigned then compute base value for a row
160 if self._curr_base_value is None or not getattr(self.masker, "fixed_background", False):
--> 161 self._curr_base_value = fm(m00.reshape(1, -1), zero_index=0)[0] # the zero index param tells the masked model what the baseline is
162 f11 = fm(~m00.reshape(1, -1))[0]
163
[/usr/local/lib/python3.7/dist-packages/shap/utils/_masked_model.py](https://localhost:8080/#) in __call__(self, masks, zero_index, batch_size)
65
66 else:
---> 67 return self._full_masking_call(masks, batch_size=batch_size)
68
69 def _full_masking_call(self, masks, zero_index=None, batch_size=None):
[/usr/local/lib/python3.7/dist-packages/shap/utils/_masked_model.py](https://localhost:8080/#) in _full_masking_call(self, masks, zero_index, batch_size)
142
143 joined_masked_inputs = tuple([np.concatenate(v) for v in all_masked_inputs])
--> 144 outputs = self.model(*joined_masked_inputs)
145 _assert_output_input_match(joined_masked_inputs, outputs)
146 all_outputs.append(outputs)
[/usr/local/lib/python3.7/dist-packages/shap/models/_transformers_pipeline.py](https://localhost:8080/#) in __call__(self, strings)
33 val = [val]
34 for obj in val:
---> 35 output[i, self.label2id[obj["label"]]] = sp.special.logit(obj["score"]) if self.rescale_to_logits else obj["score"]
36 return output
KeyError: 'label'
I installed pynput module (version 1.7.4) using this command: pip3 install pynput
I tried to import the module in my Jupyter-lab, which always ended up a failure. The error message looks like this:
AttributeError: dlsym(0x7f90f7d0c310, PyObjCObject_New): symbol not found
I tried to find previous questions but could not find one that could help me solve this issue. If someone can help me with dealing with this issue, that would be highly appreciated.
Just in case it would be necessary to figure out my issue, the entire error message is attached below:
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
/var/folders/l3/gg_2y0zx4zz2rqytp5sctpy80000gn/T/ipykernel_64397/3885633262.py in <module>
----> 1 import pynput
~/opt/anaconda3/envs/GE/lib/python3.9/site-packages/pynput/__init__.py in <module>
38
39
---> 40 from . import keyboard
41 from . import mouse
~/opt/anaconda3/envs/GE/lib/python3.9/site-packages/pynput/keyboard/__init__.py in <module>
29
30
---> 31 backend = backend(__name__)
32 KeyCode = backend.KeyCode
33 Key = backend.Key
~/opt/anaconda3/envs/GE/lib/python3.9/site-packages/pynput/_util/__init__.py in backend(package)
68 for module in modules:
69 try:
---> 70 return importlib.import_module('._' + module, package)
71 except ImportError as e:
72 errors.append(e)
~/opt/anaconda3/envs/GE/lib/python3.9/importlib/__init__.py in import_module(name, package)
125 break
126 level += 1
--> 127 return _bootstrap._gcd_import(name[level:], package, level)
128
129
~/opt/anaconda3/envs/GE/lib/python3.9/site-packages/pynput/keyboard/_darwin.py in <module>
49 NSSystemDefined)
50
---> 51 from pynput._util.darwin import (
52 get_unicode_to_keycode_map,
53 keycode_context,
~/opt/anaconda3/envs/GE/lib/python3.9/site-packages/pynput/_util/darwin.py in <module>
58 OBJC = ctypes.PyDLL(objc._objc.__file__)
59
---> 60 OBJC.PyObjCObject_New.restype = ctypes.py_object
61 OBJC.PyObjCObject_New.argtypes = [ctypes.c_void_p, ctypes.c_int, ctypes.c_int]
62
~/opt/anaconda3/envs/GE/lib/python3.9/ctypes/__init__.py in __getattr__(self, name)
393 if name.startswith('__') and name.endswith('__'):
394 raise AttributeError(name)
--> 395 func = self.__getitem__(name)
396 setattr(self, name, func)
397 return func
~/opt/anaconda3/envs/GE/lib/python3.9/ctypes/__init__.py in __getitem__(self, name_or_ordinal)
398
399 def __getitem__(self, name_or_ordinal):
--> 400 func = self._FuncPtr((name_or_ordinal, self))
401 if not isinstance(name_or_ordinal, int):
402 func.__name__ = name_or_ordinal
AttributeError: dlsym(0x7f90f7d0c310, PyObjCObject_New): symbol not found
https://github.com/moses-palmer/pynput/issues/420
The latest Pyobjc breaks pynput. Downgrading it to 7.3 fixes this issue.
I'm new to Anaconda. I tried to execute Pytorch Adversarial Neural Network in anaconda. It shows some error that I have no clue. Here is the code that downloads dataset
# MNIST Test dataset and dataloader declaration
test_loader = torch.utils.data.DataLoader(datasets.MNIST('../data', train=False, download=True, transform=transforms.Compose([
transforms.ToTensor(),])),batch_size=1, shuffle=True)
This is the error message I got :
PermissionError Traceback (most recent call last)
<ipython-input-4-59310f6a37f8> in <module>
41
42 # MNIST Test dataset and dataloader declaration
43 test_loader = torch.utils.data.DataLoader(datasets.MNIST('../data', train=False, download=True, transform=transforms.Compose([transforms.ToTensor(),])),batch_size=1, shuffle=True)
44
45 # Define what device we are using
~\anaconda3\lib\site-packages\torchvision\datasets\mnist.py in __init__(self, root,
train,
transform, target_transform, download)
77
78 if download:
79 self.download()
80
81 if not self._check_exists():
~\anaconda3\lib\site-packages\torchvision\datasets\mnist.py in download(self)
138 return
139
140 os.makedirs(self.raw_folder, exist_ok=True)
141 os.makedirs(self.processed_folder, exist_ok=True)
142
~\anaconda3\lib\os.py in makedirs(name, mode, exist_ok)
211 if head and tail and not path.exists(head):
212 try:
213 makedirs(head, exist_ok=exist_ok)
214 except FileExistsError:
215 # Defeats race condition when another thread created the path
~\anaconda3\lib\os.py in makedirs(name, mode, exist_ok)
211 if head and tail and not path.exists(head):
212 try:
213 makedirs(head, exist_ok=exist_ok)
214 except FileExistsError:
215 # Defeats race condition when another thread created the path
~\anaconda3\lib\os.py in makedirs(name, mode, exist_ok)
221 return
222 try:
223 mkdir(name, mode)
224 except OSError:
225 # Cannot rely on checking for EEXIST, since the operating system
PermissionError: [WinError 5] Access is denied: '../data' .
How about changing the '../data' to another directory, like '/Users/***/Downloads/data' or somewhere else.
I have the following code for ingesting data into Azure Data Explore using Python in Databricks:
df=pd.DataFrame({"StringCol": ["123ABC", 'B123', 'C123','D123'],"NumberCol": [1,2,3,4],"DecimalCol": [1,2.2,3.3,4.4],"DateCol": ['1/1/20','2/2/20','3/3/30','4/4/20']})
ingestion_props = IngestionProperties(database=db, table='TestTable_DeleteMe')
connWrite.ingest_from_dataframe(df, ingestion_properties=ingestion_props)
This gives me the error:
BadRequest_SyntaxError', 'message': 'Request is invalid and cannot be executed
Earlier in my code I created a table using the same data types as this dummy pandas dataframe. Now I'm trying to load the data into the table. Full stack trace:
KustoServiceError Traceback (most recent call last)
<command-3953651275234016> in <module>
1 df=pd.DataFrame({"StringCol": ["123ABC", 'B123', 'C123','D123'],"NumberCol": [1,2,3,4],"DecimalCol": [1,2.2,3.3,4.4],"DateCol": ['1/1/20','2/2/20','3/3/30','4/4/20']})
2 ingestion_props = IngestionProperties(database=db, table='TestTable_DeleteMe')
----> 3 connWrite.ingest_from_dataframe(df, ingestion_properties=ingestion_props)
4
5 #adx_loadIntoTable(connWrite,db,df,'TestTable_DeleteMe')
/databricks/python/lib/python3.7/site-packages/azure/kusto/ingest/ingest_client.py in ingest_from_dataframe(self, df, ingestion_properties)
52 ingestion_properties.format = DataFormat.CSV
53
---> 54 self.ingest_from_file(temp_file_path, ingestion_properties)
55
56 os.unlink(temp_file_path)
/databricks/python/lib/python3.7/site-packages/azure/kusto/ingest/ingest_client.py in ingest_from_file(self, file_descriptor, ingestion_properties)
64 :param azure.kusto.ingest.IngestionProperties ingestion_properties: Ingestion properties.
65 """
---> 66 containers = self._resource_manager.get_containers()
67
68 if isinstance(file_descriptor, FileDescriptor):
/databricks/python/lib/python3.7/site-packages/azure/kusto/ingest/_resource_manager.py in get_containers(self)
121
122 def get_containers(self) -> List[_ResourceUri]:
--> 123 self._refresh_ingest_client_resources()
124 return self._ingest_client_resources.containers
125
/databricks/python/lib/python3.7/site-packages/azure/kusto/ingest/_resource_manager.py in _refresh_ingest_client_resources(self)
79 or not self._ingest_client_resources.is_applicable()
80 ):
---> 81 self._ingest_client_resources = self._get_ingest_client_resources_from_service()
82 self._ingest_client_resources_last_update = datetime.utcnow()
83
/databricks/python/lib/python3.7/site-packages/azure/kusto/ingest/_resource_manager.py in _get_ingest_client_resources_from_service(self)
86
87 def _get_ingest_client_resources_from_service(self):
---> 88 table = self._kusto_client.execute("NetDefaultDB", ".get ingestion resources").primary_results[0]
89
90 secured_ready_for_aggregation_queues = self._get_resource_by_name(table, "SecuredReadyForAggregationQueue")
/databricks/python/lib/python3.7/site-packages/azure/kusto/data/client.py in execute(self, database, query, properties)
553 query = query.strip()
554 if query.startswith("."):
--> 555 return self.execute_mgmt(database, query, properties)
556 return self.execute_query(database, query, properties)
557
/databricks/python/lib/python3.7/site-packages/azure/kusto/data/client.py in execute_mgmt(self, database, query, properties)
578 :rtype: azure.kusto.data.response.KustoResponseDataSet
579 """
--> 580 return self._execute(self._mgmt_endpoint, database, query, None, KustoClient._mgmt_default_timeout, properties)
581
582 def execute_streaming_ingest(
/databricks/python/lib/python3.7/site-packages/azure/kusto/data/client.py in _execute(self, endpoint, database, query, payload, timeout, properties)
654 )
655
--> 656 raise KustoServiceError([response.json()], response)
KustoServiceError: (KustoServiceError(...), [{'error': {'code': 'BadRequest_SyntaxError', 'message': 'Request is invalid and cannot be executed.', '#type': 'Kusto.Data.Exceptions.SyntaxException', '#message': "Syntax error: Query could not be parsed: . Query: '.get ingestion resources'", '#context': {'timestamp': '2020-06-27T21:44:48.0697658Z', 'serviceAlias': 'USCPIRSTASADE01', 'machineName': 'KEngine000000', 'processName': 'Kusto.WinSvc.Svc', 'processId': 7124, 'threadId': 7240, 'appDomainName': 'Kusto.WinSvc.Svc.exe', 'clientRequestId': 'KPC.execute;0c2173bf-ea69-4253-bbaf-0203f3aa298c', 'activityId': 'cf41c806-8e15-458e-b388-386613f63952', 'subActivityId': 'df366667-ca8d-487b-a281-723f696a8f68', 'activityType': 'DN.FE.ExecuteControlCommand', 'parentActivityId': 'f8cd0bb8-04e9-48cf-8a84-8b16e1e24197', 'activityStack': '(Activity stack: CRID=KPC.execute;0c2173bf-ea69-4253-bbaf-0203f3aa298c ARID=cf41c806-8e15-458e-b388-386613f63952 > DN.Admin.Client.ExecuteControlCommand/7271d9ec-2adf-4714-b19e-69495ad80d65 > P.WCF.Service.ExecuteControlCommandInternal..IAdminClientServiceCommunicationContract/f8cd0bb8-04e9-48cf-8a84-8b16e1e24197 > DN.FE.ExecuteControlCommand/df366667-ca8d-487b-a281-723f696a8f68)'}, '#permanent': True}}])
It is likely that your connection has the engine endpoint instead of the data management endpoint. Can you check that the connection to the cluster starts with "ingest-"? See here an example:
client = KustoIngestClient("https://ingest-{cluster_name}.kusto.windows.net")
when i try to run this code,
ftr_mtrx_custmr, features_defs = ft.dfs(entities=entities,
relationships=relationship,
target_entity="transactions")
i get such error，
490 featuretools.entityset - WARNING index session_id not found in dataframe, creating new integer column
KeyError Traceback (most recent call last)
<ipython-input-82-d467a36d5254> in <module>()
1 ftr_mtrx_custmr, features_defs = ft.dfs(entities=entities,
2 relationships=relationshp,
----> 3 target_entity="transactions")
4 frames
/usr/local/lib/python3.6/dist-packages/featuretools/utils/entry_point.py
in function_wrapper(*args, **kwargs)
38 ep.on_error(error=e,
39 runtime=runtime)
---> 40 raise e
41
42 # send return value
/usr/local/lib/python3.6/dist-packages/featuretools/utils/entry_point.py
in function_wrapper(*args, **kwargs)
30 # call function
31 start = time.time()
---> 32 return_value = func(*args, **kwargs)
33 runtime = time.time() - start
34 except Exception as e:
/usr/local/lib/python3.6/dist-packages/featuretools/synthesis/dfs.py
in dfs(entities, relationships, entityset, target_entity, cutoff_time,
instance_ids, agg_primitives, trans_primitives,
groupby_trans_primitives, allowed_paths, max_depth, ignore_entities,
ignore_variables, primitive_options, seed_features, drop_contains,
drop_exact, where_primitives, max_features, cutoff_time_in_index,
save_progress, features_only, training_window, approximate,
chunk_size, n_jobs, dask_kwargs, verbose, return_variable_types,
progress_callback)
225 '''
226 if not isinstance(entityset, EntitySet):
--> 227 entityset = EntitySet("dfs", entities, relationships)
228
229 dfs_object = DeepFeatureSynthesis(target_entity, entityset,
/usr/local/lib/python3.6/dist-packages/featuretools/entityset/entityset.py
in init(self, id, entities, relationships)
83
84 for relationship in relationships:
---> 85 parent_variable = self[relationship[0]][relationship[1]]
86 child_variable = self[relationship[2]][relationship[3]]
87 self.add_relationship(Relationship(parent_variable,
/usr/local/lib/python3.6/dist-packages/featuretools/entityset/entityset.py
in getitem(self, entity_id)
124 return self.entity_dict[entity_id]
125 name = self.id or "entity set"
--> 126 raise KeyError('Entity %s does not exist in %s' % (entity_id, name))
127
128 #property
however, this returned KeyError : 'Entity c does not exist in dfs'
any idea what's wrong with my code?