I'm getting this error when running the third tutorial for tomorrow's release, wonderi

I'm also getting a similar error here: <div class="highlight highlight-source-pyth

Also getting it in Tutorial 4: <div class="highlight highlight-source-python notra

Missmatched pytorch version. See <a class="issue-link js-issue-link" data-error-text="

[0.1.1] Problem with KGLab Tutorial,about argilla-io/argilla

Comments (6)

ignacioct commented on August 17, 2024

I'm also getting a similar error here:

from torch_geometric.utils import k_hop_subgraph
# here we take all connected nodes with k hops
k = 1
node_idx, edge_index, mapping, edge_mask = k_hop_subgraph(
    node_idx, 
    k, 
    data.edge_index, 
    relabel_nodes=False
)

OSError: dlopen(/Users/ignaciotalaveracepeda/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch_sparse/_convert_cpu.so, 6): Symbol not found: __ZNK2at6Tensor6deviceEv
Referenced from: /Users/ignaciotalaveracepeda/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch_sparse/_convert_cpu.so
Expected in: /Users/ignaciotalaveracepeda/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch/lib/libtorch_cpu.dylib
in /Users/ignaciotalaveracepeda/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch_sparse/_convert_cpu.so
---------------------------------------------------------------------------
OSError                                   Traceback (most recent call last)
<ipython-input-36-eb2e6b5dea66> in <module>
----> 1 from torch_geometric.utils import k_hop_subgraph
      2 # here we take all connected nodes with k hops
      3 k = 1
      4 node_idx, edge_index, mapping, edge_mask = k_hop_subgraph(
      5     node_idx,

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch_geometric/__init__.py in <module>
      3 
      4 from .debug import is_debug_enabled, debug, set_debug
----> 5 import torch_geometric.data
      6 import torch_geometric.transforms
      7 import torch_geometric.utils

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch_geometric/data/__init__.py in <module>
----> 1 from .data import Data
      2 from .temporal import TemporalData
      3 from .batch import Batch
      4 from .dataset import Dataset
      5 from .in_memory_dataset import InMemoryDataset

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch_geometric/data/data.py in <module>
      6 import torch
      7 import torch_geometric
----> 8 from torch_sparse import coalesce, SparseTensor
      9 from torch_geometric.utils import (contains_isolated_nodes,
     10                                    contains_self_loops, is_undirected)

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch_sparse/__init__.py in <module>
     13 ]:
     14     torch.ops.load_library(importlib.machinery.PathFinder().find_spec(
---> 15         f'{library}_{suffix}', [osp.dirname(__file__)]).origin)
     16 
     17 if torch.cuda.is_available():  # pragma: no cover

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch/_ops.py in load_library(self, path)
    102             # static (global) initialization code in order to register custom
    103             # operators with the JIT.
--> 104             ctypes.CDLL(path)
    105         self.loaded_libraries.add(path)
    106 

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/ctypes/__init__.py in __init__(self, name, mode, handle, use_errno, use_last_error)
    362 
    363         if handle is None:
--> 364             self._handle = _dlopen(self._name, mode)
    365         else:
    366             self._handle = handle

OSError: dlopen(/Users/ignaciotalaveracepeda/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch_sparse/_convert_cpu.so, 6): Symbol not found: __ZNK2at6Tensor6deviceEv
  Referenced from: /Users/ignaciotalaveracepeda/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch_sparse/_convert_cpu.so
  Expected in: /Users/ignaciotalaveracepeda/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch/lib/libtorch_cpu.dylib
 in /Users/ignaciotalaveracepeda/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch_sparse/_convert_cpu.so

from argilla.

ignacioct commented on August 17, 2024

Also getting it in Tutorial 4:

import re

from snorkel.labeling import labeling_function, LabelingFunction
from snorkel.labeling.lf.nlp import nlp_labeling_function
from snorkel.preprocess import preprocessor
from snorkel.preprocess.nlp import SpacyPreprocessor

from textblob import TextBlob


ABSTAIN = -1
HAM = 0
SPAM = 1

# Keyword searches
@labeling_function()
def check(x):
    return SPAM if "check" in x.text.lower() else ABSTAIN

@labeling_function()
def check_out(x):
    return SPAM if "check out" in x.text.lower() else ABSTAIN

# Heuristics
@labeling_function()
def short_comment(x):
    """Ham comments are often short, such as 'cool video!'"""
    return HAM if len(x.text.split()) < 5 else ABSTAIN

# List of keywords
def keyword_lookup(x, keywords, label):
    if any(word in x.text.lower() for word in keywords):
        return label
    return ABSTAIN

def make_keyword_lf(keywords, label=SPAM):
    return LabelingFunction(
        name=f"keyword_{keywords[0]}",
        f=keyword_lookup,
        resources=dict(keywords=keywords, label=label),
    )

"""Spam comments talk about 'my channel', 'my video', etc."""
keyword_my = make_keyword_lf(keywords=["my"])

"""Spam comments ask users to subscribe to their channels."""
keyword_subscribe = make_keyword_lf(keywords=["subscribe"])

"""Spam comments post links to other channels."""
keyword_link = make_keyword_lf(keywords=["http"])

"""Spam comments make requests rather than commenting."""
keyword_please = make_keyword_lf(keywords=["please", "plz"])

"""Ham comments actually talk about the video's content."""
keyword_song = make_keyword_lf(keywords=["song"], label=HAM)


# Pattern matching with regex
@labeling_function()
def regex_check_out(x):
    return SPAM if re.search(r"check.*out", x.text, flags=re.I) else ABSTAIN


# Third party models (TextBlob and spaCy)
# TextBlob
@preprocessor(memoize=True)
def textblob_sentiment(x):
    scores = TextBlob(x.text)
    x.polarity = scores.sentiment.polarity
    x.subjectivity = scores.sentiment.subjectivity
    return x

@labeling_function(pre=[textblob_sentiment])
def textblob_subjectivity(x):
    return HAM if x.subjectivity >= 0.5 else ABSTAIN

@labeling_function(pre=[textblob_sentiment])
def textblob_polarity(x):
    return HAM if x.polarity >= 0.9 else ABSTAIN

# spaCy

# There are two different methods to use spaCy:
# Method 1:
spacy = SpacyPreprocessor(text_field="text", doc_field="doc", memoize=True)

@labeling_function(pre=[spacy])
def has_person(x):
    """Ham comments mention specific people and are short."""
    if len(x.doc) < 20 and any([ent.label_ == "PERSON" for ent in x.doc.ents]):
        return HAM
    else:
        return ABSTAIN
    
# Method 2:
@nlp_labeling_function()
def has_person_nlp(x):
    """Ham comments mention specific people."""
    if any([ent.label_ == "PERSON" for ent in x.doc.ents]):
        return HAM
    else:
        return ABSTAIN

OSError: dlopen(/Users/ignaciotalaveracepeda/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch_scatter/_scatter_cpu.so, 6): Symbol not found: __ZN2at8GradMode10is_enabledEv
Referenced from: /Users/ignaciotalaveracepeda/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch_scatter/_scatter_cpu.so
Expected in: /Users/ignaciotalaveracepeda/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch/lib/libtorch_cpu.dylib
in /Users/ignaciotalaveracepeda/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch_scatter/_scatter_cpu.so
---------------------------------------------------------------------------
OSError                                   Traceback (most recent call last)
<ipython-input-2-e815fa8a2051> in <module>
     84 # There are two different methods to use spaCy:
     85 # Method 1:
---> 86 spacy = SpacyPreprocessor(text_field="text", doc_field="doc", memoize=True)
     87 
     88 @labeling_function(pre=[spacy])

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/snorkel/preprocess/nlp.py in __init__(self, text_field, doc_field, language, disable, pre, memoize, memoize_key, gpu)
     70         if self.gpu:
     71             spacy.prefer_gpu()
---> 72         self._nlp = spacy.load(language, disable=disable or [])
     73 
     74     def run(self, text: str) -> FieldMap:  # type: ignore

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/spacy/__init__.py in load(name, vocab, disable, exclude, config)
     49     """
     50     return util.load_model(
---> 51         name, vocab=vocab, disable=disable, exclude=exclude, config=config
     52     )
     53 

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/spacy/util.py in load_model(name, vocab, disable, exclude, config)
    322             return get_lang_class(name.replace("blank:", ""))()
    323         if is_package(name):  # installed as package
--> 324             return load_model_from_package(name, **kwargs)
    325         if Path(name).exists():  # path to model data directory
    326             return load_model_from_path(Path(name), **kwargs)

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/spacy/util.py in load_model_from_package(name, vocab, disable, exclude, config)
    355     """
    356     cls = importlib.import_module(name)
--> 357     return cls.load(vocab=vocab, disable=disable, exclude=exclude, config=config)
    358 
    359 

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/en_core_web_sm/__init__.py in load(**overrides)
      8 
      9 def load(**overrides):
---> 10     return load_model_from_init_py(__file__, **overrides)

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/spacy/util.py in load_model_from_init_py(init_file, vocab, disable, exclude, config)
    520         disable=disable,
    521         exclude=exclude,
--> 522         config=config,
    523     )
    524 

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/spacy/util.py in load_model_from_path(model_path, meta, vocab, disable, exclude, config)
    389     config_path = model_path / "config.cfg"
    390     config = load_config(config_path, overrides=dict_to_dot(config))
--> 391     nlp = load_model_from_config(config, vocab=vocab, disable=disable, exclude=exclude)
    392     return nlp.from_disk(model_path, exclude=exclude)
    393 

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/spacy/util.py in load_model_from_config(config, vocab, disable, exclude, auto_fill, validate)
    432         exclude=exclude,
    433         auto_fill=auto_fill,
--> 434         validate=validate,
    435     )
    436     return nlp

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/spacy/language.py in from_config(cls, config, vocab, disable, exclude, meta, auto_fill, validate)
   1637         # then we would load them twice at runtime: once when we make from config,
   1638         # and then again when we load from disk.
-> 1639         nlp = lang_cls(vocab=vocab, create_tokenizer=create_tokenizer, meta=meta)
   1640         if after_creation is not None:
   1641             nlp = after_creation(nlp)

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/spacy/language.py in __init__(self, vocab, max_length, meta, create_tokenizer, batch_size, **kwargs)
    148         # points. The factory decorator applied to these functions takes care
    149         # of the rest.
--> 150         util.registry._entry_point_factories.get_all()
    151 
    152         self._config = DEFAULT_CONFIG.merge(self.default_config)

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/catalogue/__init__.py in get_all(self)
    106         result = {}
    107         if self.entry_points:
--> 108             result.update(self.get_entry_points())
    109         for keys, value in REGISTRY.items():
    110             if len(self.namespace) == len(keys) - 1 and all(

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/catalogue/__init__.py in get_entry_points(self)
    121         result = {}
    122         for entry_point in AVAILABLE_ENTRY_POINTS.get(self.entry_point_namespace, []):
--> 123             result[entry_point.name] = entry_point.load()
    124         return result
    125 

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/catalogue/_importlib_metadata/__init__.py in load(self)
     92         """
     93         match = self.pattern.match(self.value)
---> 94         module = import_module(match.group('module'))
     95         attrs = filter(None, (match.group('attr') or '').split('.'))
     96         return functools.reduce(getattr, attrs, module)

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/importlib/__init__.py in import_module(name, package)
    125                 break
    126             level += 1
--> 127     return _bootstrap._gcd_import(name[level:], package, level)
    128 
    129 

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/importlib/_bootstrap.py in _gcd_import(name, package, level)

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/importlib/_bootstrap.py in _find_and_load(name, import_)

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/importlib/_bootstrap.py in _find_and_load_unlocked(name, import_)

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/importlib/_bootstrap.py in _call_with_frames_removed(f, *args, **kwds)

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/importlib/_bootstrap.py in _gcd_import(name, package, level)

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/importlib/_bootstrap.py in _find_and_load(name, import_)

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/importlib/_bootstrap.py in _find_and_load_unlocked(name, import_)

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/importlib/_bootstrap.py in _load_unlocked(spec)

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/importlib/_bootstrap_external.py in exec_module(self, module)

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/importlib/_bootstrap.py in _call_with_frames_removed(f, *args, **kwds)

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/spacy_transformers/__init__.py in <module>
----> 1 from . import architectures
      2 from . import annotation_setters
      3 from . import span_getters
      4 from .layers import TransformerModel
      5 from .pipeline_component import Transformer, install_extensions

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/spacy_transformers/architectures.py in <module>
      3 from thinc.types import Ragged, Floats2d
      4 from spacy.tokens import Doc
----> 5 from .layers import TransformerModel, TransformerListener
      6 from .layers import trfs2arrays, split_trf_batch
      7 from .util import registry

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/spacy_transformers/layers/__init__.py in <module>
----> 1 from .listener import TransformerListener
      2 from .transformer_model import TransformerModel
      3 from .split_trf import split_trf_batch
      4 from .trfs2arrays import trfs2arrays
      5 

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/spacy_transformers/layers/listener.py in <module>
      2 from thinc.api import Model
      3 from spacy.tokens import Doc
----> 4 from ..data_classes import TransformerData
      5 
      6 

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/spacy_transformers/data_classes.py in <module>
      9 import srsly
     10 
---> 11 from .util import transpose_list
     12 from .align import get_token_positions
     13 

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/spacy_transformers/util.py in <module>
      2 from pathlib import Path
      3 import random
----> 4 from transformers import AutoModel, AutoTokenizer
      5 from transformers.tokenization_utils import BatchEncoding
      6 from transformers.tokenization_utils_fast import PreTrainedTokenizerFast

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/importlib/_bootstrap.py in _handle_fromlist(module, fromlist, import_, recursive)

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/transformers/__init__.py in __getattr__(self, name)
   2707             if name == "__version__":
   2708                 return __version__
-> 2709             return super().__getattr__(name)
   2710 
   2711     sys.modules[__name__] = _LazyModule(__name__, _import_structure)

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/transformers/file_utils.py in __getattr__(self, name)
   1820         elif name in self._class_to_module.keys():
   1821             module = self._get_module(self._class_to_module[name])
-> 1822             value = getattr(module, name)
   1823         else:
   1824             raise AttributeError(f"module {self.__name__} has no attribute {name}")

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/transformers/file_utils.py in __getattr__(self, name)
   1819             value = self._get_module(name)
   1820         elif name in self._class_to_module.keys():
-> 1821             module = self._get_module(self._class_to_module[name])
   1822             value = getattr(module, name)
   1823         else:

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/transformers/models/auto/__init__.py in _get_module(self, module_name)
    200 
    201         def _get_module(self, module_name: str):
--> 202             return importlib.import_module("." + module_name, self.__name__)
    203 
    204     sys.modules[__name__] = _LazyModule(__name__, _import_structure)

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/importlib/__init__.py in import_module(name, package)
    125                 break
    126             level += 1
--> 127     return _bootstrap._gcd_import(name[level:], package, level)
    128 
    129 

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/transformers/models/auto/modeling_auto.py in <module>
    251 )
    252 from ..t5.modeling_t5 import T5ForConditionalGeneration, T5Model
--> 253 from ..tapas.modeling_tapas import (
    254     TapasForMaskedLM,
    255     TapasForQuestionAnswering,

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/transformers/models/tapas/modeling_tapas.py in <module>
     49 # soft dependency
     50 if is_scatter_available():
---> 51     from torch_scatter import scatter
     52 
     53 logger = logging.get_logger(__name__)

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch_scatter/__init__.py in <module>
     12     for library in ['_version', '_scatter', '_segment_csr', '_segment_coo']:
     13         torch.ops.load_library(importlib.machinery.PathFinder().find_spec(
---> 14             f'{library}_{suffix}', [osp.dirname(__file__)]).origin)
     15 except AttributeError as e:
     16     if os.getenv('BUILD_DOCS', '0') != '1':

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch/_ops.py in load_library(self, path)
    102             # static (global) initialization code in order to register custom
    103             # operators with the JIT.
--> 104             ctypes.CDLL(path)
    105         self.loaded_libraries.add(path)
    106 

~/anaconda3/envs/rubrix0.1.1/lib/python3.7/ctypes/__init__.py in __init__(self, name, mode, handle, use_errno, use_last_error)
    362 
    363         if handle is None:
--> 364             self._handle = _dlopen(self._name, mode)
    365         else:
    366             self._handle = handle

OSError: dlopen(/Users/ignaciotalaveracepeda/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch_scatter/_scatter_cpu.so, 6): Symbol not found: __ZN2at8GradMode10is_enabledEv
  Referenced from: /Users/ignaciotalaveracepeda/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch_scatter/_scatter_cpu.so
  Expected in: /Users/ignaciotalaveracepeda/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch/lib/libtorch_cpu.dylib
 in /Users/ignaciotalaveracepeda/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch_scatter/_scatter_cpu.so

from argilla.

dvsrepo commented on August 17, 2024

It seems like an issue related to the c libraries for torch related dependencies, and in particular torch_scatter. I'd try to reinstall the deps from the kglab tutorial. Or uninstall, run the snorkel tutorial to see if that one is ok, and then try to debug the install for torch geometric deps. El jue., 24 jun. 2021 19:50, Ignacio Talavera ***@***.***> escribió:

…

I'm also getting a similar error here: from torch_geometric.utils import k_hop_subgraph# here we take all connected nodes with k hopsk = 1node_idx, edge_index, mapping, edge_mask = k_hop_subgraph( node_idx, k, data.edge_index, relabel_nodes=False ) OSError: dlopen(/Users/ignaciotalaveracepeda/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch_sparse/_convert_cpu.so, 6): Symbol not found: __ZNK2at6Tensor6deviceEv Referenced from: /Users/ignaciotalaveracepeda/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch_sparse/_convert_cpu.so Expected in: /Users/ignaciotalaveracepeda/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch/lib/libtorch_cpu.dylib in /Users/ignaciotalaveracepeda/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch_sparse/_convert_cpu.so --------------------------------------------------------------------------- OSError Traceback (most recent call last) <ipython-input-36-eb2e6b5dea66> in <module> ----> 1 from torch_geometric.utils import k_hop_subgraph 2 # here we take all connected nodes with k hops 3 k = 1 4 node_idx, edge_index, mapping, edge_mask = k_hop_subgraph( 5 node_idx, ~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch_geometric/__init__.py in <module> 3 4 from .debug import is_debug_enabled, debug, set_debug ----> 5 import torch_geometric.data 6 import torch_geometric.transforms 7 import torch_geometric.utils ~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch_geometric/data/__init__.py in <module> ----> 1 from .data import Data 2 from .temporal import TemporalData 3 from .batch import Batch 4 from .dataset import Dataset 5 from .in_memory_dataset import InMemoryDataset ~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch_geometric/data/data.py in <module> 6 import torch 7 import torch_geometric ----> 8 from torch_sparse import coalesce, SparseTensor 9 from torch_geometric.utils import (contains_isolated_nodes, 10 contains_self_loops, is_undirected) ~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch_sparse/__init__.py in <module> 13 ]: 14 torch.ops.load_library(importlib.machinery.PathFinder().find_spec( ---> 15 f'{library}_{suffix}', [osp.dirname(__file__)]).origin) 16 17 if torch.cuda.is_available(): # pragma: no cover ~/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch/_ops.py in load_library(self, path) 102 # static (global) initialization code in order to register custom 103 # operators with the JIT. --> 104 ctypes.CDLL(path) 105 self.loaded_libraries.add(path) 106 ~/anaconda3/envs/rubrix0.1.1/lib/python3.7/ctypes/__init__.py in __init__(self, name, mode, handle, use_errno, use_last_error) 362 363 if handle is None: --> 364 self._handle = _dlopen(self._name, mode) 365 else: 366 self._handle = handle OSError: dlopen(/Users/ignaciotalaveracepeda/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch_sparse/_convert_cpu.so, 6): Symbol not found: __ZNK2at6Tensor6deviceEv Referenced from: /Users/ignaciotalaveracepeda/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch_sparse/_convert_cpu.so Expected in: /Users/ignaciotalaveracepeda/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch/lib/libtorch_cpu.dylib in /Users/ignaciotalaveracepeda/anaconda3/envs/rubrix0.1.1/lib/python3.7/site-packages/torch_sparse/_convert_cpu.so — You are receiving this because you were assigned. Reply to this email directly, view it on GitHub <#164 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AAIOJJZKCJ4MUJLX4T6WBF3TUNV6ZANCNFSM47ILDC7A> .

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ignacioct commented on August 17, 2024

What scares me is that I've made all of this from a fresh environment, so we may need some code changing.

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dvsrepo commented on August 17, 2024

Not sure we need to change anything on core Rubrix codebase. It might be the case for the tutorial or the pip install on that tutorial, as is certainly related to core operating system libs for torch* and we dont have torch as a Rubrix dep.

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frascuchon commented on August 17, 2024

Missmatched pytorch version. See rusty1s/pytorch_sparse#85 (comment)

1.9.0 installed VS 1.8.0 defined in pytorch_geometics

PR incoming

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[0.1.1] Problem with KGLab Tutorial about argilla HOT 6 CLOSED

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