Fail to run ClusterAutoK() #72
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Hi @TengyuZz, the errors comes from an older version of Try updating pytorch-lightning with |
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Hi @marcovarrone , thanks for your suggestion. After I ran it, I still got error when I import modules. seed_everything(12345) And I got the different error messgage: AttributeError: module 'torch' has no attribute 'compiler' Seems need to upgrate torch packages as well, and then I use coed [pip install --upgrade torch] to upgrate torch, 
I attched the current packages in my env as well. Name Version Build Channel_libgcc_mutex 0.1 conda_forge conda-forge |
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Hi there, when I running the autok.fit() in CosMx data with HPC, I always got the errors message as below:
AttributeError Traceback (most recent call last)
Cell In[55], line 1
----> 1 autok.fit(adata, use_rep='X_cellcharter')
File /mnt/data/project0051/anaconda/anaconda3/envs/cellcharter/lib/python3.10/site-packages/cellcharter/tl/_autok.py:125, in ClusterAutoK.fit(self, adata, use_rep)
123 clustering = self.model_class(n_clusters=k, random_state=i + random_state, **self.model_params)
124 clustering.fit(X)
--> 125 new_labels[k] = clustering.predict(X)
127 logging.getLogger("lightning.pytorch").setLevel(logging_level)
129 if (k not in self.best_models.keys()) or (clustering.nll_ < self.best_models[k].nll_):
File /mnt/data/project0051/anaconda/anaconda3/envs/cellcharter/lib/python3.10/site-packages/cellcharter/tl/_gmm.py:153, in GaussianMixture.predict(self, data)
132 def predict(self, data: TensorLike) -> torch.Tensor:
133 """
134 Computes the most likely components for each of the provided datapoints.
135
(...)
151 the values returned from this method.
152 """
--> 153 return super().predict(data).numpy()
File /mnt/data/project0051/anaconda/anaconda3/envs/cellcharter/lib/python3.10/site-packages/torchgmm/bayes/gmm/estimator.py:297, in GaussianMixture.predict(self, data)
277 def predict(self, data: TensorLike) -> torch.Tensor:
278 """
279 Computes the most likely components for each of the provided datapoints.
280
(...)
295 the values returned from this method.
296 """
--> 297 return self.predict_proba(data).argmax(-1)
File /mnt/data/project0051/anaconda/anaconda3/envs/cellcharter/lib/python3.10/site-packages/cellcharter/tl/_gmm.py:182, in GaussianMixture.predict_proba(self, data)
180 trainer_params = self.trainer_params.copy()
181 trainer_params["logger"] = False
--> 182 result = Trainer(**trainer_params).predict(GaussianMixtureLightningModule(self.model_), loader)
183 return torch.cat([x[0] for x in cast(List[Tuple[torch.Tensor, torch.Tensor]], result)])
File /mnt/data/project0051/anaconda/anaconda3/envs/cellcharter/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py:892, in Trainer.predict(self, model, dataloaders, datamodule, return_predictions, ckpt_path)
890 model = self._maybe_unwrap_optimized(model)
891 self.strategy._lightning_module = model
--> 892 return call._call_and_handle_interrupt(
893 self, self._predict_impl, model, dataloaders, datamodule, return_predictions, ckpt_path
894 )
File /mnt/data/project0051/anaconda/anaconda3/envs/cellcharter/lib/python3.10/site-packages/pytorch_lightning/trainer/call.py:38, in _call_and_handle_interrupt(trainer, trainer_fn, *args, **kwargs)
36 return trainer.strategy.launcher.launch(trainer_fn, *args, trainer=trainer, **kwargs)
37 else:
---> 38 return trainer_fn(*args, **kwargs)
40 except _TunerExitException:
41 trainer._call_teardown_hook()
File /mnt/data/project0051/anaconda/anaconda3/envs/cellcharter/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py:938, in Trainer._predict_impl(self, model, dataloaders, datamodule, return_predictions, ckpt_path)
932 self._ckpt_path = self._checkpoint_connector._set_ckpt_path(
933 self.state.fn, ckpt_path, model_provided=model_provided, model_connected=self.lightning_module is not None
934 )
936 self._predicted_ckpt_path = self.ckpt_path # TODO: remove in v1.8
--> 938 results = self._run(model, ckpt_path=self.ckpt_path)
940 assert self.state.stopped
941 self.predicting = False
File /mnt/data/project0051/anaconda/anaconda3/envs/cellcharter/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py:1112, in Trainer._run(self, model, ckpt_path)
1108 self._checkpoint_connector.restore_training_state()
1110 self._checkpoint_connector.resume_end()
-> 1112 results = self._run_stage()
1114 log.detail(f"{self.class.name}: trainer tearing down")
1115 self._teardown()
File /mnt/data/project0051/anaconda/anaconda3/envs/cellcharter/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py:1190, in Trainer._run_stage(self)
1188 return self._run_evaluate()
1189 if self.predicting:
-> 1190 return self._run_predict()
1191 self._run_train()
File /mnt/data/project0051/anaconda/anaconda3/envs/cellcharter/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py:1240, in Trainer._run_predict(self)
1239 def _run_predict(self) -> Optional[_PREDICT_OUTPUT]:
-> 1240 self.reset_predict_dataloader(self.lightning_module)
1241 # reset trainer on this loop and all child loops in case user connected a custom loop
1242 self.predict_loop.trainer = self
File /mnt/data/project0051/anaconda/anaconda3/envs/cellcharter/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py:1678, in Trainer.reset_predict_dataloader(self, model)
1676 enable_prediction = self.limit_predict_batches > 0
1677 if source.is_defined() and enable_prediction:
-> 1678 self.num_predict_batches, self.predict_dataloaders = self._data_connector._reset_eval_dataloader(
1679 RunningStage.PREDICTING, model=pl_module
1680 )
File /mnt/data/project0051/anaconda/anaconda3/envs/cellcharter/lib/python3.10/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:377, in DataConnector._reset_eval_dataloader(self, mode, model)
369 apply_to_collection(
370 loader.loaders if isinstance(loader, CombinedLoader) else loader,
371 DataLoader,
372 self._check_eval_shuffling,
373 mode=mode,
374 )
376 # add samplers
--> 377 dataloaders = [self._prepare_dataloader(dl, mode=mode) for dl in dataloaders if dl is not None]
379 # add worker_init_fn for correct seeding in worker processes
380 apply_to_collection(
381 dataloaders, dtype=DataLoader, function=_auto_add_worker_init_fn, rank=self.trainer.global_rank
382 )
File /mnt/data/project0051/anaconda/anaconda3/envs/cellcharter/lib/python3.10/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:377, in (.0)
369 apply_to_collection(
370 loader.loaders if isinstance(loader, CombinedLoader) else loader,
371 DataLoader,
372 self._check_eval_shuffling,
373 mode=mode,
374 )
376 # add samplers
--> 377 dataloaders = [self._prepare_dataloader(dl, mode=mode) for dl in dataloaders if dl is not None]
379 # add worker_init_fn for correct seeding in worker processes
380 apply_to_collection(
381 dataloaders, dtype=DataLoader, function=_auto_add_worker_init_fn, rank=self.trainer.global_rank
382 )
File /mnt/data/project0051/anaconda/anaconda3/envs/cellcharter/lib/python3.10/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:284, in DataConnector._prepare_dataloader(self, dataloader, shuffle, mode)
281 shuffle = True if mode == RunningStage.TRAINING else _is_dataloader_shuffled(dataloader)
283 sampler = self._resolve_sampler(dataloader, shuffle=shuffle, mode=mode)
--> 284 dataloader = _update_dataloader(dataloader, sampler, mode=mode)
286 dataloader = self.trainer.strategy.process_dataloader(dataloader)
288 if cycle_iterator is not None:
File /mnt/data/project0051/anaconda/anaconda3/envs/cellcharter/lib/python3.10/site-packages/pytorch_lightning/utilities/data.py:158, in _update_dataloader(dataloader, sampler, mode)
154 def _update_dataloader(
155 dataloader: DataLoader, sampler: Union[Sampler, Iterable], mode: Optional[RunningStage] = None
156 ) -> DataLoader:
157 dl_args, dl_kwargs = _get_dataloader_init_args_and_kwargs(dataloader, sampler, mode)
--> 158 dataloader = _reinstantiate_wrapped_cls(dataloader, *dl_args, **dl_kwargs)
159 return dataloader
File /mnt/data/project0051/anaconda/anaconda3/envs/cellcharter/lib/python3.10/site-packages/lightning_fabric/utilities/data.py:255, in _reinstantiate_wrapped_cls(orig_object, explicit_cls, *args, **kwargs)
252 constructor = type(orig_object) if explicit_cls is None else explicit_cls
254 try:
--> 255 result = constructor(*args, **kwargs)
256 except TypeError as e:
257 # improve exception message due to an incorrect implementation of the
DataLoaderwhere multiple subclass258 #
__init__arguments map to oneDataLoader.__init__argument259 import re
File /mnt/data/project0051/anaconda/anaconda3/envs/cellcharter/lib/python3.10/site-packages/torchgmm/base/data/loader.py:69, in DataLoader.init(self, dataset, **kwargs)
56 kwargs.setdefault("collate_fn", collate_tuple)
58 super().init(dataset, **kwargs) # type: ignore
60 self.custom_batching = self.num_workers == 0 and (
61 isinstance(self.batch_sampler, RangeBatchSampler)
62 or (
63 self.batch_sampler is not None
64 and hasattr(self.batch_sampler, "sampler")
65 and isinstance(self.batch_sampler.sampler, RangeBatchSampler)
66 )
67 or (
68 isinstance(self.batch_sampler, IndexBatchSamplerWrapper)
---> 69 and isinstance(self.batch_sampler._batch_sampler, RangeBatchSampler) # type: ignore
70 )
71 )
AttributeError: 'IndexBatchSamplerWrapper' object has no attribute '_batch_sampler'
See Below are my codes:
import anndata as ad
import squidpy as sq
import cellcharter as cc
import pandas as pd
import scanpy as sc
import scvi
import numpy as np
import matplotlib.pyplot as plt
from lightning.pytorch import seed_everything
seed_everything(12345)
scvi.settings.seed = 12345
model_params = {
'random_state': 12345,
'trainer_params': {
'accelerator':'gpu',
'enable_progress_bar': True
},
}
autok = cc.tl.ClusterAutoK(n_clusters=(2,10),
model_class=cc.tl.GaussianMixture,
model_params=model_params,
max_runs=10)
autok.fit(adata, use_rep='X_cellcharter')
And here is the process bar showing:
Can you help me with figuring out this? Great thanks!
Version information
Name Version Build Channel
_libgcc_mutex 0.1 conda_forge conda-forge
_openmp_mutex 4.5 2_kmp_llvm conda-forge
absl-py 2.1.0 pypi_0 pypi
affine 2.4.0 pypi_0 pypi
aiobotocore 2.5.4 pypi_0 pypi
aiohappyeyeballs 2.4.4 pypi_0 pypi
aiohttp 3.11.11 pypi_0 pypi
aioitertools 0.12.0 pypi_0 pypi
aiosignal 1.3.2 pypi_0 pypi
anndata 0.10.9 pypi_0 pypi
aom 3.5.0 h27087fc_0 conda-forge
array-api-compat 1.10.0 pypi_0 pypi
asciitree 0.3.3 pypi_0 pypi
asttokens 2.0.5 pyhd3eb1b0_0
async-timeout 5.0.1 pypi_0 pypi
attrs 24.3.0 pypi_0 pypi
blas 2.126 mkl conda-forge
blas-devel 3.9.0 26_linux64_mkl conda-forge
botocore 1.31.17 pypi_0 pypi
brotli-python 1.1.0 py310hf71b8c6_2 conda-forge
bzip2 1.0.8 h4bc722e_7 conda-forge
c-ares 1.34.4 hb9d3cd8_0 conda-forge
ca-certificates 2025.1.31 hbcca054_0 conda-forge
certifi 2024.12.14 pyhd8ed1ab_0 conda-forge
cffi 1.17.1 py310h8deb56e_0 conda-forge
charset-normalizer 3.4.1 pyhd8ed1ab_0 conda-forge
chex 0.1.88 pypi_0 pypi
click 8.1.8 pypi_0 pypi
click-plugins 1.1.1 pypi_0 pypi
cligj 0.7.2 pypi_0 pypi
cloudpickle 3.1.1 pypi_0 pypi
colorama 0.4.6 pyhd8ed1ab_1 conda-forge
colorcet 3.1.0 pypi_0 pypi
comm 0.2.1 py310h06a4308_0
contourpy 1.3.1 pypi_0 pypi
cpp-expected 1.1.0 hf52228f_0 conda-forge
cpython 3.10.16 py310hd8ed1ab_1 conda-forge
cudatoolkit 11.6.2 hfc3e2af_13 conda-forge
cycler 0.12.1 pypi_0 pypi
dask 2024.12.1 pypi_0 pypi
dask-expr 1.1.21 pypi_0 pypi
dask-image 2024.5.3 pypi_0 pypi
datashader 0.16.3 pypi_0 pypi
debugpy 1.8.11 py310h6a678d5_0
decorator 5.1.1 pyhd3eb1b0_0
distributed 2024.12.1 pypi_0 pypi
docrep 0.3.2 pypi_0 pypi
et-xmlfile 2.0.0 pypi_0 pypi
etils 1.11.0 pypi_0 pypi
exceptiongroup 1.2.2 pypi_0 pypi
executing 0.8.3 pyhd3eb1b0_0
fasteners 0.19 pypi_0 pypi
ffmpeg 5.1.2 gpl_h8dda1f0_106 conda-forge
filelock 3.16.1 pypi_0 pypi
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fmt 11.0.2 h434a139_0 conda-forge
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fontconfig 2.15.0 h7e30c49_1 conda-forge
fonts-conda-ecosystem 1 0 conda-forge
fonts-conda-forge 1 0 conda-forge
fonttools 4.55.3 pypi_0 pypi
freetype 2.12.1 h267a509_2 conda-forge
frozenlist 1.5.0 pypi_0 pypi
fsspec 2023.6.0 pypi_0 pypi
geopandas 1.0.1 pypi_0 pypi
gettext 0.22.5 he02047a_3 conda-forge
gettext-tools 0.22.5 he02047a_3 conda-forge
gmp 6.3.0 hac33072_2 conda-forge
gmpy2 2.1.5 py310he8512ff_3 conda-forge
gnutls 3.7.9 hb077bed_0 conda-forge
h2 4.1.0 pyhd8ed1ab_1 conda-forge
h5py 3.12.1 pypi_0 pypi
hpack 4.0.0 pyhd8ed1ab_1 conda-forge
humanize 4.11.0 pypi_0 pypi
hyperframe 6.0.1 pyhd8ed1ab_1 conda-forge
idna 3.10 pyhd8ed1ab_1 conda-forge
igraph 0.11.8 pypi_0 pypi
imageio 2.36.1 pypi_0 pypi
importlib-metadata 8.5.0 pypi_0 pypi
importlib-resources 6.5.2 pypi_0 pypi
inflect 7.5.0 pypi_0 pypi
ipykernel 6.29.5 py310h06a4308_0
ipython 8.30.0 py310h06a4308_0
jax 0.4.38 pypi_0 pypi
jaxlib 0.4.38 pypi_0 pypi
jedi 0.19.2 py310h06a4308_0
jinja2 3.1.5 pyhd8ed1ab_0 conda-forge
jmespath 1.0.1 pypi_0 pypi
joblib 1.4.2 pypi_0 pypi
jpeg 9e h0b41bf4_3 conda-forge
jupyter_client 8.6.0 py310h06a4308_0
jupyter_core 5.7.2 py310h06a4308_0
keyutils 1.6.1 h166bdaf_0 conda-forge
kiwisolver 1.4.8 pypi_0 pypi
krb5 1.21.3 h659f571_0 conda-forge
lame 3.100 h166bdaf_1003 conda-forge
lazy-loader 0.4 pypi_0 pypi
lcms2 2.15 hfd0df8a_0 conda-forge
ld_impl_linux-64 2.43 h712a8e2_2 conda-forge
legacy-api-wrap 1.4.1 pypi_0 pypi
leidenalg 0.10.2 pypi_0 pypi
lerc 4.0.0 h27087fc_0 conda-forge
libabseil 20240722.0 cxx17_hbbce691_4 conda-forge
libarchive 3.7.7 h4585015_3 conda-forge
libasprintf 0.22.5 he8f35ee_3 conda-forge
libasprintf-devel 0.22.5 he8f35ee_3 conda-forge
libblas 3.9.0 26_linux64_mkl conda-forge
libcblas 3.9.0 26_linux64_mkl conda-forge
libcurl 8.11.1 h332b0f4_0 conda-forge
libdeflate 1.17 h0b41bf4_0 conda-forge
libdrm 2.4.124 hb9d3cd8_0 conda-forge
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libev 4.33 hd590300_2 conda-forge
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liblzma 5.6.3 hb9d3cd8_1 conda-forge
liblzma-devel 5.6.3 hb9d3cd8_1 conda-forge
libmamba 2.0.5 h49b8a8d_1 conda-forge
libnghttp2 1.64.0 h161d5f1_0 conda-forge
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libtorch 2.5.1 cpu_mkl_h89e7157_111 conda-forge
libunistring 0.9.10 h7f98852_0 conda-forge
libuuid 2.38.1 h0b41bf4_0 conda-forge
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libvpx 1.11.0 h9c3ff4c_3 conda-forge
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libxml2 2.13.5 h0d44e9d_1 conda-forge
libzlib 1.3.1 hb9d3cd8_2 conda-forge
lightning 2.5.0.post0 pyhd8ed1ab_0 conda-forge
lightning-utilities 0.11.9 pypi_0 pypi
llvm-openmp 19.1.7 h024ca30_0 conda-forge
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ncurses 6.5 h2d0b736_2 conda-forge
nest-asyncio 1.6.0 py310h06a4308_0
nettle 3.9.1 h7ab15ed_0 conda-forge
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nlohmann_json 3.11.3 he02047a_1 conda-forge
numba 0.60.0 pypi_0 pypi
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numpy 1.26.4 pypi_0 pypi
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nvidia-cublas-cu12 12.4.5.8 pypi_0 pypi
nvidia-cuda-cupti-cu12 12.4.127 pypi_0 pypi
nvidia-cuda-nvrtc-cu12 12.4.127 pypi_0 pypi
nvidia-cuda-runtime-cu12 12.4.127 pypi_0 pypi
nvidia-cudnn-cu12 9.1.0.70 pypi_0 pypi
nvidia-cufft-cu12 11.2.1.3 pypi_0 pypi
nvidia-curand-cu12 10.3.5.147 pypi_0 pypi
nvidia-cusolver-cu12 11.6.1.9 pypi_0 pypi
nvidia-cusparse-cu12 12.3.1.170 pypi_0 pypi
nvidia-nccl-cu12 2.21.5 pypi_0 pypi
nvidia-nvjitlink-cu12 12.4.127 pypi_0 pypi
nvidia-nvtx-cu12 12.4.127 pypi_0 pypi
ome-zarr 0.10.3 pypi_0 pypi
omnipath 1.0.8 pypi_0 pypi
openh264 2.3.1 hcb278e6_2 conda-forge
openjpeg 2.5.0 hfec8fc6_2 conda-forge
openpyxl 3.1.5 pypi_0 pypi
openssl 3.4.0 h7b32b05_1 conda-forge
opt-einsum 3.4.0 pypi_0 pypi
optax 0.2.4 pypi_0 pypi
orbax-checkpoint 0.11.0 pypi_0 pypi
p11-kit 0.24.1 hc5aa10d_0 conda-forge
packaging 24.2 py310h06a4308_0
pandas 2.2.3 pypi_0 pypi
param 2.2.0 pypi_0 pypi
parso 0.8.4 py310h06a4308_0
partd 1.4.2 pypi_0 pypi
patsy 1.0.1 pypi_0 pypi
pexpect 4.8.0 pyhd3eb1b0_3
pillow 11.1.0 pypi_0 pypi
pims 0.7 pypi_0 pypi
pip 24.3.1 pyh8b19718_2 conda-forge
platformdirs 4.3.6 pypi_0 pypi
pooch 1.8.2 pypi_0 pypi
prompt-toolkit 3.0.43 py310h06a4308_0
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ptyprocess 0.7.0 pyhd3eb1b0_2
pure_eval 0.2.2 pyhd3eb1b0_0
pyarrow 19.0.0 pypi_0 pypi
pybind11 2.13.6 pyh1ec8472_2 conda-forge
pybind11-global 2.13.6 pyh415d2e4_2 conda-forge
pycparser 2.22 pyh29332c3_1 conda-forge
pyct 0.5.0 pypi_0 pypi
pygments 2.19.1 pypi_0 pypi
pynndescent 0.5.13 pypi_0 pypi
pyogrio 0.10.0 pypi_0 pypi
pyparsing 3.2.1 pypi_0 pypi
pyproj 3.7.0 pypi_0 pypi
pyro-api 0.1.2 pypi_0 pypi
pyro-ppl 1.8.6 pypi_0 pypi
pysocks 1.7.1 pyha55dd90_7 conda-forge
python 3.10.16 he725a3c_1_cpython conda-forge
python-dateutil 2.9.0post0 py310h06a4308_2
python_abi 3.10 5_cp310 conda-forge
pytorch 2.5.1 cpu_mkl_py310_h27a6d43_111 conda-forge
pytorch-lightning 1.9.5 pypi_0 pypi
pytorch-mutex 1.0 cuda pytorch
pytz 2024.2 pypi_0 pypi
pyyaml 6.0.2 py310h89163eb_2 conda-forge
pyzmq 26.2.0 py310h6a678d5_0
rasterio 1.4.3 pypi_0 pypi
readline 8.2 h8228510_1 conda-forge
reproc 14.2.5.post0 hb9d3cd8_0 conda-forge
reproc-cpp 14.2.5.post0 h5888daf_0 conda-forge
requests 2.32.3 pyhd8ed1ab_1 conda-forge
rich 13.9.4 pypi_0 pypi
s3fs 2023.6.0 pypi_0 pypi
scanpy 1.10.4 pypi_0 pypi
scikit-image 0.25.0 pypi_0 pypi
scikit-learn 1.6.1 pypi_0 pypi
scipy 1.15.1 pypi_0 pypi
scvi-tools 0.20.3 pypi_0 pypi
seaborn 0.13.2 pypi_0 pypi
session-info 1.0.0 pypi_0 pypi
setuptools 75.8.0 pyhff2d567_0 conda-forge
shapely 2.0.6 pypi_0 pypi
simdjson 3.11.6 h84d6215_0 conda-forge
simplejson 3.19.3 pypi_0 pypi
six 1.17.0 pypi_0 pypi
sknw 0.15 pypi_0 pypi
sleef 3.8 h1b44611_0 conda-forge
slicerator 1.1.0 pypi_0 pypi
sortedcontainers 2.4.0 pypi_0 pypi
spatial-image 1.1.0 pypi_0 pypi
spatialdata 0.2.6 pypi_0 pypi
spatialdata-plot 0.2.8 pypi_0 pypi
spdlog 1.15.0 h10c9db5_0 conda-forge
squidpy 1.6.1 pypi_0 pypi
stack_data 0.2.0 pyhd3eb1b0_0
statsmodels 0.14.4 pypi_0 pypi
stdlib-list 0.11.0 pypi_0 pypi
svt-av1 1.4.1 hcb278e6_0 conda-forge
sympy 1.13.1 pypi_0 pypi
tbb 2021.13.0 hceb3a55_1 conda-forge
tblib 3.0.0 pypi_0 pypi
tensorstore 0.1.71 pypi_0 pypi
texttable 1.7.0 pypi_0 pypi
threadpoolctl 3.5.0 pypi_0 pypi
tifffile 2025.1.10 pypi_0 pypi
tk 8.6.13 noxft_h4845f30_101 conda-forge
toolz 1.0.0 pypi_0 pypi
torchaudio 0.12.1 py310_cu116 pytorch
torchmetrics 1.6.1 pyhd8ed1ab_0 conda-forge
torchvision 0.13.1 py310_cu116 pytorch
tornado 6.4.2 py310h5eee18b_0
tqdm 4.67.1 pyhd8ed1ab_1 conda-forge
traitlets 5.14.3 py310h06a4308_0
triton 3.1.0 pypi_0 pypi
typeguard 4.4.1 pypi_0 pypi
typing-extensions 4.12.2 hd8ed1ab_1 conda-forge
typing_extensions 4.12.2 pyha770c72_1 conda-forge
tzdata 2024.2 pypi_0 pypi
umap-learn 0.5.7 pypi_0 pypi
urllib3 1.26.20 pypi_0 pypi
validators 0.34.0 pypi_0 pypi
wcwidth 0.2.5 pyhd3eb1b0_0
wheel 0.45.1 pyhd8ed1ab_1 conda-forge
wrapt 1.17.2 pypi_0 pypi
x264 1!164.3095 h166bdaf_2 conda-forge
x265 3.5 h924138e_3 conda-forge
xarray 2024.11.0 pypi_0 pypi
xarray-dataclasses 1.9.1 pypi_0 pypi
xarray-schema 0.0.3 pypi_0 pypi
xarray-spatial 0.4.0 pypi_0 pypi
xorg-fixesproto 5.0 hb9d3cd8_1003 conda-forge
xorg-kbproto 1.0.7 hb9d3cd8_1003 conda-forge
xorg-libx11 1.8.4 h0b41bf4_0 conda-forge
xorg-libxau 1.0.12 hb9d3cd8_0 conda-forge
xorg-libxdmcp 1.1.5 hb9d3cd8_0 conda-forge
xorg-libxext 1.3.4 h0b41bf4_2 conda-forge
xorg-libxfixes 5.0.3 h7f98852_1004 conda-forge
xorg-xextproto 7.3.0 hb9d3cd8_1004 conda-forge
xorg-xproto 7.0.31 hb9d3cd8_1008 conda-forge
xz 5.6.3 hbcc6ac9_1 conda-forge
xz-gpl-tools 5.6.3 hbcc6ac9_1 conda-forge
xz-tools 5.6.3 hb9d3cd8_1 conda-forge
yaml 0.2.5 h7f98852_2 conda-forge
yaml-cpp 0.8.0 h59595ed_0 conda-forge
yarl 1.18.3 pypi_0 pypi
zarr 2.18.3 pypi_0 pypi
zeromq 4.3.5 h6a678d5_0
zict 3.0.0 pypi_0 pypi
zipp 3.21.0 pypi_0 pypi
zstandard 0.23.0 py310ha39cb0e_1 conda-forge
zstd 1.5.6 ha6fb4c9_0 conda-forge
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