Commit ·
d4cd645
1
Parent(s): f34a470
Updated README and Conda environment configuration file
Browse files- .gitignore +1 -0
- README.md +27 -16
- environment.yml +399 -0
.gitignore
CHANGED
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@@ -165,5 +165,6 @@ cython_debug/
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data/uniprot2embedding.h5
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data/PROTAC-DB.csv
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data/PROTAC-Pedia.csv
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logs/
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notebooks/per-protein*
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data/uniprot2embedding.h5
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data/PROTAC-DB.csv
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data/PROTAC-Pedia.csv
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+
data/cellosaurus.txt
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logs/
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notebooks/per-protein*
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README.md
CHANGED
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@@ -1,22 +1,19 @@
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# PROTAC-Degradation-Predictor -->
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<img src="https://img.shields.io/badge/Maturity%20Level-ML--0-red" alt="Maturity level-0">
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</p>
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<p align="center">
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A machine learning-based tool for predicting PROTAC protein degradation activity.
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</p>
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## 📚 Table of Contents
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- [Data Curation](#-data-curation)
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- [Installation](#-installation)
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- [Usage](#-usage)
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## 📝 Data Curation
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## 🎯 Usage
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After installing the package, you can use it as follows:
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```python
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import protac_degradation_predictor as pdp
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protac_smiles = '
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e3_ligase = 'VHL'
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target_uniprot = 'P04637'
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cell_line = 'HeLa'
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e3_ligase,
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target_uniprot,
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cell_line,
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device='cuda', # Default to 'cpu'
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proba_threshold=0.5, # Default value
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)
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print(f'The given PROTAC is: {"active" if active_protac else "inactive"}')
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The function supports batch computation by passing lists of SMILES strings, E3 ligases, UniProt IDs, and cell lines. In this case, it returns a list of booleans indicating the activity of each PROTAC.
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-
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The code for training the model can be found in the file [`run_experiments.py`](src/run_experiments.py).
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## 📄 Citation
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<a href="https://colab.research.google.com/github/ribesstefano/PROTAC-Degradation-Predictor/blob/main/notebooks/protac_degradation_predictor_tutorial.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
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# PROTAC-Degradation-Predictor
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A machine learning-based tool for predicting PROTAC protein degradation activity.
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## 📚 Table of Contents
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- [Data Curation](#-data-curation)
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- [Installation](#-installation)
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- [Usage](#-usage)
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- [Training](#-training)
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- [Citation](#-citation)
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- [License](#-license)
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## 📝 Data Curation
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## 🎯 Usage
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For a thorough explanation on how to use the package, please refer to the tutorial notebook [`protac_degradation_tutorial.ipynb`](notebooks/protac_degradation_tutorial.ipynb).
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After installing the package, you can use it as follows:
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```python
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import protac_degradation_predictor as pdp
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protac_smiles = 'Cc1ncsc1-c1ccc(CNC(=O)[C@@H]2C[C@@H](O)CN2C(=O)[C@@H](NC(=O)COCCCCCCCCCOCC(=O)Nc2ccc(C(=O)Nc3ccc(F)cc3N)cc2)C(C)(C)C)cc1'
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e3_ligase = 'VHL'
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target_uniprot = 'P04637'
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cell_line = 'HeLa'
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e3_ligase,
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target_uniprot,
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cell_line,
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)
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print(f'The given PROTAC is: {"active" if active_protac else "inactive"}')
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The function supports batch computation by passing lists of SMILES strings, E3 ligases, UniProt IDs, and cell lines. In this case, it returns a list of booleans indicating the activity of each PROTAC.
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## 📈 Training
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Before running the experiments, here are some required steps to follow (assuming one is in the repository directory already):
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1. Download the data from the [Cellosaurus database](https://web.expasy.org/cellosaurus/) and save it in the `data` directory:
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```bash
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wget https://ftp.expasy.org/databases/cellosaurus/cellosaurus.txt data/
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```
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2. Make a copy of the Uniprot embeddings to be placed in the `data` directory:
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```bash
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cp protac_degradation_predictor/data/uniprot2embedding.h5 data/
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```
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3. Create a virtual environment and install the required packages by running the following commands:
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```bash
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conda env create -f environment.yaml
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conda activate protac-degradation-predictor
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```
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4. The code for training the model can be found in the file [`run_experiments.py`](src/run_experiments.py).
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(Don't forget to adjust the `PYTHONPATH` environment variable to include the repository directory: `export PYTHONPATH=$PYTHONPATH:/path/to/PROTAC-Degradation-Predictor`)
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## 📄 Citation
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environment.yml
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name: env-protac-degradation-predictor
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channels:
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- pyg
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- anaconda
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- pytorch
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- huggingface
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- nvidia
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- conda-forge
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- defaults
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dependencies:
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- _libgcc_mutex=0.1=main
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- _openmp_mutex=5.1=1_gnu
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| 13 |
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- _py-xgboost-mutex=2.0=cpu_0
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| 14 |
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- abseil-cpp=20211102.0=h27087fc_1
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| 15 |
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- absl-py=1.4.0=pyhd8ed1ab_0
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| 16 |
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- accelerate=0.21.0=pyhd8ed1ab_0
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| 17 |
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- aiohttp=3.8.3=py310h5eee18b_0
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| 18 |
+
- aiosignal=1.2.0=pyhd8ed1ab_0
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| 19 |
+
- alembic=1.12.0=pyhd8ed1ab_0
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| 20 |
+
- anyio=3.7.1=pyhd8ed1ab_0
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| 21 |
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- arrow=1.2.3=pyhd8ed1ab_0
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| 22 |
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- arrow-cpp=11.0.0=py310h7516544_0
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| 23 |
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- async-timeout=4.0.2=pyhd8ed1ab_0
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| 24 |
+
- aws-c-common=0.4.57=he1b5a44_1
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| 25 |
+
- aws-c-event-stream=0.1.6=h72b8ae1_3
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| 26 |
+
- aws-checksums=0.1.9=h346380f_0
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| 27 |
+
- aws-sdk-cpp=1.8.185=hce553d0_0
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| 28 |
+
- backports=1.0=pyhd8ed1ab_3
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| 29 |
+
- backports.functools_lru_cache=1.6.5=pyhd8ed1ab_0
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| 30 |
+
- beautifulsoup4=4.12.2=pyha770c72_0
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| 31 |
+
- binaryornot=0.4.4=py_1
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| 32 |
+
- blas=1.0=mkl
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| 33 |
+
- blessed=1.19.1=pyhe4f9e05_2
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| 34 |
+
- blinker=1.6.2=pyhd8ed1ab_0
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| 35 |
+
- boltons=23.0.0=pyhd8ed1ab_0
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| 36 |
+
- boost-cpp=1.73.0=h7f8727e_12
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| 37 |
+
- bottleneck=1.3.5=py310ha9d4c09_0
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| 38 |
+
- brotlipy=0.7.0=py310h5764c6d_1004
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| 39 |
+
- bzip2=1.0.8=h7f98852_4
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| 40 |
+
- c-ares=1.19.0=h5eee18b_0
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| 41 |
+
- ca-certificates=2023.08.22=h06a4308_0
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| 42 |
+
- cachecontrol=0.12.14=pyhd8ed1ab_0
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| 43 |
+
- certifi=2023.7.22=py310h06a4308_0
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| 44 |
+
- cffi=1.15.1=py310h5eee18b_3
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| 45 |
+
- chardet=5.1.0=py310hff52083_0
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| 46 |
+
- charset-normalizer=2.0.4=pyhd8ed1ab_0
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| 47 |
+
- cleo=2.0.1=pyhd8ed1ab_0
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| 48 |
+
- click=8.0.4=py310hff52083_0
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| 49 |
+
- cmaes=0.10.0=pyhd8ed1ab_0
|
| 50 |
+
- colorama=0.4.6=pyhd8ed1ab_0
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| 51 |
+
- colorlog=6.7.0=py310hff52083_1
|
| 52 |
+
- conda=23.7.4=py310hff52083_0
|
| 53 |
+
- conda-content-trust=0.1.3=pyhd8ed1ab_0
|
| 54 |
+
- conda-package-handling=1.9.0=py310h5eee18b_1
|
| 55 |
+
- cookiecutter=2.3.0=pyh1a96a4e_0
|
| 56 |
+
- crashtest=0.4.1=pyhd8ed1ab_0
|
| 57 |
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- croniter=1.3.15=pyhd8ed1ab_0
|
| 58 |
+
- cryptography=38.0.1=py310h9ce1e76_0
|
| 59 |
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- cuda-cudart=11.8.89=0
|
| 60 |
+
- cuda-cupti=11.8.87=0
|
| 61 |
+
- cuda-libraries=11.8.0=0
|
| 62 |
+
- cuda-nvrtc=11.8.89=0
|
| 63 |
+
- cuda-nvtx=11.8.86=0
|
| 64 |
+
- cuda-runtime=11.8.0=0
|
| 65 |
+
- dataclasses=0.8=pyhc8e2a94_3
|
| 66 |
+
- datasets=2.14.4=py_0
|
| 67 |
+
- dateutils=0.6.12=py_0
|
| 68 |
+
- dbus=1.13.0=h4e0c4b3_1000
|
| 69 |
+
- deepdiff=6.2.2=pyhd8ed1ab_0
|
| 70 |
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- dill=0.3.6=pyhd8ed1ab_1
|
| 71 |
+
- distlib=0.3.7=pyhd8ed1ab_0
|
| 72 |
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- dulwich=0.21.3=py310h5eee18b_0
|
| 73 |
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- evaluate=0.2.2=pyhd8ed1ab_0
|
| 74 |
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- exceptiongroup=1.1.3=pyhd8ed1ab_0
|
| 75 |
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- expat=2.4.8=h27087fc_0
|
| 76 |
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|
| 77 |
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- ffmpeg=4.3=hf484d3e_0
|
| 78 |
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- filelock=3.9.0=pyhd8ed1ab_0
|
| 79 |
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- freetype=2.12.1=h4a9f257_0
|
| 80 |
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- frozenlist=1.3.3=py310h5eee18b_0
|
| 81 |
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|
| 82 |
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- gflags=2.2.2=he1b5a44_1004
|
| 83 |
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|
| 84 |
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|
| 85 |
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- gmp=6.2.1=h58526e2_0
|
| 86 |
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|
| 87 |
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- gnutls=3.6.15=he1e5248_0
|
| 88 |
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|
| 89 |
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|
| 90 |
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|
| 91 |
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- grpcio=1.42.0=py310hce63b2e_0
|
| 92 |
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- h11=0.14.0=pyhd8ed1ab_0
|
| 93 |
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- html5lib=1.1=pyh9f0ad1d_0
|
| 94 |
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|
| 95 |
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- icu=58.2=hf484d3e_1000
|
| 96 |
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- idna=3.4=pyhd8ed1ab_0
|
| 97 |
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|
| 98 |
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|
| 99 |
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- importlib_resources=6.0.1=pyhd8ed1ab_0
|
| 100 |
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|
| 101 |
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|
| 102 |
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|
| 103 |
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|
| 104 |
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|
| 105 |
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|
| 106 |
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|
| 107 |
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|
| 108 |
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|
| 109 |
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|
| 110 |
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|
| 111 |
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|
| 112 |
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|
| 113 |
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|
| 114 |
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|
| 115 |
+
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|
| 116 |
+
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|
| 117 |
+
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|
| 118 |
+
- libbrotlidec=1.0.9=h166bdaf_7
|
| 119 |
+
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|
| 120 |
+
- libcublas=11.11.3.6=0
|
| 121 |
+
- libcufft=10.9.0.58=0
|
| 122 |
+
- libcufile=1.7.1.12=0
|
| 123 |
+
- libcurand=10.3.3.129=0
|
| 124 |
+
- libcurl=8.1.1=h91b91d3_2
|
| 125 |
+
- libcusolver=11.4.1.48=0
|
| 126 |
+
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|
| 127 |
+
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|
| 128 |
+
- libedit=3.1.20221030=h5eee18b_0
|
| 129 |
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- libev=4.33=h516909a_1
|
| 130 |
+
- libevent=2.1.12=h8f2d780_0
|
| 131 |
+
- libffi=3.4.2=h7f98852_5
|
| 132 |
+
- libgcc-ng=11.2.0=h1234567_1
|
| 133 |
+
- libgfortran-ng=11.2.0=h00389a5_1
|
| 134 |
+
- libgfortran5=11.2.0=h1234567_1
|
| 135 |
+
- libgomp=11.2.0=h1234567_1
|
| 136 |
+
- libiconv=1.16=h516909a_0
|
| 137 |
+
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|
| 138 |
+
- libnghttp2=1.52.0=ha637b67_1
|
| 139 |
+
- libnpp=11.8.0.86=0
|
| 140 |
+
- libnvjpeg=11.9.0.86=0
|
| 141 |
+
- libpng=1.6.39=h5eee18b_0
|
| 142 |
+
- libprotobuf=3.20.3=he621ea3_0
|
| 143 |
+
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|
| 144 |
+
- libstdcxx-ng=11.2.0=he4da1e4_16
|
| 145 |
+
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|
| 146 |
+
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|
| 147 |
+
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|
| 148 |
+
- libunistring=0.9.10=h7f98852_0
|
| 149 |
+
- libuuid=1.41.5=h5eee18b_0
|
| 150 |
+
- libwebp=1.2.4=h11a3e52_1
|
| 151 |
+
- libwebp-base=1.2.4=h5eee18b_1
|
| 152 |
+
- libxgboost=1.5.1=cpu_h3d145d1_2
|
| 153 |
+
- lightning=2.0.4=pyhd8ed1ab_0
|
| 154 |
+
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|
| 155 |
+
- lightning-utilities=0.9.0=pyhd8ed1ab_0
|
| 156 |
+
- lockfile=0.12.2=py_1
|
| 157 |
+
- lz4-c=1.9.4=h6a678d5_0
|
| 158 |
+
- mako=1.2.4=pyhd8ed1ab_0
|
| 159 |
+
- markdown=3.4.4=pyhd8ed1ab_0
|
| 160 |
+
- markdown-it-py=3.0.0=pyhd8ed1ab_0
|
| 161 |
+
- markupsafe=2.1.1=py310h5764c6d_1
|
| 162 |
+
- mdurl=0.1.0=pyhd8ed1ab_0
|
| 163 |
+
- mkl=2023.1.0=h213fc3f_46343
|
| 164 |
+
- mkl-service=2.4.0=py310h5eee18b_1
|
| 165 |
+
- mkl_fft=1.3.6=py310h1128e8f_1
|
| 166 |
+
- mkl_random=1.2.2=py310h1128e8f_1
|
| 167 |
+
- more-itertools=10.1.0=pyhd8ed1ab_0
|
| 168 |
+
- mpc=1.1.0=h04dde30_1009
|
| 169 |
+
- mpfr=4.0.2=he80fd80_1
|
| 170 |
+
- mpmath=1.3.0=pyhd8ed1ab_0
|
| 171 |
+
- msgpack-python=1.0.3=py310hbf28c38_1
|
| 172 |
+
- multidict=6.0.2=py310h5764c6d_1
|
| 173 |
+
- multiprocess=0.70.14=py310h06a4308_0
|
| 174 |
+
- ncurses=6.3=h27087fc_1
|
| 175 |
+
- nettle=3.7.3=hbbd107a_1
|
| 176 |
+
- networkx=3.1=pyhd8ed1ab_0
|
| 177 |
+
- numexpr=2.8.4=py310h85018f9_1
|
| 178 |
+
- numpy=1.25.2=py310h5f9d8c6_0
|
| 179 |
+
- numpy-base=1.25.2=py310hb5e798b_0
|
| 180 |
+
- oauthlib=3.2.2=pyhd8ed1ab_0
|
| 181 |
+
- openh264=2.1.1=h780b84a_0
|
| 182 |
+
- openssl=1.1.1w=h7f8727e_0
|
| 183 |
+
- optuna=3.3.0=pyhd8ed1ab_0
|
| 184 |
+
- orc=1.7.4=hb3bc3d3_1
|
| 185 |
+
- ordered-set=4.1.0=pyhd8ed1ab_0
|
| 186 |
+
- packaging=23.0=pyhd8ed1ab_0
|
| 187 |
+
- pandas=1.5.3=py310h1128e8f_0
|
| 188 |
+
- pexpect=4.8.0=pyh1a96a4e_2
|
| 189 |
+
- pillow=9.4.0=py310h6a678d5_0
|
| 190 |
+
- pip=22.3.1=pyhd8ed1ab_0
|
| 191 |
+
- pkginfo=1.9.6=pyhd8ed1ab_0
|
| 192 |
+
- pkgutil-resolve-name=1.3.10=pyhd8ed1ab_1
|
| 193 |
+
- platformdirs=2.6.2=pyhd8ed1ab_0
|
| 194 |
+
- poetry=1.4.2=linux_pyhd8ed1ab_0
|
| 195 |
+
- poetry-core=1.5.2=pyhd8ed1ab_0
|
| 196 |
+
- poetry-plugin-export=1.3.1=pyhd8ed1ab_0
|
| 197 |
+
- protobuf=3.20.3=py310h6a678d5_0
|
| 198 |
+
- psutil=5.9.0=py310h5764c6d_1
|
| 199 |
+
- ptyprocess=0.7.0=pyhd3deb0d_0
|
| 200 |
+
- py-xgboost=1.5.1=cpu_py310hd1aba9c_2
|
| 201 |
+
- pyarrow=11.0.0=py310h468efa6_0
|
| 202 |
+
- pyasn1=0.4.8=py_0
|
| 203 |
+
- pyasn1-modules=0.2.7=py_0
|
| 204 |
+
- pycosat=0.6.4=py310h5eee18b_0
|
| 205 |
+
- pycparser=2.21=pyhd8ed1ab_0
|
| 206 |
+
- pydantic=1.9.1=py310h5764c6d_0
|
| 207 |
+
- pyg=2.3.1=py310_torch_2.0.0_cu118
|
| 208 |
+
- pygments=2.16.1=pyhd8ed1ab_0
|
| 209 |
+
- pyjwt=2.8.0=pyhd8ed1ab_0
|
| 210 |
+
- pyopenssl=22.0.0=pyhd8ed1ab_1
|
| 211 |
+
- pyparsing=3.0.9=py310h06a4308_0
|
| 212 |
+
- pyproject_hooks=1.0.0=pyhd8ed1ab_0
|
| 213 |
+
- pyrsistent=0.18.1=py310h5764c6d_1
|
| 214 |
+
- pysocks=1.7.1=pyha2e5f31_6
|
| 215 |
+
- python=3.10.8=h7a1cb2a_1
|
| 216 |
+
- python-build=0.10.0=pyhd8ed1ab_1
|
| 217 |
+
- python-dateutil=2.8.2=pyhd8ed1ab_0
|
| 218 |
+
- python-editor=1.0.4=py_0
|
| 219 |
+
- python-installer=0.7.0=pyhd8ed1ab_0
|
| 220 |
+
- python-multipart=0.0.6=pyhd8ed1ab_0
|
| 221 |
+
- python-slugify=8.0.1=pyhd8ed1ab_0
|
| 222 |
+
- python-xxhash=2.0.2=py310h6acc77f_1
|
| 223 |
+
- python_abi=3.10=2_cp310
|
| 224 |
+
- pytorch=2.0.1=py3.10_cuda11.8_cudnn8.7.0_0
|
| 225 |
+
- pytorch-cuda=11.8=h7e8668a_5
|
| 226 |
+
- pytorch-lightning=2.0.9=pyhd8ed1ab_0
|
| 227 |
+
- pytorch-mutex=1.0=cuda
|
| 228 |
+
- pytz=2022.7.1=pyhd8ed1ab_0
|
| 229 |
+
- pyu2f=0.1.5=pyhd8ed1ab_0
|
| 230 |
+
- pyyaml=6.0=py310h5764c6d_4
|
| 231 |
+
- rapidfuzz=2.13.7=py310h1128e8f_0
|
| 232 |
+
- re2=2022.04.01=h27087fc_0
|
| 233 |
+
- readchar=4.0.5=pyhd8ed1ab_0
|
| 234 |
+
- readline=8.2=h5eee18b_0
|
| 235 |
+
- regex=2022.7.9=py310h5eee18b_0
|
| 236 |
+
- requests-oauthlib=1.3.1=pyhd8ed1ab_0
|
| 237 |
+
- requests-toolbelt=0.10.1=pyhd8ed1ab_0
|
| 238 |
+
- responses=0.18.0=pyhd8ed1ab_0
|
| 239 |
+
- rich=13.5.1=pyhd8ed1ab_0
|
| 240 |
+
- rsa=4.9=pyhd8ed1ab_0
|
| 241 |
+
- ruamel.yaml=0.17.21=py310h5764c6d_1
|
| 242 |
+
- ruamel.yaml.clib=0.2.6=py310h5764c6d_1
|
| 243 |
+
- sacremoses=master=py_0
|
| 244 |
+
- scikit-learn=1.2.0=py310h6a678d5_1
|
| 245 |
+
- scipy=1.9.3=py310h5f9d8c6_2
|
| 246 |
+
- secretstorage=3.3.3=py310hff52083_1
|
| 247 |
+
- setuptools=65.5.0=pyhd8ed1ab_0
|
| 248 |
+
- shellingham=1.5.3=pyhd8ed1ab_0
|
| 249 |
+
- six=1.16.0=pyh6c4a22f_0
|
| 250 |
+
- snappy=1.1.9=hbd366e4_1
|
| 251 |
+
- sniffio=1.3.0=pyhd8ed1ab_0
|
| 252 |
+
- soupsieve=2.5=pyhd8ed1ab_1
|
| 253 |
+
- sqlalchemy=1.4.36=py310h5764c6d_0
|
| 254 |
+
- sqlite=3.40.0=h5082296_0
|
| 255 |
+
- starlette=0.27.0=pyhd8ed1ab_0
|
| 256 |
+
- starsessions=1.3.0=pyhd8ed1ab_0
|
| 257 |
+
- sympy=1.11.1=pyh04b8f61_3
|
| 258 |
+
- tabulate=0.9.0=pyhd8ed1ab_1
|
| 259 |
+
- tbb=2021.8.0=hdb19cb5_0
|
| 260 |
+
- tensorboard=2.6.0=py_0
|
| 261 |
+
- tensorboard-plugin-wit=1.8.1=pyhd8ed1ab_0
|
| 262 |
+
- text-unidecode=1.3=py_0
|
| 263 |
+
- threadpoolctl=2.2.0=pyh0d69192_0
|
| 264 |
+
- tk=8.6.12=h1ccaba5_0
|
| 265 |
+
- tokenizers=0.13.2=py310he7d60b5_1
|
| 266 |
+
- tomli=2.0.1=pyhd8ed1ab_0
|
| 267 |
+
- tomlkit=0.12.1=pyha770c72_0
|
| 268 |
+
- toolz=0.12.0=pyhd8ed1ab_0
|
| 269 |
+
- torchaudio=2.0.2=py310_cu118
|
| 270 |
+
- torchmetrics=1.1.2=pyhd8ed1ab_0
|
| 271 |
+
- torchtriton=2.0.0=py310
|
| 272 |
+
- torchvision=0.15.2=py310_cu118
|
| 273 |
+
- tqdm=4.64.1=pyhd8ed1ab_0
|
| 274 |
+
- transformers=4.29.2=pyhd8ed1ab_0
|
| 275 |
+
- trove-classifiers=2023.8.7=pyhd8ed1ab_0
|
| 276 |
+
- typing-extensions=4.7.1=hd8ed1ab_0
|
| 277 |
+
- typing_extensions=4.7.1=pyha770c72_0
|
| 278 |
+
- tzdata=2022g=h191b570_0
|
| 279 |
+
- unidecode=1.3.6=pyhd8ed1ab_0
|
| 280 |
+
- urllib3=1.26.13=pyhd8ed1ab_0
|
| 281 |
+
- utf8proc=2.6.1=h27cfd23_0
|
| 282 |
+
- uvicorn=0.23.2=py310hff52083_0
|
| 283 |
+
- virtualenv=20.21.1=pyhd8ed1ab_0
|
| 284 |
+
- wcwidth=0.2.6=pyhd8ed1ab_0
|
| 285 |
+
- webencodings=0.5.1=pyhd8ed1ab_2
|
| 286 |
+
- websockets=10.3=py310h5764c6d_0
|
| 287 |
+
- werkzeug=2.3.6=pyhd8ed1ab_0
|
| 288 |
+
- wheel=0.37.1=pyhd8ed1ab_0
|
| 289 |
+
- xxhash=0.8.0=h7f98852_3
|
| 290 |
+
- xz=5.2.8=h5eee18b_0
|
| 291 |
+
- yaml=0.2.5=h7f98852_2
|
| 292 |
+
- yarl=1.8.1=py310h5eee18b_0
|
| 293 |
+
- zipp=3.16.2=pyhd8ed1ab_0
|
| 294 |
+
- zlib=1.2.13=h5eee18b_0
|
| 295 |
+
- zstd=1.5.2=ha4553b6_0
|
| 296 |
+
- pip:
|
| 297 |
+
- appdirs==1.4.4
|
| 298 |
+
- argon2-cffi==23.1.0
|
| 299 |
+
- argon2-cffi-bindings==21.2.0
|
| 300 |
+
- asttokens==2.4.1
|
| 301 |
+
- async-lru==2.0.4
|
| 302 |
+
- attrs==23.2.0
|
| 303 |
+
- babel==2.14.0
|
| 304 |
+
- bleach==6.1.0
|
| 305 |
+
- cachetools==4.2.4
|
| 306 |
+
- comm==0.2.2
|
| 307 |
+
- contourpy==1.2.1
|
| 308 |
+
- cycler==0.12.1
|
| 309 |
+
- debugpy==1.8.1
|
| 310 |
+
- decorator==5.1.1
|
| 311 |
+
- defusedxml==0.7.1
|
| 312 |
+
- docker-pycreds==0.4.0
|
| 313 |
+
- docstring-parser==0.15
|
| 314 |
+
- executing==2.0.1
|
| 315 |
+
- fastjsonschema==2.19.1
|
| 316 |
+
- fonttools==4.51.0
|
| 317 |
+
- fqdn==1.5.1
|
| 318 |
+
- gitdb==4.0.11
|
| 319 |
+
- gitpython==3.1.42
|
| 320 |
+
- google-auth==1.35.0
|
| 321 |
+
- h5py==3.10.0
|
| 322 |
+
- httpcore==1.0.5
|
| 323 |
+
- httpx==0.27.0
|
| 324 |
+
- imbalanced-learn==0.12.0
|
| 325 |
+
- iniconfig==2.0.0
|
| 326 |
+
- ipykernel==6.29.4
|
| 327 |
+
- ipython==8.23.0
|
| 328 |
+
- ipywidgets==8.1.2
|
| 329 |
+
- isoduration==20.11.0
|
| 330 |
+
- jedi==0.19.1
|
| 331 |
+
- json5==0.9.25
|
| 332 |
+
- jsonargparse==4.23.1
|
| 333 |
+
- jsonschema==4.21.1
|
| 334 |
+
- jsonschema-specifications==2023.12.1
|
| 335 |
+
- jupyter==1.0.0
|
| 336 |
+
- jupyter-client==8.6.1
|
| 337 |
+
- jupyter-console==6.6.3
|
| 338 |
+
- jupyter-core==5.7.2
|
| 339 |
+
- jupyter-events==0.10.0
|
| 340 |
+
- jupyter-lsp==2.2.5
|
| 341 |
+
- jupyter-server==2.14.0
|
| 342 |
+
- jupyter-server-terminals==0.5.3
|
| 343 |
+
- jupyterlab==4.1.6
|
| 344 |
+
- jupyterlab-pygments==0.3.0
|
| 345 |
+
- jupyterlab-server==2.26.0
|
| 346 |
+
- jupyterlab-widgets==3.0.10
|
| 347 |
+
- kiwisolver==1.4.5
|
| 348 |
+
- llvmlite==0.42.0
|
| 349 |
+
- matplotlib==3.8.4
|
| 350 |
+
- matplotlib-inline==0.1.7
|
| 351 |
+
- mistune==3.0.2
|
| 352 |
+
- nbclient==0.10.0
|
| 353 |
+
- nbconvert==7.16.3
|
| 354 |
+
- nbformat==5.10.4
|
| 355 |
+
- nest-asyncio==1.6.0
|
| 356 |
+
- nltk==3.8.1
|
| 357 |
+
- notebook==7.1.3
|
| 358 |
+
- notebook-shim==0.2.4
|
| 359 |
+
- numba==0.59.1
|
| 360 |
+
- overrides==7.7.0
|
| 361 |
+
- pandocfilters==1.5.1
|
| 362 |
+
- parso==0.8.4
|
| 363 |
+
- pluggy==1.5.0
|
| 364 |
+
- prometheus-client==0.20.0
|
| 365 |
+
- prompt-toolkit==3.0.43
|
| 366 |
+
- pure-eval==0.2.2
|
| 367 |
+
- pynndescent==0.5.12
|
| 368 |
+
- pynvml==11.5.0
|
| 369 |
+
- pytest==8.1.1
|
| 370 |
+
- python-json-logger==2.0.7
|
| 371 |
+
- pyzmq==26.0.1
|
| 372 |
+
- qtconsole==5.5.1
|
| 373 |
+
- qtpy==2.4.1
|
| 374 |
+
- rdkit==2023.9.5
|
| 375 |
+
- rdkit-pypi==2022.9.5
|
| 376 |
+
- referencing==0.34.0
|
| 377 |
+
- requests==2.31.0
|
| 378 |
+
- rfc3339-validator==0.1.4
|
| 379 |
+
- rfc3986-validator==0.1.1
|
| 380 |
+
- rouge-score==0.1.2
|
| 381 |
+
- rpds-py==0.18.0
|
| 382 |
+
- seaborn==0.13.2
|
| 383 |
+
- send2trash==1.8.3
|
| 384 |
+
- sentry-sdk==1.41.0
|
| 385 |
+
- setproctitle==1.3.3
|
| 386 |
+
- smmap==5.0.1
|
| 387 |
+
- stack-data==0.6.3
|
| 388 |
+
- tensorboard-data-server==0.6.1
|
| 389 |
+
- terminado==0.18.1
|
| 390 |
+
- tinycss2==1.2.1
|
| 391 |
+
- tornado==6.4
|
| 392 |
+
- traitlets==5.14.3
|
| 393 |
+
- typeshed-client==2.3.0
|
| 394 |
+
- umap-learn==0.5.6
|
| 395 |
+
- uri-template==1.3.0
|
| 396 |
+
- wandb==0.16.4
|
| 397 |
+
- webcolors==1.13
|
| 398 |
+
- websocket-client==1.7.0
|
| 399 |
+
- widgetsnbextension==4.0.10
|