├── .github └── dependabot.yml ├── .gitignore ├── LICENSE ├── README.md ├── attention.png ├── example.py ├── model ├── config.json ├── encoder.json └── vocab.bpe ├── poetry.lock ├── pyproject.toml ├── tinygpt2 ├── __init__.py ├── encoder.py ├── gpt2_minimal.py ├── gpt2_ops.py ├── gpt2_run.py ├── gpt2_tensors.py └── gpt2_viz.py └── tokens.py /.github/dependabot.yml: -------------------------------------------------------------------------------- 1 | # To get started with Dependabot version updates, you'll need to specify which 2 | # package ecosystems to update and where the package manifests are located. 3 | # Please see the documentation for all configuration options: 4 | # https://docs.github.com/code-security/dependabot/dependabot-version-updates/configuration-options-for-the-dependabot.yml-file 5 | 6 | version: 2 7 | updates: 8 | - package-ecosystem: "pip" # See documentation for possible values 9 | directory: "/" # Location of package manifests 10 | schedule: 11 | interval: "weekly" 12 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | *.safetensors 2 | __pycache__ 3 | .DS_Store 4 | *.pyc 5 | *.pyo 6 | *.pyd 7 | *.pyw 8 | .venv 9 | .mypy_cache 10 | .ruff_cache -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | Copyright (c) 2025, Stephen Diehl 2 | 3 | Permission is hereby granted, free of charge, to any person obtaining a copy 4 | of this software and associated documentation files (the "Software"), to 5 | deal in the Software without restriction, including without limitation the 6 | rights to use, copy, modify, merge, publish, distribute, sublicense, and/or 7 | sell copies of the Software, and to permit persons to whom the Software is 8 | furnished to do so, subject to the following conditions: 9 | 10 | The above copyright notice and this permission notice shall be included in 11 | all copies or substantial portions of the Software. 12 | 13 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 14 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 15 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 16 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 17 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING 18 | FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS 19 | IN THE SOFTWARE. 20 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # tinygpt2 2 | 3 | A reference implementation of GPT-2 in pure Python. Download the weights from 4 | HuggingFace and performs inference just using NumPy. Really only useful for as 5 | a teaching tool, don't actually use this for anything. 6 | 7 | * [GPT2 Safetensors](https://huggingface.co/openai-community/gpt2/blob/main/model.safetensors) 8 | * [Download Link](https://huggingface.co/openai-community/gpt2/resolve/main/model.safetensors) ( 548 MB ) 9 | 10 | Also need to download the encoder and vocab files `vocab.bpe` and `encoder.json` 11 | 12 | 13 | ## Running 14 | 15 | ```bash 16 | # Install dependencies 17 | poetry install 18 | 19 | # Run inference examples 20 | poetry run python example.py 21 | ``` 22 | 23 | ## Structure 24 | 25 | The core logic is split into several files: 26 | 27 | * [`gpt2_tensors.py`](tinygpt2/gpt2_tensors.py) - Loads the tensors into layer forms that can be used for inference 28 | * [`gpt2_ops.py`](tinygpt2/gpt2_ops.py) - Implements the GPT-2 primitives (gelu, layernorm, softmax, etc.) 29 | * [`gpt2_run.py`](tinygpt2/gpt2_run.py) - Loads the weights and runs inference 30 | 31 | In addition, the following files are included: 32 | 33 | * [`encoder.py`](tinygpt2/encoder.py) - The BPE encoder from the original GPT-2 repository 34 | * [`tokens.py`](tokens.py) - Example of how to use the encoder 35 | * [`gpt2_minimal.py`](tinygpt2/gpt2_minimal.py) - The GPT-2 model in a single function 36 | * [`gpt2_viz.py`](tinygpt2/gpt2_viz.py) - Visualize the attention patterns of the model 37 | 38 | In the model directory, you will find the following files: 39 | 40 | * [`config.json`](model/config.json) - The GPT-2 model configuration 41 | * `model.safetensors` - The model weights 42 | * `vocab.bpe` - The BPE vocab from the original GPT-2 repository 43 | * `encoder.json` - The encoder json from the original GPT-2 repository 44 | 45 | ## Visualization 46 | 47 | The attention patterns of the model can be visualized using the `gpt2_viz.py` script. This will generate a heatmap of the attention patterns for a given input sequence. 48 | 49 | ![](./attention.png) 50 | 51 | ## License 52 | 53 | MIT License 54 | -------------------------------------------------------------------------------- /attention.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sdiehl/tiny-gpt2/4cff8cc17a7782f6e898314a54ecc2f05aa0d47c/attention.png -------------------------------------------------------------------------------- /example.py: -------------------------------------------------------------------------------- 1 | from tinygpt2 import load_gpt2_weights, generate 2 | 3 | # Load model parameters once 4 | print("Loading model parameters...") 5 | params, hparams = load_gpt2_weights() 6 | 7 | example_prompts = [ 8 | ("The rain in Spain falls mainly in the", 40), 9 | ("You're a wizard Harry,", 10), 10 | ("What is the capital of France?", 10), 11 | ("Stephen Hawking is a", 40), 12 | ("The quick brown fox jumped over", 10), 13 | ("Star Wars is a movie about", 40), 14 | ("Alan Turing theorized that computers would one day become", 10), 15 | ] 16 | 17 | # Run each prompt and print the results 18 | for prompt, max_tokens in example_prompts: 19 | print(f"\nPrompt: {prompt}") 20 | generate(params, hparams, prompt.strip(), max_tokens) 21 | -------------------------------------------------------------------------------- /model/config.json: -------------------------------------------------------------------------------- 1 | { 2 | "activation_function": "gelu_new", 3 | "architectures": [ 4 | "GPT2LMHeadModel" 5 | ], 6 | "attn_pdrop": 0.1, 7 | "bos_token_id": 50256, 8 | "embd_pdrop": 0.1, 9 | "eos_token_id": 50256, 10 | "initializer_range": 0.02, 11 | "layer_norm_epsilon": 1e-05, 12 | "model_type": "gpt2", 13 | "n_ctx": 1024, 14 | "n_embd": 768, 15 | "n_head": 12, 16 | "n_layer": 12, 17 | "n_positions": 1024, 18 | "resid_pdrop": 0.1, 19 | "summary_activation": null, 20 | "summary_first_dropout": 0.1, 21 | "summary_proj_to_labels": true, 22 | "summary_type": "cls_index", 23 | "summary_use_proj": true, 24 | "task_specific_params": { 25 | "text-generation": { 26 | "do_sample": true, 27 | "max_length": 50 28 | } 29 | }, 30 | "vocab_size": 50257 31 | } -------------------------------------------------------------------------------- /poetry.lock: -------------------------------------------------------------------------------- 1 | # This file is automatically @generated by Poetry 2.1.1 and should not be changed by hand. 2 | 3 | [[package]] 4 | name = "black" 5 | version = "25.1.0" 6 | description = "The uncompromising code formatter." 7 | optional = false 8 | python-versions = ">=3.9" 9 | groups = ["dev"] 10 | files = [ 11 | {file = "black-25.1.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:759e7ec1e050a15f89b770cefbf91ebee8917aac5c20483bc2d80a6c3a04df32"}, 12 | {file = "black-25.1.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:0e519ecf93120f34243e6b0054db49c00a35f84f195d5bce7e9f5cfc578fc2da"}, 13 | {file = "black-25.1.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:055e59b198df7ac0b7efca5ad7ff2516bca343276c466be72eb04a3bcc1f82d7"}, 14 | {file = "black-25.1.0-cp310-cp310-win_amd64.whl", hash = "sha256:db8ea9917d6f8fc62abd90d944920d95e73c83a5ee3383493e35d271aca872e9"}, 15 | {file = "black-25.1.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:a39337598244de4bae26475f77dda852ea00a93bd4c728e09eacd827ec929df0"}, 16 | {file = "black-25.1.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:96c1c7cd856bba8e20094e36e0f948718dc688dba4a9d78c3adde52b9e6c2299"}, 17 | {file = "black-25.1.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:bce2e264d59c91e52d8000d507eb20a9aca4a778731a08cfff7e5ac4a4bb7096"}, 18 | {file = "black-25.1.0-cp311-cp311-win_amd64.whl", hash = "sha256:172b1dbff09f86ce6f4eb8edf9dede08b1fce58ba194c87d7a4f1a5aa2f5b3c2"}, 19 | {file = "black-25.1.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:4b60580e829091e6f9238c848ea6750efed72140b91b048770b64e74fe04908b"}, 20 | {file = "black-25.1.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:1e2978f6df243b155ef5fa7e558a43037c3079093ed5d10fd84c43900f2d8ecc"}, 21 | {file = "black-25.1.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:3b48735872ec535027d979e8dcb20bf4f70b5ac75a8ea99f127c106a7d7aba9f"}, 22 | {file = "black-25.1.0-cp312-cp312-win_amd64.whl", hash = "sha256:ea0213189960bda9cf99be5b8c8ce66bb054af5e9e861249cd23471bd7b0b3ba"}, 23 | {file = "black-25.1.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:8f0b18a02996a836cc9c9c78e5babec10930862827b1b724ddfe98ccf2f2fe4f"}, 24 | {file = "black-25.1.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:afebb7098bfbc70037a053b91ae8437c3857482d3a690fefc03e9ff7aa9a5fd3"}, 25 | {file = "black-25.1.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:030b9759066a4ee5e5aca28c3c77f9c64789cdd4de8ac1df642c40b708be6171"}, 26 | {file = "black-25.1.0-cp313-cp313-win_amd64.whl", hash = "sha256:a22f402b410566e2d1c950708c77ebf5ebd5d0d88a6a2e87c86d9fb48afa0d18"}, 27 | {file = "black-25.1.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:a1ee0a0c330f7b5130ce0caed9936a904793576ef4d2b98c40835d6a65afa6a0"}, 28 | {file = "black-25.1.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:f3df5f1bf91d36002b0a75389ca8663510cf0531cca8aa5c1ef695b46d98655f"}, 29 | {file = "black-25.1.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:d9e6827d563a2c820772b32ce8a42828dc6790f095f441beef18f96aa6f8294e"}, 30 | {file = "black-25.1.0-cp39-cp39-win_amd64.whl", hash = "sha256:bacabb307dca5ebaf9c118d2d2f6903da0d62c9faa82bd21a33eecc319559355"}, 31 | {file = "black-25.1.0-py3-none-any.whl", hash = "sha256:95e8176dae143ba9097f351d174fdaf0ccd29efb414b362ae3fd72bf0f710717"}, 32 | {file = "black-25.1.0.tar.gz", hash = "sha256:33496d5cd1222ad73391352b4ae8da15253c5de89b93a80b3e2c8d9a19ec2666"}, 33 | ] 34 | 35 | [package.dependencies] 36 | click = ">=8.0.0" 37 | mypy-extensions = ">=0.4.3" 38 | packaging = ">=22.0" 39 | pathspec = ">=0.9.0" 40 | platformdirs = ">=2" 41 | 42 | [package.extras] 43 | colorama = ["colorama (>=0.4.3)"] 44 | d = ["aiohttp (>=3.10)"] 45 | jupyter = ["ipython (>=7.8.0)", "tokenize-rt (>=3.2.0)"] 46 | uvloop = ["uvloop (>=0.15.2)"] 47 | 48 | [[package]] 49 | name = "certifi" 50 | version = "2025.1.31" 51 | description = "Python package for providing Mozilla's CA Bundle." 52 | optional = false 53 | python-versions = ">=3.6" 54 | groups = ["main"] 55 | files = [ 56 | {file = "certifi-2025.1.31-py3-none-any.whl", hash = "sha256:ca78db4565a652026a4db2bcdf68f2fb589ea80d0be70e03929ed730746b84fe"}, 57 | {file = "certifi-2025.1.31.tar.gz", hash = "sha256:3d5da6925056f6f18f119200434a4780a94263f10d1c21d032a6f6b2baa20651"}, 58 | ] 59 | 60 | [[package]] 61 | name = "charset-normalizer" 62 | version = "3.4.1" 63 | description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet." 64 | optional = false 65 | python-versions = ">=3.7" 66 | groups = ["main"] 67 | files = [ 68 | {file = "charset_normalizer-3.4.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:91b36a978b5ae0ee86c394f5a54d6ef44db1de0815eb43de826d41d21e4af3de"}, 69 | {file = "charset_normalizer-3.4.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7461baadb4dc00fd9e0acbe254e3d7d2112e7f92ced2adc96e54ef6501c5f176"}, 70 | {file = "charset_normalizer-3.4.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e218488cd232553829be0664c2292d3af2eeeb94b32bea483cf79ac6a694e037"}, 71 | {file = "charset_normalizer-3.4.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:80ed5e856eb7f30115aaf94e4a08114ccc8813e6ed1b5efa74f9f82e8509858f"}, 72 | {file = "charset_normalizer-3.4.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b010a7a4fd316c3c484d482922d13044979e78d1861f0e0650423144c616a46a"}, 73 | {file = "charset_normalizer-3.4.1-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:4532bff1b8421fd0a320463030c7520f56a79c9024a4e88f01c537316019005a"}, 74 | {file = "charset_normalizer-3.4.1-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:d973f03c0cb71c5ed99037b870f2be986c3c05e63622c017ea9816881d2dd247"}, 75 | {file = "charset_normalizer-3.4.1-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:3a3bd0dcd373514dcec91c411ddb9632c0d7d92aed7093b8c3bbb6d69ca74408"}, 76 | {file = "charset_normalizer-3.4.1-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:d9c3cdf5390dcd29aa8056d13e8e99526cda0305acc038b96b30352aff5ff2bb"}, 77 | {file = "charset_normalizer-3.4.1-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:2bdfe3ac2e1bbe5b59a1a63721eb3b95fc9b6817ae4a46debbb4e11f6232428d"}, 78 | {file = "charset_normalizer-3.4.1-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:eab677309cdb30d047996b36d34caeda1dc91149e4fdca0b1a039b3f79d9a807"}, 79 | {file = "charset_normalizer-3.4.1-cp310-cp310-win32.whl", hash = "sha256:c0429126cf75e16c4f0ad00ee0eae4242dc652290f940152ca8c75c3a4b6ee8f"}, 80 | {file = "charset_normalizer-3.4.1-cp310-cp310-win_amd64.whl", hash = "sha256:9f0b8b1c6d84c8034a44893aba5e767bf9c7a211e313a9605d9c617d7083829f"}, 81 | {file = "charset_normalizer-3.4.1-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:8bfa33f4f2672964266e940dd22a195989ba31669bd84629f05fab3ef4e2d125"}, 82 | {file = "charset_normalizer-3.4.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:28bf57629c75e810b6ae989f03c0828d64d6b26a5e205535585f96093e405ed1"}, 83 | {file = "charset_normalizer-3.4.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f08ff5e948271dc7e18a35641d2f11a4cd8dfd5634f55228b691e62b37125eb3"}, 84 | {file = "charset_normalizer-3.4.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:234ac59ea147c59ee4da87a0c0f098e9c8d169f4dc2a159ef720f1a61bbe27cd"}, 85 | {file = "charset_normalizer-3.4.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:fd4ec41f914fa74ad1b8304bbc634b3de73d2a0889bd32076342a573e0779e00"}, 86 | {file = "charset_normalizer-3.4.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:eea6ee1db730b3483adf394ea72f808b6e18cf3cb6454b4d86e04fa8c4327a12"}, 87 | {file = "charset_normalizer-3.4.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:c96836c97b1238e9c9e3fe90844c947d5afbf4f4c92762679acfe19927d81d77"}, 88 | {file = "charset_normalizer-3.4.1-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:4d86f7aff21ee58f26dcf5ae81a9addbd914115cdebcbb2217e4f0ed8982e146"}, 89 | {file = "charset_normalizer-3.4.1-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:09b5e6733cbd160dcc09589227187e242a30a49ca5cefa5a7edd3f9d19ed53fd"}, 90 | {file = "charset_normalizer-3.4.1-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:5777ee0881f9499ed0f71cc82cf873d9a0ca8af166dfa0af8ec4e675b7df48e6"}, 91 | {file = "charset_normalizer-3.4.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:237bdbe6159cff53b4f24f397d43c6336c6b0b42affbe857970cefbb620911c8"}, 92 | {file = "charset_normalizer-3.4.1-cp311-cp311-win32.whl", hash = "sha256:8417cb1f36cc0bc7eaba8ccb0e04d55f0ee52df06df3ad55259b9a323555fc8b"}, 93 | {file = "charset_normalizer-3.4.1-cp311-cp311-win_amd64.whl", hash = "sha256:d7f50a1f8c450f3925cb367d011448c39239bb3eb4117c36a6d354794de4ce76"}, 94 | {file = "charset_normalizer-3.4.1-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:73d94b58ec7fecbc7366247d3b0b10a21681004153238750bb67bd9012414545"}, 95 | {file = "charset_normalizer-3.4.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:dad3e487649f498dd991eeb901125411559b22e8d7ab25d3aeb1af367df5efd7"}, 96 | {file = "charset_normalizer-3.4.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:c30197aa96e8eed02200a83fba2657b4c3acd0f0aa4bdc9f6c1af8e8962e0757"}, 97 | {file = "charset_normalizer-3.4.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2369eea1ee4a7610a860d88f268eb39b95cb588acd7235e02fd5a5601773d4fa"}, 98 | {file = "charset_normalizer-3.4.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bc2722592d8998c870fa4e290c2eec2c1569b87fe58618e67d38b4665dfa680d"}, 99 | {file = "charset_normalizer-3.4.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ffc9202a29ab3920fa812879e95a9e78b2465fd10be7fcbd042899695d75e616"}, 100 | {file = "charset_normalizer-3.4.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:804a4d582ba6e5b747c625bf1255e6b1507465494a40a2130978bda7b932c90b"}, 101 | {file = "charset_normalizer-3.4.1-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:0f55e69f030f7163dffe9fd0752b32f070566451afe180f99dbeeb81f511ad8d"}, 102 | {file = "charset_normalizer-3.4.1-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:c4c3e6da02df6fa1410a7680bd3f63d4f710232d3139089536310d027950696a"}, 103 | {file = "charset_normalizer-3.4.1-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:5df196eb874dae23dcfb968c83d4f8fdccb333330fe1fc278ac5ceeb101003a9"}, 104 | {file = "charset_normalizer-3.4.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:e358e64305fe12299a08e08978f51fc21fac060dcfcddd95453eabe5b93ed0e1"}, 105 | {file = "charset_normalizer-3.4.1-cp312-cp312-win32.whl", hash = "sha256:9b23ca7ef998bc739bf6ffc077c2116917eabcc901f88da1b9856b210ef63f35"}, 106 | {file = "charset_normalizer-3.4.1-cp312-cp312-win_amd64.whl", hash = "sha256:6ff8a4a60c227ad87030d76e99cd1698345d4491638dfa6673027c48b3cd395f"}, 107 | {file = "charset_normalizer-3.4.1-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:aabfa34badd18f1da5ec1bc2715cadc8dca465868a4e73a0173466b688f29dda"}, 108 | {file = "charset_normalizer-3.4.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:22e14b5d70560b8dd51ec22863f370d1e595ac3d024cb8ad7d308b4cd95f8313"}, 109 | {file = "charset_normalizer-3.4.1-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8436c508b408b82d87dc5f62496973a1805cd46727c34440b0d29d8a2f50a6c9"}, 110 | {file = "charset_normalizer-3.4.1-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2d074908e1aecee37a7635990b2c6d504cd4766c7bc9fc86d63f9c09af3fa11b"}, 111 | {file = "charset_normalizer-3.4.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:955f8851919303c92343d2f66165294848d57e9bba6cf6e3625485a70a038d11"}, 112 | {file = "charset_normalizer-3.4.1-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:44ecbf16649486d4aebafeaa7ec4c9fed8b88101f4dd612dcaf65d5e815f837f"}, 113 | {file = "charset_normalizer-3.4.1-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:0924e81d3d5e70f8126529951dac65c1010cdf117bb75eb02dd12339b57749dd"}, 114 | {file = "charset_normalizer-3.4.1-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:2967f74ad52c3b98de4c3b32e1a44e32975e008a9cd2a8cc8966d6a5218c5cb2"}, 115 | {file = "charset_normalizer-3.4.1-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:c75cb2a3e389853835e84a2d8fb2b81a10645b503eca9bcb98df6b5a43eb8886"}, 116 | {file = "charset_normalizer-3.4.1-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:09b26ae6b1abf0d27570633b2b078a2a20419c99d66fb2823173d73f188ce601"}, 117 | {file = "charset_normalizer-3.4.1-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:fa88b843d6e211393a37219e6a1c1df99d35e8fd90446f1118f4216e307e48cd"}, 118 | {file = "charset_normalizer-3.4.1-cp313-cp313-win32.whl", hash = "sha256:eb8178fe3dba6450a3e024e95ac49ed3400e506fd4e9e5c32d30adda88cbd407"}, 119 | {file = "charset_normalizer-3.4.1-cp313-cp313-win_amd64.whl", hash = "sha256:b1ac5992a838106edb89654e0aebfc24f5848ae2547d22c2c3f66454daa11971"}, 120 | {file = "charset_normalizer-3.4.1-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f30bf9fd9be89ecb2360c7d94a711f00c09b976258846efe40db3d05828e8089"}, 121 | {file = "charset_normalizer-3.4.1-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:97f68b8d6831127e4787ad15e6757232e14e12060bec17091b85eb1486b91d8d"}, 122 | {file = "charset_normalizer-3.4.1-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:7974a0b5ecd505609e3b19742b60cee7aa2aa2fb3151bc917e6e2646d7667dcf"}, 123 | {file = "charset_normalizer-3.4.1-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:fc54db6c8593ef7d4b2a331b58653356cf04f67c960f584edb7c3d8c97e8f39e"}, 124 | {file = "charset_normalizer-3.4.1-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:311f30128d7d333eebd7896965bfcfbd0065f1716ec92bd5638d7748eb6f936a"}, 125 | {file = "charset_normalizer-3.4.1-cp37-cp37m-musllinux_1_2_aarch64.whl", hash = "sha256:7d053096f67cd1241601111b698f5cad775f97ab25d81567d3f59219b5f1adbd"}, 126 | {file = "charset_normalizer-3.4.1-cp37-cp37m-musllinux_1_2_i686.whl", hash = "sha256:807f52c1f798eef6cf26beb819eeb8819b1622ddfeef9d0977a8502d4db6d534"}, 127 | {file = "charset_normalizer-3.4.1-cp37-cp37m-musllinux_1_2_ppc64le.whl", hash = "sha256:dccbe65bd2f7f7ec22c4ff99ed56faa1e9f785482b9bbd7c717e26fd723a1d1e"}, 128 | {file = "charset_normalizer-3.4.1-cp37-cp37m-musllinux_1_2_s390x.whl", hash = "sha256:2fb9bd477fdea8684f78791a6de97a953c51831ee2981f8e4f583ff3b9d9687e"}, 129 | {file = "charset_normalizer-3.4.1-cp37-cp37m-musllinux_1_2_x86_64.whl", hash = "sha256:01732659ba9b5b873fc117534143e4feefecf3b2078b0a6a2e925271bb6f4cfa"}, 130 | {file = "charset_normalizer-3.4.1-cp37-cp37m-win32.whl", hash = "sha256:7a4f97a081603d2050bfaffdefa5b02a9ec823f8348a572e39032caa8404a487"}, 131 | {file = "charset_normalizer-3.4.1-cp37-cp37m-win_amd64.whl", hash = "sha256:7b1bef6280950ee6c177b326508f86cad7ad4dff12454483b51d8b7d673a2c5d"}, 132 | {file = "charset_normalizer-3.4.1-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:ecddf25bee22fe4fe3737a399d0d177d72bc22be6913acfab364b40bce1ba83c"}, 133 | {file = "charset_normalizer-3.4.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8c60ca7339acd497a55b0ea5d506b2a2612afb2826560416f6894e8b5770d4a9"}, 134 | {file = "charset_normalizer-3.4.1-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b7b2d86dd06bfc2ade3312a83a5c364c7ec2e3498f8734282c6c3d4b07b346b8"}, 135 | {file = "charset_normalizer-3.4.1-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:dd78cfcda14a1ef52584dbb008f7ac81c1328c0f58184bf9a84c49c605002da6"}, 136 | {file = "charset_normalizer-3.4.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6e27f48bcd0957c6d4cb9d6fa6b61d192d0b13d5ef563e5f2ae35feafc0d179c"}, 137 | {file = "charset_normalizer-3.4.1-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:01ad647cdd609225c5350561d084b42ddf732f4eeefe6e678765636791e78b9a"}, 138 | {file = "charset_normalizer-3.4.1-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:619a609aa74ae43d90ed2e89bdd784765de0a25ca761b93e196d938b8fd1dbbd"}, 139 | {file = "charset_normalizer-3.4.1-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:89149166622f4db9b4b6a449256291dc87a99ee53151c74cbd82a53c8c2f6ccd"}, 140 | {file = "charset_normalizer-3.4.1-cp38-cp38-musllinux_1_2_ppc64le.whl", hash = "sha256:7709f51f5f7c853f0fb938bcd3bc59cdfdc5203635ffd18bf354f6967ea0f824"}, 141 | {file = "charset_normalizer-3.4.1-cp38-cp38-musllinux_1_2_s390x.whl", hash = "sha256:345b0426edd4e18138d6528aed636de7a9ed169b4aaf9d61a8c19e39d26838ca"}, 142 | {file = "charset_normalizer-3.4.1-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:0907f11d019260cdc3f94fbdb23ff9125f6b5d1039b76003b5b0ac9d6a6c9d5b"}, 143 | {file = "charset_normalizer-3.4.1-cp38-cp38-win32.whl", hash = "sha256:ea0d8d539afa5eb2728aa1932a988a9a7af94f18582ffae4bc10b3fbdad0626e"}, 144 | {file = "charset_normalizer-3.4.1-cp38-cp38-win_amd64.whl", hash = "sha256:329ce159e82018d646c7ac45b01a430369d526569ec08516081727a20e9e4af4"}, 145 | {file = "charset_normalizer-3.4.1-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:b97e690a2118911e39b4042088092771b4ae3fc3aa86518f84b8cf6888dbdb41"}, 146 | {file = "charset_normalizer-3.4.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:78baa6d91634dfb69ec52a463534bc0df05dbd546209b79a3880a34487f4b84f"}, 147 | {file = "charset_normalizer-3.4.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1a2bc9f351a75ef49d664206d51f8e5ede9da246602dc2d2726837620ea034b2"}, 148 | {file = "charset_normalizer-3.4.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:75832c08354f595c760a804588b9357d34ec00ba1c940c15e31e96d902093770"}, 149 | {file = "charset_normalizer-3.4.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0af291f4fe114be0280cdd29d533696a77b5b49cfde5467176ecab32353395c4"}, 150 | {file = "charset_normalizer-3.4.1-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0167ddc8ab6508fe81860a57dd472b2ef4060e8d378f0cc555707126830f2537"}, 151 | {file = "charset_normalizer-3.4.1-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:2a75d49014d118e4198bcee5ee0a6f25856b29b12dbf7cd012791f8a6cc5c496"}, 152 | {file = "charset_normalizer-3.4.1-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:363e2f92b0f0174b2f8238240a1a30142e3db7b957a5dd5689b0e75fb717cc78"}, 153 | {file = "charset_normalizer-3.4.1-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:ab36c8eb7e454e34e60eb55ca5d241a5d18b2c6244f6827a30e451c42410b5f7"}, 154 | {file = "charset_normalizer-3.4.1-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:4c0907b1928a36d5a998d72d64d8eaa7244989f7aaaf947500d3a800c83a3fd6"}, 155 | {file = "charset_normalizer-3.4.1-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:04432ad9479fa40ec0f387795ddad4437a2b50417c69fa275e212933519ff294"}, 156 | {file = "charset_normalizer-3.4.1-cp39-cp39-win32.whl", hash = "sha256:3bed14e9c89dcb10e8f3a29f9ccac4955aebe93c71ae803af79265c9ca5644c5"}, 157 | {file = "charset_normalizer-3.4.1-cp39-cp39-win_amd64.whl", hash = "sha256:49402233c892a461407c512a19435d1ce275543138294f7ef013f0b63d5d3765"}, 158 | {file = "charset_normalizer-3.4.1-py3-none-any.whl", hash = "sha256:d98b1668f06378c6dbefec3b92299716b931cd4e6061f3c875a71ced1780ab85"}, 159 | {file = "charset_normalizer-3.4.1.tar.gz", hash = "sha256:44251f18cd68a75b56585dd00dae26183e102cd5e0f9f1466e6df5da2ed64ea3"}, 160 | ] 161 | 162 | [[package]] 163 | name = "click" 164 | version = "8.1.8" 165 | description = "Composable command line interface toolkit" 166 | optional = false 167 | python-versions = ">=3.7" 168 | groups = ["dev"] 169 | files = [ 170 | {file = "click-8.1.8-py3-none-any.whl", hash = "sha256:63c132bbbed01578a06712a2d1f497bb62d9c1c0d329b7903a866228027263b2"}, 171 | {file = "click-8.1.8.tar.gz", hash = "sha256:ed53c9d8990d83c2a27deae68e4ee337473f6330c040a31d4225c9574d16096a"}, 172 | ] 173 | 174 | [package.dependencies] 175 | colorama = {version = "*", markers = "platform_system == \"Windows\""} 176 | 177 | [[package]] 178 | name = "colorama" 179 | version = "0.4.6" 180 | description = "Cross-platform colored terminal text." 181 | optional = false 182 | python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7" 183 | groups = ["dev"] 184 | markers = "platform_system == \"Windows\"" 185 | files = [ 186 | {file = "colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6"}, 187 | {file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"}, 188 | ] 189 | 190 | [[package]] 191 | name = "contourpy" 192 | version = "1.3.1" 193 | description = "Python library for calculating contours of 2D quadrilateral grids" 194 | optional = false 195 | python-versions = ">=3.10" 196 | groups = ["vis"] 197 | files = [ 198 | {file = "contourpy-1.3.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:a045f341a77b77e1c5de31e74e966537bba9f3c4099b35bf4c2e3939dd54cdab"}, 199 | {file = "contourpy-1.3.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:500360b77259914f7805af7462e41f9cb7ca92ad38e9f94d6c8641b089338124"}, 200 | {file = "contourpy-1.3.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b2f926efda994cdf3c8d3fdb40b9962f86edbc4457e739277b961eced3d0b4c1"}, 201 | {file = "contourpy-1.3.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:adce39d67c0edf383647a3a007de0a45fd1b08dedaa5318404f1a73059c2512b"}, 202 | {file = "contourpy-1.3.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:abbb49fb7dac584e5abc6636b7b2a7227111c4f771005853e7d25176daaf8453"}, 203 | {file = "contourpy-1.3.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a0cffcbede75c059f535725c1680dfb17b6ba8753f0c74b14e6a9c68c29d7ea3"}, 204 | {file = "contourpy-1.3.1-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:ab29962927945d89d9b293eabd0d59aea28d887d4f3be6c22deaefbb938a7277"}, 205 | {file = "contourpy-1.3.1-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:974d8145f8ca354498005b5b981165b74a195abfae9a8129df3e56771961d595"}, 206 | {file = "contourpy-1.3.1-cp310-cp310-win32.whl", hash = "sha256:ac4578ac281983f63b400f7fe6c101bedc10651650eef012be1ccffcbacf3697"}, 207 | {file = "contourpy-1.3.1-cp310-cp310-win_amd64.whl", hash = "sha256:174e758c66bbc1c8576992cec9599ce8b6672b741b5d336b5c74e35ac382b18e"}, 208 | {file = "contourpy-1.3.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:3e8b974d8db2c5610fb4e76307e265de0edb655ae8169e8b21f41807ccbeec4b"}, 209 | {file = "contourpy-1.3.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:20914c8c973f41456337652a6eeca26d2148aa96dd7ac323b74516988bea89fc"}, 210 | {file = "contourpy-1.3.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:19d40d37c1c3a4961b4619dd9d77b12124a453cc3d02bb31a07d58ef684d3d86"}, 211 | {file = "contourpy-1.3.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:113231fe3825ebf6f15eaa8bc1f5b0ddc19d42b733345eae0934cb291beb88b6"}, 212 | {file = "contourpy-1.3.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:4dbbc03a40f916a8420e420d63e96a1258d3d1b58cbdfd8d1f07b49fcbd38e85"}, 213 | {file = "contourpy-1.3.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3a04ecd68acbd77fa2d39723ceca4c3197cb2969633836ced1bea14e219d077c"}, 214 | {file = "contourpy-1.3.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:c414fc1ed8ee1dbd5da626cf3710c6013d3d27456651d156711fa24f24bd1291"}, 215 | {file = "contourpy-1.3.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:31c1b55c1f34f80557d3830d3dd93ba722ce7e33a0b472cba0ec3b6535684d8f"}, 216 | {file = "contourpy-1.3.1-cp311-cp311-win32.whl", hash = "sha256:f611e628ef06670df83fce17805c344710ca5cde01edfdc72751311da8585375"}, 217 | {file = "contourpy-1.3.1-cp311-cp311-win_amd64.whl", hash = "sha256:b2bdca22a27e35f16794cf585832e542123296b4687f9fd96822db6bae17bfc9"}, 218 | {file = "contourpy-1.3.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:0ffa84be8e0bd33410b17189f7164c3589c229ce5db85798076a3fa136d0e509"}, 219 | {file = "contourpy-1.3.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:805617228ba7e2cbbfb6c503858e626ab528ac2a32a04a2fe88ffaf6b02c32bc"}, 220 | {file = "contourpy-1.3.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ade08d343436a94e633db932e7e8407fe7de8083967962b46bdfc1b0ced39454"}, 221 | {file = "contourpy-1.3.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:47734d7073fb4590b4a40122b35917cd77be5722d80683b249dac1de266aac80"}, 222 | {file = "contourpy-1.3.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2ba94a401342fc0f8b948e57d977557fbf4d515f03c67682dd5c6191cb2d16ec"}, 223 | {file = "contourpy-1.3.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:efa874e87e4a647fd2e4f514d5e91c7d493697127beb95e77d2f7561f6905bd9"}, 224 | {file = "contourpy-1.3.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:1bf98051f1045b15c87868dbaea84f92408337d4f81d0e449ee41920ea121d3b"}, 225 | {file = "contourpy-1.3.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:61332c87493b00091423e747ea78200659dc09bdf7fd69edd5e98cef5d3e9a8d"}, 226 | {file = "contourpy-1.3.1-cp312-cp312-win32.whl", hash = "sha256:e914a8cb05ce5c809dd0fe350cfbb4e881bde5e2a38dc04e3afe1b3e58bd158e"}, 227 | {file = "contourpy-1.3.1-cp312-cp312-win_amd64.whl", hash = "sha256:08d9d449a61cf53033612cb368f3a1b26cd7835d9b8cd326647efe43bca7568d"}, 228 | {file = "contourpy-1.3.1-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:a761d9ccfc5e2ecd1bf05534eda382aa14c3e4f9205ba5b1684ecfe400716ef2"}, 229 | {file = "contourpy-1.3.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:523a8ee12edfa36f6d2a49407f705a6ef4c5098de4f498619787e272de93f2d5"}, 230 | {file = "contourpy-1.3.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ece6df05e2c41bd46776fbc712e0996f7c94e0d0543af1656956d150c4ca7c81"}, 231 | {file = "contourpy-1.3.1-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:573abb30e0e05bf31ed067d2f82500ecfdaec15627a59d63ea2d95714790f5c2"}, 232 | {file = "contourpy-1.3.1-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a9fa36448e6a3a1a9a2ba23c02012c43ed88905ec80163f2ffe2421c7192a5d7"}, 233 | {file = "contourpy-1.3.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3ea9924d28fc5586bf0b42d15f590b10c224117e74409dd7a0be3b62b74a501c"}, 234 | {file = "contourpy-1.3.1-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:5b75aa69cb4d6f137b36f7eb2ace9280cfb60c55dc5f61c731fdf6f037f958a3"}, 235 | {file = "contourpy-1.3.1-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:041b640d4ec01922083645a94bb3b2e777e6b626788f4095cf21abbe266413c1"}, 236 | {file = "contourpy-1.3.1-cp313-cp313-win32.whl", hash = "sha256:36987a15e8ace5f58d4d5da9dca82d498c2bbb28dff6e5d04fbfcc35a9cb3a82"}, 237 | {file = "contourpy-1.3.1-cp313-cp313-win_amd64.whl", hash = "sha256:a7895f46d47671fa7ceec40f31fae721da51ad34bdca0bee83e38870b1f47ffd"}, 238 | {file = "contourpy-1.3.1-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:9ddeb796389dadcd884c7eb07bd14ef12408aaae358f0e2ae24114d797eede30"}, 239 | {file = "contourpy-1.3.1-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:19c1555a6801c2f084c7ddc1c6e11f02eb6a6016ca1318dd5452ba3f613a1751"}, 240 | {file = "contourpy-1.3.1-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:841ad858cff65c2c04bf93875e384ccb82b654574a6d7f30453a04f04af71342"}, 241 | {file = "contourpy-1.3.1-cp313-cp313t-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:4318af1c925fb9a4fb190559ef3eec206845f63e80fb603d47f2d6d67683901c"}, 242 | {file = "contourpy-1.3.1-cp313-cp313t-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:14c102b0eab282427b662cb590f2e9340a9d91a1c297f48729431f2dcd16e14f"}, 243 | {file = "contourpy-1.3.1-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:05e806338bfeaa006acbdeba0ad681a10be63b26e1b17317bfac3c5d98f36cda"}, 244 | {file = "contourpy-1.3.1-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:4d76d5993a34ef3df5181ba3c92fabb93f1eaa5729504fb03423fcd9f3177242"}, 245 | {file = "contourpy-1.3.1-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:89785bb2a1980c1bd87f0cb1517a71cde374776a5f150936b82580ae6ead44a1"}, 246 | {file = "contourpy-1.3.1-cp313-cp313t-win32.whl", hash = "sha256:8eb96e79b9f3dcadbad2a3891672f81cdcab7f95b27f28f1c67d75f045b6b4f1"}, 247 | {file = "contourpy-1.3.1-cp313-cp313t-win_amd64.whl", hash = "sha256:287ccc248c9e0d0566934e7d606201abd74761b5703d804ff3df8935f523d546"}, 248 | {file = "contourpy-1.3.1-pp310-pypy310_pp73-macosx_10_15_x86_64.whl", hash = "sha256:b457d6430833cee8e4b8e9b6f07aa1c161e5e0d52e118dc102c8f9bd7dd060d6"}, 249 | {file = "contourpy-1.3.1-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cb76c1a154b83991a3cbbf0dfeb26ec2833ad56f95540b442c73950af2013750"}, 250 | {file = "contourpy-1.3.1-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:44a29502ca9c7b5ba389e620d44f2fbe792b1fb5734e8b931ad307071ec58c53"}, 251 | {file = "contourpy-1.3.1.tar.gz", hash = "sha256:dfd97abd83335045a913e3bcc4a09c0ceadbe66580cf573fe961f4a825efa699"}, 252 | ] 253 | 254 | [package.dependencies] 255 | numpy = ">=1.23" 256 | 257 | [package.extras] 258 | bokeh = ["bokeh", "selenium"] 259 | docs = ["furo", "sphinx (>=7.2)", "sphinx-copybutton"] 260 | mypy = ["contourpy[bokeh,docs]", "docutils-stubs", "mypy (==1.11.1)", "types-Pillow"] 261 | test = ["Pillow", "contourpy[test-no-images]", "matplotlib"] 262 | test-no-images = ["pytest", "pytest-cov", "pytest-rerunfailures", "pytest-xdist", "wurlitzer"] 263 | 264 | [[package]] 265 | name = "cycler" 266 | version = "0.12.1" 267 | description = "Composable style cycles" 268 | optional = false 269 | python-versions = ">=3.8" 270 | groups = ["vis"] 271 | files = [ 272 | {file = "cycler-0.12.1-py3-none-any.whl", hash = "sha256:85cef7cff222d8644161529808465972e51340599459b8ac3ccbac5a854e0d30"}, 273 | {file = "cycler-0.12.1.tar.gz", hash = "sha256:88bb128f02ba341da8ef447245a9e138fae777f6a23943da4540077d3601eb1c"}, 274 | ] 275 | 276 | [package.extras] 277 | docs = ["ipython", "matplotlib", "numpydoc", "sphinx"] 278 | tests = ["pytest", "pytest-cov", "pytest-xdist"] 279 | 280 | [[package]] 281 | name = "fonttools" 282 | version = "4.57.0" 283 | description = "Tools to manipulate font files" 284 | optional = false 285 | python-versions = ">=3.8" 286 | groups = ["vis"] 287 | files = [ 288 | {file = "fonttools-4.57.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:babe8d1eb059a53e560e7bf29f8e8f4accc8b6cfb9b5fd10e485bde77e71ef41"}, 289 | {file = "fonttools-4.57.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:81aa97669cd726349eb7bd43ca540cf418b279ee3caba5e2e295fb4e8f841c02"}, 290 | {file = "fonttools-4.57.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f0e9618630edd1910ad4f07f60d77c184b2f572c8ee43305ea3265675cbbfe7e"}, 291 | {file = "fonttools-4.57.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:34687a5d21f1d688d7d8d416cb4c5b9c87fca8a1797ec0d74b9fdebfa55c09ab"}, 292 | {file = "fonttools-4.57.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:69ab81b66ebaa8d430ba56c7a5f9abe0183afefd3a2d6e483060343398b13fb1"}, 293 | {file = "fonttools-4.57.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:d639397de852f2ccfb3134b152c741406752640a266d9c1365b0f23d7b88077f"}, 294 | {file = "fonttools-4.57.0-cp310-cp310-win32.whl", hash = "sha256:cc066cb98b912f525ae901a24cd381a656f024f76203bc85f78fcc9e66ae5aec"}, 295 | {file = "fonttools-4.57.0-cp310-cp310-win_amd64.whl", hash = "sha256:7a64edd3ff6a7f711a15bd70b4458611fb240176ec11ad8845ccbab4fe6745db"}, 296 | {file = "fonttools-4.57.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:3871349303bdec958360eedb619169a779956503ffb4543bb3e6211e09b647c4"}, 297 | {file = "fonttools-4.57.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:c59375e85126b15a90fcba3443eaac58f3073ba091f02410eaa286da9ad80ed8"}, 298 | {file = "fonttools-4.57.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:967b65232e104f4b0f6370a62eb33089e00024f2ce143aecbf9755649421c683"}, 299 | {file = "fonttools-4.57.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:39acf68abdfc74e19de7485f8f7396fa4d2418efea239b7061d6ed6a2510c746"}, 300 | {file = "fonttools-4.57.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:9d077f909f2343daf4495ba22bb0e23b62886e8ec7c109ee8234bdbd678cf344"}, 301 | {file = "fonttools-4.57.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:46370ac47a1e91895d40e9ad48effbe8e9d9db1a4b80888095bc00e7beaa042f"}, 302 | {file = "fonttools-4.57.0-cp311-cp311-win32.whl", hash = "sha256:ca2aed95855506b7ae94e8f1f6217b7673c929e4f4f1217bcaa236253055cb36"}, 303 | {file = "fonttools-4.57.0-cp311-cp311-win_amd64.whl", hash = "sha256:17168a4670bbe3775f3f3f72d23ee786bd965395381dfbb70111e25e81505b9d"}, 304 | {file = "fonttools-4.57.0-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:889e45e976c74abc7256d3064aa7c1295aa283c6bb19810b9f8b604dfe5c7f31"}, 305 | {file = "fonttools-4.57.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:0425c2e052a5f1516c94e5855dbda706ae5a768631e9fcc34e57d074d1b65b92"}, 306 | {file = "fonttools-4.57.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:44c26a311be2ac130f40a96769264809d3b0cb297518669db437d1cc82974888"}, 307 | {file = "fonttools-4.57.0-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:84c41ba992df5b8d680b89fd84c6a1f2aca2b9f1ae8a67400c8930cd4ea115f6"}, 308 | {file = "fonttools-4.57.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:ea1e9e43ca56b0c12440a7c689b1350066595bebcaa83baad05b8b2675129d98"}, 309 | {file = "fonttools-4.57.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:84fd56c78d431606332a0627c16e2a63d243d0d8b05521257d77c6529abe14d8"}, 310 | {file = "fonttools-4.57.0-cp312-cp312-win32.whl", hash = "sha256:f4376819c1c778d59e0a31db5dc6ede854e9edf28bbfa5b756604727f7f800ac"}, 311 | {file = "fonttools-4.57.0-cp312-cp312-win_amd64.whl", hash = "sha256:57e30241524879ea10cdf79c737037221f77cc126a8cdc8ff2c94d4a522504b9"}, 312 | {file = "fonttools-4.57.0-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:408ce299696012d503b714778d89aa476f032414ae57e57b42e4b92363e0b8ef"}, 313 | {file = "fonttools-4.57.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:bbceffc80aa02d9e8b99f2a7491ed8c4a783b2fc4020119dc405ca14fb5c758c"}, 314 | {file = "fonttools-4.57.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f022601f3ee9e1f6658ed6d184ce27fa5216cee5b82d279e0f0bde5deebece72"}, 315 | {file = "fonttools-4.57.0-cp313-cp313-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4dea5893b58d4637ffa925536462ba626f8a1b9ffbe2f5c272cdf2c6ebadb817"}, 316 | {file = "fonttools-4.57.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:dff02c5c8423a657c550b48231d0a48d7e2b2e131088e55983cfe74ccc2c7cc9"}, 317 | {file = "fonttools-4.57.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:767604f244dc17c68d3e2dbf98e038d11a18abc078f2d0f84b6c24571d9c0b13"}, 318 | {file = "fonttools-4.57.0-cp313-cp313-win32.whl", hash = "sha256:8e2e12d0d862f43d51e5afb8b9751c77e6bec7d2dc00aad80641364e9df5b199"}, 319 | {file = "fonttools-4.57.0-cp313-cp313-win_amd64.whl", hash = "sha256:f1d6bc9c23356908db712d282acb3eebd4ae5ec6d8b696aa40342b1d84f8e9e3"}, 320 | {file = "fonttools-4.57.0-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:9d57b4e23ebbe985125d3f0cabbf286efa191ab60bbadb9326091050d88e8213"}, 321 | {file = "fonttools-4.57.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:579ba873d7f2a96f78b2e11028f7472146ae181cae0e4d814a37a09e93d5c5cc"}, 322 | {file = "fonttools-4.57.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6e3e1ec10c29bae0ea826b61f265ec5c858c5ba2ce2e69a71a62f285cf8e4595"}, 323 | {file = "fonttools-4.57.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a1968f2a2003c97c4ce6308dc2498d5fd4364ad309900930aa5a503c9851aec8"}, 324 | {file = "fonttools-4.57.0-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:aff40f8ac6763d05c2c8f6d240c6dac4bb92640a86d9b0c3f3fff4404f34095c"}, 325 | {file = "fonttools-4.57.0-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:d07f1b64008e39fceae7aa99e38df8385d7d24a474a8c9872645c4397b674481"}, 326 | {file = "fonttools-4.57.0-cp38-cp38-win32.whl", hash = "sha256:51d8482e96b28fb28aa8e50b5706f3cee06de85cbe2dce80dbd1917ae22ec5a6"}, 327 | {file = "fonttools-4.57.0-cp38-cp38-win_amd64.whl", hash = "sha256:03290e818782e7edb159474144fca11e36a8ed6663d1fcbd5268eb550594fd8e"}, 328 | {file = "fonttools-4.57.0-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:7339e6a3283e4b0ade99cade51e97cde3d54cd6d1c3744459e886b66d630c8b3"}, 329 | {file = "fonttools-4.57.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:05efceb2cb5f6ec92a4180fcb7a64aa8d3385fd49cfbbe459350229d1974f0b1"}, 330 | {file = "fonttools-4.57.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a97bb05eb24637714a04dee85bdf0ad1941df64fe3b802ee4ac1c284a5f97b7c"}, 331 | {file = "fonttools-4.57.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:541cb48191a19ceb1a2a4b90c1fcebd22a1ff7491010d3cf840dd3a68aebd654"}, 332 | {file = "fonttools-4.57.0-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:cdef9a056c222d0479a1fdb721430f9efd68268014c54e8166133d2643cb05d9"}, 333 | {file = "fonttools-4.57.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:3cf97236b192a50a4bf200dc5ba405aa78d4f537a2c6e4c624bb60466d5b03bd"}, 334 | {file = "fonttools-4.57.0-cp39-cp39-win32.whl", hash = "sha256:e952c684274a7714b3160f57ec1d78309f955c6335c04433f07d36c5eb27b1f9"}, 335 | {file = "fonttools-4.57.0-cp39-cp39-win_amd64.whl", hash = "sha256:a2a722c0e4bfd9966a11ff55c895c817158fcce1b2b6700205a376403b546ad9"}, 336 | {file = "fonttools-4.57.0-py3-none-any.whl", hash = "sha256:3122c604a675513c68bd24c6a8f9091f1c2376d18e8f5fe5a101746c81b3e98f"}, 337 | {file = "fonttools-4.57.0.tar.gz", hash = "sha256:727ece10e065be2f9dd239d15dd5d60a66e17eac11aea47d447f9f03fdbc42de"}, 338 | ] 339 | 340 | [package.extras] 341 | all = ["brotli (>=1.0.1) ; platform_python_implementation == \"CPython\"", "brotlicffi (>=0.8.0) ; platform_python_implementation != \"CPython\"", "fs (>=2.2.0,<3)", "lxml (>=4.0)", "lz4 (>=1.7.4.2)", "matplotlib", "munkres ; platform_python_implementation == \"PyPy\"", "pycairo", "scipy ; platform_python_implementation != \"PyPy\"", "skia-pathops (>=0.5.0)", "sympy", "uharfbuzz (>=0.23.0)", "unicodedata2 (>=15.1.0) ; python_version <= \"3.12\"", "xattr ; sys_platform == \"darwin\"", "zopfli (>=0.1.4)"] 342 | graphite = ["lz4 (>=1.7.4.2)"] 343 | interpolatable = ["munkres ; platform_python_implementation == \"PyPy\"", "pycairo", "scipy ; platform_python_implementation != \"PyPy\""] 344 | lxml = ["lxml (>=4.0)"] 345 | pathops = ["skia-pathops (>=0.5.0)"] 346 | plot = ["matplotlib"] 347 | repacker = ["uharfbuzz (>=0.23.0)"] 348 | symfont = ["sympy"] 349 | type1 = ["xattr ; sys_platform == \"darwin\""] 350 | ufo = ["fs (>=2.2.0,<3)"] 351 | unicode = ["unicodedata2 (>=15.1.0) ; python_version <= \"3.12\""] 352 | woff = ["brotli (>=1.0.1) ; platform_python_implementation == \"CPython\"", "brotlicffi (>=0.8.0) ; platform_python_implementation != \"CPython\"", "zopfli (>=0.1.4)"] 353 | 354 | [[package]] 355 | name = "idna" 356 | version = "3.10" 357 | description = "Internationalized Domain Names in Applications (IDNA)" 358 | optional = false 359 | python-versions = ">=3.6" 360 | groups = ["main"] 361 | files = [ 362 | {file = "idna-3.10-py3-none-any.whl", hash = "sha256:946d195a0d259cbba61165e88e65941f16e9b36ea6ddb97f00452bae8b1287d3"}, 363 | {file = "idna-3.10.tar.gz", hash = "sha256:12f65c9b470abda6dc35cf8e63cc574b1c52b11df2c86030af0ac09b01b13ea9"}, 364 | ] 365 | 366 | [package.extras] 367 | all = ["flake8 (>=7.1.1)", "mypy (>=1.11.2)", "pytest (>=8.3.2)", "ruff (>=0.6.2)"] 368 | 369 | [[package]] 370 | name = "kiwisolver" 371 | version = "1.4.8" 372 | description = "A fast implementation of the Cassowary constraint solver" 373 | optional = false 374 | python-versions = ">=3.10" 375 | groups = ["vis"] 376 | files = [ 377 | {file = "kiwisolver-1.4.8-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:88c6f252f6816a73b1f8c904f7bbe02fd67c09a69f7cb8a0eecdbf5ce78e63db"}, 378 | {file = "kiwisolver-1.4.8-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:c72941acb7b67138f35b879bbe85be0f6c6a70cab78fe3ef6db9c024d9223e5b"}, 379 | {file = "kiwisolver-1.4.8-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:ce2cf1e5688edcb727fdf7cd1bbd0b6416758996826a8be1d958f91880d0809d"}, 380 | {file = "kiwisolver-1.4.8-cp310-cp310-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:c8bf637892dc6e6aad2bc6d4d69d08764166e5e3f69d469e55427b6ac001b19d"}, 381 | {file = "kiwisolver-1.4.8-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:034d2c891f76bd3edbdb3ea11140d8510dca675443da7304205a2eaa45d8334c"}, 382 | {file = "kiwisolver-1.4.8-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d47b28d1dfe0793d5e96bce90835e17edf9a499b53969b03c6c47ea5985844c3"}, 383 | {file = "kiwisolver-1.4.8-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:eb158fe28ca0c29f2260cca8c43005329ad58452c36f0edf298204de32a9a3ed"}, 384 | {file = "kiwisolver-1.4.8-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d5536185fce131780ebd809f8e623bf4030ce1b161353166c49a3c74c287897f"}, 385 | {file = "kiwisolver-1.4.8-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:369b75d40abedc1da2c1f4de13f3482cb99e3237b38726710f4a793432b1c5ff"}, 386 | {file = "kiwisolver-1.4.8-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:641f2ddf9358c80faa22e22eb4c9f54bd3f0e442e038728f500e3b978d00aa7d"}, 387 | {file = "kiwisolver-1.4.8-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:d561d2d8883e0819445cfe58d7ddd673e4015c3c57261d7bdcd3710d0d14005c"}, 388 | {file = "kiwisolver-1.4.8-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:1732e065704b47c9afca7ffa272f845300a4eb959276bf6970dc07265e73b605"}, 389 | {file = "kiwisolver-1.4.8-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:bcb1ebc3547619c3b58a39e2448af089ea2ef44b37988caf432447374941574e"}, 390 | {file = "kiwisolver-1.4.8-cp310-cp310-win_amd64.whl", hash = "sha256:89c107041f7b27844179ea9c85d6da275aa55ecf28413e87624d033cf1f6b751"}, 391 | {file = "kiwisolver-1.4.8-cp310-cp310-win_arm64.whl", hash = "sha256:b5773efa2be9eb9fcf5415ea3ab70fc785d598729fd6057bea38d539ead28271"}, 392 | {file = "kiwisolver-1.4.8-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:a4d3601908c560bdf880f07d94f31d734afd1bb71e96585cace0e38ef44c6d84"}, 393 | {file = "kiwisolver-1.4.8-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:856b269c4d28a5c0d5e6c1955ec36ebfd1651ac00e1ce0afa3e28da95293b561"}, 394 | {file = "kiwisolver-1.4.8-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:c2b9a96e0f326205af81a15718a9073328df1173a2619a68553decb7097fd5d7"}, 395 | {file = "kiwisolver-1.4.8-cp311-cp311-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c5020c83e8553f770cb3b5fc13faac40f17e0b205bd237aebd21d53d733adb03"}, 396 | {file = "kiwisolver-1.4.8-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:dace81d28c787956bfbfbbfd72fdcef014f37d9b48830829e488fdb32b49d954"}, 397 | {file = "kiwisolver-1.4.8-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:11e1022b524bd48ae56c9b4f9296bce77e15a2e42a502cceba602f804b32bb79"}, 398 | {file = "kiwisolver-1.4.8-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3b9b4d2892fefc886f30301cdd80debd8bb01ecdf165a449eb6e78f79f0fabd6"}, 399 | {file = "kiwisolver-1.4.8-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3a96c0e790ee875d65e340ab383700e2b4891677b7fcd30a699146f9384a2bb0"}, 400 | {file = "kiwisolver-1.4.8-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:23454ff084b07ac54ca8be535f4174170c1094a4cff78fbae4f73a4bcc0d4dab"}, 401 | {file = "kiwisolver-1.4.8-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:87b287251ad6488e95b4f0b4a79a6d04d3ea35fde6340eb38fbd1ca9cd35bbbc"}, 402 | {file = "kiwisolver-1.4.8-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:b21dbe165081142b1232a240fc6383fd32cdd877ca6cc89eab93e5f5883e1c25"}, 403 | {file = "kiwisolver-1.4.8-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:768cade2c2df13db52475bd28d3a3fac8c9eff04b0e9e2fda0f3760f20b3f7fc"}, 404 | {file = "kiwisolver-1.4.8-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:d47cfb2650f0e103d4bf68b0b5804c68da97272c84bb12850d877a95c056bd67"}, 405 | {file = "kiwisolver-1.4.8-cp311-cp311-win_amd64.whl", hash = "sha256:ed33ca2002a779a2e20eeb06aea7721b6e47f2d4b8a8ece979d8ba9e2a167e34"}, 406 | {file = "kiwisolver-1.4.8-cp311-cp311-win_arm64.whl", hash = "sha256:16523b40aab60426ffdebe33ac374457cf62863e330a90a0383639ce14bf44b2"}, 407 | {file = "kiwisolver-1.4.8-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:d6af5e8815fd02997cb6ad9bbed0ee1e60014438ee1a5c2444c96f87b8843502"}, 408 | {file = "kiwisolver-1.4.8-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:bade438f86e21d91e0cf5dd7c0ed00cda0f77c8c1616bd83f9fc157fa6760d31"}, 409 | {file = "kiwisolver-1.4.8-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:b83dc6769ddbc57613280118fb4ce3cd08899cc3369f7d0e0fab518a7cf37fdb"}, 410 | {file = "kiwisolver-1.4.8-cp312-cp312-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:111793b232842991be367ed828076b03d96202c19221b5ebab421ce8bcad016f"}, 411 | {file = "kiwisolver-1.4.8-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:257af1622860e51b1a9d0ce387bf5c2c4f36a90594cb9514f55b074bcc787cfc"}, 412 | {file = "kiwisolver-1.4.8-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:69b5637c3f316cab1ec1c9a12b8c5f4750a4c4b71af9157645bf32830e39c03a"}, 413 | {file = "kiwisolver-1.4.8-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:782bb86f245ec18009890e7cb8d13a5ef54dcf2ebe18ed65f795e635a96a1c6a"}, 414 | {file = "kiwisolver-1.4.8-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cc978a80a0db3a66d25767b03688f1147a69e6237175c0f4ffffaaedf744055a"}, 415 | {file = "kiwisolver-1.4.8-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:36dbbfd34838500a31f52c9786990d00150860e46cd5041386f217101350f0d3"}, 416 | {file = "kiwisolver-1.4.8-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:eaa973f1e05131de5ff3569bbba7f5fd07ea0595d3870ed4a526d486fe57fa1b"}, 417 | {file = "kiwisolver-1.4.8-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:a66f60f8d0c87ab7f59b6fb80e642ebb29fec354a4dfad687ca4092ae69d04f4"}, 418 | {file = "kiwisolver-1.4.8-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:858416b7fb777a53f0c59ca08190ce24e9abbd3cffa18886a5781b8e3e26f65d"}, 419 | {file = "kiwisolver-1.4.8-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:085940635c62697391baafaaeabdf3dd7a6c3643577dde337f4d66eba021b2b8"}, 420 | {file = "kiwisolver-1.4.8-cp312-cp312-win_amd64.whl", hash = "sha256:01c3d31902c7db5fb6182832713d3b4122ad9317c2c5877d0539227d96bb2e50"}, 421 | {file = "kiwisolver-1.4.8-cp312-cp312-win_arm64.whl", hash = "sha256:a3c44cb68861de93f0c4a8175fbaa691f0aa22550c331fefef02b618a9dcb476"}, 422 | {file = "kiwisolver-1.4.8-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:1c8ceb754339793c24aee1c9fb2485b5b1f5bb1c2c214ff13368431e51fc9a09"}, 423 | {file = "kiwisolver-1.4.8-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:54a62808ac74b5e55a04a408cda6156f986cefbcf0ada13572696b507cc92fa1"}, 424 | {file = "kiwisolver-1.4.8-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:68269e60ee4929893aad82666821aaacbd455284124817af45c11e50a4b42e3c"}, 425 | {file = "kiwisolver-1.4.8-cp313-cp313-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:34d142fba9c464bc3bbfeff15c96eab0e7310343d6aefb62a79d51421fcc5f1b"}, 426 | {file = "kiwisolver-1.4.8-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3ddc373e0eef45b59197de815b1b28ef89ae3955e7722cc9710fb91cd77b7f47"}, 427 | {file = "kiwisolver-1.4.8-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:77e6f57a20b9bd4e1e2cedda4d0b986ebd0216236f0106e55c28aea3d3d69b16"}, 428 | {file = "kiwisolver-1.4.8-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:08e77738ed7538f036cd1170cbed942ef749137b1311fa2bbe2a7fda2f6bf3cc"}, 429 | {file = "kiwisolver-1.4.8-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a5ce1e481a74b44dd5e92ff03ea0cb371ae7a0268318e202be06c8f04f4f1246"}, 430 | {file = "kiwisolver-1.4.8-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:fc2ace710ba7c1dfd1a3b42530b62b9ceed115f19a1656adefce7b1782a37794"}, 431 | {file = "kiwisolver-1.4.8-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:3452046c37c7692bd52b0e752b87954ef86ee2224e624ef7ce6cb21e8c41cc1b"}, 432 | {file = "kiwisolver-1.4.8-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:7e9a60b50fe8b2ec6f448fe8d81b07e40141bfced7f896309df271a0b92f80f3"}, 433 | {file = "kiwisolver-1.4.8-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:918139571133f366e8362fa4a297aeba86c7816b7ecf0bc79168080e2bd79957"}, 434 | {file = "kiwisolver-1.4.8-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:e063ef9f89885a1d68dd8b2e18f5ead48653176d10a0e324e3b0030e3a69adeb"}, 435 | {file = "kiwisolver-1.4.8-cp313-cp313-win_amd64.whl", hash = "sha256:a17b7c4f5b2c51bb68ed379defd608a03954a1845dfed7cc0117f1cc8a9b7fd2"}, 436 | {file = "kiwisolver-1.4.8-cp313-cp313-win_arm64.whl", hash = "sha256:3cd3bc628b25f74aedc6d374d5babf0166a92ff1317f46267f12d2ed54bc1d30"}, 437 | {file = "kiwisolver-1.4.8-cp313-cp313t-macosx_10_13_universal2.whl", hash = "sha256:370fd2df41660ed4e26b8c9d6bbcad668fbe2560462cba151a721d49e5b6628c"}, 438 | {file = "kiwisolver-1.4.8-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:84a2f830d42707de1d191b9490ac186bf7997a9495d4e9072210a1296345f7dc"}, 439 | {file = "kiwisolver-1.4.8-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:7a3ad337add5148cf51ce0b55642dc551c0b9d6248458a757f98796ca7348712"}, 440 | {file = "kiwisolver-1.4.8-cp313-cp313t-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:7506488470f41169b86d8c9aeff587293f530a23a23a49d6bc64dab66bedc71e"}, 441 | {file = "kiwisolver-1.4.8-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2f0121b07b356a22fb0414cec4666bbe36fd6d0d759db3d37228f496ed67c880"}, 442 | {file = "kiwisolver-1.4.8-cp313-cp313t-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d6d6bd87df62c27d4185de7c511c6248040afae67028a8a22012b010bc7ad062"}, 443 | {file = "kiwisolver-1.4.8-cp313-cp313t-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:291331973c64bb9cce50bbe871fb2e675c4331dab4f31abe89f175ad7679a4d7"}, 444 | {file = "kiwisolver-1.4.8-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:893f5525bb92d3d735878ec00f781b2de998333659507d29ea4466208df37bed"}, 445 | {file = "kiwisolver-1.4.8-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:b47a465040146981dc9db8647981b8cb96366fbc8d452b031e4f8fdffec3f26d"}, 446 | {file = "kiwisolver-1.4.8-cp313-cp313t-musllinux_1_2_i686.whl", hash = "sha256:99cea8b9dd34ff80c521aef46a1dddb0dcc0283cf18bde6d756f1e6f31772165"}, 447 | {file = "kiwisolver-1.4.8-cp313-cp313t-musllinux_1_2_ppc64le.whl", hash = "sha256:151dffc4865e5fe6dafce5480fab84f950d14566c480c08a53c663a0020504b6"}, 448 | {file = "kiwisolver-1.4.8-cp313-cp313t-musllinux_1_2_s390x.whl", hash = "sha256:577facaa411c10421314598b50413aa1ebcf5126f704f1e5d72d7e4e9f020d90"}, 449 | {file = "kiwisolver-1.4.8-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:be4816dc51c8a471749d664161b434912eee82f2ea66bd7628bd14583a833e85"}, 450 | {file = "kiwisolver-1.4.8-pp310-pypy310_pp73-macosx_10_15_x86_64.whl", hash = "sha256:e7a019419b7b510f0f7c9dceff8c5eae2392037eae483a7f9162625233802b0a"}, 451 | {file = "kiwisolver-1.4.8-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:286b18e86682fd2217a48fc6be6b0f20c1d0ed10958d8dc53453ad58d7be0bf8"}, 452 | {file = "kiwisolver-1.4.8-pp310-pypy310_pp73-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:4191ee8dfd0be1c3666ccbac178c5a05d5f8d689bbe3fc92f3c4abec817f8fe0"}, 453 | {file = "kiwisolver-1.4.8-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7cd2785b9391f2873ad46088ed7599a6a71e762e1ea33e87514b1a441ed1da1c"}, 454 | {file = "kiwisolver-1.4.8-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c07b29089b7ba090b6f1a669f1411f27221c3662b3a1b7010e67b59bb5a6f10b"}, 455 | {file = "kiwisolver-1.4.8-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:65ea09a5a3faadd59c2ce96dc7bf0f364986a315949dc6374f04396b0d60e09b"}, 456 | {file = "kiwisolver-1.4.8.tar.gz", hash = "sha256:23d5f023bdc8c7e54eb65f03ca5d5bb25b601eac4d7f1a042888a1f45237987e"}, 457 | ] 458 | 459 | [[package]] 460 | name = "matplotlib" 461 | version = "3.10.3" 462 | description = "Python plotting package" 463 | optional = false 464 | python-versions = ">=3.10" 465 | groups = ["vis"] 466 | files = [ 467 | {file = "matplotlib-3.10.3-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:213fadd6348d106ca7db99e113f1bea1e65e383c3ba76e8556ba4a3054b65ae7"}, 468 | {file = "matplotlib-3.10.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:d3bec61cb8221f0ca6313889308326e7bb303d0d302c5cc9e523b2f2e6c73deb"}, 469 | {file = "matplotlib-3.10.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8c21ae75651c0231b3ba014b6d5e08fb969c40cdb5a011e33e99ed0c9ea86ecb"}, 470 | {file = "matplotlib-3.10.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a49e39755580b08e30e3620efc659330eac5d6534ab7eae50fa5e31f53ee4e30"}, 471 | {file = "matplotlib-3.10.3-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:cf4636203e1190871d3a73664dea03d26fb019b66692cbfd642faafdad6208e8"}, 472 | {file = "matplotlib-3.10.3-cp310-cp310-win_amd64.whl", hash = "sha256:fd5641a9bb9d55f4dd2afe897a53b537c834b9012684c8444cc105895c8c16fd"}, 473 | {file = "matplotlib-3.10.3-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:0ef061f74cd488586f552d0c336b2f078d43bc00dc473d2c3e7bfee2272f3fa8"}, 474 | {file = "matplotlib-3.10.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:d96985d14dc5f4a736bbea4b9de9afaa735f8a0fc2ca75be2fa9e96b2097369d"}, 475 | {file = "matplotlib-3.10.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7c5f0283da91e9522bdba4d6583ed9d5521566f63729ffb68334f86d0bb98049"}, 476 | {file = "matplotlib-3.10.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:fdfa07c0ec58035242bc8b2c8aae37037c9a886370eef6850703d7583e19964b"}, 477 | {file = "matplotlib-3.10.3-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:c0b9849a17bce080a16ebcb80a7b714b5677d0ec32161a2cc0a8e5a6030ae220"}, 478 | {file = "matplotlib-3.10.3-cp311-cp311-win_amd64.whl", hash = "sha256:eef6ed6c03717083bc6d69c2d7ee8624205c29a8e6ea5a31cd3492ecdbaee1e1"}, 479 | {file = "matplotlib-3.10.3-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:0ab1affc11d1f495ab9e6362b8174a25afc19c081ba5b0775ef00533a4236eea"}, 480 | {file = "matplotlib-3.10.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:2a818d8bdcafa7ed2eed74487fdb071c09c1ae24152d403952adad11fa3c65b4"}, 481 | {file = "matplotlib-3.10.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:748ebc3470c253e770b17d8b0557f0aa85cf8c63fd52f1a61af5b27ec0b7ffee"}, 482 | {file = "matplotlib-3.10.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ed70453fd99733293ace1aec568255bc51c6361cb0da94fa5ebf0649fdb2150a"}, 483 | {file = "matplotlib-3.10.3-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:dbed9917b44070e55640bd13419de83b4c918e52d97561544814ba463811cbc7"}, 484 | {file = "matplotlib-3.10.3-cp312-cp312-win_amd64.whl", hash = "sha256:cf37d8c6ef1a48829443e8ba5227b44236d7fcaf7647caa3178a4ff9f7a5be05"}, 485 | {file = "matplotlib-3.10.3-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:9f2efccc8dcf2b86fc4ee849eea5dcaecedd0773b30f47980dc0cbeabf26ec84"}, 486 | {file = "matplotlib-3.10.3-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:3ddbba06a6c126e3301c3d272a99dcbe7f6c24c14024e80307ff03791a5f294e"}, 487 | {file = "matplotlib-3.10.3-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:748302b33ae9326995b238f606e9ed840bf5886ebafcb233775d946aa8107a15"}, 488 | {file = "matplotlib-3.10.3-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a80fcccbef63302c0efd78042ea3c2436104c5b1a4d3ae20f864593696364ac7"}, 489 | {file = "matplotlib-3.10.3-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:55e46cbfe1f8586adb34f7587c3e4f7dedc59d5226719faf6cb54fc24f2fd52d"}, 490 | {file = "matplotlib-3.10.3-cp313-cp313-win_amd64.whl", hash = "sha256:151d89cb8d33cb23345cd12490c76fd5d18a56581a16d950b48c6ff19bb2ab93"}, 491 | {file = "matplotlib-3.10.3-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:c26dd9834e74d164d06433dc7be5d75a1e9890b926b3e57e74fa446e1a62c3e2"}, 492 | {file = "matplotlib-3.10.3-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:24853dad5b8c84c8c2390fc31ce4858b6df504156893292ce8092d190ef8151d"}, 493 | {file = "matplotlib-3.10.3-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:68f7878214d369d7d4215e2a9075fef743be38fa401d32e6020bab2dfabaa566"}, 494 | {file = "matplotlib-3.10.3-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f6929fc618cb6db9cb75086f73b3219bbb25920cb24cee2ea7a12b04971a4158"}, 495 | {file = "matplotlib-3.10.3-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:6c7818292a5cc372a2dc4c795e5c356942eb8350b98ef913f7fda51fe175ac5d"}, 496 | {file = "matplotlib-3.10.3-cp313-cp313t-win_amd64.whl", hash = "sha256:4f23ffe95c5667ef8a2b56eea9b53db7f43910fa4a2d5472ae0f72b64deab4d5"}, 497 | {file = "matplotlib-3.10.3-pp310-pypy310_pp73-macosx_10_15_x86_64.whl", hash = "sha256:86ab63d66bbc83fdb6733471d3bff40897c1e9921cba112accd748eee4bce5e4"}, 498 | {file = "matplotlib-3.10.3-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:a48f9c08bf7444b5d2391a83e75edb464ccda3c380384b36532a0962593a1751"}, 499 | {file = "matplotlib-3.10.3-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cb73d8aa75a237457988f9765e4dfe1c0d2453c5ca4eabc897d4309672c8e014"}, 500 | {file = "matplotlib-3.10.3.tar.gz", hash = "sha256:2f82d2c5bb7ae93aaaa4cd42aca65d76ce6376f83304fa3a630b569aca274df0"}, 501 | ] 502 | 503 | [package.dependencies] 504 | contourpy = ">=1.0.1" 505 | cycler = ">=0.10" 506 | fonttools = ">=4.22.0" 507 | kiwisolver = ">=1.3.1" 508 | numpy = ">=1.23" 509 | packaging = ">=20.0" 510 | pillow = ">=8" 511 | pyparsing = ">=2.3.1" 512 | python-dateutil = ">=2.7" 513 | 514 | [package.extras] 515 | dev = ["meson-python (>=0.13.1,<0.17.0)", "pybind11 (>=2.13.2,!=2.13.3)", "setuptools (>=64)", "setuptools_scm (>=7)"] 516 | 517 | [[package]] 518 | name = "mypy" 519 | version = "1.16.0" 520 | description = "Optional static typing for Python" 521 | optional = false 522 | python-versions = ">=3.9" 523 | groups = ["dev"] 524 | files = [ 525 | {file = "mypy-1.16.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:7909541fef256527e5ee9c0a7e2aeed78b6cda72ba44298d1334fe7881b05c5c"}, 526 | {file = "mypy-1.16.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:e71d6f0090c2256c713ed3d52711d01859c82608b5d68d4fa01a3fe30df95571"}, 527 | {file = "mypy-1.16.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:936ccfdd749af4766be824268bfe22d1db9eb2f34a3ea1d00ffbe5b5265f5491"}, 528 | {file = "mypy-1.16.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:4086883a73166631307fdd330c4a9080ce24913d4f4c5ec596c601b3a4bdd777"}, 529 | {file = "mypy-1.16.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:feec38097f71797da0231997e0de3a58108c51845399669ebc532c815f93866b"}, 530 | {file = "mypy-1.16.0-cp310-cp310-win_amd64.whl", hash = "sha256:09a8da6a0ee9a9770b8ff61b39c0bb07971cda90e7297f4213741b48a0cc8d93"}, 531 | {file = "mypy-1.16.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:9f826aaa7ff8443bac6a494cf743f591488ea940dd360e7dd330e30dd772a5ab"}, 532 | {file = "mypy-1.16.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:82d056e6faa508501af333a6af192c700b33e15865bda49611e3d7d8358ebea2"}, 533 | {file = "mypy-1.16.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:089bedc02307c2548eb51f426e085546db1fa7dd87fbb7c9fa561575cf6eb1ff"}, 534 | {file = "mypy-1.16.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:6a2322896003ba66bbd1318c10d3afdfe24e78ef12ea10e2acd985e9d684a666"}, 535 | {file = "mypy-1.16.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:021a68568082c5b36e977d54e8f1de978baf401a33884ffcea09bd8e88a98f4c"}, 536 | {file = "mypy-1.16.0-cp311-cp311-win_amd64.whl", hash = "sha256:54066fed302d83bf5128632d05b4ec68412e1f03ef2c300434057d66866cea4b"}, 537 | {file = "mypy-1.16.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:c5436d11e89a3ad16ce8afe752f0f373ae9620841c50883dc96f8b8805620b13"}, 538 | {file = "mypy-1.16.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:f2622af30bf01d8fc36466231bdd203d120d7a599a6d88fb22bdcb9dbff84090"}, 539 | {file = "mypy-1.16.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:d045d33c284e10a038f5e29faca055b90eee87da3fc63b8889085744ebabb5a1"}, 540 | {file = "mypy-1.16.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:b4968f14f44c62e2ec4a038c8797a87315be8df7740dc3ee8d3bfe1c6bf5dba8"}, 541 | {file = "mypy-1.16.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:eb14a4a871bb8efb1e4a50360d4e3c8d6c601e7a31028a2c79f9bb659b63d730"}, 542 | {file = "mypy-1.16.0-cp312-cp312-win_amd64.whl", hash = "sha256:bd4e1ebe126152a7bbaa4daedd781c90c8f9643c79b9748caa270ad542f12bec"}, 543 | {file = "mypy-1.16.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:a9e056237c89f1587a3be1a3a70a06a698d25e2479b9a2f57325ddaaffc3567b"}, 544 | {file = "mypy-1.16.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:0b07e107affb9ee6ce1f342c07f51552d126c32cd62955f59a7db94a51ad12c0"}, 545 | {file = "mypy-1.16.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:c6fb60cbd85dc65d4d63d37cb5c86f4e3a301ec605f606ae3a9173e5cf34997b"}, 546 | {file = "mypy-1.16.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:a7e32297a437cc915599e0578fa6bc68ae6a8dc059c9e009c628e1c47f91495d"}, 547 | {file = "mypy-1.16.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:afe420c9380ccec31e744e8baff0d406c846683681025db3531b32db56962d52"}, 548 | {file = "mypy-1.16.0-cp313-cp313-win_amd64.whl", hash = "sha256:55f9076c6ce55dd3f8cd0c6fff26a008ca8e5131b89d5ba6d86bd3f47e736eeb"}, 549 | {file = "mypy-1.16.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:f56236114c425620875c7cf71700e3d60004858da856c6fc78998ffe767b73d3"}, 550 | {file = "mypy-1.16.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:15486beea80be24ff067d7d0ede673b001d0d684d0095803b3e6e17a886a2a92"}, 551 | {file = "mypy-1.16.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:f2ed0e0847a80655afa2c121835b848ed101cc7b8d8d6ecc5205aedc732b1436"}, 552 | {file = "mypy-1.16.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:eb5fbc8063cb4fde7787e4c0406aa63094a34a2daf4673f359a1fb64050e9cb2"}, 553 | {file = "mypy-1.16.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:a5fcfdb7318c6a8dd127b14b1052743b83e97a970f0edb6c913211507a255e20"}, 554 | {file = "mypy-1.16.0-cp39-cp39-win_amd64.whl", hash = "sha256:2e7e0ad35275e02797323a5aa1be0b14a4d03ffdb2e5f2b0489fa07b89c67b21"}, 555 | {file = "mypy-1.16.0-py3-none-any.whl", hash = "sha256:29e1499864a3888bca5c1542f2d7232c6e586295183320caa95758fc84034031"}, 556 | {file = "mypy-1.16.0.tar.gz", hash = "sha256:84b94283f817e2aa6350a14b4a8fb2a35a53c286f97c9d30f53b63620e7af8ab"}, 557 | ] 558 | 559 | [package.dependencies] 560 | mypy_extensions = ">=1.0.0" 561 | pathspec = ">=0.9.0" 562 | typing_extensions = ">=4.6.0" 563 | 564 | [package.extras] 565 | dmypy = ["psutil (>=4.0)"] 566 | faster-cache = ["orjson"] 567 | install-types = ["pip"] 568 | mypyc = ["setuptools (>=50)"] 569 | reports = ["lxml"] 570 | 571 | [[package]] 572 | name = "mypy-extensions" 573 | version = "1.0.0" 574 | description = "Type system extensions for programs checked with the mypy type checker." 575 | optional = false 576 | python-versions = ">=3.5" 577 | groups = ["dev"] 578 | files = [ 579 | {file = "mypy_extensions-1.0.0-py3-none-any.whl", hash = "sha256:4392f6c0eb8a5668a69e23d168ffa70f0be9ccfd32b5cc2d26a34ae5b844552d"}, 580 | {file = "mypy_extensions-1.0.0.tar.gz", hash = "sha256:75dbf8955dc00442a438fc4d0666508a9a97b6bd41aa2f0ffe9d2f2725af0782"}, 581 | ] 582 | 583 | [[package]] 584 | name = "numpy" 585 | version = "2.2.6" 586 | description = "Fundamental package for array computing in Python" 587 | optional = false 588 | python-versions = ">=3.10" 589 | groups = ["main", "vis"] 590 | files = [ 591 | {file = "numpy-2.2.6-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:b412caa66f72040e6d268491a59f2c43bf03eb6c96dd8f0307829feb7fa2b6fb"}, 592 | {file = "numpy-2.2.6-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:8e41fd67c52b86603a91c1a505ebaef50b3314de0213461c7a6e99c9a3beff90"}, 593 | {file = "numpy-2.2.6-cp310-cp310-macosx_14_0_arm64.whl", hash = "sha256:37e990a01ae6ec7fe7fa1c26c55ecb672dd98b19c3d0e1d1f326fa13cb38d163"}, 594 | {file = "numpy-2.2.6-cp310-cp310-macosx_14_0_x86_64.whl", hash = "sha256:5a6429d4be8ca66d889b7cf70f536a397dc45ba6faeb5f8c5427935d9592e9cf"}, 595 | {file = "numpy-2.2.6-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:efd28d4e9cd7d7a8d39074a4d44c63eda73401580c5c76acda2ce969e0a38e83"}, 596 | {file = "numpy-2.2.6-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:fc7b73d02efb0e18c000e9ad8b83480dfcd5dfd11065997ed4c6747470ae8915"}, 597 | {file = "numpy-2.2.6-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:74d4531beb257d2c3f4b261bfb0fc09e0f9ebb8842d82a7b4209415896adc680"}, 598 | {file = "numpy-2.2.6-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:8fc377d995680230e83241d8a96def29f204b5782f371c532579b4f20607a289"}, 599 | {file = "numpy-2.2.6-cp310-cp310-win32.whl", hash = "sha256:b093dd74e50a8cba3e873868d9e93a85b78e0daf2e98c6797566ad8044e8363d"}, 600 | {file = "numpy-2.2.6-cp310-cp310-win_amd64.whl", hash = "sha256:f0fd6321b839904e15c46e0d257fdd101dd7f530fe03fd6359c1ea63738703f3"}, 601 | {file = "numpy-2.2.6-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:f9f1adb22318e121c5c69a09142811a201ef17ab257a1e66ca3025065b7f53ae"}, 602 | {file = "numpy-2.2.6-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:c820a93b0255bc360f53eca31a0e676fd1101f673dda8da93454a12e23fc5f7a"}, 603 | {file = "numpy-2.2.6-cp311-cp311-macosx_14_0_arm64.whl", hash = "sha256:3d70692235e759f260c3d837193090014aebdf026dfd167834bcba43e30c2a42"}, 604 | {file = "numpy-2.2.6-cp311-cp311-macosx_14_0_x86_64.whl", hash = "sha256:481b49095335f8eed42e39e8041327c05b0f6f4780488f61286ed3c01368d491"}, 605 | {file = "numpy-2.2.6-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b64d8d4d17135e00c8e346e0a738deb17e754230d7e0810ac5012750bbd85a5a"}, 606 | {file = "numpy-2.2.6-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ba10f8411898fc418a521833e014a77d3ca01c15b0c6cdcce6a0d2897e6dbbdf"}, 607 | {file = "numpy-2.2.6-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:bd48227a919f1bafbdda0583705e547892342c26fb127219d60a5c36882609d1"}, 608 | {file = "numpy-2.2.6-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:9551a499bf125c1d4f9e250377c1ee2eddd02e01eac6644c080162c0c51778ab"}, 609 | {file = "numpy-2.2.6-cp311-cp311-win32.whl", hash = "sha256:0678000bb9ac1475cd454c6b8c799206af8107e310843532b04d49649c717a47"}, 610 | {file = "numpy-2.2.6-cp311-cp311-win_amd64.whl", hash = "sha256:e8213002e427c69c45a52bbd94163084025f533a55a59d6f9c5b820774ef3303"}, 611 | {file = "numpy-2.2.6-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:41c5a21f4a04fa86436124d388f6ed60a9343a6f767fced1a8a71c3fbca038ff"}, 612 | {file = "numpy-2.2.6-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:de749064336d37e340f640b05f24e9e3dd678c57318c7289d222a8a2f543e90c"}, 613 | {file = "numpy-2.2.6-cp312-cp312-macosx_14_0_arm64.whl", hash = "sha256:894b3a42502226a1cac872f840030665f33326fc3dac8e57c607905773cdcde3"}, 614 | {file = "numpy-2.2.6-cp312-cp312-macosx_14_0_x86_64.whl", hash = "sha256:71594f7c51a18e728451bb50cc60a3ce4e6538822731b2933209a1f3614e9282"}, 615 | {file = "numpy-2.2.6-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f2618db89be1b4e05f7a1a847a9c1c0abd63e63a1607d892dd54668dd92faf87"}, 616 | {file = "numpy-2.2.6-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:fd83c01228a688733f1ded5201c678f0c53ecc1006ffbc404db9f7a899ac6249"}, 617 | {file = "numpy-2.2.6-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:37c0ca431f82cd5fa716eca9506aefcabc247fb27ba69c5062a6d3ade8cf8f49"}, 618 | {file = "numpy-2.2.6-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:fe27749d33bb772c80dcd84ae7e8df2adc920ae8297400dabec45f0dedb3f6de"}, 619 | {file = "numpy-2.2.6-cp312-cp312-win32.whl", hash = "sha256:4eeaae00d789f66c7a25ac5f34b71a7035bb474e679f410e5e1a94deb24cf2d4"}, 620 | {file = "numpy-2.2.6-cp312-cp312-win_amd64.whl", hash = "sha256:c1f9540be57940698ed329904db803cf7a402f3fc200bfe599334c9bd84a40b2"}, 621 | {file = "numpy-2.2.6-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:0811bb762109d9708cca4d0b13c4f67146e3c3b7cf8d34018c722adb2d957c84"}, 622 | {file = "numpy-2.2.6-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:287cc3162b6f01463ccd86be154f284d0893d2b3ed7292439ea97eafa8170e0b"}, 623 | {file = "numpy-2.2.6-cp313-cp313-macosx_14_0_arm64.whl", hash = "sha256:f1372f041402e37e5e633e586f62aa53de2eac8d98cbfb822806ce4bbefcb74d"}, 624 | {file = "numpy-2.2.6-cp313-cp313-macosx_14_0_x86_64.whl", hash = "sha256:55a4d33fa519660d69614a9fad433be87e5252f4b03850642f88993f7b2ca566"}, 625 | {file = "numpy-2.2.6-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f92729c95468a2f4f15e9bb94c432a9229d0d50de67304399627a943201baa2f"}, 626 | {file = "numpy-2.2.6-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1bc23a79bfabc5d056d106f9befb8d50c31ced2fbc70eedb8155aec74a45798f"}, 627 | {file = "numpy-2.2.6-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:e3143e4451880bed956e706a3220b4e5cf6172ef05fcc397f6f36a550b1dd868"}, 628 | {file = "numpy-2.2.6-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:b4f13750ce79751586ae2eb824ba7e1e8dba64784086c98cdbbcc6a42112ce0d"}, 629 | {file = "numpy-2.2.6-cp313-cp313-win32.whl", hash = "sha256:5beb72339d9d4fa36522fc63802f469b13cdbe4fdab4a288f0c441b74272ebfd"}, 630 | {file = "numpy-2.2.6-cp313-cp313-win_amd64.whl", hash = "sha256:b0544343a702fa80c95ad5d3d608ea3599dd54d4632df855e4c8d24eb6ecfa1c"}, 631 | {file = "numpy-2.2.6-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:0bca768cd85ae743b2affdc762d617eddf3bcf8724435498a1e80132d04879e6"}, 632 | {file = "numpy-2.2.6-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:fc0c5673685c508a142ca65209b4e79ed6740a4ed6b2267dbba90f34b0b3cfda"}, 633 | {file = "numpy-2.2.6-cp313-cp313t-macosx_14_0_arm64.whl", hash = "sha256:5bd4fc3ac8926b3819797a7c0e2631eb889b4118a9898c84f585a54d475b7e40"}, 634 | {file = "numpy-2.2.6-cp313-cp313t-macosx_14_0_x86_64.whl", hash = "sha256:fee4236c876c4e8369388054d02d0e9bb84821feb1a64dd59e137e6511a551f8"}, 635 | {file = "numpy-2.2.6-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e1dda9c7e08dc141e0247a5b8f49cf05984955246a327d4c48bda16821947b2f"}, 636 | {file = "numpy-2.2.6-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f447e6acb680fd307f40d3da4852208af94afdfab89cf850986c3ca00562f4fa"}, 637 | {file = "numpy-2.2.6-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:389d771b1623ec92636b0786bc4ae56abafad4a4c513d36a55dce14bd9ce8571"}, 638 | {file = "numpy-2.2.6-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:8e9ace4a37db23421249ed236fdcdd457d671e25146786dfc96835cd951aa7c1"}, 639 | {file = "numpy-2.2.6-cp313-cp313t-win32.whl", hash = "sha256:038613e9fb8c72b0a41f025a7e4c3f0b7a1b5d768ece4796b674c8f3fe13efff"}, 640 | {file = "numpy-2.2.6-cp313-cp313t-win_amd64.whl", hash = "sha256:6031dd6dfecc0cf9f668681a37648373bddd6421fff6c66ec1624eed0180ee06"}, 641 | {file = "numpy-2.2.6-pp310-pypy310_pp73-macosx_10_15_x86_64.whl", hash = "sha256:0b605b275d7bd0c640cad4e5d30fa701a8d59302e127e5f79138ad62762c3e3d"}, 642 | {file = "numpy-2.2.6-pp310-pypy310_pp73-macosx_14_0_x86_64.whl", hash = "sha256:7befc596a7dc9da8a337f79802ee8adb30a552a94f792b9c9d18c840055907db"}, 643 | {file = "numpy-2.2.6-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ce47521a4754c8f4593837384bd3424880629f718d87c5d44f8ed763edd63543"}, 644 | {file = "numpy-2.2.6-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:d042d24c90c41b54fd506da306759e06e568864df8ec17ccc17e9e884634fd00"}, 645 | {file = "numpy-2.2.6.tar.gz", hash = "sha256:e29554e2bef54a90aa5cc07da6ce955accb83f21ab5de01a62c8478897b264fd"}, 646 | ] 647 | 648 | [[package]] 649 | name = "packaging" 650 | version = "24.2" 651 | description = "Core utilities for Python packages" 652 | optional = false 653 | python-versions = ">=3.8" 654 | groups = ["dev", "vis"] 655 | files = [ 656 | {file = "packaging-24.2-py3-none-any.whl", hash = "sha256:09abb1bccd265c01f4a3aa3f7a7db064b36514d2cba19a2f694fe6150451a759"}, 657 | {file = "packaging-24.2.tar.gz", hash = "sha256:c228a6dc5e932d346bc5739379109d49e8853dd8223571c7c5b55260edc0b97f"}, 658 | ] 659 | 660 | [[package]] 661 | name = "pathspec" 662 | version = "0.12.1" 663 | description = "Utility library for gitignore style pattern matching of file paths." 664 | optional = false 665 | python-versions = ">=3.8" 666 | groups = ["dev"] 667 | files = [ 668 | {file = "pathspec-0.12.1-py3-none-any.whl", hash = "sha256:a0d503e138a4c123b27490a4f7beda6a01c6f288df0e4a8b79c7eb0dc7b4cc08"}, 669 | {file = "pathspec-0.12.1.tar.gz", hash = "sha256:a482d51503a1ab33b1c67a6c3813a26953dbdc71c31dacaef9a838c4e29f5712"}, 670 | ] 671 | 672 | [[package]] 673 | name = "pillow" 674 | version = "11.1.0" 675 | description = "Python Imaging Library (Fork)" 676 | optional = false 677 | python-versions = ">=3.9" 678 | groups = ["vis"] 679 | files = [ 680 | {file = "pillow-11.1.0-cp310-cp310-macosx_10_10_x86_64.whl", hash = "sha256:e1abe69aca89514737465752b4bcaf8016de61b3be1397a8fc260ba33321b3a8"}, 681 | {file = "pillow-11.1.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:c640e5a06869c75994624551f45e5506e4256562ead981cce820d5ab39ae2192"}, 682 | {file = "pillow-11.1.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a07dba04c5e22824816b2615ad7a7484432d7f540e6fa86af60d2de57b0fcee2"}, 683 | {file = "pillow-11.1.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e267b0ed063341f3e60acd25c05200df4193e15a4a5807075cd71225a2386e26"}, 684 | {file = "pillow-11.1.0-cp310-cp310-manylinux_2_28_aarch64.whl", hash = "sha256:bd165131fd51697e22421d0e467997ad31621b74bfc0b75956608cb2906dda07"}, 685 | {file = "pillow-11.1.0-cp310-cp310-manylinux_2_28_x86_64.whl", hash = "sha256:abc56501c3fd148d60659aae0af6ddc149660469082859fa7b066a298bde9482"}, 686 | {file = "pillow-11.1.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:54ce1c9a16a9561b6d6d8cb30089ab1e5eb66918cb47d457bd996ef34182922e"}, 687 | {file = "pillow-11.1.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:73ddde795ee9b06257dac5ad42fcb07f3b9b813f8c1f7f870f402f4dc54b5269"}, 688 | {file = "pillow-11.1.0-cp310-cp310-win32.whl", hash = "sha256:3a5fe20a7b66e8135d7fd617b13272626a28278d0e578c98720d9ba4b2439d49"}, 689 | {file = "pillow-11.1.0-cp310-cp310-win_amd64.whl", hash = "sha256:b6123aa4a59d75f06e9dd3dac5bf8bc9aa383121bb3dd9a7a612e05eabc9961a"}, 690 | {file = "pillow-11.1.0-cp310-cp310-win_arm64.whl", hash = "sha256:a76da0a31da6fcae4210aa94fd779c65c75786bc9af06289cd1c184451ef7a65"}, 691 | {file = "pillow-11.1.0-cp311-cp311-macosx_10_10_x86_64.whl", hash = "sha256:e06695e0326d05b06833b40b7ef477e475d0b1ba3a6d27da1bb48c23209bf457"}, 692 | {file = "pillow-11.1.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:96f82000e12f23e4f29346e42702b6ed9a2f2fea34a740dd5ffffcc8c539eb35"}, 693 | {file = "pillow-11.1.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a3cd561ded2cf2bbae44d4605837221b987c216cff94f49dfeed63488bb228d2"}, 694 | {file = "pillow-11.1.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f189805c8be5ca5add39e6f899e6ce2ed824e65fb45f3c28cb2841911da19070"}, 695 | {file = "pillow-11.1.0-cp311-cp311-manylinux_2_28_aarch64.whl", hash = "sha256:dd0052e9db3474df30433f83a71b9b23bd9e4ef1de13d92df21a52c0303b8ab6"}, 696 | {file = "pillow-11.1.0-cp311-cp311-manylinux_2_28_x86_64.whl", hash = "sha256:837060a8599b8f5d402e97197d4924f05a2e0d68756998345c829c33186217b1"}, 697 | {file = "pillow-11.1.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:aa8dd43daa836b9a8128dbe7d923423e5ad86f50a7a14dc688194b7be5c0dea2"}, 698 | {file = "pillow-11.1.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:0a2f91f8a8b367e7a57c6e91cd25af510168091fb89ec5146003e424e1558a96"}, 699 | {file = "pillow-11.1.0-cp311-cp311-win32.whl", hash = "sha256:c12fc111ef090845de2bb15009372175d76ac99969bdf31e2ce9b42e4b8cd88f"}, 700 | {file = "pillow-11.1.0-cp311-cp311-win_amd64.whl", hash = "sha256:fbd43429d0d7ed6533b25fc993861b8fd512c42d04514a0dd6337fb3ccf22761"}, 701 | {file = "pillow-11.1.0-cp311-cp311-win_arm64.whl", hash = "sha256:f7955ecf5609dee9442cbface754f2c6e541d9e6eda87fad7f7a989b0bdb9d71"}, 702 | {file = "pillow-11.1.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:2062ffb1d36544d42fcaa277b069c88b01bb7298f4efa06731a7fd6cc290b81a"}, 703 | {file = "pillow-11.1.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:a85b653980faad27e88b141348707ceeef8a1186f75ecc600c395dcac19f385b"}, 704 | {file = "pillow-11.1.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9409c080586d1f683df3f184f20e36fb647f2e0bc3988094d4fd8c9f4eb1b3b3"}, 705 | {file = "pillow-11.1.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7fdadc077553621911f27ce206ffcbec7d3f8d7b50e0da39f10997e8e2bb7f6a"}, 706 | {file = "pillow-11.1.0-cp312-cp312-manylinux_2_28_aarch64.whl", hash = "sha256:93a18841d09bcdd774dcdc308e4537e1f867b3dec059c131fde0327899734aa1"}, 707 | {file = "pillow-11.1.0-cp312-cp312-manylinux_2_28_x86_64.whl", hash = "sha256:9aa9aeddeed452b2f616ff5507459e7bab436916ccb10961c4a382cd3e03f47f"}, 708 | {file = "pillow-11.1.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:3cdcdb0b896e981678eee140d882b70092dac83ac1cdf6b3a60e2216a73f2b91"}, 709 | {file = "pillow-11.1.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:36ba10b9cb413e7c7dfa3e189aba252deee0602c86c309799da5a74009ac7a1c"}, 710 | {file = "pillow-11.1.0-cp312-cp312-win32.whl", hash = "sha256:cfd5cd998c2e36a862d0e27b2df63237e67273f2fc78f47445b14e73a810e7e6"}, 711 | {file = "pillow-11.1.0-cp312-cp312-win_amd64.whl", hash = "sha256:a697cd8ba0383bba3d2d3ada02b34ed268cb548b369943cd349007730c92bddf"}, 712 | {file = "pillow-11.1.0-cp312-cp312-win_arm64.whl", hash = "sha256:4dd43a78897793f60766563969442020e90eb7847463eca901e41ba186a7d4a5"}, 713 | {file = "pillow-11.1.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:ae98e14432d458fc3de11a77ccb3ae65ddce70f730e7c76140653048c71bfcbc"}, 714 | {file = "pillow-11.1.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:cc1331b6d5a6e144aeb5e626f4375f5b7ae9934ba620c0ac6b3e43d5e683a0f0"}, 715 | {file = "pillow-11.1.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:758e9d4ef15d3560214cddbc97b8ef3ef86ce04d62ddac17ad39ba87e89bd3b1"}, 716 | {file = "pillow-11.1.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b523466b1a31d0dcef7c5be1f20b942919b62fd6e9a9be199d035509cbefc0ec"}, 717 | {file = "pillow-11.1.0-cp313-cp313-manylinux_2_28_aarch64.whl", hash = "sha256:9044b5e4f7083f209c4e35aa5dd54b1dd5b112b108648f5c902ad586d4f945c5"}, 718 | {file = "pillow-11.1.0-cp313-cp313-manylinux_2_28_x86_64.whl", hash = "sha256:3764d53e09cdedd91bee65c2527815d315c6b90d7b8b79759cc48d7bf5d4f114"}, 719 | {file = "pillow-11.1.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:31eba6bbdd27dde97b0174ddf0297d7a9c3a507a8a1480e1e60ef914fe23d352"}, 720 | {file = "pillow-11.1.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:b5d658fbd9f0d6eea113aea286b21d3cd4d3fd978157cbf2447a6035916506d3"}, 721 | {file = "pillow-11.1.0-cp313-cp313-win32.whl", hash = "sha256:f86d3a7a9af5d826744fabf4afd15b9dfef44fe69a98541f666f66fbb8d3fef9"}, 722 | {file = "pillow-11.1.0-cp313-cp313-win_amd64.whl", hash = "sha256:593c5fd6be85da83656b93ffcccc2312d2d149d251e98588b14fbc288fd8909c"}, 723 | {file = "pillow-11.1.0-cp313-cp313-win_arm64.whl", hash = "sha256:11633d58b6ee5733bde153a8dafd25e505ea3d32e261accd388827ee987baf65"}, 724 | {file = "pillow-11.1.0-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:70ca5ef3b3b1c4a0812b5c63c57c23b63e53bc38e758b37a951e5bc466449861"}, 725 | {file = "pillow-11.1.0-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:8000376f139d4d38d6851eb149b321a52bb8893a88dae8ee7d95840431977081"}, 726 | {file = "pillow-11.1.0-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9ee85f0696a17dd28fbcfceb59f9510aa71934b483d1f5601d1030c3c8304f3c"}, 727 | {file = "pillow-11.1.0-cp313-cp313t-manylinux_2_28_x86_64.whl", hash = "sha256:dd0e081319328928531df7a0e63621caf67652c8464303fd102141b785ef9547"}, 728 | {file = "pillow-11.1.0-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:e63e4e5081de46517099dc30abe418122f54531a6ae2ebc8680bcd7096860eab"}, 729 | {file = "pillow-11.1.0-cp313-cp313t-win32.whl", hash = "sha256:dda60aa465b861324e65a78c9f5cf0f4bc713e4309f83bc387be158b077963d9"}, 730 | {file = "pillow-11.1.0-cp313-cp313t-win_amd64.whl", hash = "sha256:ad5db5781c774ab9a9b2c4302bbf0c1014960a0a7be63278d13ae6fdf88126fe"}, 731 | {file = "pillow-11.1.0-cp313-cp313t-win_arm64.whl", hash = "sha256:67cd427c68926108778a9005f2a04adbd5e67c442ed21d95389fe1d595458756"}, 732 | {file = "pillow-11.1.0-cp39-cp39-macosx_10_10_x86_64.whl", hash = "sha256:bf902d7413c82a1bfa08b06a070876132a5ae6b2388e2712aab3a7cbc02205c6"}, 733 | {file = "pillow-11.1.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:c1eec9d950b6fe688edee07138993e54ee4ae634c51443cfb7c1e7613322718e"}, 734 | {file = "pillow-11.1.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8e275ee4cb11c262bd108ab2081f750db2a1c0b8c12c1897f27b160c8bd57bbc"}, 735 | {file = "pillow-11.1.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4db853948ce4e718f2fc775b75c37ba2efb6aaea41a1a5fc57f0af59eee774b2"}, 736 | {file = "pillow-11.1.0-cp39-cp39-manylinux_2_28_aarch64.whl", hash = "sha256:ab8a209b8485d3db694fa97a896d96dd6533d63c22829043fd9de627060beade"}, 737 | {file = "pillow-11.1.0-cp39-cp39-manylinux_2_28_x86_64.whl", hash = "sha256:54251ef02a2309b5eec99d151ebf5c9904b77976c8abdcbce7891ed22df53884"}, 738 | {file = "pillow-11.1.0-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:5bb94705aea800051a743aa4874bb1397d4695fb0583ba5e425ee0328757f196"}, 739 | {file = "pillow-11.1.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:89dbdb3e6e9594d512780a5a1c42801879628b38e3efc7038094430844e271d8"}, 740 | {file = "pillow-11.1.0-cp39-cp39-win32.whl", hash = "sha256:e5449ca63da169a2e6068dd0e2fcc8d91f9558aba89ff6d02121ca8ab11e79e5"}, 741 | {file = "pillow-11.1.0-cp39-cp39-win_amd64.whl", hash = "sha256:3362c6ca227e65c54bf71a5f88b3d4565ff1bcbc63ae72c34b07bbb1cc59a43f"}, 742 | {file = "pillow-11.1.0-cp39-cp39-win_arm64.whl", hash = "sha256:b20be51b37a75cc54c2c55def3fa2c65bb94ba859dde241cd0a4fd302de5ae0a"}, 743 | {file = "pillow-11.1.0-pp310-pypy310_pp73-macosx_10_15_x86_64.whl", hash = "sha256:8c730dc3a83e5ac137fbc92dfcfe1511ce3b2b5d7578315b63dbbb76f7f51d90"}, 744 | {file = "pillow-11.1.0-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:7d33d2fae0e8b170b6a6c57400e077412240f6f5bb2a342cf1ee512a787942bb"}, 745 | {file = "pillow-11.1.0-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a8d65b38173085f24bc07f8b6c505cbb7418009fa1a1fcb111b1f4961814a442"}, 746 | {file = "pillow-11.1.0-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:015c6e863faa4779251436db398ae75051469f7c903b043a48f078e437656f83"}, 747 | {file = "pillow-11.1.0-pp310-pypy310_pp73-manylinux_2_28_aarch64.whl", hash = "sha256:d44ff19eea13ae4acdaaab0179fa68c0c6f2f45d66a4d8ec1eda7d6cecbcc15f"}, 748 | {file = "pillow-11.1.0-pp310-pypy310_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:d3d8da4a631471dfaf94c10c85f5277b1f8e42ac42bade1ac67da4b4a7359b73"}, 749 | {file = "pillow-11.1.0-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:4637b88343166249fe8aa94e7c4a62a180c4b3898283bb5d3d2fd5fe10d8e4e0"}, 750 | {file = "pillow-11.1.0.tar.gz", hash = "sha256:368da70808b36d73b4b390a8ffac11069f8a5c85f29eff1f1b01bcf3ef5b2a20"}, 751 | ] 752 | 753 | [package.extras] 754 | docs = ["furo", "olefile", "sphinx (>=8.1)", "sphinx-copybutton", "sphinx-inline-tabs", "sphinxext-opengraph"] 755 | fpx = ["olefile"] 756 | mic = ["olefile"] 757 | tests = ["check-manifest", "coverage (>=7.4.2)", "defusedxml", "markdown2", "olefile", "packaging", "pyroma", "pytest", "pytest-cov", "pytest-timeout", "trove-classifiers (>=2024.10.12)"] 758 | typing = ["typing-extensions ; python_version < \"3.10\""] 759 | xmp = ["defusedxml"] 760 | 761 | [[package]] 762 | name = "platformdirs" 763 | version = "4.3.7" 764 | description = "A small Python package for determining appropriate platform-specific dirs, e.g. a `user data dir`." 765 | optional = false 766 | python-versions = ">=3.9" 767 | groups = ["dev"] 768 | files = [ 769 | {file = "platformdirs-4.3.7-py3-none-any.whl", hash = "sha256:a03875334331946f13c549dbd8f4bac7a13a50a895a0eb1e8c6a8ace80d40a94"}, 770 | {file = "platformdirs-4.3.7.tar.gz", hash = "sha256:eb437d586b6a0986388f0d6f74aa0cde27b48d0e3d66843640bfb6bdcdb6e351"}, 771 | ] 772 | 773 | [package.extras] 774 | docs = ["furo (>=2024.8.6)", "proselint (>=0.14)", "sphinx (>=8.1.3)", "sphinx-autodoc-typehints (>=3)"] 775 | test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=8.3.4)", "pytest-cov (>=6)", "pytest-mock (>=3.14)"] 776 | type = ["mypy (>=1.14.1)"] 777 | 778 | [[package]] 779 | name = "pyparsing" 780 | version = "3.2.3" 781 | description = "pyparsing module - Classes and methods to define and execute parsing grammars" 782 | optional = false 783 | python-versions = ">=3.9" 784 | groups = ["vis"] 785 | files = [ 786 | {file = "pyparsing-3.2.3-py3-none-any.whl", hash = "sha256:a749938e02d6fd0b59b356ca504a24982314bb090c383e3cf201c95ef7e2bfcf"}, 787 | {file = "pyparsing-3.2.3.tar.gz", hash = "sha256:b9c13f1ab8b3b542f72e28f634bad4de758ab3ce4546e4301970ad6fa77c38be"}, 788 | ] 789 | 790 | [package.extras] 791 | diagrams = ["jinja2", "railroad-diagrams"] 792 | 793 | [[package]] 794 | name = "python-dateutil" 795 | version = "2.9.0.post0" 796 | description = "Extensions to the standard Python datetime module" 797 | optional = false 798 | python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7" 799 | groups = ["vis"] 800 | files = [ 801 | {file = "python-dateutil-2.9.0.post0.tar.gz", hash = "sha256:37dd54208da7e1cd875388217d5e00ebd4179249f90fb72437e91a35459a0ad3"}, 802 | {file = "python_dateutil-2.9.0.post0-py2.py3-none-any.whl", hash = "sha256:a8b2bc7bffae282281c8140a97d3aa9c14da0b136dfe83f850eea9a5f7470427"}, 803 | ] 804 | 805 | [package.dependencies] 806 | six = ">=1.5" 807 | 808 | [[package]] 809 | name = "regex" 810 | version = "2024.11.6" 811 | description = "Alternative regular expression module, to replace re." 812 | optional = false 813 | python-versions = ">=3.8" 814 | groups = ["main"] 815 | files = [ 816 | {file = "regex-2024.11.6-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:ff590880083d60acc0433f9c3f713c51f7ac6ebb9adf889c79a261ecf541aa91"}, 817 | {file = "regex-2024.11.6-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:658f90550f38270639e83ce492f27d2c8d2cd63805c65a13a14d36ca126753f0"}, 818 | {file = "regex-2024.11.6-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:164d8b7b3b4bcb2068b97428060b2a53be050085ef94eca7f240e7947f1b080e"}, 819 | {file = "regex-2024.11.6-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d3660c82f209655a06b587d55e723f0b813d3a7db2e32e5e7dc64ac2a9e86fde"}, 820 | {file = "regex-2024.11.6-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d22326fcdef5e08c154280b71163ced384b428343ae16a5ab2b3354aed12436e"}, 821 | {file = "regex-2024.11.6-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f1ac758ef6aebfc8943560194e9fd0fa18bcb34d89fd8bd2af18183afd8da3a2"}, 822 | {file = "regex-2024.11.6-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:997d6a487ff00807ba810e0f8332c18b4eb8d29463cfb7c820dc4b6e7562d0cf"}, 823 | {file = "regex-2024.11.6-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:02a02d2bb04fec86ad61f3ea7f49c015a0681bf76abb9857f945d26159d2968c"}, 824 | {file = "regex-2024.11.6-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:f02f93b92358ee3f78660e43b4b0091229260c5d5c408d17d60bf26b6c900e86"}, 825 | {file = "regex-2024.11.6-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:06eb1be98df10e81ebaded73fcd51989dcf534e3c753466e4b60c4697a003b67"}, 826 | {file = "regex-2024.11.6-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:040df6fe1a5504eb0f04f048e6d09cd7c7110fef851d7c567a6b6e09942feb7d"}, 827 | {file = "regex-2024.11.6-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:fdabbfc59f2c6edba2a6622c647b716e34e8e3867e0ab975412c5c2f79b82da2"}, 828 | {file = "regex-2024.11.6-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:8447d2d39b5abe381419319f942de20b7ecd60ce86f16a23b0698f22e1b70008"}, 829 | {file = "regex-2024.11.6-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:da8f5fc57d1933de22a9e23eec290a0d8a5927a5370d24bda9a6abe50683fe62"}, 830 | {file = "regex-2024.11.6-cp310-cp310-win32.whl", hash = "sha256:b489578720afb782f6ccf2840920f3a32e31ba28a4b162e13900c3e6bd3f930e"}, 831 | {file = "regex-2024.11.6-cp310-cp310-win_amd64.whl", hash = "sha256:5071b2093e793357c9d8b2929dfc13ac5f0a6c650559503bb81189d0a3814519"}, 832 | {file = "regex-2024.11.6-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:5478c6962ad548b54a591778e93cd7c456a7a29f8eca9c49e4f9a806dcc5d638"}, 833 | {file = "regex-2024.11.6-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:2c89a8cc122b25ce6945f0423dc1352cb9593c68abd19223eebbd4e56612c5b7"}, 834 | {file = "regex-2024.11.6-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:94d87b689cdd831934fa3ce16cc15cd65748e6d689f5d2b8f4f4df2065c9fa20"}, 835 | {file = "regex-2024.11.6-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1062b39a0a2b75a9c694f7a08e7183a80c63c0d62b301418ffd9c35f55aaa114"}, 836 | {file = "regex-2024.11.6-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:167ed4852351d8a750da48712c3930b031f6efdaa0f22fa1933716bfcd6bf4a3"}, 837 | {file = "regex-2024.11.6-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2d548dafee61f06ebdb584080621f3e0c23fff312f0de1afc776e2a2ba99a74f"}, 838 | {file = "regex-2024.11.6-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f2a19f302cd1ce5dd01a9099aaa19cae6173306d1302a43b627f62e21cf18ac0"}, 839 | {file = "regex-2024.11.6-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:bec9931dfb61ddd8ef2ebc05646293812cb6b16b60cf7c9511a832b6f1854b55"}, 840 | {file = "regex-2024.11.6-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:9714398225f299aa85267fd222f7142fcb5c769e73d7733344efc46f2ef5cf89"}, 841 | {file = "regex-2024.11.6-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:202eb32e89f60fc147a41e55cb086db2a3f8cb82f9a9a88440dcfc5d37faae8d"}, 842 | {file = "regex-2024.11.6-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:4181b814e56078e9b00427ca358ec44333765f5ca1b45597ec7446d3a1ef6e34"}, 843 | {file = "regex-2024.11.6-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:068376da5a7e4da51968ce4c122a7cd31afaaec4fccc7856c92f63876e57b51d"}, 844 | {file = "regex-2024.11.6-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:ac10f2c4184420d881a3475fb2c6f4d95d53a8d50209a2500723d831036f7c45"}, 845 | {file = "regex-2024.11.6-cp311-cp311-win32.whl", hash = "sha256:c36f9b6f5f8649bb251a5f3f66564438977b7ef8386a52460ae77e6070d309d9"}, 846 | {file = "regex-2024.11.6-cp311-cp311-win_amd64.whl", hash = "sha256:02e28184be537f0e75c1f9b2f8847dc51e08e6e171c6bde130b2687e0c33cf60"}, 847 | {file = "regex-2024.11.6-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:52fb28f528778f184f870b7cf8f225f5eef0a8f6e3778529bdd40c7b3920796a"}, 848 | {file = "regex-2024.11.6-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:fdd6028445d2460f33136c55eeb1f601ab06d74cb3347132e1c24250187500d9"}, 849 | {file = "regex-2024.11.6-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:805e6b60c54bf766b251e94526ebad60b7de0c70f70a4e6210ee2891acb70bf2"}, 850 | {file = "regex-2024.11.6-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b85c2530be953a890eaffde05485238f07029600e8f098cdf1848d414a8b45e4"}, 851 | {file = "regex-2024.11.6-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:bb26437975da7dc36b7efad18aa9dd4ea569d2357ae6b783bf1118dabd9ea577"}, 852 | {file = "regex-2024.11.6-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:abfa5080c374a76a251ba60683242bc17eeb2c9818d0d30117b4486be10c59d3"}, 853 | {file = "regex-2024.11.6-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:70b7fa6606c2881c1db9479b0eaa11ed5dfa11c8d60a474ff0e095099f39d98e"}, 854 | {file = "regex-2024.11.6-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0c32f75920cf99fe6b6c539c399a4a128452eaf1af27f39bce8909c9a3fd8cbe"}, 855 | {file = "regex-2024.11.6-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:982e6d21414e78e1f51cf595d7f321dcd14de1f2881c5dc6a6e23bbbbd68435e"}, 856 | {file = "regex-2024.11.6-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:a7c2155f790e2fb448faed6dd241386719802296ec588a8b9051c1f5c481bc29"}, 857 | {file = "regex-2024.11.6-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:149f5008d286636e48cd0b1dd65018548944e495b0265b45e1bffecce1ef7f39"}, 858 | {file = "regex-2024.11.6-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:e5364a4502efca094731680e80009632ad6624084aff9a23ce8c8c6820de3e51"}, 859 | {file = "regex-2024.11.6-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:0a86e7eeca091c09e021db8eb72d54751e527fa47b8d5787caf96d9831bd02ad"}, 860 | {file = "regex-2024.11.6-cp312-cp312-win32.whl", hash = "sha256:32f9a4c643baad4efa81d549c2aadefaeba12249b2adc5af541759237eee1c54"}, 861 | {file = "regex-2024.11.6-cp312-cp312-win_amd64.whl", hash = "sha256:a93c194e2df18f7d264092dc8539b8ffb86b45b899ab976aa15d48214138e81b"}, 862 | {file = "regex-2024.11.6-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:a6ba92c0bcdf96cbf43a12c717eae4bc98325ca3730f6b130ffa2e3c3c723d84"}, 863 | {file = "regex-2024.11.6-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:525eab0b789891ac3be914d36893bdf972d483fe66551f79d3e27146191a37d4"}, 864 | {file = "regex-2024.11.6-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:086a27a0b4ca227941700e0b31425e7a28ef1ae8e5e05a33826e17e47fbfdba0"}, 865 | {file = "regex-2024.11.6-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:bde01f35767c4a7899b7eb6e823b125a64de314a8ee9791367c9a34d56af18d0"}, 866 | {file = "regex-2024.11.6-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b583904576650166b3d920d2bcce13971f6f9e9a396c673187f49811b2769dc7"}, 867 | {file = "regex-2024.11.6-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:1c4de13f06a0d54fa0d5ab1b7138bfa0d883220965a29616e3ea61b35d5f5fc7"}, 868 | {file = "regex-2024.11.6-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3cde6e9f2580eb1665965ce9bf17ff4952f34f5b126beb509fee8f4e994f143c"}, 869 | {file = "regex-2024.11.6-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0d7f453dca13f40a02b79636a339c5b62b670141e63efd511d3f8f73fba162b3"}, 870 | {file = "regex-2024.11.6-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:59dfe1ed21aea057a65c6b586afd2a945de04fc7db3de0a6e3ed5397ad491b07"}, 871 | {file = "regex-2024.11.6-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:b97c1e0bd37c5cd7902e65f410779d39eeda155800b65fc4d04cc432efa9bc6e"}, 872 | {file = "regex-2024.11.6-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:f9d1e379028e0fc2ae3654bac3cbbef81bf3fd571272a42d56c24007979bafb6"}, 873 | {file = "regex-2024.11.6-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:13291b39131e2d002a7940fb176e120bec5145f3aeb7621be6534e46251912c4"}, 874 | {file = "regex-2024.11.6-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:4f51f88c126370dcec4908576c5a627220da6c09d0bff31cfa89f2523843316d"}, 875 | {file = "regex-2024.11.6-cp313-cp313-win32.whl", hash = "sha256:63b13cfd72e9601125027202cad74995ab26921d8cd935c25f09c630436348ff"}, 876 | {file = "regex-2024.11.6-cp313-cp313-win_amd64.whl", hash = "sha256:2b3361af3198667e99927da8b84c1b010752fa4b1115ee30beaa332cabc3ef1a"}, 877 | {file = "regex-2024.11.6-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:3a51ccc315653ba012774efca4f23d1d2a8a8f278a6072e29c7147eee7da446b"}, 878 | {file = "regex-2024.11.6-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:ad182d02e40de7459b73155deb8996bbd8e96852267879396fb274e8700190e3"}, 879 | {file = "regex-2024.11.6-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:ba9b72e5643641b7d41fa1f6d5abda2c9a263ae835b917348fc3c928182ad467"}, 880 | {file = "regex-2024.11.6-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:40291b1b89ca6ad8d3f2b82782cc33807f1406cf68c8d440861da6304d8ffbbd"}, 881 | {file = "regex-2024.11.6-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:cdf58d0e516ee426a48f7b2c03a332a4114420716d55769ff7108c37a09951bf"}, 882 | {file = "regex-2024.11.6-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a36fdf2af13c2b14738f6e973aba563623cb77d753bbbd8d414d18bfaa3105dd"}, 883 | {file = "regex-2024.11.6-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d1cee317bfc014c2419a76bcc87f071405e3966da434e03e13beb45f8aced1a6"}, 884 | {file = "regex-2024.11.6-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:50153825ee016b91549962f970d6a4442fa106832e14c918acd1c8e479916c4f"}, 885 | {file = "regex-2024.11.6-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:ea1bfda2f7162605f6e8178223576856b3d791109f15ea99a9f95c16a7636fb5"}, 886 | {file = "regex-2024.11.6-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:df951c5f4a1b1910f1a99ff42c473ff60f8225baa1cdd3539fe2819d9543e9df"}, 887 | {file = "regex-2024.11.6-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:072623554418a9911446278f16ecb398fb3b540147a7828c06e2011fa531e773"}, 888 | {file = "regex-2024.11.6-cp38-cp38-musllinux_1_2_ppc64le.whl", hash = "sha256:f654882311409afb1d780b940234208a252322c24a93b442ca714d119e68086c"}, 889 | {file = "regex-2024.11.6-cp38-cp38-musllinux_1_2_s390x.whl", hash = "sha256:89d75e7293d2b3e674db7d4d9b1bee7f8f3d1609428e293771d1a962617150cc"}, 890 | {file = "regex-2024.11.6-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:f65557897fc977a44ab205ea871b690adaef6b9da6afda4790a2484b04293a5f"}, 891 | {file = "regex-2024.11.6-cp38-cp38-win32.whl", hash = "sha256:6f44ec28b1f858c98d3036ad5d7d0bfc568bdd7a74f9c24e25f41ef1ebfd81a4"}, 892 | {file = "regex-2024.11.6-cp38-cp38-win_amd64.whl", hash = "sha256:bb8f74f2f10dbf13a0be8de623ba4f9491faf58c24064f32b65679b021ed0001"}, 893 | {file = "regex-2024.11.6-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:5704e174f8ccab2026bd2f1ab6c510345ae8eac818b613d7d73e785f1310f839"}, 894 | {file = "regex-2024.11.6-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:220902c3c5cc6af55d4fe19ead504de80eb91f786dc102fbd74894b1551f095e"}, 895 | {file = "regex-2024.11.6-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:5e7e351589da0850c125f1600a4c4ba3c722efefe16b297de54300f08d734fbf"}, 896 | {file = "regex-2024.11.6-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5056b185ca113c88e18223183aa1a50e66507769c9640a6ff75859619d73957b"}, 897 | {file = "regex-2024.11.6-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:2e34b51b650b23ed3354b5a07aab37034d9f923db2a40519139af34f485f77d0"}, 898 | {file = "regex-2024.11.6-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5670bce7b200273eee1840ef307bfa07cda90b38ae56e9a6ebcc9f50da9c469b"}, 899 | {file = "regex-2024.11.6-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:08986dce1339bc932923e7d1232ce9881499a0e02925f7402fb7c982515419ef"}, 900 | {file = "regex-2024.11.6-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:93c0b12d3d3bc25af4ebbf38f9ee780a487e8bf6954c115b9f015822d3bb8e48"}, 901 | {file = "regex-2024.11.6-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:764e71f22ab3b305e7f4c21f1a97e1526a25ebdd22513e251cf376760213da13"}, 902 | {file = "regex-2024.11.6-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:f056bf21105c2515c32372bbc057f43eb02aae2fda61052e2f7622c801f0b4e2"}, 903 | {file = "regex-2024.11.6-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:69ab78f848845569401469da20df3e081e6b5a11cb086de3eed1d48f5ed57c95"}, 904 | {file = "regex-2024.11.6-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:86fddba590aad9208e2fa8b43b4c098bb0ec74f15718bb6a704e3c63e2cef3e9"}, 905 | {file = "regex-2024.11.6-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:684d7a212682996d21ca12ef3c17353c021fe9de6049e19ac8481ec35574a70f"}, 906 | {file = "regex-2024.11.6-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:a03e02f48cd1abbd9f3b7e3586d97c8f7a9721c436f51a5245b3b9483044480b"}, 907 | {file = "regex-2024.11.6-cp39-cp39-win32.whl", hash = "sha256:41758407fc32d5c3c5de163888068cfee69cb4c2be844e7ac517a52770f9af57"}, 908 | {file = "regex-2024.11.6-cp39-cp39-win_amd64.whl", hash = "sha256:b2837718570f95dd41675328e111345f9b7095d821bac435aac173ac80b19983"}, 909 | {file = "regex-2024.11.6.tar.gz", hash = "sha256:7ab159b063c52a0333c884e4679f8d7a85112ee3078fe3d9004b2dd875585519"}, 910 | ] 911 | 912 | [[package]] 913 | name = "requests" 914 | version = "2.32.3" 915 | description = "Python HTTP for Humans." 916 | optional = false 917 | python-versions = ">=3.8" 918 | groups = ["main"] 919 | files = [ 920 | {file = "requests-2.32.3-py3-none-any.whl", hash = "sha256:70761cfe03c773ceb22aa2f671b4757976145175cdfca038c02654d061d6dcc6"}, 921 | {file = "requests-2.32.3.tar.gz", hash = "sha256:55365417734eb18255590a9ff9eb97e9e1da868d4ccd6402399eaf68af20a760"}, 922 | ] 923 | 924 | [package.dependencies] 925 | certifi = ">=2017.4.17" 926 | charset-normalizer = ">=2,<4" 927 | idna = ">=2.5,<4" 928 | urllib3 = ">=1.21.1,<3" 929 | 930 | [package.extras] 931 | socks = ["PySocks (>=1.5.6,!=1.5.7)"] 932 | use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"] 933 | 934 | [[package]] 935 | name = "ruff" 936 | version = "0.11.13" 937 | description = "An extremely fast Python linter and code formatter, written in Rust." 938 | optional = false 939 | python-versions = ">=3.7" 940 | groups = ["dev"] 941 | files = [ 942 | {file = "ruff-0.11.13-py3-none-linux_armv6l.whl", hash = "sha256:4bdfbf1240533f40042ec00c9e09a3aade6f8c10b6414cf11b519488d2635d46"}, 943 | {file = "ruff-0.11.13-py3-none-macosx_10_12_x86_64.whl", hash = "sha256:aef9c9ed1b5ca28bb15c7eac83b8670cf3b20b478195bd49c8d756ba0a36cf48"}, 944 | {file = "ruff-0.11.13-py3-none-macosx_11_0_arm64.whl", hash = "sha256:53b15a9dfdce029c842e9a5aebc3855e9ab7771395979ff85b7c1dedb53ddc2b"}, 945 | {file = "ruff-0.11.13-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ab153241400789138d13f362c43f7edecc0edfffce2afa6a68434000ecd8f69a"}, 946 | {file = "ruff-0.11.13-py3-none-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:6c51f93029d54a910d3d24f7dd0bb909e31b6cd989a5e4ac513f4eb41629f0dc"}, 947 | {file = "ruff-0.11.13-py3-none-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:1808b3ed53e1a777c2ef733aca9051dc9bf7c99b26ece15cb59a0320fbdbd629"}, 948 | {file = "ruff-0.11.13-py3-none-manylinux_2_17_ppc64.manylinux2014_ppc64.whl", hash = "sha256:d28ce58b5ecf0f43c1b71edffabe6ed7f245d5336b17805803312ec9bc665933"}, 949 | {file = "ruff-0.11.13-py3-none-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:55e4bc3a77842da33c16d55b32c6cac1ec5fb0fbec9c8c513bdce76c4f922165"}, 950 | {file = "ruff-0.11.13-py3-none-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:633bf2c6f35678c56ec73189ba6fa19ff1c5e4807a78bf60ef487b9dd272cc71"}, 951 | {file = "ruff-0.11.13-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4ffbc82d70424b275b089166310448051afdc6e914fdab90e08df66c43bb5ca9"}, 952 | {file = "ruff-0.11.13-py3-none-musllinux_1_2_aarch64.whl", hash = "sha256:4a9ddd3ec62a9a89578c85842b836e4ac832d4a2e0bfaad3b02243f930ceafcc"}, 953 | {file = "ruff-0.11.13-py3-none-musllinux_1_2_armv7l.whl", hash = "sha256:d237a496e0778d719efb05058c64d28b757c77824e04ffe8796c7436e26712b7"}, 954 | {file = "ruff-0.11.13-py3-none-musllinux_1_2_i686.whl", hash = "sha256:26816a218ca6ef02142343fd24c70f7cd8c5aa6c203bca284407adf675984432"}, 955 | {file = "ruff-0.11.13-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:51c3f95abd9331dc5b87c47ac7f376db5616041173826dfd556cfe3d4977f492"}, 956 | {file = "ruff-0.11.13-py3-none-win32.whl", hash = "sha256:96c27935418e4e8e77a26bb05962817f28b8ef3843a6c6cc49d8783b5507f250"}, 957 | {file = "ruff-0.11.13-py3-none-win_amd64.whl", hash = "sha256:29c3189895a8a6a657b7af4e97d330c8a3afd2c9c8f46c81e2fc5a31866517e3"}, 958 | {file = "ruff-0.11.13-py3-none-win_arm64.whl", hash = "sha256:b4385285e9179d608ff1d2fb9922062663c658605819a6876d8beef0c30b7f3b"}, 959 | {file = "ruff-0.11.13.tar.gz", hash = "sha256:26fa247dc68d1d4e72c179e08889a25ac0c7ba4d78aecfc835d49cbfd60bf514"}, 960 | ] 961 | 962 | [[package]] 963 | name = "safetensors" 964 | version = "0.5.3" 965 | description = "" 966 | optional = false 967 | python-versions = ">=3.7" 968 | groups = ["main"] 969 | files = [ 970 | {file = "safetensors-0.5.3-cp38-abi3-macosx_10_12_x86_64.whl", hash = "sha256:bd20eb133db8ed15b40110b7c00c6df51655a2998132193de2f75f72d99c7073"}, 971 | {file = "safetensors-0.5.3-cp38-abi3-macosx_11_0_arm64.whl", hash = "sha256:21d01c14ff6c415c485616b8b0bf961c46b3b343ca59110d38d744e577f9cce7"}, 972 | {file = "safetensors-0.5.3-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:11bce6164887cd491ca75c2326a113ba934be596e22b28b1742ce27b1d076467"}, 973 | {file = "safetensors-0.5.3-cp38-abi3-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:4a243be3590bc3301c821da7a18d87224ef35cbd3e5f5727e4e0728b8172411e"}, 974 | {file = "safetensors-0.5.3-cp38-abi3-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8bd84b12b1670a6f8e50f01e28156422a2bc07fb16fc4e98bded13039d688a0d"}, 975 | {file = "safetensors-0.5.3-cp38-abi3-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:391ac8cab7c829452175f871fcaf414aa1e292b5448bd02620f675a7f3e7abb9"}, 976 | {file = "safetensors-0.5.3-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cead1fa41fc54b1e61089fa57452e8834f798cb1dc7a09ba3524f1eb08e0317a"}, 977 | {file = "safetensors-0.5.3-cp38-abi3-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:1077f3e94182d72618357b04b5ced540ceb71c8a813d3319f1aba448e68a770d"}, 978 | {file = "safetensors-0.5.3-cp38-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:799021e78287bac619c7b3f3606730a22da4cda27759ddf55d37c8db7511c74b"}, 979 | {file = "safetensors-0.5.3-cp38-abi3-musllinux_1_2_armv7l.whl", hash = "sha256:df26da01aaac504334644e1b7642fa000bfec820e7cef83aeac4e355e03195ff"}, 980 | {file = "safetensors-0.5.3-cp38-abi3-musllinux_1_2_i686.whl", hash = "sha256:32c3ef2d7af8b9f52ff685ed0bc43913cdcde135089ae322ee576de93eae5135"}, 981 | {file = "safetensors-0.5.3-cp38-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:37f1521be045e56fc2b54c606d4455573e717b2d887c579ee1dbba5f868ece04"}, 982 | {file = "safetensors-0.5.3-cp38-abi3-win32.whl", hash = "sha256:cfc0ec0846dcf6763b0ed3d1846ff36008c6e7290683b61616c4b040f6a54ace"}, 983 | {file = "safetensors-0.5.3-cp38-abi3-win_amd64.whl", hash = "sha256:836cbbc320b47e80acd40e44c8682db0e8ad7123209f69b093def21ec7cafd11"}, 984 | {file = "safetensors-0.5.3.tar.gz", hash = "sha256:b6b0d6ecacec39a4fdd99cc19f4576f5219ce858e6fd8dbe7609df0b8dc56965"}, 985 | ] 986 | 987 | [package.extras] 988 | all = ["safetensors[jax]", "safetensors[numpy]", "safetensors[paddlepaddle]", "safetensors[pinned-tf]", "safetensors[quality]", "safetensors[testing]", "safetensors[torch]"] 989 | dev = ["safetensors[all]"] 990 | jax = ["flax (>=0.6.3)", "jax (>=0.3.25)", "jaxlib (>=0.3.25)", "safetensors[numpy]"] 991 | mlx = ["mlx (>=0.0.9)"] 992 | numpy = ["numpy (>=1.21.6)"] 993 | paddlepaddle = ["paddlepaddle (>=2.4.1)", "safetensors[numpy]"] 994 | pinned-tf = ["safetensors[numpy]", "tensorflow (==2.18.0)"] 995 | quality = ["black (==22.3)", "click (==8.0.4)", "flake8 (>=3.8.3)", "isort (>=5.5.4)"] 996 | tensorflow = ["safetensors[numpy]", "tensorflow (>=2.11.0)"] 997 | testing = ["h5py (>=3.7.0)", "huggingface-hub (>=0.12.1)", "hypothesis (>=6.70.2)", "pytest (>=7.2.0)", "pytest-benchmark (>=4.0.0)", "safetensors[numpy]", "setuptools-rust (>=1.5.2)"] 998 | torch = ["safetensors[numpy]", "torch (>=1.10)"] 999 | 1000 | [[package]] 1001 | name = "six" 1002 | version = "1.17.0" 1003 | description = "Python 2 and 3 compatibility utilities" 1004 | optional = false 1005 | python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7" 1006 | groups = ["vis"] 1007 | files = [ 1008 | {file = "six-1.17.0-py2.py3-none-any.whl", hash = "sha256:4721f391ed90541fddacab5acf947aa0d3dc7d27b2e1e8eda2be8970586c3274"}, 1009 | {file = "six-1.17.0.tar.gz", hash = "sha256:ff70335d468e7eb6ec65b95b99d3a2836546063f63acc5171de367e834932a81"}, 1010 | ] 1011 | 1012 | [[package]] 1013 | name = "types-regex" 1014 | version = "2024.11.6.20250403" 1015 | description = "Typing stubs for regex" 1016 | optional = false 1017 | python-versions = ">=3.9" 1018 | groups = ["dev"] 1019 | files = [ 1020 | {file = "types_regex-2024.11.6.20250403-py3-none-any.whl", hash = "sha256:e22c0f67d73f4b4af6086a340f387b6f7d03bed8a0bb306224b75c51a29b0001"}, 1021 | {file = "types_regex-2024.11.6.20250403.tar.gz", hash = "sha256:3fdf2a70bbf830de4b3a28e9649a52d43dabb57cdb18fbfe2252eefb53666665"}, 1022 | ] 1023 | 1024 | [[package]] 1025 | name = "types-requests" 1026 | version = "2.32.0.20250602" 1027 | description = "Typing stubs for requests" 1028 | optional = false 1029 | python-versions = ">=3.9" 1030 | groups = ["dev"] 1031 | files = [ 1032 | {file = "types_requests-2.32.0.20250602-py3-none-any.whl", hash = "sha256:f4f335f87779b47ce10b8b8597b409130299f6971ead27fead4fe7ba6ea3e726"}, 1033 | {file = "types_requests-2.32.0.20250602.tar.gz", hash = "sha256:ee603aeefec42051195ae62ca7667cd909a2f8128fdf8aad9e8a5219ecfab3bf"}, 1034 | ] 1035 | 1036 | [package.dependencies] 1037 | urllib3 = ">=2" 1038 | 1039 | [[package]] 1040 | name = "typing-extensions" 1041 | version = "4.13.1" 1042 | description = "Backported and Experimental Type Hints for Python 3.8+" 1043 | optional = false 1044 | python-versions = ">=3.8" 1045 | groups = ["dev"] 1046 | files = [ 1047 | {file = "typing_extensions-4.13.1-py3-none-any.whl", hash = "sha256:4b6cf02909eb5495cfbc3f6e8fd49217e6cc7944e145cdda8caa3734777f9e69"}, 1048 | {file = "typing_extensions-4.13.1.tar.gz", hash = "sha256:98795af00fb9640edec5b8e31fc647597b4691f099ad75f469a2616be1a76dff"}, 1049 | ] 1050 | 1051 | [[package]] 1052 | name = "urllib3" 1053 | version = "2.3.0" 1054 | description = "HTTP library with thread-safe connection pooling, file post, and more." 1055 | optional = false 1056 | python-versions = ">=3.9" 1057 | groups = ["main", "dev"] 1058 | files = [ 1059 | {file = "urllib3-2.3.0-py3-none-any.whl", hash = "sha256:1cee9ad369867bfdbbb48b7dd50374c0967a0bb7710050facf0dd6911440e3df"}, 1060 | {file = "urllib3-2.3.0.tar.gz", hash = "sha256:f8c5449b3cf0861679ce7e0503c7b44b5ec981bec0d1d3795a07f1ba96f0204d"}, 1061 | ] 1062 | 1063 | [package.extras] 1064 | brotli = ["brotli (>=1.0.9) ; platform_python_implementation == \"CPython\"", "brotlicffi (>=0.8.0) ; platform_python_implementation != \"CPython\""] 1065 | h2 = ["h2 (>=4,<5)"] 1066 | socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"] 1067 | zstd = ["zstandard (>=0.18.0)"] 1068 | 1069 | [metadata] 1070 | lock-version = "2.1" 1071 | python-versions = "^3.12" 1072 | content-hash = "9fb2fa2122b8ce4114550eac8bc49f0b75499409b2268d1ae3aaf3b9121e4d89" 1073 | -------------------------------------------------------------------------------- /pyproject.toml: -------------------------------------------------------------------------------- 1 | [tool.poetry] 2 | name = "gpt2-weights" 3 | version = "0.1.0" 4 | description = "" 5 | authors = ["sdiehl "] 6 | readme = "README.md" 7 | license = "MIT" 8 | packages = [ 9 | { include = "tinygpt2" }, 10 | ] 11 | 12 | [tool.poetry.dependencies] 13 | python = "^3.12" 14 | safetensors = "^0.5.3" 15 | requests = "^2.32.3" 16 | numpy = "^2.2.6" 17 | regex = "^2024.11.6" 18 | 19 | [tool.poetry.group.vis.dependencies] 20 | matplotlib = "^3.10.3" 21 | 22 | [tool.poetry.group.dev.dependencies] 23 | black = "^25.1.0" 24 | ruff = "^0.11.13" 25 | mypy = "^1.16.0" 26 | types-requests = "^2.32.0.20250602" 27 | types-regex = "^2024.11.6.20250403" 28 | 29 | [build-system] 30 | requires = ["poetry-core"] 31 | build-backend = "poetry.core.masonry.api" 32 | 33 | # Disable mypy on the file encoder.py 34 | [tool.mypy] 35 | exclude = ["tinygpt2/encoder.py"] 36 | 37 | [tool.ruff] 38 | exclude = ["encoder.py"] 39 | -------------------------------------------------------------------------------- /tinygpt2/__init__.py: -------------------------------------------------------------------------------- 1 | from tinygpt2.gpt2_tensors import load_gpt2_weights, ModelParams, HParams 2 | from tinygpt2.gpt2_run import generate 3 | from tinygpt2.encoder import get_encoder 4 | 5 | __all__ = [ 6 | "ModelParams", 7 | "HParams", 8 | "load_gpt2_weights", 9 | "generate", 10 | "get_encoder", 11 | ] 12 | -------------------------------------------------------------------------------- /tinygpt2/encoder.py: -------------------------------------------------------------------------------- 1 | """Byte pair encoding utilities""" 2 | 3 | import os 4 | import json 5 | import regex as re 6 | from functools import lru_cache 7 | 8 | 9 | @lru_cache() 10 | def bytes_to_unicode(): 11 | """ 12 | Returns list of utf-8 byte and a corresponding list of unicode strings. 13 | The reversible bpe codes work on unicode strings. 14 | This means you need a large # of unicode characters in your vocab if you want to avoid UNKs. 15 | When you're at something like a 10B token dataset you end up needing around 5K for decent coverage. 16 | This is a signficant percentage of your normal, say, 32K bpe vocab. 17 | To avoid that, we want lookup tables between utf-8 bytes and unicode strings. 18 | And avoids mapping to whitespace/control characters the bpe code barfs on. 19 | """ 20 | bs = ( 21 | list(range(ord("!"), ord("~") + 1)) 22 | + list(range(ord("¡"), ord("¬") + 1)) 23 | + list(range(ord("®"), ord("ÿ") + 1)) 24 | ) 25 | cs = bs[:] 26 | n = 0 27 | for b in range(2**8): 28 | if b not in bs: 29 | bs.append(b) 30 | cs.append(2**8 + n) 31 | n += 1 32 | cs = [chr(n) for n in cs] 33 | return dict(zip(bs, cs)) 34 | 35 | 36 | def get_pairs(word): 37 | """Return set of symbol pairs in a word. 38 | 39 | Word is represented as tuple of symbols (symbols being variable-length strings). 40 | """ 41 | pairs = set() 42 | prev_char = word[0] 43 | for char in word[1:]: 44 | pairs.add((prev_char, char)) 45 | prev_char = char 46 | return pairs 47 | 48 | 49 | class Encoder: 50 | def __init__(self, encoder, bpe_merges, errors="replace"): 51 | self.encoder = encoder 52 | self.decoder = {v: k for k, v in self.encoder.items()} 53 | self.errors = errors # how to handle errors in decoding 54 | self.byte_encoder = bytes_to_unicode() 55 | self.byte_decoder = {v: k for k, v in self.byte_encoder.items()} 56 | self.bpe_ranks = dict(zip(bpe_merges, range(len(bpe_merges)))) 57 | self.cache = {} 58 | 59 | # Should haved added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions 60 | self.pat = re.compile( 61 | r"""'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+""" 62 | ) 63 | 64 | def bpe(self, token): 65 | if token in self.cache: 66 | return self.cache[token] 67 | word = tuple(token) 68 | pairs = get_pairs(word) 69 | 70 | if not pairs: 71 | return token 72 | 73 | while True: 74 | bigram = min(pairs, key=lambda pair: self.bpe_ranks.get(pair, float("inf"))) 75 | if bigram not in self.bpe_ranks: 76 | break 77 | first, second = bigram 78 | new_word = [] 79 | i = 0 80 | while i < len(word): 81 | try: 82 | j = word.index(first, i) 83 | new_word.extend(word[i:j]) 84 | i = j 85 | except: 86 | new_word.extend(word[i:]) 87 | break 88 | 89 | if word[i] == first and i < len(word) - 1 and word[i + 1] == second: 90 | new_word.append(first + second) 91 | i += 2 92 | else: 93 | new_word.append(word[i]) 94 | i += 1 95 | new_word = tuple(new_word) 96 | word = new_word 97 | if len(word) == 1: 98 | break 99 | else: 100 | pairs = get_pairs(word) 101 | word = " ".join(word) 102 | self.cache[token] = word 103 | return word 104 | 105 | def encode(self, text): 106 | bpe_tokens = [] 107 | for token in re.findall(self.pat, text): 108 | token = "".join(self.byte_encoder[b] for b in token.encode("utf-8")) 109 | bpe_tokens.extend( 110 | self.encoder[bpe_token] for bpe_token in self.bpe(token).split(" ") 111 | ) 112 | return bpe_tokens 113 | 114 | def decode(self, tokens): 115 | text = "".join([self.decoder[token] for token in tokens]) 116 | text = bytearray([self.byte_decoder[c] for c in text]).decode( 117 | "utf-8", errors=self.errors 118 | ) 119 | return text 120 | 121 | 122 | def get_encoder(model_name, models_dir): 123 | with open(os.path.join(models_dir, model_name, "encoder.json"), "r") as f: 124 | encoder = json.load(f) 125 | with open( 126 | os.path.join(models_dir, model_name, "vocab.bpe"), "r", encoding="utf-8" 127 | ) as f: 128 | bpe_data = f.read() 129 | bpe_merges = [tuple(merge_str.split()) for merge_str in bpe_data.split("\n")[1:-1]] 130 | return Encoder( 131 | encoder=encoder, 132 | bpe_merges=bpe_merges, 133 | ) 134 | -------------------------------------------------------------------------------- /tinygpt2/gpt2_minimal.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | from tinygpt2.gpt2_tensors import ModelParams 3 | 4 | 5 | def gpt2(inputs: list[int], params: ModelParams, n_head: int) -> np.ndarray: 6 | x = params.wte[inputs] + params.wpe[range(len(inputs))] 7 | 8 | seq_len = x.shape[0] 9 | embedding_dim = x.shape[-1] 10 | head_size = embedding_dim // n_head 11 | 12 | for block_params in params.blocks: 13 | ln1_mean = np.mean(x, axis=-1, keepdims=True) 14 | ln1_variance = np.var(x, axis=-1, keepdims=True) 15 | ln1_normalized = (x - ln1_mean) / np.sqrt(ln1_variance + 1e-5) 16 | ln1_output = block_params.ln_1.g * ln1_normalized + block_params.ln_1.b 17 | 18 | qkv_proj = ln1_output @ block_params.attn.c_attn.w + block_params.attn.c_attn.b 19 | q_proj, k_proj, v_proj = np.split(qkv_proj, 3, axis=-1) 20 | 21 | q_heads = q_proj.reshape(seq_len, n_head, head_size) 22 | k_heads = k_proj.reshape(seq_len, n_head, head_size) 23 | v_heads = v_proj.reshape(seq_len, n_head, head_size) 24 | 25 | q_heads_t = q_heads.transpose(1, 0, 2) 26 | k_heads_t = k_heads.transpose(1, 0, 2) 27 | v_heads_t = v_heads.transpose(1, 0, 2) 28 | 29 | attention_scores = (q_heads_t @ k_heads_t.transpose(0, 2, 1)) / np.sqrt( 30 | head_size 31 | ) 32 | 33 | causal_mask = np.triu(np.ones((seq_len, seq_len), dtype=x.dtype) * -np.inf, k=1) 34 | attention_scores = attention_scores + causal_mask 35 | 36 | exp_scores = np.exp( 37 | attention_scores - np.max(attention_scores, axis=-1, keepdims=True) 38 | ) 39 | attention_weights = exp_scores / np.sum(exp_scores, axis=-1, keepdims=True) 40 | 41 | weighted_values = attention_weights @ v_heads_t 42 | 43 | merged_heads = weighted_values.transpose(1, 0, 2).reshape( 44 | seq_len, embedding_dim 45 | ) 46 | 47 | mha_output = ( 48 | merged_heads @ block_params.attn.c_proj.w + block_params.attn.c_proj.b 49 | ) 50 | 51 | x = x + mha_output 52 | 53 | ln2_mean = np.mean(x, axis=-1, keepdims=True) 54 | ln2_variance = np.var(x, axis=-1, keepdims=True) 55 | ln2_normalized = (x - ln2_mean) / np.sqrt(ln2_variance + 1e-5) 56 | ln2_output = block_params.ln_2.g * ln2_normalized + block_params.ln_2.b 57 | 58 | fc_output = ln2_output @ block_params.mlp.c_fc.w + block_params.mlp.c_fc.b 59 | 60 | gelu_output = ( 61 | 0.5 62 | * fc_output 63 | * (1 + np.tanh(np.sqrt(2 / np.pi) * (fc_output + 0.044715 * fc_output**3))) 64 | ) 65 | 66 | ffn_output = gelu_output @ block_params.mlp.c_proj.w + block_params.mlp.c_proj.b 67 | 68 | x = x + ffn_output 69 | 70 | lnf_mean = np.mean(x, axis=-1, keepdims=True) 71 | lnf_variance = np.var(x, axis=-1, keepdims=True) 72 | lnf_normalized = (x - lnf_mean) / np.sqrt(lnf_variance + 1e-5) 73 | x_normalized_final = params.ln_f.g * lnf_normalized + params.ln_f.b 74 | 75 | logits = x_normalized_final @ params.wte.T 76 | 77 | return logits 78 | -------------------------------------------------------------------------------- /tinygpt2/gpt2_ops.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | from tinygpt2.gpt2_tensors import ( 3 | LayerNormParams, 4 | LinearParams, 5 | MLPParams, 6 | AttentionParams, 7 | ) 8 | 9 | # N - sequence length 10 | # 768 - embedding size 11 | # 64 - number of heads 12 | # 3072 - feed forward size 13 | # 12 - number of transformer blocks 14 | 15 | 16 | # gelu: 17 | # x : (N, 768) 18 | # out : (N, 768) 19 | def gelu(x: np.ndarray) -> np.ndarray: 20 | return 0.5 * x * (1 + np.tanh(np.sqrt(2 / np.pi) * (x + 0.044715 * x**3))) 21 | 22 | 23 | # softmax: 24 | # x : (N, 64) 25 | # out : (N, 64) 26 | def softmax(x: np.ndarray) -> np.ndarray: 27 | exp_x = np.exp(x - np.max(x, axis=-1, keepdims=True)) 28 | return exp_x / np.sum(exp_x, axis=-1, keepdims=True) 29 | 30 | 31 | # layer_norm: 32 | # x : (N, 768) 33 | # g : (768,) 34 | # b : (768,) 35 | # out : (N, 768) 36 | def layer_norm( 37 | x: np.ndarray, g: np.ndarray, b: np.ndarray, eps: float = 1e-5 38 | ) -> np.ndarray: 39 | mean = np.mean(x, axis=-1, keepdims=True) 40 | variance = np.var(x, axis=-1, keepdims=True) 41 | return g * (x - mean) / np.sqrt(variance + eps) + b 42 | 43 | 44 | # linear: 45 | # x : (N, 768) 46 | # w : (768, 3072) 47 | # b : (3072,) 48 | # out : (N, 3072) 49 | def linear(x: np.ndarray, w: np.ndarray, b: np.ndarray) -> np.ndarray: 50 | return x @ w + b 51 | 52 | 53 | # ffn: 54 | # x : (N, 768) 55 | # c_fc_w : (768, 3072) 56 | # c_fc_b : (3072,) 57 | # c_proj_w : (3072, 768) 58 | # c_proj_b : (768,) 59 | # out : (N, 768) 60 | def ffn( 61 | x: np.ndarray, 62 | c_fc_w: np.ndarray, 63 | c_fc_b: np.ndarray, 64 | c_proj_w: np.ndarray, 65 | c_proj_b: np.ndarray, 66 | ) -> np.ndarray: 67 | return linear(gelu(linear(x, w=c_fc_w, b=c_fc_b)), w=c_proj_w, b=c_proj_b) 68 | 69 | 70 | # attention: 71 | # q : (N, 64) 72 | # k : (N, 64) 73 | # v : (N, 64) 74 | # mask : (N, N) 75 | # out : (N, 64) 76 | def attention( 77 | q: np.ndarray, k: np.ndarray, v: np.ndarray, mask: np.ndarray 78 | ) -> np.ndarray: 79 | attention_scores = (q @ k.T) / np.sqrt(q.shape[-1]) + mask 80 | attention_weights = softmax(attention_scores) 81 | return attention_weights @ v 82 | 83 | 84 | # mha: 85 | # x : (N, 768) 86 | # out : (N, 768) 87 | def mha( 88 | x: np.ndarray, c_attn: LinearParams, c_proj: LinearParams, n_head: int 89 | ) -> np.ndarray: 90 | # qkv projection 91 | # [N, 768] -> [N, 3*768] 92 | x = linear(x, w=c_attn.w, b=c_attn.b) 93 | 94 | # split into qkv 95 | # [N, 3*768] -> [3, N, 768] 96 | qkv = np.split(x, 3, axis=-1) 97 | 98 | # split into heads 99 | # [3, N, 768] -> [3, n_head, N, 768/n_head] 100 | qkv_heads = [np.split(x, n_head, axis=-1) for x in qkv] 101 | 102 | # causal mask to hide future inputs from being attended to 103 | # [N, N] 104 | causal_mask = (1 - np.tri(x.shape[0], dtype=x.dtype)) * -1e10 105 | 106 | # perform attention over each head 107 | # [3, n_head, N, 768/n_head] -> [n_head, N, 768/n_head] 108 | out_heads = [attention(q, k, v, causal_mask) for q, k, v in zip(*qkv_heads)] 109 | 110 | # merge heads 111 | # [n_head, N, 768/n_head] -> [N, 768] 112 | x = np.hstack(out_heads) 113 | 114 | # out projection 115 | # [N, 768] -> [N, 768] 116 | return linear(x, w=c_proj.w, b=c_proj.b) 117 | 118 | 119 | # transformer_block: 120 | # x : (N, 768) 121 | # out : (N, 768) 122 | def transformer_block( 123 | x: np.ndarray, 124 | mlp: MLPParams, 125 | attn: AttentionParams, 126 | ln_1: LayerNormParams, 127 | ln_2: LayerNormParams, 128 | n_head: int, 129 | ) -> np.ndarray: 130 | # First sub-block: Layer norm -> Attention -> Residual 131 | a = layer_norm(x, g=ln_1.g, b=ln_1.b) 132 | a = mha(a, c_attn=attn.c_attn, c_proj=attn.c_proj, n_head=n_head) 133 | x = x + a 134 | 135 | # Second sub-block: Layer norm -> FFN -> Residual 136 | m = layer_norm(x, g=ln_2.g, b=ln_2.b) 137 | m = ffn( 138 | m, 139 | c_fc_w=mlp.c_fc.w, 140 | c_fc_b=mlp.c_fc.b, 141 | c_proj_w=mlp.c_proj.w, 142 | c_proj_b=mlp.c_proj.b, 143 | ) 144 | x = x + m 145 | 146 | return x 147 | -------------------------------------------------------------------------------- /tinygpt2/gpt2_run.py: -------------------------------------------------------------------------------- 1 | """ 2 | GPT-2 model implementation using NumPy. 3 | 4 | This module implements the core GPT-2 model architecture and text generation 5 | functionality using the tensor operations and weight loading utilities. 6 | """ 7 | 8 | import numpy as np 9 | import readline 10 | 11 | from tinygpt2.encoder import get_encoder 12 | from tinygpt2.gpt2_tensors import load_gpt2_weights, ModelParams, HParams 13 | import tinygpt2.gpt2_ops as ops 14 | 15 | 16 | def gpt2(inputs: list[int], params: ModelParams, n_head: int) -> np.ndarray: 17 | """ 18 | Forward pass through the GPT-2 model. 19 | 20 | Args: 21 | inputs: List of token IDs 22 | params: Model parameters dictionary 23 | n_head: Number of attention heads 24 | 25 | Returns: 26 | Logits for next token prediction 27 | """ 28 | # Get token embeddings and position embeddings 29 | x = params.wte[inputs] + params.wpe[range(len(inputs))] 30 | 31 | # Apply transformer block stack 32 | x = ops.transformer_block( 33 | x, 34 | n_head=n_head, 35 | mlp=params.blocks[0].mlp, 36 | attn=params.blocks[0].attn, 37 | ln_1=params.blocks[0].ln_1, 38 | ln_2=params.blocks[0].ln_2, 39 | ) 40 | x = ops.transformer_block( 41 | x, 42 | n_head=n_head, 43 | mlp=params.blocks[1].mlp, 44 | attn=params.blocks[1].attn, 45 | ln_1=params.blocks[1].ln_1, 46 | ln_2=params.blocks[1].ln_2, 47 | ) 48 | x = ops.transformer_block( 49 | x, 50 | n_head=n_head, 51 | mlp=params.blocks[2].mlp, 52 | attn=params.blocks[2].attn, 53 | ln_1=params.blocks[2].ln_1, 54 | ln_2=params.blocks[2].ln_2, 55 | ) 56 | x = ops.transformer_block( 57 | x, 58 | n_head=n_head, 59 | mlp=params.blocks[3].mlp, 60 | attn=params.blocks[3].attn, 61 | ln_1=params.blocks[3].ln_1, 62 | ln_2=params.blocks[3].ln_2, 63 | ) 64 | x = ops.transformer_block( 65 | x, 66 | n_head=n_head, 67 | mlp=params.blocks[4].mlp, 68 | attn=params.blocks[4].attn, 69 | ln_1=params.blocks[4].ln_1, 70 | ln_2=params.blocks[4].ln_2, 71 | ) 72 | x = ops.transformer_block( 73 | x, 74 | n_head=n_head, 75 | mlp=params.blocks[5].mlp, 76 | attn=params.blocks[5].attn, 77 | ln_1=params.blocks[5].ln_1, 78 | ln_2=params.blocks[5].ln_2, 79 | ) 80 | x = ops.transformer_block( 81 | x, 82 | n_head=n_head, 83 | mlp=params.blocks[6].mlp, 84 | attn=params.blocks[6].attn, 85 | ln_1=params.blocks[6].ln_1, 86 | ln_2=params.blocks[6].ln_2, 87 | ) 88 | x = ops.transformer_block( 89 | x, 90 | n_head=n_head, 91 | mlp=params.blocks[7].mlp, 92 | attn=params.blocks[7].attn, 93 | ln_1=params.blocks[7].ln_1, 94 | ln_2=params.blocks[7].ln_2, 95 | ) 96 | x = ops.transformer_block( 97 | x, 98 | n_head=n_head, 99 | mlp=params.blocks[8].mlp, 100 | attn=params.blocks[8].attn, 101 | ln_1=params.blocks[8].ln_1, 102 | ln_2=params.blocks[8].ln_2, 103 | ) 104 | x = ops.transformer_block( 105 | x, 106 | n_head=n_head, 107 | mlp=params.blocks[9].mlp, 108 | attn=params.blocks[9].attn, 109 | ln_1=params.blocks[9].ln_1, 110 | ln_2=params.blocks[9].ln_2, 111 | ) 112 | x = ops.transformer_block( 113 | x, 114 | n_head=n_head, 115 | mlp=params.blocks[10].mlp, 116 | attn=params.blocks[10].attn, 117 | ln_1=params.blocks[10].ln_1, 118 | ln_2=params.blocks[10].ln_2, 119 | ) 120 | x = ops.transformer_block( 121 | x, 122 | n_head=n_head, 123 | mlp=params.blocks[11].mlp, 124 | attn=params.blocks[11].attn, 125 | ln_1=params.blocks[11].ln_1, 126 | ln_2=params.blocks[11].ln_2, 127 | ) 128 | 129 | # Apply final layer norm and project to vocabulary 130 | x = ops.layer_norm(x, g=params.ln_f.g, b=params.ln_f.b) 131 | logits = x @ params.wte.T # Project to vocabulary 132 | 133 | return logits 134 | 135 | 136 | def generate_tokens( 137 | inputs: list[int], 138 | params: ModelParams, 139 | n_head: int, 140 | n_tokens_to_generate: int, 141 | encoder=None, 142 | ) -> list[int]: 143 | inputs = list(inputs) # Make a copy to avoid modifying the original 144 | generated_tokens = [] 145 | 146 | for i in range(n_tokens_to_generate): 147 | # Get logits for the entire sequence 148 | logits = gpt2(inputs, params, n_head=n_head) 149 | 150 | # Get the next token ID from the last position 151 | next_id = np.argmax(logits[-1]) 152 | next_id_int = int(next_id) 153 | 154 | # Add the predicted token to the sequence 155 | inputs.append(next_id_int) 156 | generated_tokens.append(next_id_int) 157 | 158 | # Stream the token if encoder is provided 159 | if encoder: 160 | token_text = encoder.decode([next_id_int]) 161 | print(token_text, end="", flush=True) 162 | 163 | return generated_tokens 164 | 165 | 166 | def generate( 167 | params: ModelParams, hparams: HParams, prompt: str, n_tokens_to_generate: int = 40 168 | ) -> str: 169 | # Load tokenizer 170 | encoder = get_encoder("", "model") 171 | 172 | # Encode input 173 | input_ids = encoder.encode(prompt) 174 | 175 | # Ensure we don't exceed context length 176 | if len(input_ids) + n_tokens_to_generate >= hparams.n_ctx: 177 | print( 178 | f"Input length + tokens to generate ({len(input_ids) + n_tokens_to_generate}) exceeds model context length ({hparams.n_ctx})" 179 | ) 180 | n_tokens_to_generate = hparams.n_ctx - len(input_ids) - 1 181 | print(f"Reducing tokens to generate to {n_tokens_to_generate}") 182 | 183 | # Print the initial prompt 184 | print(prompt, end="", flush=True) 185 | 186 | # Generate tokens with streaming 187 | output_ids = generate_tokens( 188 | input_ids, params, hparams.n_head, n_tokens_to_generate, encoder=encoder 189 | ) 190 | print() # Add newline after generation 191 | 192 | # Return the generated text (though it's already been printed) 193 | return encoder.decode(output_ids) 194 | 195 | 196 | def main(): 197 | # Load model weights and configuration 198 | print("Loading model weights...") 199 | params, hparams = load_gpt2_weights() 200 | print("Model loaded successfully") 201 | 202 | # Configure readline 203 | readline.parse_and_bind("tab: complete") 204 | readline.set_history_length(100) 205 | 206 | while True: 207 | try: 208 | # Get user input with readline support 209 | prompt = input("Enter a prompt: ") 210 | generate(params, hparams, prompt.strip()) 211 | except KeyboardInterrupt: 212 | print("\nInterrupted by user") 213 | continue 214 | except EOFError: 215 | print("\nDone.") 216 | break 217 | 218 | 219 | if __name__ == "__main__": 220 | main() 221 | -------------------------------------------------------------------------------- /tinygpt2/gpt2_tensors.py: -------------------------------------------------------------------------------- 1 | """ 2 | GPT-2 weight loading and tensor transformation utilities. 3 | 4 | This module handles loading and organizing the GPT-2 weights from safetensors format 5 | into the structure expected by the model implementation. 6 | 7 | Abbreviation Dictionary: 8 | g - Gamma (scale parameter for layer normalization) 9 | b - Beta (bias parameter) 10 | w - Weight matrix/array 11 | wte - Word/Token Embeddings 12 | wpe - Word Position Embeddings 13 | ln - Layer Normalization 14 | mlp - Multi-Layer Perceptron 15 | fc - Fully Connected layer 16 | qkv - Query, Key, Value (attention components) 17 | attn - Attention 18 | proj - Projection (linear transformation) 19 | 20 | Safetensors is a fast and safe format for storing tensors. The format uses a simple key/value structure where: 21 | 22 | - Keys are UTF-8 encoded strings representing tensor names (e.g. 'model.layers.0.attention.weight') 23 | - Values are binary tensor data with a fixed header containing shape and dtype information 24 | - A metadata section at the start of the file contains an index of all tensors and their offsets 25 | 26 | This structure allows for direct memory mapping and random access to individual tensors 27 | without loading the entire file into memory. 28 | 29 | { 30 | "wpe.weight": np.array([1024, 768]), 31 | "wte.weight": np.array([50257, 768]), 32 | ... 33 | "h.0.attn.bias": np.array([1, 1, 1024, 1024]), 34 | "h.0.attn.c_attn.bias": np.array([2304]), 35 | "h.0.attn.c_attn.weight": np.array([768, 2304]), 36 | "h.0.attn.c_proj.bias": np.array([768]), 37 | "h.0.attn.c_proj.weight": np.array([768, 768]), 38 | "h.0.ln_1.bias": np.array([768]), 39 | "h.0.ln_1.weight": np.array([768]), 40 | "h.0.ln_2.bias": np.array([768]), 41 | "h.0.ln_2.weight": np.array([768]), 42 | "h.0.mlp.c_fc.bias": np.array([3072]), 43 | "h.0.mlp.c_fc.weight": np.array([768, 3072]), 44 | "h.0.mlp.c_proj.bias": np.array([768]), 45 | "h.0.mlp.c_proj.weight": np.array([3072, 768]), 46 | ... 47 | "ln_f.bias": np.array([768]), 48 | "ln_f.weight": np.array([768]) 49 | } 50 | """ 51 | 52 | import numpy as np 53 | from pathlib import Path 54 | import requests 55 | from safetensors import safe_open 56 | from dataclasses import dataclass 57 | from typing import List, Tuple 58 | import json 59 | 60 | # URLs for vocabulary and encoder files 61 | VOCAB_URL = "https://openaipublic.blob.core.windows.net/gpt-2/models/124M/vocab.bpe" 62 | ENCODE_URL = "https://openaipublic.blob.core.windows.net/gpt-2/models/124M/encoder.json" 63 | HF_API_URL = "https://huggingface.co/api/models/" 64 | HF_REPO_URL = "https://huggingface.co/" 65 | 66 | 67 | @dataclass 68 | class LayerNormParams: 69 | """Layer normalization parameters.""" 70 | 71 | g: np.ndarray # Gamma (scale) 72 | b: np.ndarray # Beta (bias) 73 | 74 | 75 | @dataclass 76 | class LinearParams: 77 | """Linear layer parameters.""" 78 | 79 | w: np.ndarray # Weight matrix 80 | b: np.ndarray # Bias vector 81 | 82 | 83 | @dataclass 84 | class MLPParams: 85 | """MLP block parameters.""" 86 | 87 | c_fc: LinearParams # First linear layer 88 | c_proj: LinearParams # Second linear layer 89 | 90 | 91 | @dataclass 92 | class AttentionParams: 93 | """Attention block parameters.""" 94 | 95 | c_attn: LinearParams # QKV projection 96 | c_proj: LinearParams # Output projection 97 | 98 | 99 | @dataclass 100 | class TransformerBlockParams: 101 | """Parameters for a single transformer block.""" 102 | 103 | ln_1: LayerNormParams # First layer norm 104 | ln_2: LayerNormParams # Second layer norm 105 | mlp: MLPParams # MLP block 106 | attn: AttentionParams # Attention block 107 | 108 | 109 | @dataclass 110 | class ModelParams: 111 | """Complete model parameters.""" 112 | 113 | wte: np.ndarray # Token embeddings 114 | wpe: np.ndarray # Position embeddings 115 | blocks: List[TransformerBlockParams] # Transformer blocks 116 | ln_f: LayerNormParams # Final layer norm 117 | 118 | 119 | @dataclass 120 | class HParams: 121 | """Hyperparameters for the GPT-2 model.""" 122 | 123 | n_layer: int # Number of transformer layers 124 | n_head: int # Number of attention heads 125 | n_ctx: int # Context length 126 | 127 | 128 | def load_gpt2_weights( 129 | model_name: str = "openai-community/gpt2", cache_dir: str = "model" 130 | ) -> Tuple[ModelParams, HParams]: 131 | """Load GPT-2 weights from HuggingFace into structured dataclasses.""" 132 | cache_path = Path(cache_dir) 133 | cache_path.mkdir(parents=True, exist_ok=True) 134 | 135 | # Download model info and config 136 | response = requests.get(f"{HF_API_URL}{model_name}") 137 | response.raise_for_status() 138 | 139 | # Get config 140 | config_path = cache_path / "config.json" 141 | if not config_path.exists(): 142 | config_url = f"{HF_REPO_URL}{model_name}/resolve/main/config.json" 143 | response = requests.get(config_url) 144 | response.raise_for_status() 145 | config_path.write_text(response.text) 146 | 147 | # Load config 148 | with open(config_path) as f: 149 | config = json.load(f) 150 | 151 | # Download safetensors file - simplified since we know there's only one 152 | weights_path = cache_path / "model.safetensors" 153 | if not weights_path.exists(): 154 | print("Downloading weights from HuggingFace...") 155 | weights_url = f"{HF_REPO_URL}{model_name}/resolve/main/model.safetensors" 156 | response = requests.get(weights_url) 157 | response.raise_for_status() 158 | weights_path.write_bytes(response.content) 159 | print(f"Weights downloaded to {weights_path}") 160 | 161 | # Load tensors 162 | tensors = {} 163 | with safe_open(weights_path, framework="numpy") as f: 164 | for key in f.keys(): 165 | tensors[key] = f.get_tensor(key) 166 | 167 | # Build transformer blocks 168 | blocks = [] 169 | for i in range(config["n_layer"]): 170 | prefix = f"h.{i}" 171 | block = TransformerBlockParams( 172 | ln_1=LayerNormParams( 173 | g=tensors[f"{prefix}.ln_1.weight"], b=tensors[f"{prefix}.ln_1.bias"] 174 | ), 175 | ln_2=LayerNormParams( 176 | g=tensors[f"{prefix}.ln_2.weight"], b=tensors[f"{prefix}.ln_2.bias"] 177 | ), 178 | mlp=MLPParams( 179 | c_fc=LinearParams( 180 | w=tensors[f"{prefix}.mlp.c_fc.weight"], 181 | b=tensors[f"{prefix}.mlp.c_fc.bias"], 182 | ), 183 | c_proj=LinearParams( 184 | w=tensors[f"{prefix}.mlp.c_proj.weight"], 185 | b=tensors[f"{prefix}.mlp.c_proj.bias"], 186 | ), 187 | ), 188 | attn=AttentionParams( 189 | c_attn=LinearParams( 190 | w=tensors[f"{prefix}.attn.c_attn.weight"], 191 | b=tensors[f"{prefix}.attn.c_attn.bias"], 192 | ), 193 | c_proj=LinearParams( 194 | w=tensors[f"{prefix}.attn.c_proj.weight"], 195 | b=tensors[f"{prefix}.attn.c_proj.bias"], 196 | ), 197 | ), 198 | ) 199 | blocks.append(block) 200 | 201 | # Build final model params 202 | params = ModelParams( 203 | wte=tensors["wte.weight"], 204 | wpe=tensors["wpe.weight"], 205 | blocks=blocks, 206 | ln_f=LayerNormParams(g=tensors["ln_f.weight"], b=tensors["ln_f.bias"]), 207 | ) 208 | 209 | # Extract hyperparameters 210 | hparams = HParams( 211 | n_layer=config["n_layer"], n_head=config["n_head"], n_ctx=config["n_ctx"] 212 | ) 213 | 214 | return params, hparams 215 | -------------------------------------------------------------------------------- /tinygpt2/gpt2_viz.py: -------------------------------------------------------------------------------- 1 | """ 2 | GPT-2 visualization tools using matplotlib to display attention patterns 3 | during model inference. 4 | """ 5 | 6 | import numpy as np 7 | import matplotlib.pyplot as plt 8 | from typing import List, Tuple, Optional 9 | 10 | from tinygpt2.encoder import get_encoder 11 | from tinygpt2.gpt2_tensors import ModelParams, HParams 12 | from tinygpt2.gpt2_tensors import load_gpt2_weights 13 | import tinygpt2.gpt2_ops as ops 14 | 15 | 16 | def compute_attention_scores( 17 | inputs: List[int], params: ModelParams, n_head: int, block_idx: int = 0 18 | ) -> Tuple[np.ndarray, np.ndarray, List[str]]: 19 | """ 20 | Compute attention scores for a specific transformer block. 21 | 22 | Args: 23 | inputs: List of token IDs 24 | params: Model parameters 25 | n_head: Number of attention heads 26 | block_idx: Index of the transformer block to visualize (default 0) 27 | 28 | Returns: 29 | raw_scores: Attention scores before masking 30 | masked_scores: Attention scores after masking 31 | tokens_text: List of token text representations 32 | """ 33 | # Get token embeddings and position embeddings 34 | x = params.wte[inputs] + params.wpe[range(len(inputs))] 35 | 36 | # Apply layer norm 37 | block = params.blocks[block_idx] 38 | ln1_output = ops.layer_norm(x, g=block.ln_1.g, b=block.ln_1.b) 39 | 40 | # Get QKV projections 41 | qkv_proj = ln1_output @ block.attn.c_attn.w + block.attn.c_attn.b 42 | q_proj, k_proj, v_proj = np.split(qkv_proj, 3, axis=-1) 43 | 44 | # Reshape for attention computation 45 | seq_len = x.shape[0] 46 | head_size = x.shape[1] // n_head 47 | 48 | # Only compute for the first head for simplicity 49 | head_idx = 0 50 | q_head = q_proj[:, head_idx * head_size : (head_idx + 1) * head_size] 51 | k_head = k_proj[:, head_idx * head_size : (head_idx + 1) * head_size] 52 | 53 | # Compute raw attention scores 54 | raw_scores = (q_head @ k_head.T) / np.sqrt(head_size) 55 | 56 | # Create attention mask 57 | causal_mask = np.triu(np.ones((seq_len, seq_len)) * -1e10, k=1) 58 | 59 | # Apply mask 60 | masked_scores = raw_scores + causal_mask 61 | 62 | # Get token text representations 63 | encoder = get_encoder("", "model") 64 | tokens_text = [encoder.decode([token_id]) for token_id in inputs] 65 | 66 | return raw_scores, masked_scores, tokens_text 67 | 68 | 69 | def display_qk_heatmap(attention_matrix: np.ndarray, tokens: List[str], title: str): 70 | """ 71 | Display a heatmap of attention scores. 72 | 73 | Args: 74 | attention_matrix: Matrix of attention scores 75 | tokens: List of token text representations 76 | title: Title for the plot 77 | """ 78 | plt.figure(figsize=(10, 8)) 79 | im = plt.imshow(attention_matrix, cmap="viridis") 80 | 81 | # Set ticks and labels 82 | plt.xticks(range(len(tokens)), tokens, rotation=90) 83 | plt.yticks(range(len(tokens)), tokens) 84 | 85 | # Add colorbar and title 86 | plt.colorbar(im) 87 | plt.title(title) 88 | plt.tight_layout() 89 | 90 | 91 | def visualize_attention( 92 | prompt: str, 93 | params: ModelParams, 94 | hparams: HParams, 95 | num_blocks: int = 3, 96 | save_path: Optional[str] = None, 97 | ): 98 | """ 99 | Visualize attention patterns for multiple transformer blocks. 100 | 101 | Args: 102 | prompt: Input text prompt 103 | params: Model parameters 104 | hparams: Model hyperparameters 105 | num_blocks: Number of transformer blocks to visualize (default 3) 106 | save_path: Path to save the visualization (if None, display instead) 107 | """ 108 | # Encode input 109 | encoder = get_encoder("", "model") 110 | input_ids = encoder.encode(prompt) 111 | 112 | # Ensure we don't exceed context length 113 | if len(input_ids) >= hparams.n_ctx: 114 | input_ids = input_ids[: hparams.n_ctx - 1] 115 | 116 | # Determine number of blocks to visualize 117 | num_blocks_to_show = min(num_blocks, len(params.blocks)) 118 | 119 | # Create a figure with a grid based on the number of blocks 120 | fig, axes = plt.subplots( 121 | num_blocks_to_show, 3, figsize=(24, 6 * num_blocks_to_show) 122 | ) 123 | 124 | # Ensure axes is 2D even if there's only one block 125 | if num_blocks_to_show == 1: 126 | axes = np.array([axes]) 127 | 128 | # Compute and visualize attention scores for each block 129 | for i in range(num_blocks_to_show): 130 | raw_scores, masked_scores, tokens = compute_attention_scores( 131 | input_ids, params, hparams.n_head, i 132 | ) 133 | 134 | # Plot raw attention scores in first column 135 | im1 = axes[i, 0].imshow(raw_scores, cmap="viridis") 136 | axes[i, 0].set_title(f"Raw QK Attention (Block {i})") 137 | axes[i, 0].set_xticks(range(len(tokens))) 138 | axes[i, 0].set_yticks(range(len(tokens))) 139 | axes[i, 0].set_xticklabels(tokens, rotation=90) 140 | axes[i, 0].set_yticklabels(tokens) 141 | fig.colorbar(im1, ax=axes[i, 0]) 142 | 143 | # Plot masked attention scores in second column - use a different colormap to highlight masked areas 144 | masked_cmap = plt.cm.viridis.copy() # type: ignore 145 | masked_cmap.set_under("black") # Set color for values below the minimum 146 | 147 | # Create a mask to show exactly where the causal mask is applied 148 | vmin = np.min(raw_scores) # Use minimum of raw scores 149 | im2 = axes[i, 1].imshow(masked_scores, cmap=masked_cmap, vmin=vmin) 150 | axes[i, 1].set_title(f"Masked Attention (Block {i})") 151 | axes[i, 1].set_xticks(range(len(tokens))) 152 | axes[i, 1].set_yticks(range(len(tokens))) 153 | axes[i, 1].set_xticklabels(tokens, rotation=90) 154 | axes[i, 1].set_yticklabels(tokens) 155 | fig.colorbar(im2, ax=axes[i, 1], extend="min") 156 | 157 | # Plot softmax probabilities in third column 158 | softmax_attn = np.exp(masked_scores) / np.sum( 159 | np.exp(masked_scores), axis=1, keepdims=True 160 | ) 161 | im3 = axes[i, 2].imshow( 162 | softmax_attn, cmap="plasma" 163 | ) # Different colormap for contrast 164 | axes[i, 2].set_title(f"Attention Probabilities (Block {i})") 165 | axes[i, 2].set_xticks(range(len(tokens))) 166 | axes[i, 2].set_yticks(range(len(tokens))) 167 | axes[i, 2].set_xticklabels(tokens, rotation=90) 168 | axes[i, 2].set_yticklabels(tokens) 169 | fig.colorbar(im3, ax=axes[i, 2]) 170 | 171 | plt.suptitle(f"Attention Visualization for: '{prompt}'", fontsize=16) 172 | plt.tight_layout(rect=(0, 0, 1, 0.97)) # Make room for the suptitle 173 | 174 | if save_path: 175 | plt.savefig(save_path) 176 | else: 177 | plt.show() 178 | 179 | 180 | if __name__ == "__main__": 181 | 182 | # Load model weights and configuration 183 | print("Loading model weights...") 184 | params, hparams = load_gpt2_weights() 185 | print("Model loaded successfully") 186 | 187 | # Example prompt 188 | prompt = "The quick brown fox jumps over the lazy dog" 189 | 190 | # Visualize attention for the first three transformer blocks 191 | visualize_attention( 192 | prompt, params, hparams, num_blocks=1, save_path="attention.png" 193 | ) 194 | -------------------------------------------------------------------------------- /tokens.py: -------------------------------------------------------------------------------- 1 | """ 2 | Example usage of the tokenizer. 3 | """ 4 | 5 | from tinygpt2 import get_encoder 6 | 7 | 8 | def main(): 9 | encoder = get_encoder("", "model") 10 | 11 | while True: 12 | try: 13 | text = input("Enter text to encode: ") 14 | encoded_ids = encoder.encode(text) 15 | 16 | # Decode each token ID back to its string representation 17 | decoded_tokens = [encoder.decode([token_id]) for token_id in encoded_ids] 18 | 19 | print("Token Mapping:") 20 | for token, token_id in zip(decoded_tokens, encoded_ids): 21 | print(f" '{token}': {token_id}") 22 | 23 | except EOFError: 24 | print("\nDone.") 25 | break 26 | 27 | 28 | if __name__ == "__main__": 29 | main() 30 | --------------------------------------------------------------------------------