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tensorflow/compiler/mlir/lite/quantization/lite/quantize_model_test.cc
// Unpacks the given flatbuffer model. // // This helper is useful as UnPackTo requires the input to not have any existing // state so directly calling UnPackTo could lead to memory leaks if the model // already had some state. Instead, the returned object from here can be used to // overwrite existing model. ModelT UnPackFlatBufferModel(const Model& flatbuffer_model) { ModelT model; flatbuffer_model.UnPackTo(&model);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 23:15:24 UTC 2024 - 73.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/lite/quantize_weights_test.cc
model_ = input_model_->GetModel(); } std::unique_ptr<FlatBufferModel> input_model_; const Model* model_; bool IsModelInputOrOutput(const Model* model, uint32_t tensor_idx) { for (size_t subgraph_idx = 0; subgraph_idx < model_->subgraphs()->size(); ++subgraph_idx) { const auto subgraph = model->subgraphs()->Get(subgraph_idx);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 23:15:24 UTC 2024 - 32.3K bytes - Viewed (0) -
docs_src/sql_databases/sql_app/models.py
Moustapha Sall <******@****.***> 1704810933 -0500
Registered: Mon Jun 17 08:32:26 UTC 2024 - Last Modified: Tue Jan 09 14:35:33 UTC 2024 - 710 bytes - Viewed (0) -
docs_src/sql_databases/sql_app_py39/models.py
Moustapha Sall <******@****.***> 1704810933 -0500
Registered: Mon Jun 17 08:32:26 UTC 2024 - Last Modified: Tue Jan 09 14:35:33 UTC 2024 - 710 bytes - Viewed (0) -
docs/ko/docs/tutorial/body-nested-models.md
```Python hl_lines="15" {!../../../docs_src/body_nested_models/tutorial008.py!} ``` ## 어디서나 편집기 지원 그리고 어디서나 편집기 지원을 받을수 있습니다. 리스트 내부 항목의 경우에도: <img src="/img/tutorial/body-nested-models/image01.png"> Pydantic 모델 대신에 `dict`를 직접 사용하여 작업할 경우, 이러한 편집기 지원을 받을수 없습니다. 하지만 수신한 딕셔너리가 자동으로 변환되고 출력도 자동으로 JSON으로 변환되므로 걱정할 필요는 없습니다. ## 단독 `dict`의 본문 일부 타입의 키와 다른 타입의 값을 사용하여 `dict`로 본문을 선언할 수 있습니다.
Registered: Mon Jun 17 08:32:26 UTC 2024 - Last Modified: Wed Jun 12 12:49:35 UTC 2024 - 7.6K bytes - Viewed (0) -
docs/ru/docs/tutorial/body-nested-models.md
``` ## Универсальная поддержка редактора И вы получаете поддержку редактора везде. Даже для элементов внутри списков: <img src="/img/tutorial/body-nested-models/image01.png"> Вы не могли бы получить такую поддержку редактора, если бы работали напрямую с `dict`, а не с моделями Pydantic.
Registered: Mon Jun 17 08:32:26 UTC 2024 - Last Modified: Fri Mar 22 01:42:11 UTC 2024 - 14.9K bytes - Viewed (0) -
docs/em/docs/tutorial/body-nested-models.md
{!> ../../../docs_src/body_nested_models/tutorial008_py39.py!} ``` ## 👨🎨 🐕🦺 🌐 & 👆 🤚 👨🎨 🐕🦺 🌐. 🏬 🔘 📇: <img src="/img/tutorial/body-nested-models/image01.png"> 👆 🚫 🚫 🤚 👉 😇 👨🎨 🐕🦺 🚥 👆 👷 🔗 ⏮️ `dict` ↩️ Pydantic 🏷. ✋️ 👆 🚫 ✔️ 😟 🔃 👫 👯♂️, 📨 #️⃣ 🗜 🔁 & 👆 🔢 🗜 🔁 🎻 💁♂️. ## 💪 ❌ `dict`Ⓜ
Registered: Mon Jun 17 08:32:26 UTC 2024 - Last Modified: Fri Mar 22 01:42:11 UTC 2024 - 9.2K bytes - Viewed (0) -
docs/de/docs/tutorial/encoder.md
Genauso würde die Datenbank kein Pydantic-Modell (ein Objekt mit Attributen) akzeptieren, sondern nur ein `dict`. Sie können für diese Fälle `jsonable_encoder` verwenden. Es nimmt ein Objekt entgegen, wie etwa ein Pydantic-Modell, und gibt eine JSON-kompatible Version zurück: === "Python 3.10+" ```Python hl_lines="4 21"
Registered: Mon Jun 17 08:32:26 UTC 2024 - Last Modified: Sat Mar 30 18:07:21 UTC 2024 - 1.9K bytes - Viewed (0) -
docs/fr/docs/advanced/additional-responses.md
**FastAPI** prendra ce modèle, générera son schéma JSON et l'inclura au bon endroit dans OpenAPI. Par exemple, pour déclarer une autre réponse avec un code HTTP `404` et un modèle Pydantic `Message`, vous pouvez écrire : ```Python hl_lines="18 22" {!../../../docs_src/additional_responses/tutorial001.py!} ``` !!! note "Remarque" Gardez à l'esprit que vous devez renvoyer directement `JSONResponse`. !!! info
Registered: Mon Jun 17 08:32:26 UTC 2024 - Last Modified: Thu Apr 18 19:53:19 UTC 2024 - 9.6K bytes - Viewed (0) -
docs/fr/docs/tutorial/body.md
## Importez le `BaseModel` de Pydantic Commencez par importer la classe `BaseModel` du module `pydantic` : ```Python hl_lines="4" {!../../../docs_src/body/tutorial001.py!} ``` ## Créez votre modèle de données Déclarez ensuite votre modèle de données en tant que classe qui hérite de `BaseModel`. Utilisez les types Python standard pour tous les attributs :
Registered: Mon Jun 17 08:32:26 UTC 2024 - Last Modified: Fri Mar 22 01:42:11 UTC 2024 - 7.8K bytes - Viewed (0)