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  1. docs/en/docs/tutorial/bigger-applications.md

    * The file `app/routers/items.py` is inside a package, `app/routers/`, so, it's a submodule: `app.routers.items`.
    * The same with `app/routers/users.py`, it's another submodule: `app.routers.users`.
    * There's also a subdirectory `app/internal/` with another file `__init__.py`, so it's another "Python subpackage": `app.internal`.
    * And the file `app/internal/admin.py` is another submodule: `app.internal.admin`.
    
    Plain Text
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  2. tensorflow/api_template.__init__.py

      )
    
    # Add Keras module aliases
    _losses = _KerasLazyLoader(globals(), submodule="losses", name="losses")
    _metrics = _KerasLazyLoader(globals(), submodule="metrics", name="metrics")
    _optimizers = _KerasLazyLoader(
        globals(), submodule="optimizers", name="optimizers")
    _initializers = _KerasLazyLoader(
        globals(), submodule="initializers", name="initializers")
    setattr(_current_module, "losses", _losses)
    Python
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  3. docs/de/docs/tutorial/bigger-applications.md

    * Das Gleiche gilt für `app/routers/users.py`, es ist ein weiteres Submodul: `app.routers.users`.
    * Es gibt auch ein Unterverzeichnis `app/internal/` mit einer weiteren Datei `__init__.py`, es handelt sich also um ein weiteres „Python-Subpackage“: `app.internal`.
    * Und die Datei `app/internal/admin.py` ist ein weiteres Submodul: `app.internal.admin`.
    
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  4. docs/em/docs/tutorial/bigger-applications.md

    │   │   ├── items.py     # "items" submodule, e.g. import app.routers.items
    │   │   └── users.py     # "users" submodule, e.g. import app.routers.users
    │   └── internal         # "internal" is a "Python subpackage"
    │       ├── __init__.py  # makes "internal" a "Python subpackage"
    │       └── admin.py     # "admin" submodule, e.g. import app.internal.admin
    ```
    
    ## `APIRouter`
    
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  5. docs/en/docs/tutorial/body-nested-models.md

        {!> ../../../docs_src/body_nested_models/tutorial005.py!}
        ```
    
    The string will be checked to be a valid URL, and documented in JSON Schema / OpenAPI as such.
    
    ## Attributes with lists of submodels
    
    You can also use Pydantic models as subtypes of `list`, `set`, etc.:
    
    === "Python 3.10+"
    
        ```Python hl_lines="18"
        {!> ../../../docs_src/body_nested_models/tutorial006_py310.py!}
        ```
    
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  6. settings.gradle.kts

      include(":okhttp-android")
      include(":android-test")
      include(":android-test-app")
    }
    
    enableFeaturePreview("TYPESAFE_PROJECT_ACCESSORS")
    
    /**
     * Avoid a crash in IntelliJ triggered by Android submodules.
     *
     * ```
     * java.lang.AssertionError: Can't find built-in class kotlin.Cloneable
     *   at org.jetbrains.kotlin.builtins.KotlinBuiltIns.getBuiltInClassByFqName(KotlinBuiltIns.java:217)
    Plain Text
    - Registered: Fri May 03 11:42:14 GMT 2024
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  7. maven-core/src/main/java/org/apache/maven/project/ProjectBuilder.java

         * Builds the projects for the specified POM files and optionally their children.
         *
         * @param pomFiles The POM files to build, must not be {@code null}.
         * @param recursive {@code true} to recursively build submodules referenced by the POM files, {@code false} to
         *            build only the specified POM files.
         * @param request The project builder configuration that provides further parameters, must not be {@code null}.
    Java
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  8. RELEASE.md

        `TF_Run`, `TF_SessionRun`, `TF_SetAttrTensor` etc.
    *   Renamed `tf.image.per_image_whitening()` to
        `tf.image.per_image_standardization()`
    *   Move Summary protobuf constructors to `tf.summary` submodule.
    *   Deprecate `histogram_summary`, `audio_summary`, `scalar_summary`,
        `image_summary`, `merge_summary`, and `merge_all_summaries`.
    *   Combined `batch_*` and regular version of linear algebra and FFT ops. The
    Plain Text
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  9. fastapi/routing.py

                    name=response_name,
                    type_=self.response_model,
                    mode="serialization",
                )
                # Create a clone of the field, so that a Pydantic submodel is not returned
                # as is just because it's an instance of a subclass of a more limited class
                # e.g. UserInDB (containing hashed_password) could be a subclass of User
    Python
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  10. docs/en/docs/release-notes.md

            * When a `response_model` is declared, the same `response_model` type declaration won't be used as is, it will be "cloned" to create an new one (a cloned Pydantic `Field` with all the submodels cloned as well).
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