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doc/next/6-stdlib/99-minor/reflect/61308.md
The [SliceAt(typ Type, p unsafe.Pointer, len int)] function returns a Value representing a slice whose underlying array starts
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common-protos/k8s.io/apimachinery/pkg/apis/meta/v1/generated.proto
// Valid operators are In, NotIn, Exists and DoesNotExist. optional string operator = 2; // values is an array of string values. If the operator is In or NotIn, // the values array must be non-empty. If the operator is Exists or DoesNotExist, // the values array must be empty. This array is replaced during a strategic // merge patch. // +optional repeated string values = 3; }
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analysis/analysis-api-fir/src/org/jetbrains/kotlin/analysis/api/fir/components/KtFirCallResolver.kt
val leftOperandPsi = deparenthesize(psi.left) ?: return null val compoundAssignKind = psi.getCompoundAssignKind() // handle compound assignment with array access convention if (fir is FirFunctionCall && fir.calleeReference.name == OperatorNameConventions.SET && leftOperandPsi is KtArrayAccessExpression) {
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analysis/analysis-api-fir/src/org/jetbrains/kotlin/analysis/api/fir/diagnostics/KtFirDataClassConverters.kt
) } add(FirErrors.TYPE_PARAMETER_AS_REIFIED_ARRAY.errorFactory) { firDiagnostic -> TypeParameterAsReifiedArrayErrorImpl( firSymbolBuilder.classifierBuilder.buildTypeParameterSymbol(firDiagnostic.a), firDiagnostic as KtPsiDiagnostic, token, ) } add(FirErrors.TYPE_PARAMETER_AS_REIFIED_ARRAY.warningFactory) { firDiagnostic ->
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docs/es/docs/features.md
Pero, todo **simplemente funciona** por defecto. ### Validación * Validación para la mayoría (¿o todos?) los **tipos de datos** de Python incluyendo: * Objetos JSON (`dict`). * JSON array (`list`) definiendo tipos de ítem. * Campos de texto (`str`) definiendo longitudes mínimas y máximas. * Números (`int`, `float`) con valores mínimos y máximos, etc. * Validación para tipos más exóticos como:
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docs/ja/docs/tutorial/body-nested-models.md
{!../../../docs_src/body_nested_models/tutorial007.py!} ``` !!! info "情報" `Offer`は`Item`のリストであり、オプションの`Image`のリストを持っていることに注目してください。 ## 純粋なリストのボディ 期待するJSONボディのトップレベルの値がJSON`array`(Pythonの`list`)であれば、Pydanticモデルと同じように、関数のパラメータで型を宣言することができます: ```Python images: List[Image] ``` 以下のように: ```Python hl_lines="15" {!../../../docs_src/body_nested_models/tutorial008.py!} ```
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docs/zh/docs/tutorial/body-nested-models.md
{!> ../../../docs_src/body_nested_models/tutorial007.py!} ``` !!! info 请注意 `Offer` 拥有一组 `Item` 而反过来 `Item` 又是一个可选的 `Image` 列表是如何发生的。 ## 纯列表请求体 如果你期望的 JSON 请求体的最外层是一个 JSON `array`(即 Python `list`),则可以在路径操作函数的参数中声明此类型,就像声明 Pydantic 模型一样: ```Python images: List[Image] ``` 例如: === "Python 3.9+" ```Python hl_lines="13"
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tensorflow/c/BUILD
"//tensorflow/cc:grad_ops", "//tensorflow/cc/saved_model:signature_constants", "//tensorflow/cc/saved_model:tag_constants", "//tensorflow/compiler/jit", "//tensorflow/core:array_ops_op_lib", "//tensorflow/core:bitwise_ops_op_lib", "//tensorflow/core:control_flow_ops_op_lib", "//tensorflow/core:core_cpu_internal", "//tensorflow/core:direct_session",
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docs/em/docs/tutorial/body-nested-models.md
{!> ../../../docs_src/body_nested_models/tutorial007_py310.py!} ``` !!! info 👀 ❔ `Offer` ✔️ 📇 `Item`Ⓜ, ❔ 🔄 ✔️ 📦 📇 `Image`Ⓜ ## 💪 😁 📇 🚥 🔝 🎚 💲 🎻 💪 👆 ⌛ 🎻 `array` (🐍 `list`), 👆 💪 📣 🆎 🔢 🔢, 🎏 Pydantic 🏷: ```Python images: List[Image] ``` ⚖️ 🐍 3️⃣.9️⃣ & 🔛: ```Python images: list[Image] ``` : === "🐍 3️⃣.6️⃣ & 🔛"
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CONTRIBUTING.md
```bash bazel run //tensorflow/tools/docs:tf_doctest ``` or ```bash bazel run //tensorflow/tools/docs:tf_doctest -- --module=ops.array_ops ``` The `--module` is relative to `tensorflow.python`. #### Debug builds When [building Tensorflow](https://www.tensorflow.org/install/source), passing
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