absl::Span<const int64_t> shape, const TF_DataType dtype)
      : device_(device),
        tensors_(std::move(tensors)),
        shape_(std::vector<int64_t>(shape.begin(), shape.end())),
        dtype_(dtype) {}
  ParallelTensor(const ParallelDevice& device,
                 std::vector<TensorHandlePtr> tensors, const TF_DataType dtype)
      : device_(device),
        tensors_(std::move(tensors)),

import static java.lang.annotation.ElementType.FIELD;
import static java.lang.annotation.ElementType.METHOD;
import static java.lang.annotation.ElementType.TYPE;
import static java.lang.annotation.RetentionPolicy.RUNTIME;

@Target({FIELD, METHOD, TYPE})
@Retention(RUNTIME)
@Documented
public @interface Typed {
    Class<?>[] value() default {};

        CURRENT = JAVA6;
      }
    }

    abstract Type newArrayType(Type componentType);

    abstract Type usedInGenericType(Type type);

    final ImmutableList<Type> usedInGenericType(Type[] types) {
      ImmutableList.Builder<Type> builder = ImmutableList.builder();
      for (Type type : types) {
        builder.add(usedInGenericType(type));
      }
      return builder.build();
    }

	"sort"
	"strings"
	"sync"

	"github.com/tinylib/msgp/msgp"
)

// Recycler will override the internal reuse in typed handlers.
// When this is supported, the handler will not do internal pooling of objects,
// call Recycle() when the object is no longer needed.
// The recycler should handle nil pointers.
type Recycler interface {
	Recycle()
}

// MSS is a map[string]string that can be serialized.

| Params               | Value                                          |
| :--                  | :--                                            |
| _Type_               | _String_                                       |
| _Length Constraints_ | _Minimum length of 2. Maximum length of 2048._ |
| _Required_           | _Yes_                                          |

Todo **FastAPI** está basado en estos type hints, lo que le da muchas ventajas y beneficios.

Pero, así nunca uses **FastAPI** te beneficiarás de aprender un poco sobre los type hints.

/// note | Nota

Si eres un experto en Python y ya lo sabes todo sobre los type hints, salta al siguiente capítulo.

O Python possui suporte para "dicas de tipo" ou "type hints" (também chamado de "anotações de tipo" ou "type annotations")

Esses **"type hints"** são uma sintaxe especial que permite declarar o <abbr title = "por exemplo: str, int, float, bool">tipo</abbr> de uma variável.

Ao declarar tipos para suas variáveis, editores e ferramentas podem oferecer um melhor suporte.

                               tensorflow::CustomDevice* device,
                               tensorflow::DataType dtype, void* data,
                               TFE_CustomDeviceTensorHandleMethods methods)
      : tensorflow::CustomDeviceTensorHandle(context, device, dtype),
        data_(data),
        methods_(methods) {}

  ~CAPICustomDeviceTensorHandle() override { methods_.deallocator(data_); }

Taran Pelkey <******@****.***> 1716916456 -0400

একই পর্যায়ে, আপনি অটোকমপ্লিট ট্রিগার করতে `Ctrl+Space` চাপেন এবং আপনি দেখতে পান:

<img src="/img/python-types/image02.png">

এর সাথে, আপনি অপশনগুলি দেখে, স্ক্রল করতে পারেন, যতক্ষণ না আপনি এমন একটি অপশন খুঁজে পান যা কিছু মনে পরিয়ে দেয়:

<img src="/img/python-types/image03.png">

## আরও প্রেরণা

এই ফাংশনটি দেখুন, এটিতে ইতিমধ্যে টাইপ হিন্ট রয়েছে:

```Python hl_lines="1"