* <a href="https://github.com/Rebilly/ReDoc" class="external-link" target="_blank">ReDoc</a>

Esses dois foram escolhidos por serem bem populares e estáveis, mas fazendo uma pesquisa rápida, você pode encontrar dúzias de interfaces alternativas adicionais para OpenAPI (assim você poderá utilizar com **FastAPI**).

///

### Flask REST frameworks

#                                                     ------

suggest.popular.word.seed=0
suggest.popular.word.tags=
suggest.popular.word.fields=
suggest.popular.word.excludes=
suggest.popular.word.size=10
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suggest.popular.word.query.freq=10
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suggest.field.contents=_default
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* <a href="https://github.com/Rebilly/ReDoc" class="external-link" target="_blank">ReDoc</a>

Ces deux-là ont été choisis parce qu'ils sont populaires et stables, mais en faisant une recherche rapide, vous pourriez trouver des dizaines d'alternatives supplémentaires pour OpenAPI (que vous pouvez utiliser avec **FastAPI**).

///

### Frameworks REST pour Flask

field, [`Policies`](/pkg/crypto/x509/#Certificate.Policies), which supports
certificate policy OIDs with components larger than 31 bits. By default this
field is only used during parsing, when it is populated with policy OIDs, but
not used during marshaling. It can be used to marshal these larger OIDs, instead
of the existing PolicyIdentifiers field, by using the
[`x509usepolicies` setting.](/pkg/crypto/x509/#CreateCertificate).

    float grad_data[1];
    memcpy(&grad_data[0], TF_TensorData(grad_tensor),
           TF_TensorByteSize(grad_tensor));
    TF_DeleteTensor(grad_tensor);
    dtheta_approx[i] = grad_data[0];
  }

  // Populate *numerical_grad with the data from dtheta_approx.
  TF_RETURN_IF_ERROR(TestTensorHandleWithDims<float, TF_FLOAT>(
      ctx, dtheta_approx.data(), theta_dims.data(), num_dims, numerical_grad));
  TF_DeleteTensor(theta_tensor);

  // once unless the tape is persistent) and produces the gradient of the target
  // tensors with respect to the source tensors. The output gradients are used
  // if not empty and not null. The result is populated with one tensor per
  // target element.
  absl::Status ComputeGradient(
      AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> targets,
      absl::Span<AbstractTensorHandle* const> sources,

                                    "Encountered while creating function '",
                                    fn_name, "'");
    output_tensors->emplace_back(node, idx);
  }
  return absl::OkStatus();
}

// Populates `body_nodes` with the nodes that will become function's body.
// Performs various checks.
absl::Status ComputeBodyNodes(
    const TF_Graph* fn_body, const char* fn_name, int num_opers,
    const TF_Operation* const* opers,

  static bool classof(const AbstractTensorHandle* ptr) {
    return ptr->getKind() == kGraph;
  }

 private:
  TF_Graph* graph_;  // For shape inference.
};

// GraphOperation wraps and populates a TF_OperationDescription.
class GraphOperation : public TracingOperation {
 public:
  explicit GraphOperation(TF_Graph* g) : TracingOperation(kGraph), g_(g) {}
  void Release() override { delete this; }

## Previous tools

### <a href="https://www.djangoproject.com/" class="external-link" target="_blank">Django</a>

It's the most popular Python framework and is widely trusted. It is used to build systems like Instagram.

/// info

Pour envoyer de la donnée, vous devriez utiliser : `POST` (le plus populaire), `PUT`, `DELETE` ou `PATCH`.

Envoyer un corps dans une requête `GET` a un comportement non défini dans les spécifications, cela est néanmoins supporté par **FastAPI**, seulement pour des cas d'utilisation très complexes/extrêmes.