const int64_t* dims, int num_dims,
                                  TF_Status* status) {
  std::vector<int64_t> dimvec(num_dims);
  for (int i = 0; i < num_dims; ++i) {
    dimvec[i] = static_cast<int64_t>(dims[i]);
  }

  if (ctx == nullptr) {
    status->status = tensorflow::errors::InvalidArgument("Invalid Context");
    return nullptr;
  }

    status->status =
        tensorflow::errors::InvalidArgument(device_name, " unknown device.");
    return nullptr;
  }
  std::vector<int64_t> dimvec(num_dims);
  for (int i = 0; i < num_dims; ++i) {
    dimvec[i] = static_cast<int64_t>(dims[i]);
  }

  // TODO(apassos) do we need to wrap the deallocator here to make sure to sync
  // the device?
  TF_ManagedBuffer* buf =

        } catch (GeneralSecurityException e) {
            throw new GeneralSecurityException("Checksum failed while decrypting.");
        }
        byte[] ivec = new byte[8];
        IvParameterSpec params = new IvParameterSpec(ivec);

        SecretKeySpec skSpec = new SecretKeySpec(key.getEncoded(), "DES");
        SecretKey sk = skSpec;

        cipher.init(Cipher.DECRYPT_MODE, sk, params);

First, you might want to see the basic ways to [help FastAPI and get help](help-fastapi.md).

## Developing

If you already cloned the [fastapi repository](https://github.com/fastapi/fastapi) and you want to deep dive in the code, here are some guidelines to set up your environment.

### Install requirements

Create a virtual environment and install the required packages with [`uv`](https://github.com/astral-sh/uv):

<div class="termy">

## Twittea sobre **FastAPI** { #tweet-about-fastapi }

[Twittea sobre **FastAPI**](https://x.com/compose/tweet?text=I'm loving @fastapi because... https://github.com/fastapi/fastapi) y dime a mí y a otros por qué te gusta. 🎉

Me encanta escuchar cómo se está utilizando **FastAPI**, qué te ha gustado, en qué proyecto/empresa lo estás usando, etc.

## Vota por FastAPI { #vote-for-fastapi }