- nihpo
  - armand-sauzay
  - databento-bot
  - databento
  - nanram22
  - Flint-company
  - porter-dev
  - fern-api
  - ndimares
  - svixhq
  - Alek99
  - codacy
  - zanfaruqui
  - scalar
  - bump-sh
  - andrew-propelauth
  - svix
  - zuplo-oss
  - zuplo
  - Kong
  - speakeasy-api
  - jess-render
  - blockbee-io
  - liblaber
  - render-sponsorships
  - renderinc

  Run({{func_feed, Int32Tensor(3)}}, func_op, 2 + 3);
  VerifyFDef(
      {"add_0", "scalar"}, M({{"feed1"}, {"feed2"}}), M({{"add"}}),
      {{"feed1", "add_0:0"}, {"feed2", "add_0:1"}, {"add_0:sum:0", "add"}},
      {{"^scalar", "add_0:2"}});
}

TEST_F(CApiFunctionTest, ControlDependencyOutsideOfBody) {
  /*
   *                  |  |    scalar
   *                  |  |    .

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    url: https://github.com/BoostryJP
  - login: acsone
    avatarUrl: https://avatars.githubusercontent.com/u/7601056?v=4
    url: https://github.com/acsone
- - login: scalar
    avatarUrl: https://avatars.githubusercontent.com/u/301879?v=4
    url: https://github.com/scalar
  - login: Trivie
    avatarUrl: https://avatars.githubusercontent.com/u/8161763?v=4
    url: https://github.com/Trivie
- - login: takashi-yoneya

// APIs specific to Eager modes
// -----------------------------------------------------------------------------

// Temporary APIs till we figure out how to create scalar valued Eager
// tensors and how to get value out of eager abstract tensors.
TF_AbstractTensor* TF_CreateAbstractTensorFromEagerTensor(TFE_TensorHandle* t,
                                                          TF_Status* s);

&y.s) return s } // Subtract sets s = x - y mod l, and returns s. func (s *Scalar) Subtract(x, y *Scalar) *Scalar { // s = -1 * y + x mod l fiatScalarSub(&s.s, &x.s, &y.s) return s } // Negate sets s = -x mod l, and returns s. func (s *Scalar) Negate(x *Scalar) *Scalar { // s = -1 * x + 0 mod l fiatScalarOpp(&s.s, &x.s) return s } // Multiply sets s = x * y mod l, and returns s. func (s *Scalar) Multiply(x, y *Scalar) *Scalar { // s = x * y + 0 mod l fiatScalarMul(&s.s, &x.s, &y.s) return s } // Set...

&y.s) return s } // Subtract sets s = x - y mod l, and returns s. func (s *Scalar) Subtract(x, y *Scalar) *Scalar { // s = -1 * y + x mod l fiatScalarSub(&s.s, &x.s, &y.s) return s } // Negate sets s = -x mod l, and returns s. func (s *Scalar) Negate(x *Scalar) *Scalar { // s = -1 * x + 0 mod l fiatScalarOpp(&s.s, &x.s) return s } // Multiply sets s = x * y mod l, and returns s. func (s *Scalar) Multiply(x, y *Scalar) *Scalar { // s = x * y + 0 mod l fiatScalarMul(&s.s, &x.s, &y.s) return s } // Set...

// Abstract interface to a context.
//
// A context is responsible for creating key objects such as Tensors,
// TensorHandles & Operations.
class ImmediateExecutionContext : public AbstractContext {
 public:
  // Optimized scalar creation functions
  virtual AbstractTensorInterface* CreateInt64Scalar(int64_t value) = 0;
  virtual AbstractTensorInterface* CreateUint64Scalar(uint64 value) = 0;

// Platform-specific implementation to return an unused port. (This should used
// in tests only.)
TF_CAPI_EXPORT int TF_PickUnusedPortOrDie(void);

// Fast path method that makes constructing a single scalar tensor require less
// overhead and copies.
TF_CAPI_EXPORT extern TFE_TensorHandle* TFE_NewTensorHandleFromScalar(
    TF_DataType data_type, void* data, size_t len, TF_Status* status);

You can use **type annotations** the same way you would for input data in function **parameters**, you can use Pydantic models, lists, dictionaries, scalar values like integers, booleans, etc.

{* ../../docs_src/response_model/tutorial001_01_py310.py hl[16,21] *}

FastAPI will use this return type to:

* **Validate** the returned data.