from fastapi import Body, FastAPI, status
from fastapi.responses import JSONResponse

app = FastAPI()

items = {"foo": {"name": "Fighters", "size": 6}, "bar": {"name": "Tenders", "size": 3}}


@app.put("/items/{item_id}")
async def upsert_item(
    item_id: str,
    name: str | None = Body(default=None),
    size: int | None = Body(default=None),
):
    if item_id in items:
        item = items[item_id]
        item["name"] = name

}
TF_AbstractTensor* TF_OutputListGet(TF_OutputList* o, int i) {
  return wrap(unwrap(o)->outputs[i]);
}
void TF_OutputListPushBack(TF_OutputList* o, TF_AbstractTensor* tensor,
                           TF_Status* s) {
  unwrap(o)->outputs.push_back(unwrap(tensor));
}

void TF_AbstractOpSetOpType(TF_AbstractOp* op, const char* const op_type,
                            TF_Status* s) {
  tsl::Set_TF_Status_from_Status(

  virtual ImmediateExecutionContext* GetContext() const = 0;

  // Following two methods are used to support custom device.
  // Return true if the inputs contain custom device tensor handle. It means
  // that the argument need to be handled by a custom device.
  virtual bool HasCustomDeviceInput() const = 0;

  virtual const tensorflow::OpDef* OpDef() const = 0;

        "//tensorflow/core:reader_base",
        "//tensorflow/core:script_ops_op_lib",
        "//tensorflow/distribute/experimental/rpc/kernels:rpc_ops",
        "//tensorflow/dtensor/cc:dtensor_device_cc",
        "//tensorflow/dtensor/cc:tensor_layout",
        "//tensorflow/lite/c:common",
        "//tensorflow/lite/core/api",
        "//tensorflow/lite/delegates/flex:delegate",

from fastapi import FastAPI

app = FastAPI()

items = {}


@app.on_event("startup")
async def startup_event():
    items["foo"] = {"name": "Fighters"}
    items["bar"] = {"name": "Tenders"}


@app.get("/items/{item_id}")
async def read_items(item_id: str):

    op_->node_builder.Attr(attr_name, func_name);
    return absl::OkStatus();
  }
  absl::Status SetAttrTensor(const char* attr_name,
                             AbstractTensorInterface* tensor) override {
    return tensorflow::errors::Unimplemented(
        "SetAttrTensor has not been implemented yet.");
  }
  absl::Status SetAttrStringList(const char* attr_name,

                                        "example": {
                                            "id": "bar",
                                            "value": "The bar tenders",
                                        },
                                    }
                                },
                            },
                            "422": {

        200: {
            "description": "Item requested by ID",
            "content": {
                "application/json": {
                    "example": {"id": "bar", "value": "The bar tenders"}
                }
            },
        },
    },
)
async def read_item(item_id: str):
    if item_id == "foo":
        return {"id": "foo", "value": "there goes my hero"}
    else:

  TFE_TensorHandle* h0_task0 = TestMatrixTensorHandle(ctx);
  TFE_TensorHandle* h1_task0 = TestMatrixTensorHandle(ctx);
  std::vector<TFE_TensorHandle*> handles_task0;
  if (heavy_load_on_streaming_rpc) {
    // Send 50 tensor copy requests to simulate that there have been some RPC
    // requests been enqueued.
    for (int i = 0; i < 50; ++i) {
      handles_task0.push_back(TestMatrixTensorHandle(ctx));
    }
  }

                                 ForwardOperation*);
absl::Status SetAttrTensor(AbstractOperation*, const char* attr_name,
                           AbstractTensorInterface* tensor, ForwardOperation*);
absl::Status SetAttrStringList(AbstractOperation*, const char* attr_name,
                               const void* const* values, const size_t* lengths,