t.Errorf("Values(%v) = %v, want %v", m, got, want)
		}
	}
}

func TestInsert(t *testing.T) {
	got := map[int]int{
		1: 1,
		2: 1,
	}
	Insert(got, func(yield func(int, int) bool) {
		for i := 0; i < 10; i += 2 {
			if !yield(i, i+1) {
				return
			}
		}
	})

	want := map[int]int{
		1: 1,
		2: 1,
	}
	for i, v := range map[int]int{
		0: 1,
		2: 3,
		4: 5,
		6: 7,
		8: 9,

async def get_db():
    db = DBSession()
    try:
        yield db
    finally:

import java.util.concurrent.Executors
import java.util.concurrent.TimeUnit

class DefaultFileSystemAccessConcurrencyTest extends AbstractFileSystemAccessTest {

    def "parallel invalidation yields correct results"() {
        def dir = temporaryFolder.createDir("some/deep/hierarchy")
        (1..1000).each {
            def subdir = dir.file(it)
            subdir.file("in-dir.txt").createFile()
        }

        %4 = "tf.Mul" (%arg1, %2) {device = "y"}: (tensor<f32>, tensor<f32>) -> tensor<f32>
        "tf.Yield"(%4) : (tensor<f32>) -> ()
      }, {
        // CHECK: device = "/device:TPU_REPLICATED_CORE:0"
        %5 = "tf.Div" (%arg1, %2) {device = "/device:TPU_REPLICATED_CORE:0"} : (tensor<f32>, tensor<f32>) -> tensor<f32>
        "tf.Yield"(%5) : (tensor<f32>) -> ()

      %reduce_next =  tfr.call @tf__risc_add_dummy(%reduce_iter, %v) : (!tfr.tensor, !tfr.tensor) -> !tfr.tensor
      scf.yield %reduce_next : !tfr.tensor
    }
    scf.yield %reduce : !tfr.tensor
  }
  tfr.return %res : !tfr.tensor
}

tfr.func @tf__my_add_n_(!tfr.tensor_list<N,T>, i64 {tfr.name="N"}) -> !tfr.tensor attributes{N,T}

     & ⤴️ 👥 🔐 ⚫️ `finally` 🍫.

    👉 🌌 👥 ⚒ 💭 💽 🎉 🕧 📪 ⏮️ 📨. 🚥 📤 ⚠ ⏪ 🏭 📨.

    ✋️ 👆 💪 🚫 🤚 ➕1️⃣ ⚠ ⚪️➡️ 🚪 📟 (⏮️ `yield`). 👀 🌖 [🔗 ⏮️ `yield` & `HTTPException`](dependencies/dependencies-with-yield.md#yield-httpexception){.internal-link target=_blank}

& ⤴️, 🕐❔ ⚙️ 🔗 *➡ 🛠️ 🔢*, 👥 📣 ⚫️ ⏮️ 🆎 `Session` 👥 🗄 🔗 ⚪️➡️ 🇸🇲.

from fastapi import FastAPI
from fastapi.responses import StreamingResponse

app = FastAPI()


async def fake_video_streamer():
    for i in range(10):
        yield b"some fake video bytes"


@app.get("/")
async def main():

      CHECK-NEXT: %[[if:.*]] = scf.if %pred -> (!tfr.tensor) {
      CHECK-NEXT:   arith.constant true
      CHECK-NEXT:   scf.yield %x : !tfr.tensor
      CHECK-NEXT: } else {
      CHECK-NEXT:   arith.constant true
      CHECK-NEXT:   scf.yield %y : !tfr.tensor
      CHECK-NEXT:   }
      CHECK-NEXT:   tfr.return %if_stmt : !tfr.tensor
      CHECK-NEXT: }

        rng.uniform(low=0.0, high=1.0, size=static_input_shape).astype(
            np.float32
        )
    )

    def data_gen() -> repr_dataset.RepresentativeDataset:
      for _ in range(100):
        yield {
            'input_tensor': rng.uniform(
                low=0.0, high=1.0, size=static_input_shape
            ).astype(np.float32)
        }

    dataset_path = self.create_tempfile('tfrecord').full_path

some_file_path = "large-video-file.mp4"
app = FastAPI()


@app.get("/")
def main():
    def iterfile():  # (1)
        with open(some_file_path, mode="rb") as file_like:  # (2)
            yield from file_like  # (3)