indices_type.getDimSize(1) != 1)
    return false;

  // Checks the `params_type` is equal to `output_type`. If not equal, we
  // cannot replace the scatter_nd/gather_nd op with `params`.
  if (params_type != output_type) return false;

  // Checks the value in `indices` is from 0 to n-1.
  int cur_value = 0;
  for (const auto &v : indices.getValues<APInt>()) {

				Port:    echo.Port{ServicePort: 12346, Protocol: protocol.HTTP},
				Timeout: time.Millisecond * 100,
				Check:   check.OK(),
			},
		})
	}
}

func externalNameCases(t TrafficContext) {
	calls := func(name string, checks ...echo.Checker) []TrafficCall {
		checks = append(checks, check.OK())
		ch := []TrafficCall{}
		for _, c := range t.Apps.A {

}
// CHECK-LABEL: pad_with_interior_padding
// CHECK-SAME: %[[ARG0:.+]]: tensor<2x3x!quant.uniform<i8:f32, 2.000000e+00:-1>>
// CHECK-SAME: %[[ARG1:.+]]: tensor<!quant.uniform<i8:f32, 2.000000e+00:-1>>
// CHECK: %[[PADDING:.+]] = arith.constant
// CHECK{LITERAL}: dense<[[0, 2], [1, 1]]> : tensor<2x2xi32>
// CHECK: %[[INTERIOR:.+]] = arith.constant
// CHECK{LITERAL}: dense<[1, 2]> : tensor<2xi32>

	CheckI("&sp", &sp, 2)

	wv := Twordv(3)
	CheckI("wv", wv, 3)
	CheckI("&wv", &wv, 3)

	wp := Twordp(4)
	CheckI("&wp", &wp, 4)

	bv := Tbigv([2]uintptr{5, 6})
	CheckI("bv", bv, 11)
	CheckI("&bv", &bv, 11)

	bp := Tbigp([2]uintptr{7, 8})
	CheckI("&bp", &bp, 15)

	t4 := Tm4{}
	t3 := Tm3{&t4}
	t2 := Tm2{&t3}
	t1 := Tm1{t2}
	CheckI("t4", t4, 40)
	CheckI("&t4", &t4, 40)

						errs = appendErrors(errs, check(len(src.Principals) != 0, "From.Principals"))
						errs = appendErrors(errs, check(len(src.NotPrincipals) != 0, "From.NotPrincipals"))
						errs = appendErrors(errs, check(len(src.RequestPrincipals) != 0, "From.RequestPrincipals"))
						errs = appendErrors(errs, check(len(src.NotRequestPrincipals) != 0, "From.NotRequestPrincipals"))
					}
				}

}

// NOTE: Assertions have been autogenerated by utils/generate-test-checks.py
// CHECK-LABEL:   func @embedding(
// CHECK-SAME:              [[VAL_0:%.*]]: tensor<*xf32>, [[VAL_1:%.*]]: tensor<*xi32>) -> tensor<*xf32>

// CHECK-LABEL:   attributes  {tf._implements = "embedding_lookup", tf._reference = "mlir"} {

  // CHECK-LABEL: func @nodep_single_cluster_multiple_ops_outside_compilation
  func.func @nodep_single_cluster_multiple_ops_outside_compilation() -> () {
     // CHECK: "tf_device.parallel_execute"
     // CHECK-NEXT: "tf_device.launch"
     // CHECK-NEXT: "tf.B"
     // CHECK-NEXT: "tf.C"
     // CHECK-NEXT: "tf.D"
     // CHECK-NOT: _xla_outside_compilation
     // CHECK: "tf_device.cluster"

  // CHECK: %0 = "tf.Bitcast"(%arg0) : (tensor<8x16x32x64xf32>) -> tensor<8x16x32x64x2xi16>
  // CHECK: %1 = "tf.Bitcast"(%arg0) {device = "/job:localhost/replica:0/task:0/device:GPU:0"} : (tensor<8x16x32x64xf32>) -> tensor<8x16x32x64xi32>
  // CHECK: %2 = "tf.Identity"(%0) : (tensor<8x16x32x64x2xi16>) -> tensor<8x16x32x64x2xi16>
  // CHECK: return %1, %2
}

// CHECK-LABEL: testSameCastType

      }
      // CHECK: tf_executor.Merge
      // CHECK-SAME: : (tensor<32x?x4xf32>, tensor<?x?x?xf32>) ->
      // CHECK: tf_executor.Switch
      // CHECK-SAME: : (tensor<32x?x4xf32>, tensor<i1>) ->
      // CHECK: tf_executor._SwitchN
      // CHECK-SAME: : tensor<?x?x?xf32>
      // CHECK: tf_executor.Enter
      // CHECK-SAME: : (tensor<32x?x4xf32>) ->
      // CHECK: tf_executor.Exit

// CHECK-LABEL:reverse_v2_i64
// CHECK:  "tfl.cast"
// CHECK:  "tfl.reverse_v2"
// CHECK:  return
}

func.func @matrix_diag(%arg0: tensor<8x16xf32>) -> tensor<8x16x16xf32> {
  %0 = "tf.MatrixDiag"(%arg0) : (tensor<8x16xf32>) -> tensor<8x16x16xf32>
  func.return %0 : tensor<8x16x16xf32>

// CHECK-LABEL:matrix_diag
// CHECK:  "tfl.matrix_diag"(%arg0) : (tensor<8x16xf32>) -> tensor<8x16x16xf32>