// CHECK-NEXT:  name: "min_runtime_version",
  // CHECK-NEXT:  buffer: 5
  // CHECK-NEXT:  } ]
  // CHECK-NEXT:  signature_defs: [ ]
  // CHECK-NEXT:}

  %cst = "tfl.no_value"() {value = unit} : () -> none
  %0:2 = "tfl.fully_connected"(%arg0, %arg1, %cst) {fused_activation_function = "NONE", keep_num_dims = false, weights_format = "SHUFFLED4x16INT8"} : (tensor<40x37xf32>, tensor<40x37xf32>, none) -> (tensor<40x40xf32>, tensor<40x40xf32>)

  // CHECK: "tf.Identity"
  // CHECK-SAME: {device = "/TPU:0"}
  %id0 = "tf.Identity"(%arg0) : (!tf_res) -> !tf_res
  %read = "tf.ReadVariableOp"(%id0) : (!tf_res) -> tensor<32xf32>
  %cst = arith.constant dense<3.0> : tensor<32xf32>
  %add = "tf.AddV2"(%read, %cst) : (tensor<32xf32>, tensor<32xf32>) -> tensor<32xf32>
  "tf.AssignVariableOp"(%arg0, %add) : (!tf_res, tensor<32xf32>) -> ()
  func.return
}

}
func.func private @XlaCallModule_aten.avg_pool2d.default.impl_2(%arg0: tensor<1x1x1x8xf32>) -> tensor<1x1x1x4xf32>

// CHECK-LABEL: avg_pool2d_3
// CHECK: %cst = arith.constant dense<[0, 2, 3, 1]> : tensor<4xi32>
// CHECK: %0 = "tfl.transpose"(%arg0, %cst) : (tensor<1x1x1x8xf32>, tensor<4xi32>) -> tensor<1x1x8x1xf32>
// CHECK{LITERAL}: %cst_0 = arith.constant dense<[[0, 0], [0, 0], [1, 1], [0, 0]]> : tensor<4x2xi32>

  %cst = "tf.Const"() {value = dense<5.000000e+00> : tensor<f32>} : () -> tensor<f32>
  %0 = "tf.TPUCompilationResult"() {_tpu_compilation_status = "cluster_tpu_function", device = ""} : () -> tensor<!tf_type.string>

  %index = arith.constant 0 : index
  %cst = arith.constant 1 : i64
  %eq = arith.cmpi eq, %n, %cst : i64
  %v1 = tfr.get_element %values[%index] : (!tfr.tensor_list, index) -> !tfr.tensor
  %res = scf.if %eq -> !tfr.tensor {
    scf.yield %v1 : !tfr.tensor
  } else {
    %step = arith.index_cast %cst : i64 to index
    %end = arith.index_cast %n : i64 to index

			GotConn: func(info httptrace.GotConnInfo) {
				rt.conn = info.Conn.(*transportDialTesterConn)
			},
		})
		req, _ := http.NewRequestWithContext(ctx, "POST", dt.cst.ts.URL, pr)
		req.Header.Set("Content-Type", "text/plain")
		rt.res, rt.err = dt.cst.tr.RoundTrip(req)
		dt.t.Logf("RoundTrip %v: done (err:%v)", rt.roundTripID, rt.err)
		close(rt.done)
	}()
	return rt
}

  %0 = arith.constant 3.0: f32
  %t = tfr.constant f32 -> !tfr.attr
  %cst = tfr.call @tf__const(%0, %t) : (f32, !tfr.attr) -> !tfr.tensor
  %4 = "tfr.cast"(%cst) : (!tfr.tensor) -> tensor<f32>
  func.return %4 : tensor<f32>

// CHECK: %[[cst:.*]] = "tf.Const"() <{value = dense<3.000000e+00> : tensor<f32>}> : () -> tensor<f32>
// CHECK: return %[[cst]] : tensor<f32>
}

// CHECK-LABEL: attribute_propagate

  %cst = "tf.Const"() {__op_key = 2: i32, device = "/device:CPU:0", value = dense<0> : tensor<i32>} : () -> tensor<i32>
  // Predicate should be inlined.
  // CHECK-NEXT: tf_mlrt.predicate
  // CHECK-NEXT: mlrt.cond
  // CHECK-NEXT: tf_mlrt.predicate

  // CHECK-NEXT: mlrt.while

// CHECK-NEXT:    name: "min_runtime_version",
// CHECK-NEXT:    buffer: 5
// CHECK-NEXT:  } ]
// CHECK-NEXT:  signature_defs: [ ]
// CHECK-NEXT:}

  %cst = "tfl.no_value"() {value = unit} : () -> none
  %0 = "tfl.transpose_conv"(%arg0, %arg1, %arg2, %cst) {padding = "SAME", stride_h = 2 : i32, stride_w = 2 : i32, fused_activation_function = "NONE"} : (tensor<4xi32>, tensor<32x4x4x128xf32>, tensor<1x32x42x128xf32>, none) -> tensor<1x64x84x32xf32>

  %index = arith.constant 0 : index
  %cst = arith.constant 1 : i64
  %eq = arith.cmpi "eq", %n, %cst : i64
  %v1 = tfr.get_element %values[%index] : (!tfr.tensor_list, index) -> !tfr.tensor
  %res = scf.if %eq -> !tfr.tensor {
    scf.yield %v1 : !tfr.tensor
  } else {
    %step = arith.index_cast %cst : i64 to index
    %end = arith.index_cast %n : i64 to index