}

// TODO(lyandy): Investigate supported dtypes (`minval`, `maxval`, `output`) for
// `tf.StatefulUniformInt`. tf2xla kernels support i32, i64, ui32, and ui64
// while TensorFlow CPU/GPU kernels only support i32 and i64.
def TF_StatefulUniformIntOp : TF_Op<"StatefulUniformInt", []> {
  let summary = "Outputs random integers from a uniform distribution.";

  let description = [{

  %60 = "tf.Sub"(%59, %13) {device = ""} : (tensor<i64>, tensor<i64>) -> tensor<i64>

	}
	if float64(i64) != di64 {
		t.Errorf("float64(i64) != di64")
	}
	if float64(i32) != di32 {
		t.Errorf("float64(i32) != di32")
	}
	if float64(i16) != di16 {
		t.Errorf("float64(i16) != di16")
	}
	if float64(i8) != di8 {
		t.Errorf("float64(i8) != di8")
	}
	if float32(u64) != su64 {
		t.Errorf("float32(u64) != su64")
	}
	if float32(u32) != su32 {
		t.Errorf("float32(u32) != su32")
	}

  %3 = "tf.Multinomial"(%0, %1) {device = "/job:localhost/replica:0/task:0/device:CPU:0", seed = 1 : i64, seed2 = 1 : i64} : (tensor<*xf32>, tensor<*xi32>) -> tensor<*xi64>
  %4 = "tf.Multinomial"(%0, %1) {device = "/job:localhost/replica:0/task:0/device:CPU:0", seed = 0 : i64, seed2 = 0 : i64} : (tensor<*xf32>, tensor<*xi32>) -> tensor<*xi64>

    // expected-remark@+1 {{Cost: 2}}
    %28 = "tf.Cast"(%dense_values#0) {Truncate = false, device = "/job:localhost/replica:0/task:0/device:CPU:0"} : (tensor<?xi64>) -> tensor<?xf32>
    // expected-remark@+1 {{Cost: 2}}

  %1 = "tf.LookupTableSizeV2"(%0) {device = ""} : (tensor<!tf_type.resource>) -> tensor<i64>
  %2 = "tf.LookupTableFindV2"(%0, %arg, %default) {device = "/CPU:0"} : (tensor<!tf_type.resource>, tensor<?x!tf_type.string>, tensor<i64>) -> tensor<*xi64>
  func.return %1, %2 : tensor<i64>, tensor<*xi64>
}

}

    tf_executor.fetch %1#0 : tensor<i64>
  }
  func.return %0 : tensor<i64>
}

// CHECK-LABEL: func @testExitOp
// CHECK-SAME: ({{%.+}}: tensor<i64> {tf.device = "/job:localhost/replica:0/task:0/device:TPU:0"})
// CHECK-SAME: -> (tensor<i64> {tf.device = "/job:localhost/replica:0/task:0/device:TPU:0"})
func.func @testExitOp(%arg0: tensor<i64> {tf.device = "/job:localhost/replica:0/task:0/device:TPU:0"}) -> tensor<i64> {
  %0 = tf_executor.graph {

  %ragged_keys: tensor<0x!tf_type.string>,
  %dense_default: tensor<0xi64>) -> tensor<?xi64> {

  %dense_value =
    "tf.ParseExampleV2"(%serialized, %names, %sparse_keys, %dense_keys, %ragged_keys, %dense_default)
    // CHECK: Tdense = [i64]
    // CHECK-SAME: dense_shapes = [#corert.shape<>]
    { device = "/device:CPU:0", num_sparse = 0 : i64, dense_shapes = [#tf_type.shape<>], resultSegmentSizes = array<i32: 0, 0, 0, 1, 0, 0>}

      %out_1, %ctl_2 = tf_executor.island wraps "tf.LookupTableFindV2"(%out_0, %arg0, %out) {device = ""} : (tensor<!tf_type.resource>, tensor<?x!tf_type.string>, tensor<i64>) -> tensor<*xi64>
      tf_executor.fetch %out_1 : tensor<*xi64>
    }
    return %0 : tensor<*xi64>
  }
// Sanity check: The contents of @serving_default is untouched.

    %3 = "tf.XlaCallModule"(%2#0, %0, %1) {Sout = [#tf_type.shape<1x3>], _entry_function = @composite_dot_general_fn_1, _original_entry_function = "composite_dot_general_fn_1", _tfl_quant_trait = "fully_quantizable", dim_args_spec = [], disabled_checks = [], function_list = [], has_token_input_output = false, module = "", platforms = ["CPU"], version = 9 : i64} : (tensor<1x1024xf32>, tensor<1024x3xf32>, tensor<1x3xf32>) ->...