const e int = 1.00000001 // ERROR "constant truncated to integer|truncated to int|truncated"

  // CHECK-DAG: %[[HALF_RANGE:.*]] = "tf.Const"() <{value = dense<1.280000e+02> : tensor<f32>}>
  // CHECK-DAG: %[[C255:.*]] = "tf.Const"() <{value = dense<2.550000e+02> : tensor<f32>}>
  // CHECK-DAG: %[[CAST:.*]] = "tf.Cast"(%arg0) <{Truncate = false}>
  // CHECK-DAG: %[[SHIFT:.*]] = "tf.AddV2"(%[[CAST]], %[[HALF_RANGE]])
  // CHECK-DAG: %[[DRANGE:.*]] = "tf.Sub"(%arg2, %arg1)
  // CHECK-DAG: %[[SCALE:.*]] = "tf.Div"(%[[DRANGE]], %[[C255:.*]])

// Timestamp returns the Time as a new Timestamp value.
func (m *MicroTime) ProtoMicroTime() *Timestamp {
	if m == nil {
		return &Timestamp{}
	}

	// truncate precision to microseconds to match JSON marshaling/unmarshaling
	truncatedNanoseconds := time.Duration(m.Time.Nanosecond()).Truncate(time.Microsecond)
	return &Timestamp{
		Seconds: m.Time.Unix(),
		Nanos:   int32(truncatedNanoseconds),
	}
}

	assert(f == f3div2, "f == f3div2");

	i = f3div2;	// ERROR "truncate"
	assert(i == c3div2, "i == c3div2 from f3div2");
	assert(i != f3div2, "i != f3div2");	// ERROR "truncate"

	const g float64 = 1.0;
	i = g;  // ERROR "convert|incompatible|cannot"

	const h float64 = 3.14;
	i = h;  // ERROR "convert|incompatible|cannot"
	i = int(h);	// ERROR "truncate|cannot convert"

	const _ int = 1e64645       // ERROR "integer too large|floating-point constant truncated to integer|exponent too large|truncated"

	const _ uint64 = 1e646456992 // ERROR "integer too large|floating-point constant truncated to integer|exponent too large|truncated"
	const _ uint32 = 1e64645699  // ERROR "integer too large|floating-point constant truncated to integer|exponent too large|truncated"

John Howard <******@****.***> 1709052916 -0800

	_ int64 = 1e-1000    // ERROR "1e\-1000 truncated|.* truncated to int64|truncated"
	_ int64 = 1e-10000   // ERROR "1e\-10000 truncated|.* truncated to int64|truncated"
	_ int64 = 1e-100000  // ERROR "1e\-100000 truncated|.* truncated to int64|truncated"
	_ int64 = 1e-1000000 // ERROR "1e\-1000000 truncated|.* truncated to int64|truncated"
)

const (
	_ int64 = -1e10000000 // ERROR "integer too large|truncated to int64|truncated"

  %4 = "tf.ClipByValue"(%3, %cst, %cst_9) : (tensor<1x100x100x1xi32>, tensor<i32>, tensor<i32>) -> tensor<1x100x100x1xi32>
  %5 = "tf.Cast"(%4) {Truncate = false} : (tensor<1x100x100x1xi32>) -> tensor<1x100x100x1xi8>
  %6 = "tf.Cast"(%5) {Truncate = false} : (tensor<1x100x100x1xi8>) -> tensor<1x100x100x1xf32>

  %7 = "tf.Sub"(%6, %cst_4) : (tensor<1x100x100x1xf32>, tensor<f32>) -> tensor<1x100x100x1xf32>

    %cst = "tf.Const"() {value = dense<1024> : tensor<i32>} : () -> tensor<i32>
    %0:2 = "tf_device.launch"() ({
	  %1 = "tf.Cast"(%arg0) {Truncate = false} : (tensor<2048xi64>) -> tensor<2048xi32>
	  %2 = "tf.Cast"(%arg1) {Truncate = false} : (tensor<2048xi64>) -> tensor<2048xi32>

    %cst_0 = "tf.Const"() {value = dense<0.0157480314> : tensor<f32>} : () -> tensor<f32>
    %0 = "tf.Identity"(%cst) : (tensor<2x1024xi8>) -> tensor<2x1024xi8>
    %1 = "tf.Cast"(%0) {Truncate = false} : (tensor<2x1024xi8>) -> tensor<2x1024xf32>