case stateJSDqStr, stateJSSqStr, stateJSTmplLit, stateJSRegexp:
		return true
	}
	return false
}

// delim is the delimiter that will end the current HTML attribute.
type delim uint8

//go:generate stringer -type delim

const (
	// delimNone occurs outside any attribute.
	delimNone delim = iota
	// delimDoubleQuote occurs when a double quote (") closes the attribute.
	delimDoubleQuote

  attr {
    key: "output_shapes"
    value {
      list {
        shape {
          dim {
            size: 1
          }
          dim {
            size: 8
          }
        }
        shape {
          dim {
            size: 2
          }
          dim {
            size: -1
          }
          dim {
            size: 16
          }
        }
        shape {

  %0 = "tf.ReadVariableOp"(%arg0) {_output_shapes = ["tfshape$dim { size: 1 } dim { size: 3 }"], device = "/device:CPU:0", dtype = !tf_type.quint8} : (tensor<!tf_type.resource<tensor<1x3x!tf_type.quint8>>>) -> tensor<1x3x!tf_type.quint8>

  // CHECK: tf.ReadVariableOp
  // CHECK-SAME: dtype = !corert.quint16

  // CHECK: device = "xpu"
  %1 = "tf.MatMul"(%arg0, %0) {T = f32, _output_shapes = ["tfshape$dim { size: 3 } dim { size: 3 }"], device = "", transpose_a = false, transpose_b = false} : (tensor<3x1xf32>, tensor<1x3xf32>) -> tensor<3x3xf32>
  // CHECK: device = "cpu"
  %2 = "tf.Relu"(%1) {T = f32, _output_shapes = ["tfshape$dim { size: 3 } dim { size: 3 }"], device = "cpu"} : (tensor<3x3xf32>) -> tensor<3x3xf32>
  // CHECK: device = "xpu"

	l.pos += Pos(len(leftComment))
	x := strings.Index(l.input[l.pos:], rightComment)
	if x < 0 {
		return l.errorf("unclosed comment")
	}
	l.pos += Pos(x + len(rightComment))
	delim, trimSpace := l.atRightDelim()
	if !delim {
		return l.errorf("comment ends before closing delimiter")
	}
	i := l.thisItem(itemComment)
	if trimSpace {
		l.pos += trimMarkerLen
	}
	l.pos += Pos(len(l.rightDelim))

  %2 = "tf.MatMul"(%arg0, %1) {T = f32, _output_shapes = ["tfshape$dim { size: 3 } dim { size: 3 }"], device = "/device:CPU:0", transpose_a = false, transpose_b = false} : (tensor<3x1xf32>, tensor<1x3xf32>) -> tensor<3x3xf32>
  // CHECK-NEXT: [[r1:%.*]] = tfrt_fallback_async.executeop {{.*}} "tf.BiasAdd"([[r0]], [[result]])

        value {
          list {
            shape {
              dim {
                size: -1
              }
              dim {
                size: 1
              }
            }
            shape {
              dim {
                size: -1
              }
              dim {
                size: 1
              }
            }
          }

tuple_value: {
    values: {
    tuple_value: {
        values: {
        tensor_spec_value: {
            name : "x"
            shape: {
            dim: {
                size: 1
            }
            dim: {
                size: 10
            }
            }
            dtype: DT_FLOAT
        }
        }
    }
    }
    values: {
    dict_value: {
    }
    }

"tfdtype$DT_FLOAT", "tfdtype$DT_FLOAT"], Tout = ["tfdtype$DT_FLOAT", "tfdtype$DT_FLOAT", "tfdtype$DT_FLOAT", "tfdtype$DT_FLOAT", "tfdtype$DT_FLOAT"], _output_shapes = ["tfshape$dim { size: 9 } dim { size: 10 }", "tfshape$dim { size: -1 } dim { size: 9 } dim { size: 10 }", "tfshape$dim { size: 8 } dim { size: 10 }", "tfshape$dim { size: 8 } dim { size: 10 }", "tfshape$"], _read_only_resource_inputs = [], config = "", config_proto = "\0A\07\0A\03CPU\10\01\0A\07\0A\03GPU\10\002\02J\008\01", device = "", executor_type...

    key: "dtype"
    value {
      type: DT_DOUBLE
    }
  }
  attr {
    key: "value"
    value {
      tensor {
        dtype: DT_DOUBLE
        tensor_shape {
          dim {
            size: 2
          }
          dim {
            size: 3
          }
        }