attributes {tf._input_shapes = [#tf_type.shape<1x3>, #tf_type.shape<*>], tf.signature.is_stateful} {
  // CHECK-DAG: [[handle1:%.*]] = "tf.VarHandleOp"() <{{{.*}}, shared_name = "variable1"}>
  // CHECK-DAG: [[handle2:%.*]] = "tf.VarHandleOp"() <{{{.*}}, shared_name = "variable2"}>
  // CHECK: "tf.ReadVariableOp"([[handle1]])
  // CHECK: "tf.ReadVariableOp"([[handle2]])

// VariableApplyConfiguration represents an declarative configuration of the Variable type for use
// with apply.
type VariableApplyConfiguration struct {
	Name       *string `json:"name,omitempty"`
	Expression *string `json:"expression,omitempty"`
}

// VariableApplyConfiguration constructs an declarative configuration of the Variable type for use with
// apply.
func Variable() *VariableApplyConfiguration {
	return &VariableApplyConfiguration{}
}

// VariableApplyConfiguration represents an declarative configuration of the Variable type for use
// with apply.
type VariableApplyConfiguration struct {
	Name       *string `json:"name,omitempty"`
	Expression *string `json:"expression,omitempty"`
}

// VariableApplyConfiguration constructs an declarative configuration of the Variable type for use with
// apply.
func Variable() *VariableApplyConfiguration {
	return &VariableApplyConfiguration{}
}

  // CHECK: "tfl.pseudo_const"() <{value = dense<0> : tensor<3x2xi32>}> {tfl.is_variable} : () -> tensor<3x2xi32>
  %0 = "tfl.pseudo_const"() {value = dense<0> : tensor<3x2xi32>, tfl.is_variable} : () -> tensor<3x2xi32> loc("variable")
  func.return %0 : tensor<3x2xi32>

/**
 * A variable library entry.
 */
public class Variable extends AbstractLibrary {
    public Variable(Node node, FileReferenceFactory fileReferenceFactory) {
        super(node, fileReferenceFactory);
        setSourcePath(fileReferenceFactory.fromVariablePath((String) node.attribute("sourcepath")));
    }

    public Variable(FileReference library) {
        super(library);
    }

// VariableApplyConfiguration represents an declarative configuration of the Variable type for use
// with apply.
type VariableApplyConfiguration struct {
	Name       *string `json:"name,omitempty"`
	Expression *string `json:"expression,omitempty"`
}

// VariableApplyConfiguration constructs an declarative configuration of the Variable type for use with
// apply.
func Variable() *VariableApplyConfiguration {
	return &VariableApplyConfiguration{}
}

  func.return %0 : tensor<3x2xi32>
}

// CHECK:      {
// CHECK-NEXT:     version: 3,
// CHECK-NEXT:     operator_codes: [ ],
// CHECK-NEXT:     subgraphs: [ {
// CHECK-NEXT:       tensors: [ {
// CHECK-NEXT:         shape: [ 3, 2 ],
// CHECK-NEXT:         type: INT32,
// CHECK-NEXT:         name: "variable",
// CHECK-NEXT:         quantization: {
// CHECK-EMPTY:

  """Three vars (one in a sub-module) and compute method."""

  def __init__(self):
    self.x = variables.Variable(1.0, name="variable_x")
    self.y = variables.Variable(2.0, name="variable_y")
    self.child = module.Module()
    self.child.z = variables.Variable(3.0, name="child_variable")
    self.child.c = ops.convert_to_tensor(5.0)

  @def_function.function(input_signature=[

local g = import './g.libsonnet';
local var = g.dashboard.variable;

{
  datasource:
    var.datasource.new('datasource', 'prometheus'),

  cluster:
    var.query.new('cluster')
    + var.query.withDatasourceFromVariable(self.datasource)
    + var.query.queryTypes.withLabelValues(
      'cluster',
      'process_cpu_seconds_total',
    )
    + var.query.withRefresh('time')
    + var.query.selectionOptions.withMulti()

  fetch->set_name("myfetch");
  tf2xla::Variable* variable = config.add_variable();
  variable->set_node_name("myvar_readonly");
  variable->mutable_shape()->add_dim()->set_size(1);
  variable->set_type(DT_FLOAT);
  variable->set_readonly(true);
  tf2xla::Variable* variable2 = config.add_variable();
  variable2->set_node_name("myvar");
  variable2->mutable_shape()->add_dim()->set_size(1);