/**
 * 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);
    }

    "BUILD_ID",
    // Used by some tests to be ignored in specific build
    "BUILD_TYPE_ID",
    "JPROFILER_HOME",

    "LANG",
    "LANGUAGE",
    // It is possible to have many LC_xxx variables for different aspects of the locale. However, LC_ALL overrides all of them, and it is what CI uses.
    "LC_ALL",
    "LC_CTYPE",

    "JDK_10",
    "JDK_10_0",
    "JDK_10_0_x64",
    "JDK_10_x64",
    "JDK_11",

// 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()

def tfvariable(_):
  x = variables.Variable([1000.0], name='x', shape=[1])
  old_x = x.value()
  with ops.control_dependencies([old_x]):
    new_x = x.assign_add([42.0])
  array_ops_stack.stack([old_x, new_x], name='result')


def tfvariable_sequential_updates(_):
  x = variables.Variable(1.0, name='x')
  y = variables.Variable(1.0, name='y')
  updates = control_flow_ops.no_op()

#include "tensorflow/compiler/mlir/tensorflow/transforms/tf_passes.h.inc"

// A pass that converts readonly reference variables to the corresponding
// resource variables.
//
// It converts (VariableV2 -> Identity) to (VarHandle -> ReadVariable).
//
// For the background, this pass is a part of hoisting VariableV2 ops by
// re-using the pipeline for hoisting (VarHandle -> ReadVariable) cases, which
//  can be done by the following passes:

  func.return
}

// -----

// Test case: No named location found on VariableV2 op.

func.func @f() {
  // expected-error @+1 {{'tf.VariableV2' op expects variable name in '_class' attribute, but got ["unrelated_class"]}}
  %val0 = "tf.VariableV2"() {_class = ["unrelated_class"], container = "", device = "", shape = #tf_type.shape<96>, shared_name = ""} : () -> tensor<96x!tf_type.f32ref>

Adam Cogdell <******@****.***> 1684357973 -0700