// 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);

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

Brian Zhao <******@****.***> 1600836345 -0700

#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:

    // CHECK-NEXT: "tf.TPUReshardVariables"(%[[V0]], %[[V1]], %[[DEFAULT]], %[[STATE]])
    // CHECK-NEXT: tf_device.return
    func.return
  }
}


// -----

// Tests that the pass does not format variables with other uses.

!tf_res_f32 = tensor<*x!tf_type.resource<tensor<f32>>>
!tf_res_md_f32 = tensor<*x!tf_type.resource<tensor<3x3x1x32xf32>>> // Multi-dim f32

// RUN: tf-opt %s -split-input-file -tfl-analyze-variables-pass --cse | FileCheck %s

// CHECK: module attributes {tfl._legalize_tfl_variables = true}
module {
  func.func @f() -> tensor<*xi32> {
    %0 = "tf.VarHandleOp"() {container = "c", shared_name = "v"} : () -> tensor<*x!tf_type.resource<tensor<*xi32>>>
    %2 = "tf.ReadVariableOp"(%0) {dtype = i32} : (tensor<*x!tf_type.resource<tensor<*xi32>>>) -> tensor<*xi32>
    func.return %2 : tensor<*xi32>
  }
}