value: "\n\003a:0\022\010a/Assign\032\010a/read:0"
        value: "\n\003b:0\022\010b/Assign\032\010b/read:0"
        value: "\n\003c:0\022\010c/Assign\032\010c/read:0"
      }
    }
  }
  collection_def {
    key: "variables"
    value {
      bytes_list {
        value: "\n\003a:0\022\010a/Assign\032\010a/read:0"
        value: "\n\003b:0\022\010b/Assign\032\010b/read:0"

  }
  attr {
    key: "shape"
    value {
      shape {
      }
    }
  }
  attr {
    key: "shared_name"
    value {
      s: ""
    }
  }
}
node {
  name: "Variable/Assign"
  op: "Assign"
  input: "Variable"
  input: "Variable/initial_value"
  attr {
    key: "T"
    value {
      type: DT_FLOAT
    }
  }
  attr {
    key: "_class"
    value {
      list {

      if (auto device_attr = op->getAttrOfType<StringAttr>(kDeviceAttr)) {
        // We assign default device to ops with device attribute that is empty.
        if (device_attr.getValue().empty()) {
          op->setAttr(kDeviceAttr, builder.getStringAttr(default_device_));
        }
      } else if (op->getDialect() == tf) {
        // Assign default device to all ops in Tensorflow dialect that do not
        // have device attribute.

// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.

package p

func _() {
	const x = 0
	x /* ERROR "cannot assign to x" */ += 1
	x /* ERROR "cannot assign to x" */ ++

      }
    };

    // Assign a unique ID to each value seen in this function.
    func.walk([&](Operation* op) {
      // For all attached regions, assign ID to the region arguments.
      for (Region& region : op->getRegions()) {
        for (auto region_arg : TF::filter_resources(region.getArguments()))
          assign_id(region_arg);
      }

      // Assign ID for all results.

var p0i1 p0.I = t1(0) // ERROR "does not implement|incompatible"
var p0i2 p1.I = t0(0) // ERROR "does not implement|incompatible"

func foobar() {
	// check that cannot assign one to the other,
	// but can convert.
	v0 = v1 // ERROR "assign|cannot use"
	v1 = v0 // ERROR "assign|cannot use"

	v0 = p0.T(v1)
	v1 = p1.T(v0)

	i0 = i1   // ERROR "cannot use|incompatible"
	i1 = i0   // ERROR "cannot use|incompatible"

  // CHECK-NOT: tf.VariableV2
  // CHECK-NOT: tf.Assign

  // CHECK: [[handle:%.*]] = "tf.VarHandleOp"
  // CHECK-SAME: shared_name = "x"
  // CHECK: "tf.AssignVariableOp"([[handle]], {{%.*}})
  %0 = "tf.VariableV2"() {container = "", shape = #tf_type.shape<>, shared_name = "x"} : () -> tensor<!tf_type.int32ref>
  %1 = "tf.Const"() {value = dense<0> : tensor<i32>} : () -> tensor<i32>

  else
    ReplaceExecute(execute_launch, merged_execute_launch, var_access_info);

  // Remove the assign ops.
  for (const auto& entry : var_access_info.per_resource_info) {
    const auto& info = entry.getSecond();
    if (info.assign) info.assign->erase();
  }

  // Remove the read ops if they have no more uses.
  for (const auto& entry : var_access_info.per_resource_info) {

    private static final String INPUTS_FIELD_NAME = "__inputs__";
    private static final String RULE_FACTORY_FIELD_NAME = "__rule_factory__";
    private static final Token ASSIGN = new Token(Types.ASSIGN, "=", -1, -1);

    private final String scriptSourceDescription;
    private final URI location;
    private final SourceUnit sourceUnit;
    private InputReferences inputs;

	DB.Where(&User{Name: "find or create 3"}).Assign("age", 55).FirstOrCreate(&user4)

	if user4.Age != 55 {
		t.Errorf("Failed to set change to 55, got %v", user4.Age)
	}

	if updatedAt1.Format(time.RFC3339Nano) == user4.UpdatedAt.Format(time.RFC3339Nano) {
		t.Errorf("UpdateAt should be changed when update values with assign")
	}

	DB.Where(&User{Name: "find or create 4"}).Assign(User{Age: 44}).FirstOrCreate(&user4)