// Copyright 2026 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// ==============================================================================

syntax = "proto3";

package tensorflow.tf2xla;

import "xla/xla_data.proto";
import "tensorflow/core/framework/tensor.proto";
import "tensorflow/core/framework/tensor_shape.proto";
import "tensorflow/core/framework/types.proto";

option cc_enable_arenas = true;
option java_outer_classname = "Tf2XlaProtos";
option java_multiple_files = true;
option java_package = "org.tensorflow.tf2xla";

message XlaArgumentProto {
  int32 kind = 1;
  DataType type = 2;
  message Shape {
    oneof shape {
      TensorShapeProto tensor_shape = 1;
      xla.ShapeProto xla_shape = 2;
    }
  }
  optional Shape shape = 3;
  TensorProto constant_value = 4;
  optional TensorProto value_bound = 5;
  optional TensorProto value_dynamism = 6;
  string name = 7;
  string node_name = 8;
  int32 resource_kind = 9;
  bool initialized = 10;
  bool fast_mem = 11;
  int64 max_array_size = 12;
  repeated string tensor_array_gradients = 13;
  bool is_same_data_across_replicas = 14;
  bool requires_broadcast = 15;
}