string_val: "value"
      }
    }
  }
}
node {
  name: "Const_2"
  op: "Const"
  attr {
    key: "dtype"
    value {
      type: DT_INT64
    }
  }
  attr {
    key: "value"
    value {
      tensor {
        dtype: DT_INT64
        tensor_shape {
        }
        int64_val: -1
      }
    }
  }
}
node {
  name: "result"
  op: "ParseExample"
  input: "serilaized"

                   .WithXlaCluster("cluster_0");

  Output input = ops::Placeholder(root.WithOpName("input"), DT_FLOAT);
  Output begin = ops::Placeholder(root.WithOpName("begin"), DT_INT64);
  Output size = ops::Placeholder(root.WithOpName("size"), DT_INT64);
  Output slice = ops::Slice(root.WithOpName("slice"), input, begin, size);

  std::unique_ptr<Graph> result;
  TF_ASSERT_OK(IncreaseDynamismForAutoJit(root, &result));

      {},
      // Nodes
      {
          {{"two"},
           "Const",
           {},
           {{"value", test::AsScalar<int32>(2)}, {"dtype", DT_INT64}}},
          {{"scale"},
           "Cast",
           {"two"},
           {{"SrcT", DT_INT64}, {"DstT", DT_FLOAT}}},
          {{"y"}, "Mul", {"x", "scale"}, {{"T", DT_FLOAT}}},
      });

  tensorflow::set_tf2_execution(true);
  FunctionDefLibrary flib;

  return {slice_inputs};
}

// Casts `x` to a DT_INT64 if it isn't one already.
Output MakeInt64(const Scope& host_scope, absl::string_view name,
                 const Output& x) {
  return x.type() == DT_INT64
             ? x
             : ops::Cast(host_scope.WithOpName(name, "_s64"), x, DT_INT64);
}

// Returns `slice_inputs` with the index and size inputs cast to DT_INT64.

  inputs.emplace_back("min", 0, DT_FLOAT);
  inputs.emplace_back("max", 0, DT_FLOAT);
  inputs.emplace_back("histogram", 0, DT_INT64);
  inputs.emplace_back("min", 0, DT_FLOAT);
  inputs.emplace_back("max", 0, DT_FLOAT);
  inputs.emplace_back("histogram", 0, DT_INT64);

  const std::string dir = testing::TmpDir();
  const std::string output_file_path = io::JoinPath(dir, "statistics.pbtxt");

"tfdtype$DT_FLOAT"], dense_shapes = [#tf_type.shape<>, #tf_type.shape<>], device = "", num_sparse = 2 : i64, ragged_split_types = [], ragged_value_types = [], resultSegmentSizes = array<i32: 2, 2, 2, 2, 0, 0>, sparse_types = ["tfdtype$DT_STRING", "tfdtype$DT_INT64"]} : (tensor<32x!tf_type.string>, tensor<0x!tf_type.string>, tensor<2x!tf_type.string>, tensor<2x!tf_type.string>, tensor<0x!tf_type.string>, tensor<0xf32>, tensor<0xf32>) -> (tensor<?x2xi64>, tensor<?x2xi64>, tensor<?x!tf_type.string>, tensor<?xi64>,...

node {
  name: "x"
  op: "VarHandleOp"
  device: "/CPU:0"
  attr {
    key: "container"
    value {
      s: "a"
    }
  }
  attr {
    key: "dtype"
    value {
      type: DT_INT64
    }
  }
  attr {
    key: "shape"
    value {
      shape {
      }
    }
  }
  attr {
    key: "shared_name"
    value {
      s: "x"
    }
  }
}
node {

    case DT_INT16:
      *type = builder.getIntegerType(16);
      return absl::OkStatus();
    case DT_INT32:
      *type = builder.getIntegerType(32);
      return absl::OkStatus();
    case DT_INT64:
      *type = builder.getIntegerType(64);
      return absl::OkStatus();
    case DT_UINT8:
      *type = builder.getIntegerType(8, /*isSigned=*/false);
      return absl::OkStatus();
    case DT_UINT16:

// CHECK-NEXT:   value {
// CHECK-NEXT:     i: 0
// CHECK-NEXT:   }
// CHECK-NEXT: }
// CHECK-NEXT: attr {
// CHECK-NEXT:   key: "Tdense"
// CHECK-NEXT:   value {
// CHECK-NEXT:     list {
// CHECK-NEXT:       type: DT_INT64
// CHECK-NEXT:     }
// CHECK-NEXT:   }
// CHECK-NEXT: }
// CHECK-NEXT: attr {
// CHECK:        key: "dense_shapes"
// CHECK-NEXT:   value {
// CHECK-NEXT:     list {
// CHECK-NEXT:       shape {

    case tflite::TensorType_INT32:
      return tensorflow::DT_INT32;
    case tflite::TensorType_UINT32:
      return tensorflow::DT_UINT32;
    case tflite::TensorType_INT64:
      return tensorflow::DT_INT64;
    case tflite::TensorType_STRING:
      return tensorflow::DT_STRING;
    case tflite::TensorType_UINT8:
      return tensorflow::DT_UINT8;
    case tflite::TensorType_UINT16:
      return tensorflow::DT_UINT16;