// "out_tensor".
  void GetTensor(const string& name,
                 std::unique_ptr<tensorflow::Tensor>* out_tensor,
                 TF_Status* out_status) const;

 private:
  // Uses "v2_reader_" to build "var name -> shape" and "var name -> data type"
  // maps; both owned by caller.
  // REQUIRES: "v2_reader_ != nullptr && v2_reader_.status().ok()".

    ],
    visibility = ["//tensorflow/python:__pkg__"],
)

cc_library(
    name = "parallel_device",
    srcs = [":device_sources"],
    hdrs = [":device_headers"],
    visibility = ["//visibility:private"],
    deps = [
        ":parallel_device_lib",
        "//tensorflow/c:c_api",
        "//tensorflow/c:tf_status_helper",
        "//tensorflow/c/eager:c_api",
        "//tensorflow/c/eager:c_api_experimental",

#include "tensorflow/core/platform/file_system_helper.h"
#include "tsl/platform/errors.h"

// TODO(b/139060984): After all filesystems are converted, all calls to
// methods from `FileSystem` will have to be replaced to calls to private
// methods here, as part of making this class a singleton and the only way to
// register/use filesystems.

namespace tensorflow {

using UniquePtrTo_TF_Status =

    }
    op_name += type;
    return TF_NewOperation(
        graph_, op_name.c_str(),
        ::tensorflow::strings::StrCat("name", counter_++).c_str());
  }

  TF_Status* s_;

 private:
  TF_Graph* graph_;
  int counter_;
};

// Helper macros for the TF_OperationGetAttr* tests.
// TODO(ashankar): Use gmock matchers instead?

    return absl::OkStatus();
  }
  ~ReluGradientFunction() override {
    for (auto output : forward_outputs_) {
      if (output) {
        output->Unref();
      }
    }
  }

 private:
  // TODO(b/174778737): Only hold needed outputs.
  vector<AbstractTensorHandle*> forward_outputs_;
};

Status BroadcastMul(AbstractContext* ctx, AbstractTensorHandle* vec,
                    AbstractTensorHandle* mat,

      override {
    return func_record_.GetNewRef();
  }

  // For LLVM style RTTI.
  static bool classof(const AbstractFunction* ptr) {
    return ptr->getKind() == kGraph;
  }

 private:
  core::RefCountPtr<FunctionRecord> func_record_;
};
}  // namespace graph
}  // namespace tracing
}  // namespace tensorflow

  void MarkAsResult(AbstractTensorHandle* gradient) const override;

  void DeleteGradient(AbstractTensorHandle* gradient) const override;

 private:
  // The context where the aggregation op `Add` is to be created.
  AbstractContext* ctx_;
};

// Returns the number of elements in the gradient tensor.

  Status SetOption(const std::string& name,
                   const std::vector<int64_t>& values) override;
  Status SetOption(const std::string& name,
                   const std::vector<double>& values) override;

 private:
  std::unique_ptr<TF_Filesystem> filesystem_;
  std::unique_ptr<const TF_FilesystemOps> ops_;
  std::unique_ptr<const TF_RandomAccessFileOps> random_access_file_ops_;

    name = "Mul_Exp_Grad";
    TF_RETURN_IF_ERROR(
        Mul(ctx, conj_output, grad_outputs[0], &grad_inputs[0], name.c_str()));
    return absl::OkStatus();
  }
  ~ExpGradientFunction() override {}

 private:
  AbstractTensorHandlePtr exp_;
};

class SqrtGradientFunction : public GradientFunction {
 public:
  explicit SqrtGradientFunction(AbstractTensorHandle* sqrt) : sqrt_(sqrt) {
    sqrt->Ref();
  }

    } else {
      return *ft;
    }
  }

  TF_Output output_;

  // For LLVM style RTTI.
  static bool classof(const AbstractTensorHandle* ptr) {
    return ptr->getKind() == kGraph;
  }

 private:
  TF_Graph* graph_;  // For shape inference.
};

// GraphOperation wraps and populates a TF_OperationDescription.
class GraphOperation : public TracingOperation {
 public: