//
// This serves as a factory for creating `AbstractOperation`s and for
// registering traced functions.
// Operations creation within a context can only be executed in that context
// (for now at least).
// Implementations of the context may contain some state e.g. an execution
// environment, a traced representation etc.
class AbstractContext {
 protected:

#include "tensorflow/core/platform/intrusive_ptr.h"
#include "tensorflow/core/platform/refcount.h"
#include "tensorflow/core/platform/status.h"

namespace tensorflow {

class FunctionRecord;

// A traced function: this hides the complexity of converting the serialized
// representation between various supported formats e.g. FunctionDef and Mlir
// function.
class AbstractFunction : public core::RefCounted {
 protected:

                                      unneeded_gradients, out_gradients,
                                      absl::MakeSpan(in_gradients));
      if (!persistent_) {
        trace.backward_function_deleter(trace.backward_function);
      }
      if (!s.ok()) {
        return s;
      }
    } else {
      if (!persistent_) {
        trace.backward_function_deleter(trace.backward_function);

TF_CAPI_EXPORT TFE_TensorHandle* TFE_NewTensorHandleFromTensor(
    TFE_Context* ctx, TF_Tensor* t, TF_Status* status);

// Create a packed TensorHandle with the given list of TensorHandles.
// If `handles` are on the same device, assign the same device to the packed
// handle; if `handles` are on different deivces, assign a CompositeDevice to
// it.
TF_CAPI_EXPORT extern TFE_TensorHandle* TFE_CreatePackedTensorHandle(

  // Same as `AddFunctionDef`, but additionally saves the `stack_traces` under
  // the key of the function definition name (to be retrieved during function
  // instantiation).
  virtual Status AddFunctionDefWithStackTraces(
      const FunctionDef& fdef, const StackTracesMap& stack_traces) = 0;

  // Find and return a added function by its name.