#ifndef TENSORFLOW_C_EAGER_ABSTRACT_OP_ATTRS_H_
#define TENSORFLOW_C_EAGER_ABSTRACT_OP_ATTRS_H_

#include "absl/container/inlined_vector.h"
#include "tensorflow/core/framework/attr_value.pb.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/platform/status.h"

namespace tensorflow {

// Attributes of an op.
class AbstractOpAttrs {
 protected:

#ifndef TENSORFLOW_C_C_OP_REQUIRES_H_
#define TENSORFLOW_C_C_OP_REQUIRES_H_

#include "tensorflow/core/platform/macros.h"

namespace tensorflow {

// Convenience macros for asserting and handling exceptional conditions, for
// C structs, including `TF_OpKernelContext`, `TF_Status`, etc. This is analogus
// to the macros in tensorflow/core/framework/op_requires.h. This is provided

// the TFE_Op structure.
typedef struct TFE_Op TFE_Op;

namespace tensorflow {

DEFINE_CONVERSION_FUNCTIONS(tensorflow::ImmediateExecutionOperation, TFE_Op);
DEFINE_CONVERSION_FUNCTIONS(tensorflow::ImmediateExecutionOperation*, TFE_Op*);

}  // namespace tensorflow

typedef struct TFE_OpAttrs TFE_OpAttrs;

typedef struct TFE_Context TFE_Context;
typedef struct TFE_Op TFE_Op;

namespace tensorflow {
DEFINE_CONVERSION_FUNCTIONS(tensorflow::AbstractOpAttrs, TFE_OpAttrs);

// Set an AttrValue on the op. Doesn't handle the list types.
void SetOpAttrValueScalar(TFE_Context* ctx, TFE_Op* op,
                          const tensorflow::AttrValue& default_value,

---
name: TensorFlow Lite Op Request
about: Use this template for reporting Lite ops you are using or missing
labels: 'comp:lite'

---

**System information**
- OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
- TensorFlow installed from (source or binary):
- TensorFlow version (or github SHA if from source):


**Provide the text output from tflite_convert**

```
# Copy and paste here
```

//     the additional sanity checks there seem unnecessary;
typedef struct TFE_Op TFE_Op;

TF_CAPI_EXPORT extern TFE_Op* TFE_NewOp(TFE_Context* ctx,
                                        const char* op_or_function_name,
                                        TF_Status* status);
TF_CAPI_EXPORT extern void TFE_DeleteOp(TFE_Op* op);

// Returns the op or function name `op` will execute.
//

void TF_AbstractOpSetOpType(TF_AbstractOp* op, const char* const op_type,
                            TF_Status* s) {
  tsl::Set_TF_Status_from_Status(
      s, unwrap(op)->Reset(op_type,
                           /*raw_device_name=*/nullptr));
}

void TF_AbstractOpSetOpName(TF_AbstractOp* op, const char* const op_name,
                            TF_Status* s) {
  TracingOperation* tracing_op = dyn_cast<TracingOperation>(unwrap(op));

  // parent_op->Unref();
}
Status TapeOperation::Reset(const char* op, const char* raw_device_name) {
  forward_op_.op_name = op;
  forward_op_.attrs.Reset(op);
  forward_op_.inputs.clear();
  forward_op_.outputs.clear();
  return parent_op_->Reset(op, raw_device_name);
}
const string& TapeOperation::Name() const { return parent_op_->Name(); }
const string& TapeOperation::DeviceName() const {

  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());

  // Build an abstract operation.
  auto* add_op = TF_NewAbstractOp(graph_ctx);
  TF_AbstractOpSetOpType(add_op, "Add", status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
  TF_AbstractOpSetOpName(add_op, "my_add", status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());

  TFE_DeleteContextOptions(opts);

  TFE_Op* var_op = TFE_NewOp(ctx, "VarHandleOp", status);
  TFE_OpSetAttrType(var_op, "dtype", TF_INT64);
  TFE_OpSetAttrShape(var_op, "shape", {}, 0, status);
  const TFE_OpAttrs* attributes = TFE_OpGetAttrs(var_op);

  TFE_Op* copy_op = TFE_NewOp(ctx, "VarHandleOp", status);
  TFE_OpSetAttrType(copy_op, "dtype", TF_FLOAT);
  TFE_OpAddAttrs(copy_op, attributes);
  unsigned char is_list = 0;