TFE_ContextDevicePlacementPolicy device_placement_policy{
      TFE_DEVICE_PLACEMENT_SILENT};
  // If true, use TFRT backend
  bool use_tfrt = false;
  // Whether to run elementary eager ops wrapped in a call op.
  bool run_eager_op_as_function = false;
  // Whether to rewrite jit_compile functions.
  bool jit_compile_rewrite = false;
};

#define TENSORFLOW_C_EAGER_TRACING_UTILS_H_

#include "tensorflow/c/eager/abstract_operation.h"

namespace tensorflow {
namespace tracing {
Status MaybeSetOpName(AbstractOperation*, const char* op_name);
}  // namespace tracing
}  // namespace tensorflow

// the state of the ForwardOperation and call the tape as appropriate.
// These APIs are mainly to facilitate testing and are subject to change.

// Records the op name in the `ForwardOperation`.
Status Reset(AbstractOperation*, const char* op, const char* raw_device_name,
             ForwardOperation*);

// Records the inputs in the `ForwardOperation`.

                   "        type: DT_FLOAT"
                   "      }"
                   "    }"
                   "    node_def {"
                   "      name: 'matmul'"
                   "      op: 'MatMul'"
                   "      input: 'a'"
                   "      input: 'b'"
                   "      device: '",
                   matmul_device, "'",
                   "      attr {"

  if (TF_GetCode(s) != TF_OK) return;
  const char* operation_name = TFE_OpGetName(original_op, s);
  if (TF_GetCode(s) != TF_OK) return;
  const TFE_OpAttrs* attributes = TFE_OpGetAttrs(original_op);

  TFE_Op* op(TFE_NewOp(context, operation_name, s));
  if (TF_GetCode(s) != TF_OK) return;
  TFE_OpAddAttrs(op, attributes);
  TFE_OpSetDevice(op, dev->underlying_device.c_str(), s);

// Return an add op multiplying `a` by `b`.
TFE_Op* AddOp(TFE_Context* ctx, TFE_TensorHandle* a, TFE_TensorHandle* b);

// Return a matmul op multiplying `a` by `b`.
TFE_Op* MatMulOp(TFE_Context* ctx, TFE_TensorHandle* a, TFE_TensorHandle* b);

// Return an identity op.
TFE_Op* IdentityOp(TFE_Context* ctx, TFE_TensorHandle* a);

// Return a shape op fetching the shape of `a`.

  }

  AbstractOperationPtr check_numerics_op(ctx->CreateOperation());
  ForwardOperation forward_op;
  Status s = Reset(check_numerics_op.get(), "CheckNumerics",
                   /*raw_device_name=*/nullptr, &forward_op);
  ASSERT_EQ(errors::OK, s.code()) << s.message();
  if (isa<TracingOperation>(check_numerics_op.get())) {
    s = dyn_cast<TracingOperation>(check_numerics_op.get())
            ->SetOpName("check_numerics");

#define TENSORFLOW_C_EXPERIMENTAL_GRADIENTS_ARRAY_GRAD_H_

#include "tensorflow/c/eager/gradients.h"

namespace tensorflow {
namespace gradients {
GradientFunction* IdentityNRegisterer(const ForwardOperation& op);
}  // namespace gradients
}  // namespace tensorflow

inspected and debugged and it is intended to be used during the development
phase.

As part of the differences that make Eager mode easier to debug, the [shape
inference
functions](https://www.tensorflow.org/guide/create_op#define_the_op_interface)
are skipped, and any checks implemented inside the shape inference code are not
executed.

The security impact of skipping those checks should be low, since the attack

      }
      grad_inputs[i] = grad_input;
    }
    return absl::OkStatus();
  }
  ~IdentityNGradientFunction() override {}
};
}  // namespace

GradientFunction* IdentityNRegisterer(const ForwardOperation& op) {
  return new IdentityNGradientFunction;
}

}  // namespace gradients