namespace {

using ::mlir::tfg::mangling_util::PrintShortTextProto;

const char kAttributePrefix[] = "tf.";
const char kDataTypePrefix[] = "tfdtype$";
const char kTensorShapePrefix[] = "tfshape$";
const char kTensorPrefix[] = "tftensor$";

}  // namespace

string MangleAttributeName(absl::string_view str) {
  return absl::StrCat(kAttributePrefix, str);
}

bool IsMangledAttributeName(absl::string_view str) {

TF_Tensor* TF_TensorMaybeMove(TF_Tensor* t) {
  return t->tensor->CanMove() ? t : nullptr;
}

void TF_DeleteTensor(TF_Tensor* t) {
  if (t == nullptr) {
    return;
  }

  if (t->tensor) {
    t->tensor->Release();
  }

  delete t;
}

TF_DataType TF_TensorType(const TF_Tensor* t) {
  return static_cast<TF_DataType>(t->tensor->Type());

// Return the length of the tensor in the "dim_index" dimension.
// REQUIRES: 0 <= dim_index < TF_NumDims(tensor)
TF_CAPI_EXPORT extern int64_t TF_Dim(const TF_Tensor* tensor, int dim_index);

// Return the size of the underlying data in bytes.
TF_CAPI_EXPORT extern size_t TF_TensorByteSize(const TF_Tensor*);

// Return a pointer to the underlying data buffer.
TF_CAPI_EXPORT extern void* TF_TensorData(const TF_Tensor*);

// passed to or returned from C functions *by pointer*. Otherwise, changes to
// its internal structure will break the C API's binary interface.
typedef struct TF_Tensor {
  tensorflow::AbstractTensorInterface* tensor;
} TF_Tensor;

class TF_ManagedBuffer : public tensorflow::TensorBuffer {
 public:
  TF_ManagedBuffer(void* data, size_t len,
                   void (*deallocator)(void* data, size_t len, void* arg),

    TF_OpKernelContext* ctx, int input_index, int value_index, int Op,
    int isVariantType,
    void (*copyFunc)(TF_OpKernelContext* ctx, TF_Tensor* source,
                     TF_Tensor* dest),
    void (*updateFunc)(TF_OpKernelContext* ctx, TF_Tensor* tensor,
                       TF_Tensor* value, int Op),
    TF_Status* status);

// Expose higher level temporary variable operator for Pluggable vendors to

      return $tensor_list_or_flow_in[$max_iterations]
  }];

  let arguments = (ins
    TF_Tensor:$max_iterations,
    Variadic<TF_Tensor>:$tensor_list_or_flow_in,
    Variadic<TF_Tensor>:$invariant_args,
    FlatSymbolRefAttr:$body_fn,
    I32Attr:$num_tensor_list_or_flow_in
  );

  let results = (outs
     Variadic<TF_Tensor>:$result
  );

namespace {

// Operators used to create a std::unique_ptr for TF_Tensor and TF_Status.
struct TFTensorDeleter {
  void operator()(TF_Tensor* tf_tensor) const { TF_DeleteTensor(tf_tensor); }
};

struct TFStatusDeleter {
  void operator()(TF_Status* tf_status) const { TF_DeleteStatus(tf_status); }
};

// Struct that wraps TF_Tensor and TF_Status to delete once out of scope.

              !tfrt_fallback.tf_tensor, !tfrt_fallback.tf_tensor, !tfrt_fallback.tf_tensor, !tfrt_fallback.tf_tensor, !tfrt_fallback.tf_tensor, !tfrt_fallback.tf_tensor, !tfrt_fallback.tf_tensor,

// CHECK: [[body_res:%.*]]:2 = tfrt.call @while_body_add2([[ch]], [[arg]]) : (!tfrt.chain, !tfrt_fallback.tf_tensor) -> (!tfrt.chain, !tfrt_fallback.tf_tensor)
// CHECK: [[pred_res:%.*]]:2 = tfrt.call @"while_cond_lt9/tfrt_predicate"([[body_res]]#0, [[body_res]]#1) : (!tfrt.chain, !tfrt_fallback.tf_tensor) -> (!tfrt.chain, i1)

def TFTensorType : DialectType<Fallback_Dialect,
    CPred<"$_self.isa<::tfrt::fallback::TFTensorType>()">, "!tfrt_fallback.tf_tensor type">,
    BuildableType<"$_builder.getType<::tfrt::fallback::TFTensorType>()"> {
  let description = [{
    `!tfrt_fallback.tf_tensor type` represents a tensorflow::Tensor.
  }];
}

// This corresponds to tensorflow::Allocator.
def TFAllocatorType : DialectType<Fallback_Dialect,