metadata.type = TF_ATTR_STRING;
          } else if (typestr == "list(int)") {
            metadata.type = TF_ATTR_INT;
          } else if (typestr == "list(float)") {
            metadata.type = TF_ATTR_FLOAT;
          } else if (typestr == "list(bool)") {
            metadata.type = TF_ATTR_BOOL;
          } else if (typestr == "list(type)") {
            metadata.type = TF_ATTR_TYPE;

  int error_code = 0;
  if (CopyFileContents(dst_fd, src_fd, size) < 0) error_code = errno;

  close(src_fd);
  close(dst_fd);
  if (error_code != 0) {
    errno = error_code;
    return -1;
  } else {
    return 0;
  }
}

int RemoveSpecialDirectoryEntries(const struct dirent* entry) {
  return strcmp(entry->d_name, ".") != 0 && strcmp(entry->d_name, "..") != 0;
}

    EXPECT_EQ(dltensor_out->shape[i], dltensor_in->shape[i]);
    if (dltensor_out->strides) {
      if (i == dltensor_in->ndim - 1) {
        EXPECT_EQ(dltensor_out->strides[i], 1);
      } else {
        EXPECT_EQ(dltensor_out->strides[i],
                  dltensor_out->shape[i + 1] * dltensor_out->strides[i + 1]);
      }
    }
  }
  const float* data_in = static_cast<const float*>(dltensor_in->data);

      offset += static_cast<uint64_t>(r);
      n -= r;  // safe as 0 < r <= n so n will never underflow
      read += r;
    } else if (r == 0) {
      TF_SetStatus(status, TF_OUT_OF_RANGE, "Read fewer bytes than requested");
      break;
    } else if (errno == EINTR || errno == EAGAIN) {
      // Retry
    } else {
      TF_SetStatusFromIOError(status, errno, posix_file->filename);
      break;
    }
  }

  return read;
}

    if (it != loaded_libs->end()) {
      lib_handle->lib_handle = it->second;
    } else {
      status->status =
          env->LoadDynamicLibrary(library_filename, &lib_handle->lib_handle);
      if (status->status.ok()) {
        TF_CHECK_OK(
            tensorflow::RegisterPluggableDevicePlugin(lib_handle->lib_handle));
      } else {
        delete lib_handle;
        return nullptr;
      }
    }

         TF_TensorByteSize(analytical_tensor));

  for (int64_t j = 0; j < num_elem_analytical; j++) {
    if (abs_error == 0) {
      ASSERT_EQ(manuals[j], danalytical[j]);
    } else {
      ASSERT_NEAR(manuals[j], danalytical[j], abs_error);
    }
  }

  TF_DeleteTensor(analytical_tensor);
  delete[] danalytical;
}

Model BuildGradModel(Model forward, GradientRegistry registry) {

    UnifiedCAPI, CppGradients,
    ::testing::Combine(::testing::Values("graphdef", "mlir"),
                       /*tfrt*/ ::testing::Values(false),
                       /*use_function*/ ::testing::Values(true, false)));
#else
INSTANTIATE_TEST_SUITE_P(
    UnifiedCAPI, CppGradients,
    ::testing::Combine(::testing::Values("graphdef", "mlir"),
                       /*tfrt*/ ::testing::Values(false),

        found_dtype = true;
      } else {
        return false;
      }
    } else if (attr.first == "value") {
      if (attr.second.has_tensor() &&
          attr.second.tensor().int_val_size() == 1 &&
          attr.second.tensor().int_val(0) == v) {
        found_value = true;
      } else {
        return false;
      }
    }
  }

  }

  ctx.device_id = device_id;
  if (device_type == "CPU") {
    ctx.device_type = DLDeviceType::kDLCPU;
  } else if (device_type == "GPU") {
#if TENSORFLOW_USE_ROCM
    ctx.device_type = DLDeviceType::kDLROCM;
#else
    ctx.device_type = DLDeviceType::kDLCUDA;
#endif
  } else {
    status->status = tensorflow::errors::InvalidArgument(
        "Unsupported Device Type for dlpack");
  }

namespace tensorflow {

std::string ImmediateExecutionTensorHandle::DebugString() const {
  PartialTensorShape shape;
  std::string shape_string;
  if (Shape(&shape).ok()) {
    shape_string = shape.DebugString();
  } else {
    shape_string = "<error computing shape>";
  }
  std::string value_string;
  if (!SummarizeValue(value_string).ok()) {
    value_string = "<error computing value>";
  }
  if (value_string.length() > 100) {