// - mount.Path doesn't match (means cross-device mount), should error out.
			if mount.Path != path {
				crossMounts = append(crossMounts, mount)
			}
		}
	}
	msg := `Cross-device mounts detected on path (%s) at following locations %s. Export path should not have any sub-mounts, refusing to start.`
	if len(crossMounts) > 0 {
		// if paths didn't match then we do have cross-device mount.
		return fmt.Errorf(msg, path, crossMounts)

==============================================================================*/

#ifndef TENSORFLOW_C_EAGER_CUSTOM_DEVICE_TESTUTIL_H_
#define TENSORFLOW_C_EAGER_CUSTOM_DEVICE_TESTUTIL_H_

// A simple logging device to test custom device registration.
#include <memory>

#include "tensorflow/c/c_api.h"
#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/eager/c_api_experimental.h"
#include "tensorflow/c/tf_status.h"

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

  // The device of var_handle0 is local device which is the same before and
  // after cluster update. Remove resource with valid device should succeed.
  TFE_Op* op = TFE_NewOp(ctx, "DestroyResourceOp", status);
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TFE_OpAddInput(op, var_handle0, status);

        "TFE_TensorHandleDevicePointer may not be called on a ",
        handle->TypeString(), " tensor handle.");
    return nullptr;
  }
  tensorflow::Device* device(handle->device());
  if (device != nullptr) {
    status->status = device->Sync();
    if (!status->status.ok()) {
      return nullptr;
    }
  }
  const tensorflow::Tensor* tensor;
  status->status = handle->Tensor(&tensor);

	GOOS=ios GOARCH=amd64 CGO_ENABLED=1 go test archive/tar

The go_ios_exec wrapper uses GOARCH to select the emulator (amd64) or the device (arm64).
However, further setup is required to run tests or programs directly on a device.

First make sure you have a valid developer certificate and have setup your device properly
to run apps signed by your developer certificate. Then install the libimobiledevice and

  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  const DLTensor* dltensor_out = &dlm_out->dl_tensor;
  EXPECT_EQ(dltensor_out->device.device_type, dltensor_in->device.device_type);
  EXPECT_EQ(dltensor_out->device.device_id, dltensor_in->device.device_id);
  EXPECT_EQ(dltensor_out->ndim, dltensor_in->ndim);
  EXPECT_EQ(dltensor_out->dtype.code, dltensor_in->dtype.code);

See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/

// A simple logging device to test custom device registration.
#include <memory>

#include "absl/strings/match.h"
#include "tensorflow/c/c_api.h"
#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/eager/c_api_experimental.h"

## How are drives used for Erasure Code?

MinIO divides the drives you provide into erasure-coding sets of *2 to 16* drives.  Therefore, the number of drives you present must be a multiple of one of these numbers.  Each object is written to a single erasure-coding set.

	}
	// Failure case where we detected successfully cross device mounts.
	{
		absPaths := []string{"/path/to/1"}
		if err = checkCrossDevice(absPaths, mountsPath); err == nil {
			t.Fatal("Expected to fail, but found success")
		}

		mp := []mountInfo{
			{"/dev/2", "/path/to/1/2", "type2", []string{"flags"}, "2", "2"},
		}

  virtual ImmediateExecutionContext* GetContext() const = 0;

  // Following two methods are used to support custom device.
  // Return true if the inputs contain custom device tensor handle. It means
  // that the argument need to be handled by a custom device.
  virtual bool HasCustomDeviceInput() const = 0;

  virtual const tensorflow::OpDef* OpDef() const = 0;