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"

			// - 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)

  // devices.
  virtual absl::Status Dim(int dim_index, int64_t* dim) const = 0;

  // Returns the device which created the handle.
  virtual const char* DeviceName(absl::Status* status) const = 0;
  // Returns the device where the tensor was placed.
  virtual const char* BackingDeviceName(absl::Status* status) const = 0;
  // Returns the device type which created the handle.

	}
	// 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;

// Create a variable handle with name `variable_name` on a device with name
// `device_name`.
TFE_TensorHandle* CreateVarHandle(TFE_Context* ctx,
                                  const tensorflow::string& device_name,
                                  const tensorflow::string& variable_name);

// Create a variable with value `value` and name `variable_name` on a device
// with name `device_name`.

  }
  absl::Status s;
  const char* device_name = DeviceName(&s);
  if (!s.ok()) {
    device_name = "<error fetching device name>";
  }
  return absl::StrCat("TensorHandle(", value_string, ", shape=", shape_string,
                      ", dtype=", DataType_Name(DataType()), ", device=\"",
                      device_name, "\")");
}

absl::Status ImmediateExecutionTensorHandle::SummarizeValue(

Regression Test
===============

A gradle module for running Regression tests on a device, emulator or JVM.

1. Add an Emulator named `pixel5`, if you don't already have one

```
$ sdkmanager --install "system-images;android-29;google_apis;x86"
$ echo "no" | avdmanager --verbose create avd --force --name "pixel5" --device "pixel" --package "system-images;android-29;google_apis;x86" --tag "google_apis" --abi "x86"
```

            "Not enough storage is available to process this command.", "The media is write protected.", "The device is not ready.",
            "A device attached to the system is not functioning.", "A device attached to the system is not functioning.",
            "The process cannot access the file because it is being used by another process.",

    int CLIENT_UPN_TYPE = 0xC;
    /**
     * Buffer type for client claims information.
     */
    int CLIENT_CLAIMS_TYPE = 0xD;
    /**
     * Buffer type for device information.
     */
    int DEVICE_INFO_TYPE = 0xE;
    /**
     * Buffer type for device claims information.
     */
    int DEVICE_CLAIMS_TYPE = 0xF;

    /**
     * Flag for extra SIDs in logon information.
     */
    int LOGON_EXTRA_SIDS = 0x20;