tvm.runtime.ndarray

Runtime NDArray API

class tvm.runtime.ndarray.NDArray

Lightweight NDArray class of TVM runtime.

Strictly this is only an Array Container (a buffer object) No arthimetic operations are defined. All operations are performed by TVM functions.

The goal is not to re-build yet another array library. Instead, this is a minimal data structure to demonstrate how can we use TVM in existing project which might have their own array containers.

asnumpy()

Convert this array to numpy array. This API will be deprecated in TVM v0.8 release. Please use numpy instead.

copyfrom(source_array)

Perform a synchronous copy from the array.

Parameters:

source_array (array_like) – The data source we should like to copy from.

Returns:

arr – Reference to self.

Return type:

NDArray

copyto(target, mem_scope=None)

Copy array to target

Parameters:
  • target (NDArray) – The target array to be copied, must have same shape as this array.

  • mem_scope (Optional[str]) – The memory scope of the array.

property device

Device of this array

property dtype

Type of this array

numpy()

Convert this array to numpy array

Returns:

np_arr – The corresponding numpy array.

Return type:

numpy.ndarray

same_as(other)

Check object identity equality

Parameters:

other (object) – The other object to compare to

Returns:

same – Whether other is same as self.

Return type:

bool

tvm.runtime.ndarray.array(arr, device=cpu(0), mem_scope=None)

Create an array from source arr.

Parameters:
  • arr (numpy.ndarray) – The array to be copied from

  • device (Device, optional) – The device to create the array

  • mem_scope (Optional[str]) – The memory scope of the array

Returns:

ret – The created array

Return type:

NDArray

tvm.runtime.ndarray.cl(dev_id=0)

Construct a OpenCL device

Parameters:

dev_id (int, optional) – The integer device id

Returns:

dev – The created device

Return type:

Device

tvm.runtime.ndarray.cpu(dev_id=0)

Construct a CPU device

Parameters:

dev_id (int, optional) – The integer device id

Returns:

dev – The created device

Return type:

Device

tvm.runtime.ndarray.cuda(dev_id=0)

Construct a CUDA GPU device

Parameters:

dev_id (int, optional) – The integer device id

Returns:

dev – The created device

Return type:

Device

tvm.runtime.ndarray.device(dev_type, dev_id=0)

Construct a TVM device with given device type and id.

Parameters:
  • dev_type (int or str) – The device type mask or name of the device.

  • dev_id (int, optional) – The integer device id

Returns:

dev – The corresponding device.

Return type:

tvm.runtime.Device

Examples

Device can be used to create reflection of device by string representation of the device type.

assert tvm.device("cpu", 1) == tvm.cpu(1)
assert tvm.device("cuda", 0) == tvm.cuda(0)
tvm.runtime.ndarray.empty(shape, dtype='float32', device=cpu(0), mem_scope=None)

Create an empty array given shape and device

Parameters:
  • shape (Union[tvm.runtime.ShapeTuple, Sequence[SupportsInt]]) – The shape of the array.

  • dtype (type or str) – The data type of the array.

  • device (Device) – The device of the array.

  • mem_scope (Optional[str]) – The memory scope of the array.

Returns:

arr – The array tvm supported.

Return type:

tvm.nd.NDArray

tvm.runtime.ndarray.ext_dev(dev_id=0)

Construct a extension device

Parameters:

dev_id (int, optional) – The integer device id

Returns:

dev – The created device

Return type:

Device

Note

This API is reserved for quick testing of new device by plugin device API as ext_dev.

tvm.runtime.ndarray.from_dlpack(dltensor)

Produces an array from an object with __dlpack__ method or a DLPack tensor w/o memory copy. Retreives the underlying DLPack tensor’s pointer to create an array from the data. Removes the original DLPack tensor’s destructor as now the array is responsible for destruction.

Parameters:

dltensor (object with __dlpack__ attribute or a DLPack capsule) –

Returns:

arr – The array view of the tensor data.

Return type:

tvm.nd.NDArray

tvm.runtime.ndarray.gpu(dev_id=0)

Construct a CUDA GPU device

deprecated:: 0.9.0 Use tvm.cuda() instead.

Parameters:

dev_id (int, optional) – The integer device id

Returns:

dev – The created device

Return type:

Device

tvm.runtime.ndarray.hexagon(dev_id=0)

Construct a Hexagon device

Parameters:

dev_id (int, optional) – The integer device id

Returns:

dev – The created device

Return type:

Device

tvm.runtime.ndarray.metal(dev_id=0)

Construct a metal device

Parameters:

dev_id (int, optional) – The integer device id

Returns:

dev – The created device

Return type:

Device

tvm.runtime.ndarray.mtl(dev_id=0)

Construct a metal device

Parameters:

dev_id (int, optional) – The integer device id

Returns:

dev – The created device

Return type:

Device

tvm.runtime.ndarray.numpyasarray(np_data)

Return a TVMArray representation of a numpy array.

tvm.runtime.ndarray.opencl(dev_id=0)

Construct a OpenCL device

Parameters:

dev_id (int, optional) – The integer device id

Returns:

dev – The created device

Return type:

Device

tvm.runtime.ndarray.rocm(dev_id=0)

Construct a ROCM device

Parameters:

dev_id (int, optional) – The integer device id

Returns:

dev – The created device

Return type:

Device

tvm.runtime.ndarray.vpi(dev_id=0)

Construct a VPI simulated device

Parameters:

dev_id (int, optional) – The integer device id

Returns:

dev – The created device

Return type:

Device

tvm.runtime.ndarray.vulkan(dev_id=0)

Construct a Vulkan device

Parameters:

dev_id (int, optional) – The integer device id

Returns:

dev – The created device

Return type:

Device

tvm.runtime.ndarray.webgpu(dev_id=0)

Construct a webgpu device.

Parameters:

dev_id (int, optional) – The integer device id

Returns:

dev – The created device

Return type:

Device