def empty(shape, dtype="float32", ctx=context(1, 0)):
"""Create an empty array given shape and device
Parameters
----------
shape : tuple of int
The shape of the array
dtype : type or str
The data type of the array.
ctx : TVMContext
The context of the array
Returns
-------
arr : tvm.nd.NDArray
The array tvm supported.
"""
shape = c_array(tvm_shape_index_t, shape)
ndim = ctypes.c_int(len(shape))
handle = TVMArrayHandle()
dtype = DataType(dtype)
check_call(
_LIB.TVMArrayAlloc(shape, ndim, ctypes.c_int(dtype.type_code),
ctypes.c_int(dtype.bits), ctypes.c_int(dtype.lanes),
ctx.device_type, ctx.device_id,
ctypes.byref(handle)))
return _make_array(handle, False, False)
def numpyasarray(np_data):
"""Return a TVMArray representation of a numpy array."""
data = np_data
assert data.flags["C_CONTIGUOUS"]
arr = TVMArray()
shape = c_array(tvm_shape_index_t, data.shape)
arr.data = data.ctypes.data_as(ctypes.c_void_p)
arr.shape = shape
arr.strides = None
arr.dtype = DataType(np.dtype(data.dtype).name)
arr.ndim = data.ndim
# CPU device
arr.device = device(1, 0)
return arr, shape
