def numpy(self):
"""Convert this array to numpy array
Returns
-------
np_arr : numpy.ndarray
The corresponding numpy array.
"""
t = DataType(self.dtype)
shape, dtype = self.shape, self.dtype
old_dtype = dtype
if t.lanes > 1:
shape = shape + (t.lanes, )
t.lanes = 1
dtype = str(t)
if dtype == "int4":
dtype = "int8"
if dtype == "bfloat16":
dtype = "uint16"
np_arr = np.empty(shape, dtype=dtype)
assert np_arr.flags["C_CONTIGUOUS"]
data = np_arr.ctypes.data_as(ctypes.c_void_p)
nbytes = ctypes.c_size_t(np_arr.size * np_arr.dtype.itemsize)
check_call(_LIB.TVMArrayCopyToBytes(self.handle, data, nbytes))
if old_dtype == "int4":
length = np_arr.size
np_arr_ret = np.empty((length, ), dtype="int8")
np_arr = np_arr.reshape((length, ))
old_index = np.bitwise_and(np_arr, 0x0F)
even_index = np.bitwise_and(np_arr >> 4, 0x0F)
np_arr_ret[1::2] = old_index[0:length // 2]
np_arr_ret[0::2] = even_index[0:length // 2]
return np_arr_ret.reshape(shape)
return np_arr
def asnumpy(self):
"""Convert this array to numpy array
Returns
-------
np_arr : numpy.ndarray
The corresponding numpy array.
"""
t = DataType(self.dtype)
shape, dtype = self.shape, self.dtype
if t.lanes > 1:
shape = shape + (t.lanes, )
t.lanes = 1
dtype = str(t)
np_arr = np.empty(shape, dtype=dtype)
assert np_arr.flags['C_CONTIGUOUS']
data = np_arr.ctypes.data_as(ctypes.c_void_p)
nbytes = ctypes.c_size_t(np_arr.size * np_arr.dtype.itemsize)
check_call(_LIB.TVMArrayCopyToBytes(self.handle, data, nbytes))
return np_arr
