def _get_data_from_ndarray(array):
if str(array.dtype).startswith('int'):
dtype = Storage.INT
elif str(array.dtype).startswith('float'):
dtype = Storage.FLOAT
elif str(array.dtype).startswith('bool'):
dtype = Storage.BOOL
else:
raise NotImplementedError()
data = trtc.device_vector_from_numpy(array.astype(dtype).ravel())
return data, array.shape, dtype
def __setitem__(self, key, value):
if hasattr(value, 'data') and hasattr(value, 'shape') and len(value.shape) != 0:
if isinstance(value, np.ndarray):
vector = trtc.device_vector_from_numpy(value)
trtc.Copy(vector, self.data)
else:
trtc.Copy(value.data, self.data)
else:
if isinstance(value, int):
dvalue = trtc.DVInt64(value)
elif isinstance(value, float):
dvalue = PrecisionResolver.get_floating_point(value)
else:
raise TypeError("Only Storage, int and float are supported.")
trtc.Fill(self.data, dvalue)
return self
def upload(self, data):
trtc.Copy(
trtc.device_vector_from_numpy(data.astype(self.dtype).ravel()),
self.data
)
def ravel(self, other):
if isinstance(other, Storage):
trtc.Copy(other.data, self.data)
else:
self.data = trtc.device_vector_from_numpy(other.ravel())
