def create_future_from_scalar(self, scalar):
if scalar.valid:
if ty.is_string_dtype(scalar.dtype):
size = len(scalar._value)
buf = struct.pack(
f"iiQ{size}s",
scalar.valid,
ty.encode_dtype(scalar.dtype),
size,
scalar._value.encode("utf-8"),
)
else:
fmt = ty.to_format_string(scalar.dtype.storage_dtype)
buf = struct.pack(
"ii" + fmt,
scalar.valid,
ty.encode_dtype(scalar.dtype),
scalar._value,
)
else:
buf = struct.pack("iiQ", scalar.valid,
ty.encode_dtype(scalar.dtype), 0)
fut = Future()
fut.set_value(self._runtime, buf, len(buf))
return PandasFuture(self, fut, scalar.dtype, True)
def _get_tunable(self, tunable_id, cast):
f = Future(
legion.legion_runtime_select_tunable_value(
self._runtime,
self._context,
tunable_id,
self.mapper_id,
0,
))
return cast(struct.unpack_from("i", f.get_buffer(4))[0])
def create_future(self, value, dtype=None):
if ty.is_categorical_dtype(dtype):
dtype = ty.string
if ty.is_string_dtype(dtype):
return self.create_future_from_string(value)
pandas_dtype = (dtype.storage_dtype.to_pandas()
if dtype is not None else None)
result = Future()
value = numpy.array(value, dtype=pandas_dtype)
if ty.is_timestamp_dtype(dtype):
value = value.view(dtype.storage_dtype.to_pandas())
result.set_value(self._runtime, value.data, value.nbytes)
return PandasFuture(self, result, dtype, ready=True)
def measure_nanoseconds(self):
return Future(
legion.legion_issue_timing_op_nanoseconds(
self.runtime, self.context
)
)
def create_future_from_string(self, value):
bytes = value.encode("utf-8")
result = Future()
result.set_value(self._runtime, bytes, len(bytes))
return PandasFuture(self, result, dtype=ty.string, ready=True)