def get_bop_output_type(op_name, dtype_a, dtype_b):
a = np.array(1, dtype=dtype_a)
b = np.array(2, dtype=dtype_b)
op_name = np_ufunc_map.get(op_name, op_name)
try:
dtype = np.__getattribute__(op_name)(a, b).dtype
return np.__getattribute__(str(dtype))
except Exception as _:
dtype = scipy.special.__getattribute__(op_name)(a, b).dtype
return np.__getattribute__(str(dtype))
def get_bop_output_type(op_name, dtype_a, dtype_b):
a = np.array(1, dtype=dtype_a)
b = np.array(2, dtype=dtype_b)
op_name = np_ufunc_map.get(op_name, op_name)
try:
dtype = np.__getattribute__(op_name)(a, b).dtype
return to_dtype_cls(dtype)
except TypeError as err:
raise err
except Exception as _:
dtype = scipy.special.__getattribute__(op_name)(a, b).dtype
return to_dtype_cls(dtype)
def bop(self, op, a1, a2, a1_T, a2_T, axes):
if a1_T:
a1 = a1.T
if a2_T:
a2 = a2.T
if op == "tensordot":
return np.tensordot(a1, a2, axes=axes)
op = np_ufunc_map.get(op, op)
try:
ufunc = np.__getattribute__(op)
except Exception as _:
ufunc = scipy.special.__getattribute__(op)
return ufunc(a1, a2)
def get_bop_output_type(op_name, dtype_a, dtype_b):
a = np.array(1, dtype=dtype_a)
b = np.array(2, dtype=dtype_b)
op_name = np_ufunc_map.get(op_name, op_name)
try:
dtype = np.__getattribute__(op_name)(a, b).dtype
return np.__getattribute__(str(dtype))
except Exception as _:
if op_name == "sparse_tensordot":
a = coo_matrix((1, 1), dtype=dtype_a)
b = coo_matrix((1, 1), dtype=dtype_b)
dtype = (a * b).dtype
return np.__getattribute__(str(dtype))
dtype = scipy.special.__getattribute__(op_name)(a, b).dtype
return np.__getattribute__(str(dtype))
def bop(self, op, a1, a2, a1_T, a2_T, axes):
if a1_T:
a1 = a1.T
if a2_T:
a2 = a2.T
if op == "tensordot":
if axes == 1 and max(len(a1.shape), len(a2.shape)) <= 2:
# Execute this as a matmul.
# TODO: Outer product is optimized.
# detect here and execute np.outer(...)
return np.matmul(a1, a2)
return np.tensordot(a1, a2, axes=axes)
op = np_ufunc_map.get(op, op)
try:
ufunc = np.__getattribute__(op)
except Exception as _:
ufunc = scipy.special.__getattribute__(op)
return ufunc(a1, a2)
