shape = (1,)
else:
shape = tensordot_output.shape
return (shape1[0],) + shape
def compute_mask(self, inputs, mask=None):
if mask is None or all([m is None for m in mask]):
After Change
shape2.pop(0)
output_shape = shape1 + shape2
if len(output_shape) == 1:
output_shape += [1]return tuple(output_shape)
def compute_mask(self, inputs, mask=None):
if mask is None or all([m is None for m in mask]):
return None