def __init__(self, src_type=mstype.float32, dst_type=mstype.float32):
super(SaturateCast, self).__init__()
np_type = mstype.dtype_to_nptype(dst_type)
self.tensor_min_type = float(np.finfo(np_type).min)
self.tensor_max_type = float(np.finfo(np_type).max)
self.min_op = P.Minimum()
self.max_op = P.Maximum()
self.cast = P.Cast()
self.dst_type = dst_type
def __init__(self, src_type=mstype.float32, dst_type=mstype.float32):
super(SaturateCast, self).__init__()
np_type = mstype.dtype_to_nptype(dst_type)
min_type = np.finfo(np_type).min
max_type = np.finfo(np_type).max
self.tensor_min_type = Tensor([min_type], dtype=src_type)
self.tensor_max_type = Tensor([max_type], dtype=src_type)
self.min_op = ops.Minimum()
self.max_op = ops.Maximum()
self.cast = ops.Cast()
self.dst_type = dst_type
def __init__(self):
super(ClipByValue, self).__init__()
self.min = ops.Minimum()
self.max = ops.Maximum()
def __init__(self, min_val=-1.0, max_val=1.0):
super().__init__()
self.min_val = min_val
self.max_val = max_val
self.max = ops.Maximum()
self.min = ops.Minimum()
def __init__(self, alpha=1.0):
super().__init__()
self.alpha = alpha
self.exp = ops.Exp()
self.max = ops.Maximum()
self, min = ops.Minimum()