layers.py 文件源码

def __init__(self, incoming, shape, **kwargs):
        super(ReshapeLayer, self).__init__(incoming, **kwargs)
        shape = tuple(shape)
        for s in shape:
            if isinstance(s, int):
                if s == 0 or s < - 1:
                    raise ValueError("`shape` integers must be positive or -1")
            elif isinstance(s, list):
                if len(s) != 1 or not isinstance(s[0], int) or s[0] < 0:
                    raise ValueError("`shape` input references must be "
                                     "single-element lists of int >= 0")
            elif isinstance(s, (tf.Tensor, tf.Variable)):  # T.TensorVariable):
                raise NotImplementedError
                # if s.ndim != 0:
                #     raise ValueError(
                #         "A symbolic variable in a shape specification must be "
                #         "a scalar, but had %i dimensions" % s.ndim)
            else:
                raise ValueError("`shape` must be a tuple of int and/or [int]")
        if sum(s == -1 for s in shape) > 1:
            raise ValueError("`shape` cannot contain multiple -1")
        self.shape = shape
        # try computing the output shape once as a sanity check
        self.get_output_shape_for(self.input_shape)