4c50261df4847bdfd7c8067307e8532f96d04104,batchflow/models/torch/encoder_decoder.py,EncoderDecoder,decoder,#Any#Any#,147

Before Change

        -------
        nn.Module
        
        steps = kwargs.pop("num_stages", len(inputs)-1)
        factor = kwargs.pop("factor")

        if isinstance(factor, int):
            factor = int(factor ** (1/steps))
            factor = [factor] * steps
        elif not isinstance(factor, list):
            raise TypeError("factor should be int or list of int, but %s was given" % type(factor))

        x = inputs[-1]

After Change

    @classmethod
    def decoder(cls, inputs, **kwargs):
        steps = kwargs.pop("num_stages") or len(inputs)-2
        skip, upsample, block_args = cls.pop(["skip", "upsample", "blocks"], kwargs)
        base_block = block_args.get("base")

Instances