65e4f94e45f32d9cbe99337d74ed9c1ebad3412a,keras/layers/core.py,AutoEncoder,__init__,#AutoEncoder#Any#Any#Any#Any#Any#,299

Before Change

        if encoder is None or decoder is None:
            raise Exception("Please specify the encoder/decoder layers")

        if not isinstance(encoder, Layer) or not isinstance(decoder, Layer):
            raise Exception("Only Layer types are supported as inputs for autoencoders")

        self.input_dim = encoder.input_dim
        self.hidden_dim = decoder.input_dim
        self.output_reconstruction = output_reconstruction
        self.tie_weights = tie_weights

After Change

        if not encoders or not decoders:
            raise Exception("Please specify the encoder/decoder layers")

        if not len(encoders) == len(decoders):
            raise Exception("There need to be an equal number of encoders and decoders")

        // connect all encoders & decoders to their previous (respectively)
        for i in xrange(len(encoders)-1, 0, -1):
            encoders[i].connect(encoders[i-1])
            decoders[i].connect(decoders[i-1])
        decoders[0].connect(encoders[-1])  // connect the first to the last

        self.input_dim = encoders[0].input_dim
        self.hidden_dim = reversed([d.input_dim for d in decoders])
        self.output_reconstruction = output_reconstruction
        self.tie_weights = tie_weights
        self.encoders = encoders

Instances