def shred(self, seq, k_length):

        kmers = set([seq[i:i+k_length] for i in range(0, len(seq)-k_length)])

        for kmer in kmers:
            if kmer in self.kmer2entry:
                self.kmer2entry[kmer] = 0
            else:
                self.kmer2entry[kmer] = 1
Get output from each layer of the network.
dataset/ETHPy150Open CGATOxford/cgat/scripts/fasta2unique_kmers.py/KmerCounter.shred--crossover with--dataset/ETHPy150Open blackecho/Deep-Learning-TensorFlow/models/autoencoder_models/stacked_denoising_autoencoder.py/StackedDenoisingAutoencoder.get_layers_output