autoencoder.py 文件源码

def next_batch(self, batches, in_memory):
        """
        Returns the next batch in some fixed-length representation.
        Currently we use Panchenko et al.'s cumulative traces

        @param batches an iterator with all of the batches (
            if in_memory == True:
                in batch-major form without padding
            else:
                A list of paths to the files
        )
        @param in_memory is a boolean value

        @return if in_memory is False, returns a tuple of (dict, [paths]) where paths is a list of paths for each batch
            else it returns a dict for training
        """
        batch = next(batches)
        data_batch = batch

        if not in_memory:
            data_batch = [helpers.read_cell_file(path) for path in batch]

        data_batch = [self._process_trace(trace, self.layers[0]) for trace in data_batch]

        min_max_scaler = MinMaxScaler()
        data_batch = min_max_scaler.fit_transform(data_batch)

        encoder_inputs_ = data_batch
        decoder_targets_ = data_batch

        train_dict = {
            self.encoder_inputs: encoder_inputs_,
            self.decoder_targets: decoder_targets_,
        }

        if not in_memory:
            return (train_dict, batch)
        return train_dict