Alireza Rahimpour AlirezaRahimpour

## folder_splitter.py
# -*- coding: utf-8 -*-
# @author: Peter Lamut

import argparse
import os
import shutil

N = 10  # the number of files in seach subfolder folder

## attention_lstm.py
class AttentionLSTM(LSTM):
    """LSTM with attention mechanism

    This is an LSTM incorporating an attention mechanism into its hidden states.
    Currently, the context vector calculated from the attended vector is fed
    into the model's internal states, closely following the model by Xu et al.
    (2016, Sec. 3.1.2), using a soft attention model following
    Bahdanau et al. (2014).

    The layer expects two inputs instead of the usual one:
	# -- coding: utf-8 --
	# @author: Peter Lamut

	import argparse
	import os
	import shutil

	N = 10 # the number of files in seach subfolder folder
	class AttentionLSTM(LSTM):
	"""LSTM with attention mechanism

	This is an LSTM incorporating an attention mechanism into its hidden states.
	Currently, the context vector calculated from the attended vector is fed
	into the model's internal states, closely following the model by Xu et al.
	(2016, Sec. 3.1.2), using a soft attention model following
	Bahdanau et al. (2014).

	The layer expects two inputs instead of the usual one: