"""
Convert a sequence labeling data for RNN

@author Volkan Cirik
"""
import sys
import numpy as np
import pickle
import cPickle
import gzip

def convertData(tr_,val_,te_):

	try:
		tr_file = open(tr_)
	except:
		print >> sys.stderr, "seqence file",tr_,"cannot be read"
		quit(1)
	try:
		val_file = open(val_)
	except:
		print >> sys.stderr, "seqence file",val_,"cannot be read"
		quit(1)
	try:
		te_file = open(te_)
	except:
		print >> sys.stderr, "seqence file",te_,"cannot be read"
		quit(1)

	train = [line.strip().split() for line in tr_file]
	val = [line.strip().split() for line in val_file]
	test = [line.strip().split() for line in te_file]

	print >> sys.stderr,"______________"
	print >> sys.stderr,"parameters are:"
	print >> sys.stderr,tr_,val_,te_
	print >> sys.stderr,"______________"


	tok_set = {'<UNK>' : 0}
	tok_id = 1

	for pairs in train:
		if len(pairs) == 2:
			for tok in pairs:
				if tok not in tok_set:
					tok_set[tok] = tok_id
					tok_id += 1

	X_tr = []
	X_te = []
	X_val = []

	Y_tr = []
	Y_te = []
	Y_val = []

	TR = (train,X_tr,Y_tr)
	VAL = (val,X_val,Y_val)
	TE = (test,X_te,Y_te)

	x = []
	y = []
	for (inp,X,Y) in [TR,VAL,TE]:
		for l in inp:
			if len(l) != 2:

				X.append(np.array(x,dtype=np.int32))
				Y.append(np.array(y,dtype=np.int32))
				x = []
				y = []

				continue
			token = l[0]
			next_token = l[1]

			if token not in tok_set:
				token = '<UNK>'

			if next_token not in tok_set:
				next_token = '<UNK>'

			v = tok_set[token]
			t = tok_set[next_token]

			x.append(v)
			y.append(t)

		if len(x) >= 1:
			X.append(np.array(x,dtype=np.int32))
			Y.append(np.array(y,dtype=np.int32))
		x = []
		y = []
		print >> sys.stderr, "completed a file..."

	# print X_tr
	# print Y_tr
	# print "______________"
	# print X_val
	# print Y_val
	# print "______________"
	# print X_te
	# print Y_te
	# print "______________"
	# print tok_set

	# train_set = X_tr, Y_tr, Y_tr
	# val_set = X_tr, Y_tr, Y_tr #  X_val, Y_val, Y_val
	# test_set = X_tr, Y_tr, Y_tr #X_te, Y_te, Y_te

	train_set = X_tr, Y_tr, Y_tr
	val_set =  X_val, Y_val, Y_val
	test_set = X_te, Y_te, Y_te

	dic = {}
	dic['labels2idx'] = tok_set
	dic['words2idx'] = tok_set
	dic['tables2idx'] = tok_set

	return train_set, val_set,test_set, dic

def dumpDataset(d,o):
	out = gzip.open(o,'wb')
	cPickle.dump(d,out)
	out.close()

if __name__ == "__main__":
	tr_file = sys.argv[1]
	val_file = sys.argv[2]
	te_file = sys.argv[3]

	out_file = sys.argv[4]

	dataset = convertData(tr_file,val_file,te_file)
	dumpDataset(dataset,out_file)

# awk 'BEGIN{mi=100;ma=0}{if(NF<mi)mi = NF;if(NF>ma)ma = NF;}END{print mi,ma}'

369ee461a1e4f58466cda0ec2369e13d3b189713
<mask token>


def dumpDataset(d, o):
    out = gzip.open(o, 'wb')
    cPickle.dump(d, out)
    out.close()


<mask token>

<mask token>


def convertData(tr_, val_, te_):
    try:
        tr_file = open(tr_)
    except:
        print >> sys.stderr, 'seqence file', tr_, 'cannot be read'
        quit(1)
    try:
        val_file = open(val_)
    except:
        print >> sys.stderr, 'seqence file', val_, 'cannot be read'
        quit(1)
    try:
        te_file = open(te_)
    except:
        print >> sys.stderr, 'seqence file', te_, 'cannot be read'
        quit(1)
    train = [line.strip().split() for line in tr_file]
    val = [line.strip().split() for line in val_file]
    test = [line.strip().split() for line in te_file]
    print >> sys.stderr, '______________'
    print >> sys.stderr, 'parameters are:'
    print >> sys.stderr, tr_, val_, te_
    print >> sys.stderr, '______________'
    tok_set = {'<UNK>': 0}
    tok_id = 1
    for pairs in train:
        if len(pairs) == 2:
            for tok in pairs:
                if tok not in tok_set:
                    tok_set[tok] = tok_id
                    tok_id += 1
    X_tr = []
    X_te = []
    X_val = []
    Y_tr = []
    Y_te = []
    Y_val = []
    TR = train, X_tr, Y_tr
    VAL = val, X_val, Y_val
    TE = test, X_te, Y_te
    x = []
    y = []
    for inp, X, Y in [TR, VAL, TE]:
        for l in inp:
            if len(l) != 2:
                X.append(np.array(x, dtype=np.int32))
                Y.append(np.array(y, dtype=np.int32))
                x = []
                y = []
                continue
            token = l[0]
            next_token = l[1]
            if token not in tok_set:
                token = '<UNK>'
            if next_token not in tok_set:
                next_token = '<UNK>'
            v = tok_set[token]
            t = tok_set[next_token]
            x.append(v)
            y.append(t)
        if len(x) >= 1:
            X.append(np.array(x, dtype=np.int32))
            Y.append(np.array(y, dtype=np.int32))
        x = []
        y = []
        print >> sys.stderr, 'completed a file...'
    train_set = X_tr, Y_tr, Y_tr
    val_set = X_val, Y_val, Y_val
    test_set = X_te, Y_te, Y_te
    dic = {}
    dic['labels2idx'] = tok_set
    dic['words2idx'] = tok_set
    dic['tables2idx'] = tok_set
    return train_set, val_set, test_set, dic


def dumpDataset(d, o):
    out = gzip.open(o, 'wb')
    cPickle.dump(d, out)
    out.close()


<mask token>

<mask token>


def convertData(tr_, val_, te_):
    try:
        tr_file = open(tr_)
    except:
        print >> sys.stderr, 'seqence file', tr_, 'cannot be read'
        quit(1)
    try:
        val_file = open(val_)
    except:
        print >> sys.stderr, 'seqence file', val_, 'cannot be read'
        quit(1)
    try:
        te_file = open(te_)
    except:
        print >> sys.stderr, 'seqence file', te_, 'cannot be read'
        quit(1)
    train = [line.strip().split() for line in tr_file]
    val = [line.strip().split() for line in val_file]
    test = [line.strip().split() for line in te_file]
    print >> sys.stderr, '______________'
    print >> sys.stderr, 'parameters are:'
    print >> sys.stderr, tr_, val_, te_
    print >> sys.stderr, '______________'
    tok_set = {'<UNK>': 0}
    tok_id = 1
    for pairs in train:
        if len(pairs) == 2:
            for tok in pairs:
                if tok not in tok_set:
                    tok_set[tok] = tok_id
                    tok_id += 1
    X_tr = []
    X_te = []
    X_val = []
    Y_tr = []
    Y_te = []
    Y_val = []
    TR = train, X_tr, Y_tr
    VAL = val, X_val, Y_val
    TE = test, X_te, Y_te
    x = []
    y = []
    for inp, X, Y in [TR, VAL, TE]:
        for l in inp:
            if len(l) != 2:
                X.append(np.array(x, dtype=np.int32))
                Y.append(np.array(y, dtype=np.int32))
                x = []
                y = []
                continue
            token = l[0]
            next_token = l[1]
            if token not in tok_set:
                token = '<UNK>'
            if next_token not in tok_set:
                next_token = '<UNK>'
            v = tok_set[token]
            t = tok_set[next_token]
            x.append(v)
            y.append(t)
        if len(x) >= 1:
            X.append(np.array(x, dtype=np.int32))
            Y.append(np.array(y, dtype=np.int32))
        x = []
        y = []
        print >> sys.stderr, 'completed a file...'
    train_set = X_tr, Y_tr, Y_tr
    val_set = X_val, Y_val, Y_val
    test_set = X_te, Y_te, Y_te
    dic = {}
    dic['labels2idx'] = tok_set
    dic['words2idx'] = tok_set
    dic['tables2idx'] = tok_set
    return train_set, val_set, test_set, dic


def dumpDataset(d, o):
    out = gzip.open(o, 'wb')
    cPickle.dump(d, out)
    out.close()


if __name__ == '__main__':
    tr_file = sys.argv[1]
    val_file = sys.argv[2]
    te_file = sys.argv[3]
    out_file = sys.argv[4]
    dataset = convertData(tr_file, val_file, te_file)
    dumpDataset(dataset, out_file)

<mask token>
import sys
import numpy as np
import pickle
import cPickle
import gzip


def convertData(tr_, val_, te_):
    try:
        tr_file = open(tr_)
    except:
        print >> sys.stderr, 'seqence file', tr_, 'cannot be read'
        quit(1)
    try:
        val_file = open(val_)
    except:
        print >> sys.stderr, 'seqence file', val_, 'cannot be read'
        quit(1)
    try:
        te_file = open(te_)
    except:
        print >> sys.stderr, 'seqence file', te_, 'cannot be read'
        quit(1)
    train = [line.strip().split() for line in tr_file]
    val = [line.strip().split() for line in val_file]
    test = [line.strip().split() for line in te_file]
    print >> sys.stderr, '______________'
    print >> sys.stderr, 'parameters are:'
    print >> sys.stderr, tr_, val_, te_
    print >> sys.stderr, '______________'
    tok_set = {'<UNK>': 0}
    tok_id = 1
    for pairs in train:
        if len(pairs) == 2:
            for tok in pairs:
                if tok not in tok_set:
                    tok_set[tok] = tok_id
                    tok_id += 1
    X_tr = []
    X_te = []
    X_val = []
    Y_tr = []
    Y_te = []
    Y_val = []
    TR = train, X_tr, Y_tr
    VAL = val, X_val, Y_val
    TE = test, X_te, Y_te
    x = []
    y = []
    for inp, X, Y in [TR, VAL, TE]:
        for l in inp:
            if len(l) != 2:
                X.append(np.array(x, dtype=np.int32))
                Y.append(np.array(y, dtype=np.int32))
                x = []
                y = []
                continue
            token = l[0]
            next_token = l[1]
            if token not in tok_set:
                token = '<UNK>'
            if next_token not in tok_set:
                next_token = '<UNK>'
            v = tok_set[token]
            t = tok_set[next_token]
            x.append(v)
            y.append(t)
        if len(x) >= 1:
            X.append(np.array(x, dtype=np.int32))
            Y.append(np.array(y, dtype=np.int32))
        x = []
        y = []
        print >> sys.stderr, 'completed a file...'
    train_set = X_tr, Y_tr, Y_tr
    val_set = X_val, Y_val, Y_val
    test_set = X_te, Y_te, Y_te
    dic = {}
    dic['labels2idx'] = tok_set
    dic['words2idx'] = tok_set
    dic['tables2idx'] = tok_set
    return train_set, val_set, test_set, dic


def dumpDataset(d, o):
    out = gzip.open(o, 'wb')
    cPickle.dump(d, out)
    out.close()


if __name__ == '__main__':
    tr_file = sys.argv[1]
    val_file = sys.argv[2]
    te_file = sys.argv[3]
    out_file = sys.argv[4]
    dataset = convertData(tr_file, val_file, te_file)
    dumpDataset(dataset, out_file)

"""
Convert a sequence labeling data for RNN

@author Volkan Cirik
"""
import sys
import numpy as np
import pickle
import cPickle
import gzip

def convertData(tr_,val_,te_):

	try:
		tr_file = open(tr_)
	except:
		print >> sys.stderr, "seqence file",tr_,"cannot be read"
		quit(1)
	try:
		val_file = open(val_)
	except:
		print >> sys.stderr, "seqence file",val_,"cannot be read"
		quit(1)
	try:
		te_file = open(te_)
	except:
		print >> sys.stderr, "seqence file",te_,"cannot be read"
		quit(1)

	train = [line.strip().split() for line in tr_file]
	val = [line.strip().split() for line in val_file]
	test = [line.strip().split() for line in te_file]

	print >> sys.stderr,"______________"
	print >> sys.stderr,"parameters are:"
	print >> sys.stderr,tr_,val_,te_
	print >> sys.stderr,"______________"


	tok_set = {'<UNK>' : 0}
	tok_id = 1

	for pairs in train:
		if len(pairs) == 2:
			for tok in pairs:
				if tok not in tok_set:
					tok_set[tok] = tok_id
					tok_id += 1

	X_tr = []
	X_te = []
	X_val = []

	Y_tr = []
	Y_te = []
	Y_val = []

	TR = (train,X_tr,Y_tr)
	VAL = (val,X_val,Y_val)
	TE = (test,X_te,Y_te)

	x = []
	y = []
	for (inp,X,Y) in [TR,VAL,TE]:
		for l in inp:
			if len(l) != 2:

				X.append(np.array(x,dtype=np.int32))
				Y.append(np.array(y,dtype=np.int32))
				x = []
				y = []

				continue
			token = l[0]
			next_token = l[1]

			if token not in tok_set:
				token = '<UNK>'

			if next_token not in tok_set:
				next_token = '<UNK>'

			v = tok_set[token]
			t = tok_set[next_token]

			x.append(v)
			y.append(t)

		if len(x) >= 1:
			X.append(np.array(x,dtype=np.int32))
			Y.append(np.array(y,dtype=np.int32))
		x = []
		y = []
		print >> sys.stderr, "completed a file..."

	# print X_tr
	# print Y_tr
	# print "______________"
	# print X_val
	# print Y_val
	# print "______________"
	# print X_te
	# print Y_te
	# print "______________"
	# print tok_set

	# train_set = X_tr, Y_tr, Y_tr
	# val_set = X_tr, Y_tr, Y_tr #  X_val, Y_val, Y_val
	# test_set = X_tr, Y_tr, Y_tr #X_te, Y_te, Y_te

	train_set = X_tr, Y_tr, Y_tr
	val_set =  X_val, Y_val, Y_val
	test_set = X_te, Y_te, Y_te

	dic = {}
	dic['labels2idx'] = tok_set
	dic['words2idx'] = tok_set
	dic['tables2idx'] = tok_set

	return train_set, val_set,test_set, dic

def dumpDataset(d,o):
	out = gzip.open(o,'wb')
	cPickle.dump(d,out)
	out.close()

if __name__ == "__main__":
	tr_file = sys.argv[1]
	val_file = sys.argv[2]
	te_file = sys.argv[3]

	out_file = sys.argv[4]

	dataset = convertData(tr_file,val_file,te_file)
	dumpDataset(dataset,out_file)

# awk 'BEGIN{mi=100;ma=0}{if(NF<mi)mi = NF;if(NF>ma)ma = NF;}END{print mi,ma}'
