/
utils.py
188 lines (161 loc) · 5.8 KB
/
utils.py
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import tensorflow as tf
from tensorflow.python.ops import control_flow_ops as cf
'''
Replace all digits with 9s like SyntaxNet
'''
def normalizeDigits(form):
newform = ''
for i in range(len(form)):
if ord(form[i]) >= ord('0') and ord(form[i]) <= ord('9'):
newform += '9'
else:
newform += form[i]
return newform
'''
Gets array shape of dynamically shaped tensors
Ex.
dense_golden = tensorPrintShape(dense_golden, [dense_golden],
'dense_golden shape')
'''
def tensorPrintShape(inp, data, comment):
def np_print(*args):
for x in args:
print(comment, x.shape)
return cf.with_dependencies([tf.py_func(np_print, data, [])], inp)
'''
Ex.
dense_golden = tensorPrint(dense_golden, [dense_golden], 'dense_golden data')
'''
def tensorPrint(inp, data, comment):
def np_print(*args):
for x in args:
print(comment, x)
return cf.with_dependencies([tf.py_func(np_print, data, [])], inp)
tensorDumpValsCallCount = {}
'''
Ex.
dense_golden = tensorDumpVals(dense_golden, [dense_golden],
'/tmp/ash_dense_golden_1', 1)
'''
# print only the desired_iter'th time the function is called (1-based)
# for this particular filename
def tensorDumpVals(inp, data, fname, desired_iter):
global tensorDumpValsCallCount
def np_print(*args):
global tensorDumpValsCallCount
if fname not in tensorDumpValsCallCount:
tensorDumpValsCallCount[fname] = 0
tensorDumpValsCallCount[fname] += 1
# only execute for the iteration # desired
if tensorDumpValsCallCount[fname] == desired_iter:
fd = open(fname, 'w')
for x in args:
for elem in x.flatten():
fd.write('%.8f\n' % elem)
fd.close()
return cf.with_dependencies([tf.py_func(np_print, data, [])], inp)
'''
Ex.
dense_golden = tensorDumpValsAllIter(dense_golden, [dense_golden],
'/tmp/ash_dense_golden')
'''
def tensorDumpValsAllIter(inp, data, fname):
global tensorDumpValsCallCount
def np_print(*args):
global tensorDumpValsCallCount
if fname not in tensorDumpValsCallCount:
tensorDumpValsCallCount[fname] = 0
tensorDumpValsCallCount[fname] += 1
fd = open('%s_%04d' % (fname, tensorDumpValsCallCount[fname]), 'w')
for x in args:
for elem in x.flatten():
fd.write('%.8f\n' % elem)
fd.close()
return cf.with_dependencies([tf.py_func(np_print, data, [])], inp)
'''
See SyntaxNet utils.h
'''
kPunctuation = [
(33, 35), (37, 42), (44, 47), (58, 59),
(63, 64), (91, 93), (95, 95), (123, 123),
(125, 125), (161, 161), (171, 171), (183, 183),
(187, 187), (191, 191), (894, 894), (903, 903),
(1370, 1375), (1417, 1418), (1470, 1470), (1472, 1472),
(1475, 1475), (1478, 1478), (1523, 1524), (1548, 1549),
(1563, 1563), (1566, 1567), (1642, 1645), (1748, 1748),
(1792, 1805), (2404, 2405), (2416, 2416), (3572, 3572),
(3663, 3663), (3674, 3675), (3844, 3858), (3898, 3901),
(3973, 3973), (4048, 4049), (4170, 4175), (4347, 4347),
(4961, 4968), (5741, 5742), (5787, 5788), (5867, 5869),
(5941, 5942), (6100, 6102), (6104, 6106), (6144, 6154),
(6468, 6469), (6622, 6623), (6686, 6687), (8208, 8231),
(8240, 8259), (8261, 8273), (8275, 8286), (8317, 8318),
(8333, 8334), (9001, 9002), (9140, 9142), (10088, 10101),
(10181, 10182), (10214, 10219), (10627, 10648), (10712, 10715),
(10748, 10749), (11513, 11516), (11518, 11519), (11776, 11799),
(11804, 11805), (12289, 12291), (12296, 12305), (12308, 12319),
(12336, 12336), (12349, 12349), (12448, 12448), (12539, 12539),
(64830, 64831), (65040, 65049), (65072, 65106), (65108, 65121),
(65123, 65123), (65128, 65128), (65130, 65131), (65281, 65283),
(65285, 65290), (65292, 65295), (65306, 65307), (65311, 65312),
(65339, 65341), (65343, 65343), (65371, 65371), (65373, 65373),
(65375, 65381), (65792, 65793), (66463, 66463), (68176, 68184)
]
'''
Determines if the specified unicode ordinal is punctuation or not
'''
def isPunctuation(uni_ord):
assert type(uni_ord) is int
i = 0
while kPunctuation[i][0] > 0:
if uni_ord < kPunctuation[i][0]:
return False
if uni_ord <= kPunctuation[i][1]:
return True
i += 1
return False
'''
Returns true if word consists of punctuation characters.
'''
def isPunctuationToken(word):
for c in word:
if not isPunctuation(ord(c)):
return False
return True
'''
Determine if tag is a punctuation tag.
'''
def isPunctuationTag(tag):
# match SyntaxNet behavior
#if len(tag) == 0:
# return False
for c in tag:
if (c != ',' and c != ':' and c != '.' and c != '\'' and c != '`'):
return False
return True
'''
Returns true if tag is non-empty and has only punctuation or parens
symbols.
'''
def isPunctuationTagOrParens(tag):
if len(tag) == 0:
return False
for c in tag:
if (c != '(' and c != ')' and c != ',' and c != ':' and c != '.' and \
c != '\'' and c != '`'):
return False
return True
# FIXME: empty tags might show as '_' in CoNLL. '_' behavior is not
# well-defined in the specification.
'''
Return whether or not we should score a token based on the current
scoring strategy
'''
def shouldScoreToken(word, tag, scoring_strategy):
if scoring_strategy == 'default':
return len(tag) == 0 or not isPunctuationTag(tag)
elif scoring_strategy == 'conllx':
return not isPunctuationToken(word)
elif scoring_strategy == 'ignore_parens':
return not isPunctuationTagOrParens(tag)
assert None, 'unknown scoring strategy: ' + scoring_strategy