def internalPrepare(self):
f = file(self.path, "r")
inputs = []
outputs = []
num = 0
for l in f.readlines():
last = l.index(':')
first = l[0:last].strip()
if first == 'null':
continue
second = l[last + 1:len(l)].strip()
inputArray = numpy.fromstring(first, dtype=numpy.float32, sep=",")
output = numpy.fromstring(second, dtype=numpy.float32, sep=",")
output = numpy.array(output)
# output = output.reshape(1, 300)
input = numpy.array(inputArray)
input = input.reshape(3, 300)
inputs.append(input)
outputs.append(output)
return inputs, outputs
def internalPrepare(self):
f = file(self.path, "r")
inputs = []
outputs = []
num = 0
for l in f.read().split("\n"):
if l == '':
continue
last = l.index(';');
first = l[0: last].strip()
if first == 'null':
continue
second = l[last + 1:len(l)].strip();
inputArray = numpy.fromstring(first,dtype=numpy.float32,sep=",").reshape((5,357))
output = numpy.fromstring(second, dtype=numpy.float32, sep=",").reshape((5,7))
output = numpy.array(output);
input = numpy.array(inputArray);
inputs.append(input);
outputs.append(output);
return inputs,outputs
def internalPrepare(self):
f = file(self.path, "r")
inputs = []
outputs = OrderedDict()
for l in f.readlines():
parts = l.split(';')
if len(parts) < 2:
continue
embedding = numpy.fromstring(parts[0],
dtype=numpy.float32,
sep=',')
embedding = embedding.reshape(5, 300)
short_words = numpy.fromstring(parts[1],
dtype=numpy.float32,
sep=',')
short_words = short_words.reshape(5, 31)
clusters = numpy.fromstring(parts[2], dtype=numpy.float32, sep=',')
clusters = clusters.reshape(5, 31)
input1 = numpy.concatenate((embedding, short_words, clusters),
axis=1)
inputs.append(input1)
for i in range(3, len(parts)):
if i == len(parts) - 1:
output_array = numpy.fromstring(parts[i],
dtype=numpy.float32,
sep=',')[:-1]
else:
output_array = numpy.fromstring(parts[i],
dtype=numpy.float32,
sep=',')
if i in outputs.keys():
outputs[i].append(output_array)
else:
array = [output_array]
outputs[i] = array
return inputs, outputs
def internalPrepare(self):
f = file(self.path, "r")
inputs = []
outputs_food = []
outputs_family = []
outputs_dates = []
outputs_pronouns = []
outputs_ing = []
outputs_cogn = []
outputs_time = []
outputs_modal = []
outputs_adj = []
num = 0
for l in f.readlines():
parts = l.split(';')
if len(parts) < 2:
continue
embedding = numpy.fromstring(parts[0],
dtype=numpy.float32,
sep=',')
embedding = embedding.reshape(5, 300)
short_words = numpy.fromstring(parts[1],
dtype=numpy.float32,
sep=',')
short_words = short_words.reshape(5, 31)
input1 = numpy.concatenate((embedding, short_words), axis=1)
inputs.append(input1)
output_food = numpy.fromstring(parts[2],
dtype=numpy.float32,
sep=',')
outputs_food.append(output_food)
output_family = numpy.fromstring(parts[3],
dtype=numpy.float32,
sep=',')
outputs_family.append(output_family)
output_dates = numpy.fromstring(parts[4],
dtype=numpy.float32,
sep=',')
outputs_dates.append(output_dates)
output_pronouns = numpy.fromstring(parts[5],
dtype=numpy.float32,
sep=',')
outputs_pronouns.append(output_pronouns)
output_ing = numpy.fromstring(parts[6],
dtype=numpy.float32,
sep=',')
outputs_ing.append(output_ing)
output_cogn = numpy.fromstring(parts[7],
dtype=numpy.float32,
sep=',')
outputs_cogn.append(output_cogn)
output_time = numpy.fromstring(parts[8],
dtype=numpy.float32,
sep=',')
outputs_time.append(output_time)
output_modal = numpy.fromstring(parts[9],
dtype=numpy.float32,
sep=',')
outputs_modal.append(output_modal)
output_adj = numpy.fromstring(parts[10],
dtype=numpy.float32,
sep=',')[:-1]
outputs_adj.append(output_adj)
return inputs, outputs_food, outputs_family, outputs_dates, outputs_pronouns, outputs_ing, outputs_cogn, outputs_time, outputs_modal, outputs_adj