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Update keras model, sorta working
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Dhvani Patel committed Jul 20, 2017
1 parent d3ec145 commit 63aac7c
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Showing 6 changed files with 468 additions and 157 deletions.
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56 changes: 24 additions & 32 deletions keras_model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -95,9 +95,9 @@ def getInputTen():
elif(batchInd == 2):
toPass = toPassTwo[:]
elif(batchInd == 3):
toPass = toPassThree[:]
toPass = toPassOne[:]
elif(batchInd == 4):
toPass = toPassFour[:]
toPass = toPassTwo[:]
a = numpy.array(toPass).astype(int)
#print a.shape
#count+=1
Expand Down Expand Up @@ -125,7 +125,7 @@ def getInputTen():
fileInd += 1
windowInd = 0
one_hot_good, one_hot_bad_ins, one_hot_bad_del, one_hot_bad_sub, _, _, _, _, _ = perform(fileInd)
while(one_hot_good == None):
while(one_hot_good == 1):
fileInd+=1
one_hot_good, one_hot_bad_ins, one_hot_bad_del, one_hot_bad_sub, _, _, _, _, _ = perform(fileInd)

Expand Down Expand Up @@ -192,14 +192,8 @@ def getOutputTen():
three = 1
bruhTwo.append(three)
else:
zero = 1
bruhTwo.append(zero)
one = 0
bruhTwo.append(one)
two = 0
bruhTwo.append(two)
three = 0
bruhTwo.append(three)
print "GET OUT OF HERE"
print type(radha)
toPassTwo.append(bruhTwo)
toPassThree = []
for x in range(10):
Expand Down Expand Up @@ -273,9 +267,9 @@ def getOutputTen():
elif(batchInd == 2):
toPass = toPassTwo[:]
elif(batchInd == 3):
toPass = toPassThree[:]
toPass = toPassOne[:]
elif(batchInd == 4):
toPass = toPassFour[:]
toPass = toPassTwo[:]
#print len(toPass)
#print toPassOne[1]
a = numpy.array(toPass)
Expand Down Expand Up @@ -304,7 +298,7 @@ def getOutputTen():
fileInd += 1
windowInd = 0
_, _, _, _, one_hot_good_out, one_hot_bad_ins_out, one_hot_bad_del_out, one_hot_bad_sub_out, _ = perform(fileInd)
while(one_hot_good_out == None):
while(one_hot_good_out == 1):
fileInd+=1
_, _, _, _, one_hot_good_out, one_hot_bad_ins_out, one_hot_bad_del_out, one_hot_bad_sub_out, _ = perform(fileInd)

Expand Down Expand Up @@ -337,6 +331,7 @@ def getInputValTen():
#print windowInd
#print "WINDOW"
batchInd = 1

#print len(one_hot_good)
#print len(one_hot_bad_ins)
#print len(one_hot_bad_del)
Expand All @@ -361,11 +356,14 @@ def getInputValTen():
y = x + windowInd
if y < len(one_hot_bad_sub):
toPassFour.append(one_hot_bad_sub[y])
#print "TEST"
#print numpy.array(toPassOne).astype(int)[0]
#print len(toPass)
#print len(toPassOne)
#print len(toPassTwo)
#print len(toPassThree)
#print len(toPassFour)

#toPass = np.array((toPassOne, toPassTwo, toPassThree, toPassFour))
#print toPass.shape
#toPass = []
Expand All @@ -379,9 +377,9 @@ def getInputValTen():
elif(batchInd == 2):
toPass = toPassTwo[:]
elif(batchInd == 3):
toPass = toPassThree[:]
toPass = toPassOne[:]
elif(batchInd == 4):
toPass = toPassFour[:]
toPass = toPassTwo[:]
a = numpy.array(toPass).astype(int)
#print a.shape
#count+=1
Expand Down Expand Up @@ -409,7 +407,7 @@ def getInputValTen():
fileInd += 1
windowInd = 0
one_hot_good, one_hot_bad_ins, one_hot_bad_del, one_hot_bad_sub, _, _, _, _, _ = perform(fileInd)
while(one_hot_good == None):
while(one_hot_good == 1):
fileInd+=1
one_hot_good, one_hot_bad_ins, one_hot_bad_del, one_hot_bad_sub, _, _, _, _, _ = perform(fileInd)

Expand Down Expand Up @@ -476,14 +474,8 @@ def getOutputValTen():
three = 1
bruhTwo.append(three)
else:
zero = 1
bruhTwo.append(zero)
one = 0
bruhTwo.append(one)
two = 0
bruhTwo.append(two)
three = 0
bruhTwo.append(three)
print "GET OUT OF HERE"
print type(radha)
toPassTwo.append(bruhTwo)
toPassThree = []
for x in range(10):
Expand Down Expand Up @@ -557,9 +549,9 @@ def getOutputValTen():
elif(batchInd == 2):
toPass = toPassTwo[:]
elif(batchInd == 3):
toPass = toPassThree[:]
toPass = toPassOne[:]
elif(batchInd == 4):
toPass = toPassFour[:]
toPass = toPassTwo[:]
#print len(toPass)
#print toPassOne[1]
a = numpy.array(toPass)
Expand Down Expand Up @@ -588,7 +580,7 @@ def getOutputValTen():
fileInd += 1
windowInd = 0
_, _, _, _, one_hot_good_out, one_hot_bad_ins_out, one_hot_bad_del_out, one_hot_bad_sub_out, _ = perform(fileInd)
while(one_hot_good_out == None):
while(one_hot_good_out == 1):
fileInd+=1
_, _, _, _, one_hot_good_out, one_hot_bad_ins_out, one_hot_bad_del_out, one_hot_bad_sub_out, _ = perform(fileInd)

Expand All @@ -603,8 +595,8 @@ def getOutputValTen():


def getInputTestTen():
one_hot_good, one_hot_bad_ins, one_hot_bad_del, one_hot_bad_sub, _, _, _, _, passInsErrorInd = perform(4)
fileInd = 4
one_hot_good, one_hot_bad_ins, one_hot_bad_del, one_hot_bad_sub, _, _, _, _, passInsErrorInd = perform(2077)
fileInd = 2077
batchInd = 1

if True:
Expand Down Expand Up @@ -640,7 +632,7 @@ def getInputTestTen():
#print len(toPassFour)
#toPass = np.array((toPassOne, toPassTwo, toPassThree, toPassFour))
#print toPass.shape
toPass = toPassTwo[:]
toPass = toPassOne[:]
a = numpy.array(toPass).astype(int)
#print b.shape
return a
Expand Down Expand Up @@ -789,7 +781,7 @@ def initData():
# loss='binary_crossentropy',
# metrics=['accuracy'])

opt = optimizers.SGD(lr=0.001)
opt = optimizers.SGD(lr=0.001, momentum=0.005)
#opt = optimizers.Adadelta(lr=1.0, rho=0.95, epsilon=1e-08, decay=0.0)
#opt = optimizers.RMSprop(lr=0.001, rho=0.9, epsilon=1e-08, decay=0.0)
model.compile(loss = "categorical_crossentropy", optimizer = opt, metrics=['accuracy'])
Expand Down
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