def main():
try:
test.tests()
except AssertionError:
print('Problem with tests')
sys.exit()
instructions.instructions()
file_instruction.file_instruction()
flag = True
while flag:
work_with_users.cli_interface()
k = input("\nWant to continue?\n(yes/no/help me): ")
if k == 'yes':
flag = True
elif k == 'no':
flag = False
elif k == 'help me':
instructions.instructions()
flag = True
import re
import reprlib
from test import tests
RE_WORD = re.compile('\w+')
class Sentence:
def __init__(self, text):
self.text = text
self.words = RE_WORD.findall(text)
def __repr__(self):
return 'Sentence(%s)' % reprlib.repr(self.text)
def __iter__(self):
for word in self.words:
yield word
return
tests(Sentence)
def run_grader(student_func):
grade_result = dict()
try:
result = test.tests(student_func)
correct = result == 0
comment = ""
if result == 0:
comment = ""
elif result == 1:
comment = "There was an error running your solution. Please make sure there are no syntax errors, \nindentation errors, etc. and try again."
elif result == 2:
comment = "search is not defined"
elif result == 3:
comment = "search did not return anything"
elif result % 100 == 4:
if result == 4:
comment = "search didn't return the expected output for:\ngrid = ["
else:
comment = "search raised an exception for:\ngrid = ["
grid = [[0, 1, 1, 1, 1], [0, 1, 0, 0, 0], [0, 0, 0, 1, 0],
[1, 1, 1, 1, 0], [0, 0, 0, 1, 0]]
for i in range(len(grid)):
comment += str(grid[i])
if i < len(grid) - 1:
comment += ',\n '
else:
comment += ']'
elif result % 100 == 5:
if result == 5:
comment = "search didn't return the expected output for:\ngrid = ["
else:
comment = "search raised an exception for:\ngrid = ["
grid = [[0, 1, 0, 0, 0, 1, 0], [0, 1, 0, 1, 0, 1, 0],
[0, 1, 0, 1, 0, 1, 0], [0, 1, 0, 1, 0, 1, 1],
[0, 0, 0, 1, 0, 0, 0]]
for i in range(len(grid)):
comment += str(grid[i])
if i < len(grid) - 1:
comment += ',\n '
else:
comment += ']'
elif result % 100 == 6:
if result == 6:
comment = "search didn't return the expected output for:\ngrid = ["
else:
comment = "search raised an exception for:\ngrid = ["
grid = [[0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0], [0, 0, 1, 0, 1, 0],
[0, 0, 1, 0, 1, 0], [0, 0, 1, 0, 1, 0]]
for i in range(len(grid)):
comment += str(grid[i])
if i < len(grid) - 1:
comment += ',\n '
else:
comment += ']'
grade_result['correct'] = correct
if correct:
grade_result['comment'] = "Correct! " + comment
else:
grade_result['comment'] = comment
except:
grade_result['correct'] = False
grade_result[
'comment'] = """There was an error running your solution. Make sure that
search takes four arguments: grid, init, goal, cost. Also
make sure that you are not using any global variables other
than delta and delta_name."""
return grade_result.get('comment')
@staticmethod
def split(z):
sq_z = isqrt(z)
if (sq_z * sq_z) > z:
sq_z = sq_z - 1
t = z - sq_z * sq_z
if t < sq_z: return (sq_z, t)
else: return (t - sq_z, sq_z)
@staticmethod
def bounds():
return (0, 0, 0)
@staticmethod
def generate():
u, v, w = 0, 0, 0
while True:
yield (u, v)
if u == w and v < w:
if v < w-1: v += 1
else: u, v = 0, w
elif u < w and v == w:
u += 1
elif u == w and v == w:
u, v, w = (u+1, 0, w+1)
else: assert False
if __name__ == "__main__":
tests(Elegant)
q = (z + 1) // p
if q % 2 == 1:
return (i, q // 2)
@staticmethod
def bounds(): return (0, 0, 0)
@staticmethod
def generate():
z = 0
while True:
yield Poto.split(z)
z += 1
if __name__ == "__main__":
tests(Poto)
"""
# rest in piece: attempt to do a faster generate (possible?)
# stolen from:
# https://www.geeksforgeeks.org/check-n-divisible-power-2-without-using-arithmetic-operators/
# Python3 implementation to chech
# whether n is divisible by pow(2, m)
# function to chech whether n
# is divisible by pow(2, m)
def isDivBy2PowerM (n, m):
# if expression results to 0, then
def trains(self, net):
self.logs = logger.logger()
# logs.refline(1,"2334",1)
# logs.refline(4,"2334",5)
# logs.refline(1,"2334",6)
# logs.refline()
readf = readfile.readfile()
aimat = float(0.0)
# test.tests(net, 0, float(aimat), readf, self.logs)
net.train(mode=True)
torch.set_num_threads(8)
criterion = nn.CrossEntropyLoss(
) # use a Classification Cross-Entropy loss
optimizer = optim.SGD([{
'params': net.features.parameters(),
'lr': 0.00001
}, {
'params': net.lin.parameters(),
'lr': 0.001
}, {
'params': net.classifier.parameters(),
'lr': 0.0005
}],
momentum=0.9)
# scheduler = MultiStepLR(optimizer, milestones=[10, 80], gamma=0.1)
tot = 0
for epoch in range(2000): # loop over the dataset multiple times
# scheduler.step()
running_loss = 0.0
net.train(mode=True)
for i, data in enumerate(readf.dataloader, 0):
tot += 1
# get the inputs
inputs, labels = data
# wrap them in Variable
inputs, labels = Variable(inputs), Variable(labels)
# zero the parameter gradients
optimizer.zero_grad()
# forward + backward + optimize
outputs = net(inputs)
loss = criterion(outputs, labels)
loss.backward()
optimizer.step()
# print statistics
running_loss += loss.data[0]
if i % 25 == 24: # print every 2000 mini-batches
print('[%d, %5d] loss: %.3f' %
(epoch + 1, i + 1, running_loss / 25))
self.logs.defx = tot
# print(self.logs.defx)
self.logs.refline(running_loss / 25 * 100, "loss")
running_loss = 0.0
aimat = float(aimat)
aimat = test.tests(net, epoch, float(aimat), readf,
self.logs)
net.train(mode=True)
torch.save(net, "./mod2/handalexnet34")
print("saved")
print('Finished Training')
engine.say(announcement + get_news())
engine.runAndWait()
def announce_weather_and_news(announcement):
"""
This function says out loud the content of the alarm that is expected to
say also the weather and the news. It also says out loud the weather and the news.
"""
logging.info("Alarm with news and weather has been said")
try:
engine.endLoop()
except:
logging.error('PyTTSx3 Endloop error')
engine.say(announcement + get_weather() + get_news())
engine.runAndWait()
if __name__ == '__main__':
try:
tests()
except AssertionError as message:
print(message)
logging.info('System starting')
app.run(debug=True)
class Cantor:
@staticmethod
def join(x, y):
return tn(x + y) + y
@staticmethod
def split(z):
t = tr(z)
return ((t * (t + 3) // 2) - z, z - ((t * (t + 1)) // 2))
@staticmethod
def bounds():
return (0, 0, 0)
@staticmethod
def generate():
u, v = 0, 0
while True:
yield (u - v, v)
if u == v:
u += 1
v = 0
else:
v += 1
if __name__ == "__main__":
tests(Cantor)
#!/usr/bin/env python from unittest import TextTestRunner import test TextTestRunner().run(test.tests())
# half pairing (only x <= y pairs)
class Half:
@staticmethod
def join(x, y):
return tn(max(x, y)) + min(x, y)
@staticmethod
def split(z):
return (ext(z), tr(z))
@staticmethod
def bounds():
return (0, 0, 0)
@staticmethod
def generate():
u, v = 0, 0
while True:
yield (u, v)
if u == v:
v += 1
u = 0
else:
u += 1
if __name__ == "__main__":
tests(Half)
def testunit(self):
"""测试tests"""
pows = tests(8)
self.assertEquals(pows, 64)
# encoding: utf-8
import argparse
import test
if __name__ == '__main__':
argX = argparse.ArgumentParser()
argX.add_argument('--noweb', action='store_true', default=False)
args = argX.parse_args()
tests = test.tests(args)
tests.run()
