def __init__(self, master=None):
super().__init__(master)
self.master = master
self.master.title(CONST_APP_TITLE)
self.master.geometry('600x400+400+100')
self.master.resizable(0, 0)
self.config(width=500, height=500)
self.place(x=50, y=0)
self.application_widgets()
self.processor = Processor()
def __init__(self, config):
self.executor = ReadFactory(config).get_executor()
self.processor = Processor(config)
self.writer = WriterFactory().instance_writer(config, self.processor.aggregation_output_struct,
self.processor.enumerate_output_aggregation_field)
self._isAnalysis = False
if ("analysis" in config.content.keys()):
self._isAnalysis = True
self.analysis = AnalysisFactory(config,
self.processor.aggregation_output_struct,
self.processor.enumerate_output_aggregation_field)
def show_solution(self):
top = tk.Toplevel(self)
top.geometry('500x400+400+100')
top.title(RESULT_TITLE)
scroll = tk.Scrollbar(top)
c = tk.Canvas(top, yscrollcommand=scroll.set)
scroll.config(command=c.yview)
scroll.pack(side='right', fill='y')
top_frame = tk.Frame(c)
top_frame.config(width=500)
c.pack(side='left', fill='both', expand=True)
c.create_window(0, 0, window=top_frame, anchor='nw')
top.update()
c.config(scrollregion=c.bbox('all'))
response = self.run_data()
self.processor = Processor()
tk.Label(top_frame, text=CONST_TOPIC_NAME).grid(padx=(70, 80),
pady=(5, 30),
row=0,
column=0)
tk.Label(top_frame, text=CONST_RESULT_PAGES).grid(padx=(70, 80),
pady=(5, 30),
row=0,
column=1)
for i in range(len(response[TOPICS_RESPONSE])):
if response[INCLUDE_RESPONSE][i] == 'true':
tk.Label(top_frame,
text=response[TOPICS_RESPONSE][i]).grid(padx=(70, 80),
pady=(5, 30),
row=i + 1,
column=0)
tk.Label(top_frame,
text=response[PAGES_RESPONSE][i]).grid(padx=(70, 80),
pady=(5, 30),
row=i + 1,
column=1)
tk.Label(top_frame, text=CONST_READERS).grid(
padx=(70, 80),
pady=(5, 30),
row=len(response[TOPICS_RESPONSE]) + 1,
column=0)
tk.Label(top_frame, text=response[READERS_RESPONSE]).grid(
padx=(70, 80),
pady=(5, 30),
row=len(response[TOPICS_RESPONSE]) + 1,
column=1)
def main():
"""
Usage:
python3 app.py input.txt' or 'python3 < input.txt'
"""
log.info('Begin processing...')
t = process_time()
processor = Processor()
# Accept input from two types of sources:
# a filename passed in command line arguments or STDIN.
with open(sys.argv[1], 'r') if len(sys.argv) > 1 else sys.stdin as f:
for line in f:
processor.parse_event(line)
log.info('Finished processing in {0:.3f} seconds'.format(process_time() - t))
summary = processor.generate_summary()
processor.write_output(summary)
import sys
import torch
from torch.backends import cudnn
from processor.processor import Processor
torch.backends.cudnn.deterministic = False
cudnn.benchmark = True # https://discuss.pytorch.org/t/what-does-torch-backends-cudnn-benchmark-do/5936
torch.cuda.empty_cache() # release cache
if __name__ == '__main__':
proc = Processor(sys.argv[1:])
proc.start()
def run_processor():
self.processor = Processor(get_projectdb(), self.in_queue,
self.status_queue, self.newtask_queue,
self.result_queue)
self.processor.CHECK_PROJECTS_INTERVAL = 0.1
self.processor.run()
def setUp(self):
self.processor = Processor()
import os
from processor.processor import Processor
if __name__ == "__main__":
current_path = os.path.dirname(os.path.abspath(__file__))
data_path = os.path.join(current_path, "data")
resource_path = os.path.join(data_path, "resources")
input_path = os.path.join(data_path, "inputs", "1984.txt")
output_path = os.path.join(data_path, "outputs")
processor = Processor(resource_path=resource_path, config={})
processor.process(input_path=input_path, output_path=output_path)
parser.add_argument('--num_of_vertices',
type=int,
default=358,
help='The number of vertices')
parser.add_argument('--gen_config_args',
type=dict,
default=dict(),
help='The config of data generate')
return parser
if __name__ == '__main__':
parser = get_parser()
# load arg form config file
p = parser.parse_args()
if p.config is not None:
with open(p.config, 'r') as f:
default_arg = yaml.load(f)
key = vars(p).keys()
for k in default_arg.keys():
if k not in key:
print('WRONG ARG: {}'.format(k))
assert (k in key)
parser.set_defaults(**default_arg)
arg = parser.parse_args()
init_seed(0)
processor = Processor(arg)
processor.start()
def test__number__(self):
config = Config(CONFIG_PATH_NUM)
p = Processor(config)
self.assertIsInstance(
p.transformation, types.LambdaType,
"Processor#transformation should be a lambda object")
