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task_inst.trained_dependencies = trained_dependencies
#Finally, run the task
task_inst.train(**kwargs)
return task_inst"
681,"def execute_predict_task(self, task_inst, predict_data, **kwargs):
""""""
Do a prediction
task_inst - instance of a task
""""""
result = task_inst.predict(predict_data, **task_inst.args)
return result"
682,"def train(self, **kwargs):
""""""
Do the workflow training
""""""
log.info(""Starting to train..."")
if not self.setup_run:
self.setup()
self.trained_tasks = []
for task in self.tasks:
data = self.reformatted_input[task.data_format]['data']
target = self.reformatted_input[task.data_format]['target']
if data is None:
raise Exception(""Data cannot be none. Check the config file to make sure the right input is being read."")
kwargs['data']=data
kwargs['target']=target
trained_task = self.execute_train_task_with_dependencies(task, **kwargs)
self.trained_tasks.append(trained_task)
#If the trained task alters the data in any way, pass it down the chain to the next task
if hasattr(trained_task, 'data'):
self.reformatted_input[task.data_format]['data'] = trained_task.data
log.info(""Finished training."")"
683,"def predict(self, **kwargs):
""""""
Do the workflow prediction (done after training, with new data)
""""""
reformatted_predict = self.reformat_predict_data()
results = {}
for task_inst in self.trained_tasks:
predict = reformatted_predict[task_inst.data_format]['predict']
kwargs['predict']=predict
results.update({get_task_name(task_inst) : self.execute_predict_task(task_inst, predict, **kwargs)})
return results"
684,"def read_input(self, input_cls, filename, **kwargs):
""""""
Read in input and do some minimal preformatting
input_cls - the class to use to read the input
filename - input filename
""""""
input_inst = input_cls()
input_inst.read_input(filename)
return input_inst.get_data()"
685,"def reformat_file(self, input_file, input_format, output_format):
""""""
Reformat input data files to a format the tasks can use
""""""
#Return none if input_file or input_format do not exist
if input_file is None or input_format is None:
return None
#Find the needed input class and read the input stream
try:
input_cls = self.find_input(input_format)
input_inst = input_cls()
except TypeError:
#Return none if input_cls is a Nonetype
return None
#If the input file cannot be found, return None
try:
input_inst.read_input(self.absolute_filepath(input_file))
except IOError:
return None
formatter = find_needed_formatter(input_format, output_format)
if formatter is None:
raise Exception(""Cannot find a formatter that can convert from {0} to {1}"".format(self.input_format, output_format))
formatter_inst = formatter()
formatter_inst.read_input(input_inst.get_data(), input_format)
data = formatter_inst.get_data(output_format)
return data"
686,"def reformat_input(self, **kwargs):
""""""
Reformat input data
""""""
reformatted_input = {}
needed_formats = []
for task_cls in self.tasks:
needed_formats.append(task_cls.data_format)
self.needed_formats = list(set(needed_formats))
for output_format in self.needed_formats:
reformatted_input.update(
{
output_format :
{
'data' : self.reformat_file(self.input_file, self.input_format, output_format),
'target' : self.reformat_file(self.target_file, self.target_format, output_format)
}
}
)
return reformatted_input"