Datasets:
jblitzar
/
github-python-corpus

Dataset card Data Studio Files
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if self.parent:
self.parent.add_resource(response)
def process_current_task(self):
if self.current_task_idx == len(self.tasks):
self.current_task_idx = 0
if all([(isinstance(task, str) or task.done) for task in self.tasks]):
self.try_objective()
self.done = True
if not self.done:
current_task = self.tasks[self.current_task_idx]
if isinstance(current_task, str):
self.tasks[self.current_task_idx] = Objective(
current_task,
self.current_task_idx,
self.recursion_level + 1,
self.state,
parent=self
)
self.current_task_idx += 1
if self.current_task_idx == len(self.tasks):
self.current_task_idx = 0
if self.parent:
self.parent.current_task_idx += 1
else:
current_task.process_current_task()
else:
if self.parent:
self.parent.current_task_idx += 1
def to_string(self, select):
html_string = f'OBJECTIVE: {escape(self.objective)}<ul class="oobaAgentOutput">'
for task in self.tasks:
thinking = False
p_it = self
task_idx = p_it.tasks.index(task) if isinstance(task, str) else task.parent_task_idx
while ((p_it.current_task_idx % len(p_it.tasks)) == task_idx):
if not p_it.parent:
thinking = True
break
task_idx = p_it.parent_task_idx
p_it = p_it.parent
task_disp_class = "oobaAgentOutputThinking" if thinking and select else "oobaAgentOutput"
if isinstance(task, str):
html_string += f'<li class="{task_disp_class}">{escape(task)}</li>'
else:
html_string += f'<li class="{task_disp_class}">{task.to_string(select)}</li>'
for out in self.output:
html_string += f'<li class="oobaAgentOutputResource">{escape(out)}</li>'
html_string += "</ul>"
return html_string
# <FILESEP>
"""
Main file for setting up experiments, and compiling results.
@authors: James Robert Lloyd (jrl44@cam.ac.uk)
Created May 2015
"""
# TODO
# - use zeromq communication
# - make stacking tree code stuff easy - add weights as features that are recorded
# - try a test e.g. cycle vs freeze thaw
# - reintroduce database
import os
import sys
import psutil
import logging
from multiprocessing import Process
import numpy as np
import select
import signal
from managers import FixedLearnersStackingManager
import agent
import constants
import util
def load_experiment_details(filename):
"""Just loads the exp dictionary"""
exp_string = open(filename, 'r').read()
exp = eval(exp_string)
exp = exp_param_defaults(exp)
return exp
def run_experiment_file(filename, plot_override=True, separate_process=False):
"""
This is intended to be the function that's called to initiate a series of experiments.
"""
exp = load_experiment_details(filename=filename)
print('BEGIN EXPERIMENT SPECIFICATIONS')
print(exp_params_to_str(exp))
print('END EXPERIMENT SPECIFICATIONS')
# # Set number of processors
p = psutil.Process()
all_cpus = list(range(psutil.cpu_count()-1))