def define_jobs_context(self, context): # let's convert all logs for id_explog in Exp09.logs_to_learn: self.call_recursive(context, 'convert', RS2B, ['--config', self.get_config_dirs()[0], # XXX '--dummy', 'convert-one', '--boot_root', self.get_boot_root(), '--id_explog', id_explog, '--id_adapter', Exp09.id_adapter, '--id_robot', Exp09.id_robot, ]) # Everything before needs to be done before we do the rest context.checkpoint('conversion') for c, id_agent in iterate_context_agents(context, Exp09.agents): logs = Exp09.agents[id_agent] c.subtask(LearnLog, agent=id_agent, robot=Exp09.id_robot, episodes=logs, interval_publish=5000) c.checkpoint('learning') c.subtask(PublishLearningResult, agent=id_agent, robot=Exp09.id_robot) for cc, id_episode in iterate_context_episodes(c, Exp09.test_episodes): cc.subtask(ServoField, id_robot=Exp09.id_robot, id_agent=id_agent, id_episode=id_episode, variation='default')
def define_jobs_context(self, context): id_agent = 'exp04_bdse1' id_robot = 'exp05_uA_xy' id_convert_job = 'exp05_uA_xy' jobs_convert = self.call_recursive(context, 'convert', RS2B, ['--config', self.get_config_dirs()[0], # XXX '--dummy', 'convert', '--boot_root', self.get_boot_root(), '--jobs', id_convert_job, ]) jobs_learn = context.subtask(LearnLog, agent=id_agent, robot=id_robot, interval_publish=5000, extra_dep=jobs_convert.all_jobs()) test_episodes = [ 'unicornA_tran1_2013-04-12-23-34-08' ] for c, id_episode in iterate_context_episodes(context, test_episodes): c.subtask(ServoField, id_robot=id_robot, id_agent=id_agent, variation='default', id_episode=id_episode, extra_dep=jobs_learn.all_jobs())
def define_jobs_context(self, context): id_agent = 'exp10_bdser1' id_robot = 'uA_b1_tw_cf' id_adapter = 'uA_b1_tw_cf' explogs_learn = good_logs_cf explogs_test = ['unicornA_tran1_2013-04-12-23-34-08'] explogs_convert = explogs_learn + explogs_test for c, id_explog in iterate_context_explogs(context, explogs_convert): c.subtask(RS2BConvertOne, boot_root=self.get_boot_root(), id_explog=id_explog, id_adapter=id_adapter, id_robot=id_robot) context.checkpoint('conversion') context.subtask(LearnLog, agent=id_agent, robot=id_robot, interval_publish=5000) context.checkpoint('learning') context.subtask(PublishLearningResult, agent=id_agent, robot=id_robot) test_episodes = explogs_test for c, id_episode in iterate_context_episodes(context, test_episodes): c.subtask(ServoField, id_robot=id_robot, id_agent=id_agent, variation='default', id_episode=id_episode)
def define_jobs_context(self, context): id_adapter = 'unicornA_base1_tw_hlhr_sane_s4' id_agent = 'bdse1' id_robot = 'uA_b1_tw_hlhr_s4' variation = 'default' test_episodes = [ 'unicornA_tran1_2013-04-12-23-34-08' ] for c, id_episode in iterate_context_episodes(context, test_episodes): id_explog = id_episode jobs_convert = self.call_recursive(c, 'convert', RS2B, ['--config', self.get_config_dirs()[0], # XXX '--dummy', 'convert-one', '--boot_root', self.get_boot_root(), '--id_explog', id_explog, '--id_adapter', id_adapter, '--id_robot', id_robot]) self.call_recursive(c, 'servo_field', ServoField, dict(id_robot=id_robot, id_agent=id_agent, variation=variation, id_episode=id_episode), extra_dep=jobs_convert)
def define_jobs_context(self, context): id_agent = 'exp10_bdser1' id_robot = 'exp12_uA_b1_tw_cf' id_adapter = 'uA_b1_tw_cf' explogs_learn = good_logs_cf explogs_test = ['unicornA_tran1_2013-04-12-23-34-08'] explogs_convert = explogs_learn + explogs_test agent = None for c, id_explog in iterate_context_explogs(context, explogs_convert): episodes = c.subtask(RS2BConvertOne, boot_root=self.get_boot_root(), id_explog=id_explog, id_adapter=id_adapter, id_robot=id_robot) if id_explog in explogs_learn: agent_i = c.subtask(LearnLogNoSave, agent=id_agent, robot=id_robot, episodes=episodes) if agent is None: agent = agent_i else: agent = context.comp(merge_agents, agent, agent_i) id_episodes = explogs_learn data_central = self.get_data_central() context.comp(save_state, data_central, id_agent, id_robot, agent, id_episodes) context.checkpoint('learning') context.subtask(PublishLearningResult, agent=id_agent, robot=id_robot) test_episodes = [ 'unicornA_tran1_2013-04-12-23-34-08' ] for c, id_episode in iterate_context_episodes(context, test_episodes): c.subtask(ServoField, id_robot=id_robot, id_agent=id_agent, variation='default', id_episode=id_episode)
def define_jobs_context(self, cc): id_agent = 'exp13_bdser1' id_robot = 'exp13_uA_b1_tw_cf' id_adapter = 'uA_b1_tw_cf_strip' explogs_learn = good_logs_cf explogs_test = ['unicornA_tran1_2013-04-12-23-34-08'] explogs_convert = explogs_learn + explogs_test for c, id_explog in iterate_context_explogs(cc, explogs_convert): c.subtask(RS2BConvertOne, boot_root=self.get_boot_root(), id_explog=id_explog, id_adapter=id_adapter, id_robot=id_robot) cc.checkpoint('conversion') cc.subtask(LearnLog, agent=id_agent, robot=id_robot, interval_publish=5000) cc.checkpoint('learning') cc.subtask(PublishLearningResult, agent=id_agent, robot=id_robot) test_episodes = explogs_test for c, id_episode in iterate_context_episodes(cc, test_episodes): c.subtask(ServoField, id_robot=id_robot, id_agent=id_agent, variation='default', id_episode=id_episode) data_central = self.get_data_central() cc.add_report(cc.comp(report_prediction, data_central=data_central, id_agent=id_agent, id_robot=id_robot), 'prediction', id_agent=id_agent, id_robot=id_robot) cc.add_report(cc.comp(report_prediction2, data_central=data_central, id_agent=id_agent, id_robot=id_robot), 'prediction2', id_agent=id_agent, id_robot=id_robot)
def define_jobs_context(self, context): id_agent = "exp06_bgds1" id_robot = "exp05_uA_xy" id_convert_job = "exp05_uA_xy" jobs_convert = self.call_recursive( context, "convert", RS2B, [ "--config", self.get_config_dirs()[0], # XXX "--dummy", "convert", "--boot_root", self.get_boot_root(), "--jobs", id_convert_job, ], ) jobs_learn = context.subtask( LearnLog, agent=id_agent, robot=id_robot, interval_publish=5000, extra_dep=jobs_convert.all_jobs() ) test_episodes = ["unicornA_tran1_2013-04-12-23-34-08"] for c, id_episode in iterate_context_episodes(context, test_episodes): c.subtask( ServoField, id_robot=id_robot, id_agent=id_agent, variation="default", id_episode=id_episode, extra_dep=jobs_learn.all_jobs(), )