def define_jobs_context(self, context): boot_root = self.get_boot_root() data_central = self.get_data_central() GlobalConfig.global_load_dir('default') recipe_agentlearn_by_parallel_concurrent(context, data_central, Exp23.explogs_learn, n=8, only_agents=['exp23_diffeof', 'exp23_diffeo_fast']) recipe_agentlearn_by_parallel(context, data_central, Exp23.explogs_learn, only_agents=['stats2']) from diffeo2dds_learn.programs.devel.save_video import video_visualize_diffeo_stream1_robot for c, id_robot in iterate_context_names(context, Exp23.robots): out = os.path.join(context.get_output_dir(), 'videos', '%s-diffeo_stream1.mp4' % id_robot) c.comp_config(video_visualize_diffeo_stream1_robot, id_robot=id_robot, boot_root=boot_root, out=out) for id_robot in Exp23.robots: recipe_episodeready_by_convert2(context, boot_root, id_robot) jobs_publish_learning_agents_robots(context, boot_root, Exp23.agents, Exp23.robots)
def define_jobs_context(self, context): discdds_library = get_conftools_discdds() discdds = discdds_library.expand_names(self.options.discdds) discdds = natsorted(discdds) tolerance = self.options.tolerance for c, id_discdds in iterate_context_names(context, discdds): r = c.comp_config(report_dds_geometry, id_discdds, tolerance=tolerance) c.add_report(r, 'dds_geometry', tolerance=tolerance, dds=id_discdds)
def define_jobs_context(self, context): config = get_diffeo2ddslearn_config() nsamples = self.options.nsamples which = self.options.streams todo = config.streams.expand_names(which) self.info('given streams: %s' % which) self.info('using streams: %s' % todo) for c, id_stream in iterate_context_names(context, todo): report = c.comp_config(make_stream_report, id_stream, nsamples=nsamples) c.add_report(report, 'stream_report', id_stream=id_stream, nsamples=nsamples)