Restoring from checkpoints given an experiment folder #16
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hembergerik
requested changes
Nov 22, 2019
| self.grid_position = (checkpoint['topology_details']['position'][0], checkpoint['topology_details']['position'][1]) | ||
| self.local_node = checkpoint['topology_details']['cell_info'] | ||
| self.cell_number = checkpoint['cell_number'] | ||
| self.neighbours = checkpoint['adjacent_cells'] |
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Why do the checkpoints keys have different names from the variables?
| splitted_source = source.split(':') | ||
| return {'address': splitted_source[0], 'port': splitted_source[1], 'id': source} | ||
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| class ExperimentResuming(): |
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Rename to checkpoint.py and ExperimentRestarter makes it easier to read
| return checkpoint | ||
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| def get_population_cell_info(self): | ||
| client_soueces = self.get_population_sources() |
| return clients | ||
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| def get_population_sources(self): | ||
| sources = set() |
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Why is this a set is it intentional to get different size populations?
| [sources.add(local_discriminator) for local_discriminator in checkpoint['local_discriminators']] | ||
| return list(sources) | ||
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| def get_local_generators_paths(self, source): |
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Looks like code duplication for 2 methods, that could be simplified with function parameters e.g. get_checkpoint_local_values(self, source, key)
| @@ -102,6 +109,9 @@ def add_config_file(grp, is_required): | |||
| def initialize_settings(args): | |||
| cc = ConfigurationContainer.instance() | |||
| cc.settings = read_settings(args.configuration_file) | |||
| if args.checkpoint_folder is not None: | |||
| cc.settings['general']['distribution']['auto_discover'] = False | |||
| cc.settings['general']['distribution']['resuming'] = args.checkpoint_folder | |||
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resume = resuming easier to read
| gen, dis = self.network_factory.create_both() | ||
| populations[TYPE_GENERATOR].individuals.append(Individual(genome=gen, fitness=gen.default_fitness)) | ||
| populations[TYPE_DISCRIMINATOR].individuals.append(Individual(genome=dis, fitness=dis.default_fitness)) | ||
| if checkpoint is not None: |
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Maybe reverse branches and write if checkpoint for readability
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| # Resume status from checkpoint | ||
| checkpoint = self.cc.settings['general']['distribution'].get('client_checkpoint', None) | ||
| if checkpoint is not None: |
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Maybe reverse branches and write if checkpoint for readability
| n_iterations = self.cc.settings['trainer'].get('n_iterations', 0) | ||
| assert 0 <= checkpoint_period <= n_iterations, 'Checkpoint period paramenter (checkpoint_period) should be ' \ | ||
| 'between 0 and the number of iterations (n_iterations).' | ||
| self.checkpoint_period = self.cc.settings['general'].get('checkpoint_period', checkpoint_period) | ||
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| def read_ckeckpoint(self): | ||
| checkpoint = self.cc.settings['general']['distribution']['client_checkpoint'] | ||
| return checkpoint.get('iteration', 0), float(checkpoint.get('generators_learning_rate', None)), float(checkpoint.get('discriminators_learning_rate', None)) |
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Is None a good default value?
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| for iteration in range(n_iterations): | ||
| while(self.iteration < n_iterations): | ||
| iteration = self.iteration |
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