def __init__(self, config: 'bittensor.config' = None): if config == None: config = server.config() config = config self.check_config(config) bittensor.logging( config=config, logging_dir=config.neuron.full_path, ) self.model = server(config=config) self.config = config
def __init__(self, config: 'bittensor.config' = None): if config == None: config = neuron.config() config = config self.check_config(config) bittensor.logging( config=config, logging_dir=config.neuron.full_path, ) self.config = config print(config) # Load/Create our bittensor wallet. self.wallet = bittensor.wallet(config=config).create().register() # Connect to the chain. self.subtensor = bittensor.subtensor(config=config) # Load/Sync/Save our metagraph. self.metagraph = bittensor.metagraph( subtensor=self.subtensor).load().sync().save() self.uid = self.metagraph.hotkeys.index( self.wallet.hotkey.ss58_address) # Create Dendrite. self.dendrite = bittensor.dendrite(config=config) # Load genesis dataset. self.dataset = bittensor.dataset(config=config) # Build Device. self.device = torch.device(device=config.neuron.device) self.nucleus = Validator(config=config, metagraph=self.metagraph_callback, dendrite=self.dendrite, device=self.device)
import bittensor logging = bittensor.logging() def test_construct_text_corpus(): # text corpus for the train set dataset = bittensor.dataset(max_corpus_size=10000, save_dataset=True) dataset.construct_text_corpus() dataset.close() def test_next(): dataset = bittensor.dataset(max_corpus_size=1000) next(dataset) next(dataset) next(dataset) dataset.close() if __name__ == "__main__": test_construct_text_corpus()