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()