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10 results for DHT
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learning-at-home - Hivemind DHT
... To initialize the first DHT node, run from hivemind import DHT, get_dht_time dht = DHT(start=True) # ...
... = DHT(initial_peers=dht.get_visible_maddrs(), start=True) bob_dht = DHT(initial_peers=dht2.get_visible_maddrs ...
... Once the DHT is formed, all participants can dht.store key-value pairs in the DHT and dht.get them by ...
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learning-at-home - Benchmarking
... It spawns a DHT with num_peers participants, then chooses one peer that will declare num_experts total ...
... The benchmark will start one server without DHT with several experts, and then spawn trainer processes ...
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learning-at-home - hivemind.moe.server
... ; if dht is None, this parameter is ignored. expiration – when server declares its experts to the DHT ...
... Initializes dht if necessary, starts connection handlers, runs Runtime (self.runtime) to process incoming ...
... It periodically re-publishes these experts to the dht via a dedicated hivemind.dht.DHT peer that runs ...
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learning-at-home - hivemind.dht
... Utility functions for crawling DHT nodes, used to get and store keys in a DHT ...
...
RPC protocol that provides nodes a way to communicate with each other ...
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learning-at-home - Quick Start
... =dht, # use a DHT that is connected with other peers run_id='my_cifar_run', # unique identifier of this ...
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learning-at-home - hivemind.moe.client
... – a DHT instance used to search for best experts k_best – average this many highest-scoring experts ...
... – a DHT instance used to search for best experts k_best – average this many highest-scoring experts ...
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... DecentralizedAverager (class in hivemind.averaging) DHT (class in hivemind.dht) DHTID (class in hivemind.dht.routing ...
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learning-at-home - hivemind.averaging
run_in_background(await_ready: bool = True, timeout: Optional[float] = None) → None[source]
... Starts averager in a background process. if await_ready, this method will wait until background dht is ...
... Parameters averaged_tensors – a sequence of pytorch tensors that will be averaged in each all-reduce dht ...
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learning-at-home - hivemind.optim
... = hivemind.DHT(initial_peers=INITIAL_PEERS, start=True) >>> opt = hivemind.Optimizer(dht=dht, run_id ...
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learning-at-home - Mixture-of-Experts
... Create a python console (or a jupyter) and run: import torch import hivemind dht = hivemind.DHT( initial_peers ...
... You can find more details in the DHT tutorial. ...