Fix/remove live backward

README.md

@@ -262,15 +262,14 @@ $ nohup python neurons/validator.py --netuid 8 --wallet.name <wallet> --wallet.h
 
 # Running a Miner
 
-If you're running a miner, you should see three types of requests: LiveForwardHash, LiveForward, and LiveBackward. 
+If you're running a miner, you should see two types of requests: LiveForwardHash and LiveForward. 
 
 LiveForwardHash is requested first, which will be a hash of your predictions. LiveForward will be requested 60 seconds later which
 will request the actual predictions made (non-hashed). Using the hash and the actual predictions, validators can validate the 
 authenticity of the predictions made, ensuring no participants are copying anothers.
 
 - **LiveForwardHash** - will be when you provide a hash of your predictions.
 - **LiveForward** - will be when your miner provides your actual predictions.
-- **LiveBackward** - will receive the results that occurred live if you want to use them for any updating purposes.
 
 You'll receive rewards for your predictions `~10 hours` after making them. Therefore, if you start running on the network, you should expect a lag in receiving rewards. Predictions are reviewed and rewarded every 30 minutes.
 

neurons/miner.py

@@ -96,13 +96,13 @@ def get_config():
 
 # TODO: Move this into a stream mining solution class, so each stream can be predicted using different sources, models, etc...
 def get_predictions(
-    tims_ms: int,
+    time_ms: int,
     feature_source: FeatureSource,
     feature_scaler: FeatureScaler,
     model: BaseMiningModel,
 ):
     # TODO: interval should come from the stream definition
-    lookback_time_ms = tims_ms - (model.sample_count * INTERVAL_MS)
+    lookback_time_ms = time_ms - (model.sample_count * INTERVAL_MS)
 
     feature_samples = feature_source.get_feature_samples(
         lookback_time_ms, INTERVAL_MS, model.sample_count
@@ -499,21 +499,6 @@ def live_f(synapse: template.protocol.LiveForward) -> template.protocol.LiveForw
         except Exception as e:
             bt.logging.error(f"error returning synapse to vali: {e}")
 
-    # def lb_blacklist_fn(synapse: template.protocol.LiveBackward) -> Tuple[bool, str]:
-    #     # standardizing not accepting lb for now. Miner can override if they'd like.
-    #     return False, synapse.dendrite.hotkey
-    #
-    # def lb_priority_fn(synapse: template.protocol.LiveBackward) -> float:
-    #     caller_uid = metagraph.hotkeys.index( synapse.dendrite.hotkey ) # Get the caller index.
-    #     prirority = float( metagraph.S[ caller_uid ] ) # Return the stake as the priority.
-    #     bt.logging.trace(f'Prioritizing {synapse.dendrite.hotkey} with value: ', prirority)
-    #     return prirority
-
-    # def live_b(synapse: template.protocol.LiveBackward) -> template.protocol.LiveBackward:
-    #     bt.logging.debug(f'received lb with length {len(synapse.samples.numpy())}')
-    #     synapse.received = True
-    #     return synapse
-
     # Build and link miner functions to the axon.
     # The axon handles request processing, allowing validators to send this process requests.
     bt.logging.info(f"setting port [{config.axon.port}]")
@@ -624,4 +609,4 @@ def live_f(synapse: template.protocol.LiveForward) -> template.protocol.LiveForw
 
 # This is the main function, which runs the miner.
 if __name__ == "__main__":
-    main(get_config())
+    main(get_config())

neurons/validator.py

@@ -18,7 +18,6 @@
 )
 from template.protocol import (
     LiveForward,
-    LiveBackward,
     LiveForwardHash,
 )
 import time
@@ -190,7 +189,9 @@ def run_time_series_validation(
                             # check for invalid miner pred
                             for miner_pred in predictions:
                                 if math.isnan(miner_pred):
-                                    raise ValueError(f"invalid miner preds [{miner_pred}]")
+                                    raise ValueError(
+                                        f"invalid miner preds [{miner_pred}]"
+                                    )
 
                             hashed_predictions = HashingUtils.hash_predictions(
                                 miner_hotkey, str(predictions.tolist())
@@ -287,30 +288,7 @@ def run_time_series_validation(
                 # TODO: Improve validators to allow multiple features in predictions
                 validation_array = validation_array.flatten()
 
-                bt.logging.info(
-                    "results gathered sending back to miners via backprop and weighing"
-                )
-
-                # Send back the results for backprop so miners can learn
-                results = bt.tensor(validation_array)
-
-                results_backprop_proto = LiveBackward(
-                    request_uuid=request_uuid,
-                    stream_id=stream_type,
-                    samples=results,
-                    topic_id=request_df.topic_id,
-                )
-
-                try:
-                    dendrite.query(
-                        metagraph.axons, results_backprop_proto, deserialize=True
-                    )
-                    bt.logging.info("live results sent back to miners")
-                except Exception:  # noqa
-                    traceback.print_exc()
-                    bt.logging.info(
-                        "failed sending back results to miners and continuing..."
-                    )
+                bt.logging.info("results gathered sending back to miners via weighing")
 
                 scores = {}
                 for miner_uid, miner_preds in vali_request.predictions.items():