From 3a41abba77a332459987734e15d679ab093fade8 Mon Sep 17 00:00:00 2001
From: Sid <sid.data.universe@gmail.com>
Date: Sun, 18 Aug 2024 15:11:50 -0700
Subject: [PATCH 01/10] Log metadata in eval loop.

---
 neurons/validator.py | 44 +++++++++++++++++++++++++++++---------------
 1 file changed, 29 insertions(+), 15 deletions(-)

diff --git a/neurons/validator.py b/neurons/validator.py
index 376ddbe..bbc1668 100644
--- a/neurons/validator.py
+++ b/neurons/validator.py
@@ -725,21 +725,25 @@ async def run_step(self):
             pages_per_eval = constants.pages_per_eval_pack
 
         # If the option is set in the config, override
-        pages_per_eval = self.config.pages_per_eval if self.config.pages_per_eval is not None else pages_per_eval
+        pages_per_eval = (
+            self.config.pages_per_eval
+            if self.config.pages_per_eval is not None
+            else pages_per_eval
+        )
 
-        bt.logging.debug(f'Sample packing is set to: {pack_samples}.')
-        bt.logging.debug(f'Number of pages per evaluation step is: {pages_per_eval}')
+        bt.logging.debug(f"Sample packing is set to: {pack_samples}.")
+        bt.logging.debug(f"Number of pages per evaluation step is: {pages_per_eval}")
 
         dataloader = SubsetDataLoader(
             batch_size=constants.batch_size,
             sequence_length=competition.constraints.sequence_length,
-            num_pages= pages_per_eval,
+            num_pages=pages_per_eval,
             tokenizer=tokenizer,
-            pack_samples=pack_samples
-            )
+            pack_samples=pack_samples,
+        )
 
         batches = list(dataloader)
-        bt.logging.debug(f'Number of validation batches is {len(batches)}')
+        bt.logging.debug(f"Number of validation batches is {len(batches)}")
 
         # This is useful for logging to wandb
         pages = dataloader.get_page_names()
@@ -758,11 +762,11 @@ async def run_step(self):
         compute_loss_perf = PerfMonitor("Eval: Compute loss")
 
         for uid_i in uids:
-            bt.logging.trace(f"Computing model losses for uid:{uid_i}.")
-
             # This variable should be overwritten below if the model has metadata.
             losses: typing.List[float] = [math.inf for _ in range(len(batches))]
 
+            bt.logging.trace(f"Getting metadata for uid: {uid_i}.")
+
             # Check that the model is in the tracker.
             with self.metagraph_lock:
                 hotkey = self.metagraph.hotkeys[uid_i]
@@ -776,6 +780,10 @@ async def run_step(self):
                 and model_i_metadata.id.competition_id == competition.id
             ):
                 try:
+                    bt.logging.info(
+                        f"Evaluating uid: {uid_i} / hotkey: {hotkey} with metadata: {model_i_metadata}."
+                    )
+
                     # Update the block this uid last updated their model.
                     uid_to_block[uid_i] = model_i_metadata.block
 
@@ -795,7 +803,7 @@ async def run_step(self):
                                 batches,
                                 self.config.device,
                                 tokenizer.eos_token_id,
-                                pack_samples
+                                pack_samples,
                             ),
                             ttl=400,
                             mode="spawn",
@@ -912,7 +920,9 @@ async def run_step(self):
         # If the model has any significant weight, prioritize by weight with greater weights being kept first.
         # Then for the unweighted models, prioritize by win_rate.
         # Use the competition weights from the tracker which also handles moving averages.
-        tracker_competition_weights = self.competition_tracker.get_competition_weights(competition.id)
+        tracker_competition_weights = self.competition_tracker.get_competition_weights(
+            competition.id
+        )
         model_prioritization = {
             uid: (
                 # Add 1 to ensure it is always greater than a win rate.
@@ -952,7 +962,6 @@ async def run_step(self):
             compute_loss_perf,
         )
 
-
         # Increment the number of completed run steps by 1
         self.run_step_count += 1
 
@@ -981,7 +990,9 @@ def log_step(
         }
 
         # The sub-competition weights
-        sub_competition_weights = torch.softmax(model_weights / constants.temperature, dim=0)
+        sub_competition_weights = torch.softmax(
+            model_weights / constants.temperature, dim=0
+        )
 
         for idx, uid in enumerate(uids):
             step_log["uid_data"][str(uid)] = {
@@ -1069,7 +1080,10 @@ def log_step(
                     str(uid): uid_data[str(uid)]["win_total"] for uid in uids
                 },
                 "weight_data": {str(uid): self.weights[uid].item() for uid in uids},
-                "norm_weight_data": {str(uid): sub_competition_weights[i].item() for i, uid in enumerate(uids)},
+                "norm_weight_data": {
+                    str(uid): sub_competition_weights[i].item()
+                    for i, uid in enumerate(uids)
+                },
                 "competition_id": {
                     str(uid): uid_to_competition_id[uid]
                     for uid in uids
@@ -1094,7 +1108,7 @@ def log_step(
                 step=self.last_wandb_step,
             )
 
-            self.last_wandb_step+=1
+            self.last_wandb_step += 1
 
     def _get_uids_to_competition_ids(
         self,

From 607b243a7c2428c29e986586c305b536551c0a85 Mon Sep 17 00:00:00 2001
From: Sid <sid.data.universe@gmail.com>
Date: Sun, 18 Aug 2024 15:28:31 -0700
Subject: [PATCH 02/10] Also construct hf_url for the log.

---
 neurons/validator.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/neurons/validator.py b/neurons/validator.py
index bbc1668..662e370 100644
--- a/neurons/validator.py
+++ b/neurons/validator.py
@@ -33,6 +33,7 @@
 import constants
 from taoverse.metagraph import utils as metagraph_utils
 from taoverse.metagraph.metagraph_syncer import MetagraphSyncer
+from taoverse.model import utils as model_utils
 from taoverse.model.competition import utils as competition_utils
 from taoverse.model.competition.competition_tracker import CompetitionTracker
 from taoverse.model.competition.data import Competition
@@ -781,7 +782,7 @@ async def run_step(self):
             ):
                 try:
                     bt.logging.info(
-                        f"Evaluating uid: {uid_i} / hotkey: {hotkey} with metadata: {model_i_metadata}."
+                        f"Evaluating uid: {uid_i} / hotkey: {hotkey} with metadata: {model_i_metadata} and hf_url: {model_utils.get_hf_url(model_i_metadata)}."
                     )
 
                     # Update the block this uid last updated their model.

From bdb2a3b1e2e3fd3a85726c20c2a6f6c56c2df3df Mon Sep 17 00:00:00 2001
From: Sid <sid.data.universe@gmail.com>
Date: Sun, 18 Aug 2024 18:44:37 -0700
Subject: [PATCH 03/10] Also include hf_url in the step_log.

---
 neurons/validator.py | 11 +++++++++++
 1 file changed, 11 insertions(+)

diff --git a/neurons/validator.py b/neurons/validator.py
index 662e370..77b5173 100644
--- a/neurons/validator.py
+++ b/neurons/validator.py
@@ -703,9 +703,12 @@ async def run_step(self):
                 time.sleep(300)
             return
 
+        # TODO: Consider condensing the following + competition id into a uid to metadata map.
         # Keep track of which block this uid last updated their model.
         # Default to an infinite block if we can't retrieve the metadata for the miner.
         uid_to_block = defaultdict(lambda: math.inf)
+        # Keep track of the hugging face url for this uid.
+        uid_to_hf_url = defaultdict(lambda: "unknown")
 
         bt.logging.trace(f"Current block: {cur_block}")
 
@@ -787,6 +790,8 @@ async def run_step(self):
 
                     # Update the block this uid last updated their model.
                     uid_to_block[uid_i] = model_i_metadata.block
+                    # Update the hf url for this model.
+                    uid_to_hf_url[uid_i] = model_utils.get_hf_url(model_i_metadata)
 
                     # Get the model locally and evaluate its loss.
                     model_i = None
@@ -888,6 +893,7 @@ async def run_step(self):
                 CompetitionId.B7_MODEL_LOWER_EPSILON,
                 uids,
                 uid_to_block,
+                uid_to_hf_url,
                 uids_to_competition_ids_epsilon_experiment,
                 pages,
                 model_weights_epsilon_experiment,
@@ -953,6 +959,7 @@ async def run_step(self):
             competition.id,
             uids,
             uid_to_block,
+            uid_to_hf_url,
             self._get_uids_to_competition_ids(),
             pages,
             model_weights,
@@ -971,6 +978,7 @@ def log_step(
         competition_id: CompetitionId,
         uids: typing.List[int],
         uid_to_block: typing.Dict[int, int],
+        uid_to_hf_url: typing.Dict[int, str],
         uid_to_competition_id: typing.Dict[int, typing.Optional[int]],
         pages: typing.List[str],
         model_weights: typing.List[float],
@@ -999,6 +1007,7 @@ def log_step(
             step_log["uid_data"][str(uid)] = {
                 "uid": uid,
                 "block": uid_to_block[uid],
+                "hf_url": uid_to_hf_url[uid],
                 "competition_id": uid_to_competition_id[uid],
                 "average_loss": sum(losses_per_uid[uid]) / len(losses_per_uid[uid]),
                 "win_rate": win_rate[uid],
@@ -1015,6 +1024,7 @@ def log_step(
         table.add_column("competition_weights", style="magenta")
         table.add_column("block", style="magenta")
         table.add_column("competition", style="magenta")
+        table.add_column("hugging_face_url", style="magenta")
         for idx, uid in enumerate(uids):
             try:
                 table.add_row(
@@ -1026,6 +1036,7 @@ def log_step(
                     str(round(sub_competition_weights[idx].item(), 4)),
                     str(step_log["uid_data"][str(uid)]["block"]),
                     str(step_log["uid_data"][str(uid)]["competition_id"]),
+                    str(step_log["uid_data"][str(uid)]["hf_url"]),
                 )
             except:
                 pass

From 39fe37e9f7aebffd51833ca63a7cb6d0de60f61d Mon Sep 17 00:00:00 2001
From: Sid <sid.data.universe@gmail.com>
Date: Tue, 20 Aug 2024 16:26:04 -0700
Subject: [PATCH 04/10] Bump bittensor to 6.9.4.

---
 requirements.txt | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/requirements.txt b/requirements.txt
index 4f48ddf..a96638d 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,4 +1,4 @@
-bittensor==6.9.3
+bittensor==6.9.4
 huggingface_hub
 matplotlib
 pydantic==1.10

From 4c4e5e9f089dce8e65c2a7811abecd1aaadcc327 Mon Sep 17 00:00:00 2001
From: Sid <sid.data.universe@gmail.com>
Date: Tue, 20 Aug 2024 19:55:13 -0700
Subject: [PATCH 05/10] Use a config wandb project in the validator wandb
 logging.

---
 neurons/config.py    |  6 ++++++
 neurons/validator.py | 38 ++++++++++++++++++++++++--------------
 2 files changed, 30 insertions(+), 14 deletions(-)

diff --git a/neurons/config.py b/neurons/config.py
index 4e4742e..eeb58d1 100644
--- a/neurons/config.py
+++ b/neurons/config.py
@@ -20,6 +20,12 @@ def validator_config():
         action="store_false",
         help="Turn off wandb logging.",
     )
+    parser.add_argument(
+        "--wandb_project",
+        type=str,
+        default=constants.WANDB_PROJECT,
+        help="The wandb project to log to.",
+    )
     parser.add_argument(
         "--blocks_per_epoch",
         type=int,
diff --git a/neurons/validator.py b/neurons/validator.py
index 376ddbe..c20dfcc 100644
--- a/neurons/validator.py
+++ b/neurons/validator.py
@@ -278,7 +278,7 @@ def _new_wandb_run(self):
         name = "validator-" + str(self.uid) + "-" + run_id
         self.wandb_run = wandb.init(
             name=name,
-            project=constants.WANDB_PROJECT,
+            project=self.config.wandb_project,
             entity="macrocosmos",
             config={
                 "uid": self.uid,
@@ -725,21 +725,25 @@ async def run_step(self):
             pages_per_eval = constants.pages_per_eval_pack
 
         # If the option is set in the config, override
-        pages_per_eval = self.config.pages_per_eval if self.config.pages_per_eval is not None else pages_per_eval
+        pages_per_eval = (
+            self.config.pages_per_eval
+            if self.config.pages_per_eval is not None
+            else pages_per_eval
+        )
 
-        bt.logging.debug(f'Sample packing is set to: {pack_samples}.')
-        bt.logging.debug(f'Number of pages per evaluation step is: {pages_per_eval}')
+        bt.logging.debug(f"Sample packing is set to: {pack_samples}.")
+        bt.logging.debug(f"Number of pages per evaluation step is: {pages_per_eval}")
 
         dataloader = SubsetDataLoader(
             batch_size=constants.batch_size,
             sequence_length=competition.constraints.sequence_length,
-            num_pages= pages_per_eval,
+            num_pages=pages_per_eval,
             tokenizer=tokenizer,
-            pack_samples=pack_samples
-            )
+            pack_samples=pack_samples,
+        )
 
         batches = list(dataloader)
-        bt.logging.debug(f'Number of validation batches is {len(batches)}')
+        bt.logging.debug(f"Number of validation batches is {len(batches)}")
 
         # This is useful for logging to wandb
         pages = dataloader.get_page_names()
@@ -795,7 +799,7 @@ async def run_step(self):
                                 batches,
                                 self.config.device,
                                 tokenizer.eos_token_id,
-                                pack_samples
+                                pack_samples,
                             ),
                             ttl=400,
                             mode="spawn",
@@ -912,7 +916,9 @@ async def run_step(self):
         # If the model has any significant weight, prioritize by weight with greater weights being kept first.
         # Then for the unweighted models, prioritize by win_rate.
         # Use the competition weights from the tracker which also handles moving averages.
-        tracker_competition_weights = self.competition_tracker.get_competition_weights(competition.id)
+        tracker_competition_weights = self.competition_tracker.get_competition_weights(
+            competition.id
+        )
         model_prioritization = {
             uid: (
                 # Add 1 to ensure it is always greater than a win rate.
@@ -952,7 +958,6 @@ async def run_step(self):
             compute_loss_perf,
         )
 
-
         # Increment the number of completed run steps by 1
         self.run_step_count += 1
 
@@ -981,7 +986,9 @@ def log_step(
         }
 
         # The sub-competition weights
-        sub_competition_weights = torch.softmax(model_weights / constants.temperature, dim=0)
+        sub_competition_weights = torch.softmax(
+            model_weights / constants.temperature, dim=0
+        )
 
         for idx, uid in enumerate(uids):
             step_log["uid_data"][str(uid)] = {
@@ -1069,7 +1076,10 @@ def log_step(
                     str(uid): uid_data[str(uid)]["win_total"] for uid in uids
                 },
                 "weight_data": {str(uid): self.weights[uid].item() for uid in uids},
-                "norm_weight_data": {str(uid): sub_competition_weights[i].item() for i, uid in enumerate(uids)},
+                "norm_weight_data": {
+                    str(uid): sub_competition_weights[i].item()
+                    for i, uid in enumerate(uids)
+                },
                 "competition_id": {
                     str(uid): uid_to_competition_id[uid]
                     for uid in uids
@@ -1094,7 +1104,7 @@ def log_step(
                 step=self.last_wandb_step,
             )
 
-            self.last_wandb_step+=1
+            self.last_wandb_step += 1
 
     def _get_uids_to_competition_ids(
         self,

From 76e239e4c383d5301f235a3432017d7d84fac7b3 Mon Sep 17 00:00:00 2001
From: rusticluftig <rusticluftig@gmail.com>
Date: Wed, 21 Aug 2024 19:57:05 -0700
Subject: [PATCH 06/10] Bump transformers version

---
 requirements.txt | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/requirements.txt b/requirements.txt
index 4f48ddf..cece18c 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -7,7 +7,7 @@ rich
 safetensors
 torch
 numpy
-transformers==4.42.0
+transformers==4.44.1
 wandb
 datasets
 flash-attn

From 3427236d8bedb101ec89b99250ee78ea6ab1188f Mon Sep 17 00:00:00 2001
From: Alan Aboudib <alan.aboudib@macrocosmos.ai>
Date: Fri, 23 Aug 2024 18:06:30 +0000
Subject: [PATCH 07/10] bumped version to 4.4.1 and took down stablLm and Phi3

---
 constants/__init__.py | 8 +-------
 1 file changed, 1 insertion(+), 7 deletions(-)

diff --git a/constants/__init__.py b/constants/__init__.py
index 302998c..e0d5ecb 100644
--- a/constants/__init__.py
+++ b/constants/__init__.py
@@ -14,11 +14,9 @@
     GPTNeoXForCausalLM,
     GPTJForCausalLM,
     PhiForCausalLM,
-    Phi3ForCausalLM,
     GemmaForCausalLM,
     Gemma2ForCausalLM,
     Qwen2ForCausalLM,
-    StableLmForCausalLM,
 )
 
 from taoverse.model.competition.data import (
@@ -35,7 +33,7 @@
 # ---------------------------------
 
 # Release
-__version__ = "4.1.0"
+__version__ = "4.1.1"
 
 # Validator schema version
 __validator_version__ = "3.0.0"
@@ -75,8 +73,6 @@
     FalconForCausalLM,
     GPTNeoXForCausalLM,
     GPTJForCausalLM,
-    StableLmForCausalLM,
-    Phi3ForCausalLM,
     Qwen2ForCausalLM,
 }
 ALLOWED_MODEL_TYPES_2 = {
@@ -88,8 +84,6 @@
     PhiForCausalLM,
     GemmaForCausalLM,
     Gemma2ForCausalLM,
-    StableLmForCausalLM,
-    Phi3ForCausalLM,
     Qwen2ForCausalLM,
 }
 

From b3f9e5f3c9635af17236eafda8338efc8170c50e Mon Sep 17 00:00:00 2001
From: Sid <sid.data.universe@gmail.com>
Date: Fri, 23 Aug 2024 10:53:02 -0700
Subject: [PATCH 08/10] Fix table wrapping and bump taoverse.

---
 neurons/validator.py | 38 +++++++++++++++++++-------------------
 requirements.txt     |  2 +-
 2 files changed, 20 insertions(+), 20 deletions(-)

diff --git a/neurons/validator.py b/neurons/validator.py
index 923b60e..23ff066 100644
--- a/neurons/validator.py
+++ b/neurons/validator.py
@@ -707,8 +707,8 @@ async def run_step(self):
         # Keep track of which block this uid last updated their model.
         # Default to an infinite block if we can't retrieve the metadata for the miner.
         uid_to_block = defaultdict(lambda: math.inf)
-        # Keep track of the hugging face url for this uid.
-        uid_to_hf_url = defaultdict(lambda: "unknown")
+        # Keep track of the hugging face repo for this uid.
+        uid_to_hf = defaultdict(lambda: "unknown")
 
         bt.logging.trace(f"Current block: {cur_block}")
 
@@ -790,8 +790,8 @@ async def run_step(self):
 
                     # Update the block this uid last updated their model.
                     uid_to_block[uid_i] = model_i_metadata.block
-                    # Update the hf url for this model.
-                    uid_to_hf_url[uid_i] = model_utils.get_hf_url(model_i_metadata)
+                    # Update the hf repo for this model.
+                    uid_to_hf[uid_i] = model_utils.get_hf_repo_name(model_i_metadata)
 
                     # Get the model locally and evaluate its loss.
                     model_i = None
@@ -893,7 +893,7 @@ async def run_step(self):
                 CompetitionId.B7_MODEL_LOWER_EPSILON,
                 uids,
                 uid_to_block,
-                uid_to_hf_url,
+                uid_to_hf,
                 uids_to_competition_ids_epsilon_experiment,
                 pages,
                 model_weights_epsilon_experiment,
@@ -959,7 +959,7 @@ async def run_step(self):
             competition.id,
             uids,
             uid_to_block,
-            uid_to_hf_url,
+            uid_to_hf,
             self._get_uids_to_competition_ids(),
             pages,
             model_weights,
@@ -978,7 +978,7 @@ def log_step(
         competition_id: CompetitionId,
         uids: typing.List[int],
         uid_to_block: typing.Dict[int, int],
-        uid_to_hf_url: typing.Dict[int, str],
+        uid_to_hf: typing.Dict[int, str],
         uid_to_competition_id: typing.Dict[int, typing.Optional[int]],
         pages: typing.List[str],
         model_weights: typing.List[float],
@@ -1007,7 +1007,7 @@ def log_step(
             step_log["uid_data"][str(uid)] = {
                 "uid": uid,
                 "block": uid_to_block[uid],
-                "hf_url": uid_to_hf_url[uid],
+                "hf": uid_to_hf[uid],
                 "competition_id": uid_to_competition_id[uid],
                 "average_loss": sum(losses_per_uid[uid]) / len(losses_per_uid[uid]),
                 "win_rate": win_rate[uid],
@@ -1015,20 +1015,21 @@ def log_step(
                 "weight": self.weights[uid].item(),
                 "norm_weight": sub_competition_weights[idx].item(),
             }
-        table = Table(title="Step")
+        table = Table(title="Step", expand=True)
         table.add_column("uid", justify="right", style="cyan", no_wrap=True)
-        table.add_column("average_loss", style="magenta")
-        table.add_column("win_rate", style="magenta")
-        table.add_column("win_total", style="magenta")
-        table.add_column("weights", style="magenta")
-        table.add_column("competition_weights", style="magenta")
-        table.add_column("block", style="magenta")
-        table.add_column("competition", style="magenta")
-        table.add_column("hugging_face_url", style="magenta")
+        table.add_column("hf", style="magenta", overflow="fold")
+        table.add_column("average_loss", style="magenta", overflow="fold")
+        table.add_column("win_rate", style="magenta", overflow="fold")
+        table.add_column("win_total", style="magenta", overflow="fold")
+        table.add_column("total_weight", style="magenta", overflow="fold")
+        table.add_column("compe_weight", style="magenta", overflow="fold")
+        table.add_column("block", style="magenta", overflow="fold")
+        table.add_column("comp", style="magenta", overflow="fold")
         for idx, uid in enumerate(uids):
             try:
                 table.add_row(
                     str(uid),
+                    str(step_log["uid_data"][str(uid)]["hf"]),
                     str(round(step_log["uid_data"][str(uid)]["average_loss"], 4)),
                     str(round(step_log["uid_data"][str(uid)]["win_rate"], 4)),
                     str(step_log["uid_data"][str(uid)]["win_total"]),
@@ -1036,7 +1037,6 @@ def log_step(
                     str(round(sub_competition_weights[idx].item(), 4)),
                     str(step_log["uid_data"][str(uid)]["block"]),
                     str(step_log["uid_data"][str(uid)]["competition_id"]),
-                    str(step_log["uid_data"][str(uid)]["hf_url"]),
                 )
             except:
                 pass
@@ -1092,7 +1092,7 @@ def log_step(
                     str(uid): uid_data[str(uid)]["win_total"] for uid in uids
                 },
                 "weight_data": {str(uid): self.weights[uid].item() for uid in uids},
-                "norm_weight_data": {
+                "competition_weight_data": {
                     str(uid): sub_competition_weights[i].item()
                     for i, uid in enumerate(uids)
                 },
diff --git a/requirements.txt b/requirements.txt
index 08fa165..dcfee97 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -11,4 +11,4 @@ transformers==4.44.1
 wandb
 datasets
 flash-attn
-taoverse==1.0.1
+taoverse==1.0.2

From 2384ff60b0b7d0e3557edf2d3741d6a64d267dec Mon Sep 17 00:00:00 2001
From: Sid <sid.data.universe@gmail.com>
Date: Fri, 23 Aug 2024 11:04:41 -0700
Subject: [PATCH 09/10] Add currently unused epsilon_func for taoverse 1.0.2.

---
 constants/__init__.py | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/constants/__init__.py b/constants/__init__.py
index e0d5ecb..d02abbe 100644
--- a/constants/__init__.py
+++ b/constants/__init__.py
@@ -24,6 +24,7 @@
     ModelConstraints,
     NormValidationConstraints,
 )
+from taoverse.model.competition.epsilon import FixedEpsilon
 from competitions.data import CompetitionId
 
 from typing import Dict, List, Tuple
@@ -103,6 +104,7 @@
         allowed_architectures=ALLOWED_MODEL_TYPES_1,
         tokenizer="distilgpt2",
         eval_block_delay=0,
+        epsilon_func=FixedEpsilon(0.005),
     ),
     CompetitionId.B7_MODEL: ModelConstraints(
         max_model_parameter_size=6_900_000_000,
@@ -115,6 +117,7 @@
             "attn_implementation": "flash_attention_2",
         },
         eval_block_delay=0,
+        epsilon_func=FixedEpsilon(0.005),
     ),
     CompetitionId.B3_MODEL: ModelConstraints(
         max_model_parameter_size=3_400_000_000,
@@ -127,6 +130,7 @@
             "attn_implementation": "flash_attention_2",
         },
         eval_block_delay=0,
+        epsilon_func=FixedEpsilon(0.005),
     ),
 }
 

From 288466b74454acabf9a75b9361c0970a6a81e64a Mon Sep 17 00:00:00 2001
From: Sid <sid.data.universe@gmail.com>
Date: Fri, 23 Aug 2024 11:28:13 -0700
Subject: [PATCH 10/10] Bump to 4.1.2 and fix typo.

---
 constants/__init__.py | 2 +-
 neurons/validator.py  | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/constants/__init__.py b/constants/__init__.py
index d02abbe..2838c56 100644
--- a/constants/__init__.py
+++ b/constants/__init__.py
@@ -34,7 +34,7 @@
 # ---------------------------------
 
 # Release
-__version__ = "4.1.1"
+__version__ = "4.1.2"
 
 # Validator schema version
 __validator_version__ = "3.0.0"
diff --git a/neurons/validator.py b/neurons/validator.py
index 23ff066..615eb9b 100644
--- a/neurons/validator.py
+++ b/neurons/validator.py
@@ -1022,7 +1022,7 @@ def log_step(
         table.add_column("win_rate", style="magenta", overflow="fold")
         table.add_column("win_total", style="magenta", overflow="fold")
         table.add_column("total_weight", style="magenta", overflow="fold")
-        table.add_column("compe_weight", style="magenta", overflow="fold")
+        table.add_column("comp_weight", style="magenta", overflow="fold")
         table.add_column("block", style="magenta", overflow="fold")
         table.add_column("comp", style="magenta", overflow="fold")
         for idx, uid in enumerate(uids):