From 6cafb4b6d960459b2c3e081d06e2d8e11d26f4e3 Mon Sep 17 00:00:00 2001
From: opentaco <opentaco@protonmail.com>
Date: Wed, 29 Mar 2023 13:41:54 +0200
Subject: [PATCH 1/3] Change u16 weight normalization to max-upscaling

Use full u16 bitwidth so that max_weight=U16_MAX, then rely on subtensor epoch to properly normalize weights in I32F32. This means that weights submission extrinsic to subtensor does not have to be pre-normalized.
---
 bittensor/utils/weight_utils.py | 8 ++++++--
 1 file changed, 6 insertions(+), 2 deletions(-)

diff --git a/bittensor/utils/weight_utils.py b/bittensor/utils/weight_utils.py
index c89d6a9c34..b96b5a21a7 100644
--- a/bittensor/utils/weight_utils.py
+++ b/bittensor/utils/weight_utils.py
@@ -80,7 +80,8 @@ def convert_weight_uids_and_vals_to_tensor( n: int, uids: List[int], weights: Li
     """
     row_weights = torch.zeros( [ n ], dtype=torch.float32 )
     for uid_j, wij in list(zip( uids, weights )):
-        row_weights[ uid_j ] = float( wij ) / float(U16_MAX)
+        row_weights[ uid_j ] = float( wij )  # assumes max-upscaled values (w_max = U16_MAX).
+    row_weights /= row_weights.sum()  # normalize
     return row_weights
 
 def convert_bond_uids_and_vals_to_tensor( n: int, uids: List[int], bonds: List[int] ) -> 'torch.LongTensor':
@@ -119,6 +120,8 @@ def convert_weights_and_uids_for_emit( uids: torch.LongTensor, weights: torch.Fl
     uids = uids.tolist()
     if min(weights) < 0:
         raise ValueError('Passed weight is negative cannot exist on chain {}'.format(weights))
+    if max(weights) == 0:
+        raise ValueError('Passed weight all zero cannot exist on chain {}'.format(weights))
     if min(uids) < 0:
         raise ValueError('Passed uid is negative cannot exist on chain {}'.format(uids))
     if len(uids) != len(weights):
@@ -126,7 +129,8 @@ def convert_weights_and_uids_for_emit( uids: torch.LongTensor, weights: torch.Fl
     if sum(weights) == 0:
         return [],[] # Nothing to set on chain.
     else:
-        weights = [ float(value) / sum(weights) for value in weights] # Initial normalization.
+        max_weight = float(max(weights))
+        weights = [float(value) / max_weight for value in weights]  # max-upscale values (max_weight = 1).
 
     weight_vals = []
     weight_uids = []

From fc0dabba38822c673668eff1e50198151b0e6b6a Mon Sep 17 00:00:00 2001
From: opentaco <opentaco@protonmail.com>
Date: Wed, 29 Mar 2023 17:32:41 +0200
Subject: [PATCH 2/3] Skip zero sum in weight conversion

---
 bittensor/utils/weight_utils.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/bittensor/utils/weight_utils.py b/bittensor/utils/weight_utils.py
index b96b5a21a7..58179d7b8e 100644
--- a/bittensor/utils/weight_utils.py
+++ b/bittensor/utils/weight_utils.py
@@ -81,7 +81,9 @@ def convert_weight_uids_and_vals_to_tensor( n: int, uids: List[int], weights: Li
     row_weights = torch.zeros( [ n ], dtype=torch.float32 )
     for uid_j, wij in list(zip( uids, weights )):
         row_weights[ uid_j ] = float( wij )  # assumes max-upscaled values (w_max = U16_MAX).
-    row_weights /= row_weights.sum()  # normalize
+    row_sum = row_weights.sum()
+    if row_sum > 0:
+        row_weights /= row_sum  # normalize
     return row_weights
 
 def convert_bond_uids_and_vals_to_tensor( n: int, uids: List[int], bonds: List[int] ) -> 'torch.LongTensor':
@@ -120,8 +122,6 @@ def convert_weights_and_uids_for_emit( uids: torch.LongTensor, weights: torch.Fl
     uids = uids.tolist()
     if min(weights) < 0:
         raise ValueError('Passed weight is negative cannot exist on chain {}'.format(weights))
-    if max(weights) == 0:
-        raise ValueError('Passed weight all zero cannot exist on chain {}'.format(weights))
     if min(uids) < 0:
         raise ValueError('Passed uid is negative cannot exist on chain {}'.format(uids))
     if len(uids) != len(weights):

From 820c6f7a2410591a0de8d9aaa2c9c3aba17b509d Mon Sep 17 00:00:00 2001
From: opentaco <opentaco@protonmail.com>
Date: Wed, 5 Apr 2023 11:00:17 +0200
Subject: [PATCH 3/3] Round u16 weights

---
 bittensor/utils/weight_utils.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/bittensor/utils/weight_utils.py b/bittensor/utils/weight_utils.py
index 58179d7b8e..5f5c8b9dc8 100644
--- a/bittensor/utils/weight_utils.py
+++ b/bittensor/utils/weight_utils.py
@@ -135,7 +135,7 @@ def convert_weights_and_uids_for_emit( uids: torch.LongTensor, weights: torch.Fl
     weight_vals = []
     weight_uids = []
     for i, (weight_i, uid_i) in enumerate(list(zip(weights, uids))):
-        uint16_val = int(float(weight_i) * int(U16_MAX))  # convert to int representation.
+        uint16_val = round(float(weight_i) * int(U16_MAX))  # convert to int representation.
 
         # Filter zeros
         if uint16_val != 0: # Filter zeros