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All metagraph subtensor methods now use block #2738

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Merged
thewhaleking merged 2 commits into from
Mar 11, 2025
Merged

All metagraph subtensor methods now use block #2738

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47a45c3
Ensures we use block for every metagraph call
thewhaleking Mar 11, 2025
b7ff756
Merge branch 'staging' into fix/thewhaleking/not-querying-metagraph-a…
basfroman Mar 11, 2025
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44 changes: 23 additions & 21 deletions bittensor/core/metagraph.py
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Original file line number Diff line number Diff line change
@@ -1,3 +1,4 @@
import asyncio
import copy
import os
import pickle
Expand Down Expand Up @@ -1397,13 +1398,13 @@ async def sync(

# If not a 'lite' version, compute and set weights and bonds for each neuron
if not lite:
await self._set_weights_and_bonds(subtensor=subtensor)
await self._set_weights_and_bonds(subtensor=subtensor, block=block)

# Fills in the stake associated attributes of a class instance from a chain response.
await self._get_all_stakes_from_chain(block=block)

# apply MetagraphInfo data to instance
await self._apply_metagraph_info()
await self._apply_metagraph_info(block=block)

async def _initialize_subtensor(
self, subtensor: "AsyncSubtensor"
Expand Down Expand Up @@ -1476,9 +1477,7 @@ async def _assign_neurons(
self.neurons = await subtensor.neurons(block=block, netuid=self.netuid)
self.lite = lite

async def _set_weights_and_bonds(
self, subtensor: Optional["AsyncSubtensor"] = None
):
async def _set_weights_and_bonds(self, subtensor: "AsyncSubtensor", block: int):
"""
Computes and sets the weights and bonds for each neuron in the metagraph. This method is responsible for
processing the raw weight and bond data obtained from the network and converting it into a structured format
Expand All @@ -1499,6 +1498,7 @@ async def _set_weights_and_bonds(
[neuron.weights for neuron in self.neurons],
"weights",
subtensor,
block=block,
)
else:
self.weights = self._process_weights_or_bonds(
Expand All @@ -1509,7 +1509,7 @@ async def _set_weights_and_bonds(
)

async def _process_root_weights(
self, data: list, attribute: str, subtensor: "AsyncSubtensor"
self, data: list, attribute: str, subtensor: "AsyncSubtensor", block: int
) -> Union[NDArray, "torch.nn.Parameter"]:
"""
Specifically processes the root weights data for the metagraph. This method is similar to :func:`_process_weights_or_bonds`
Expand All @@ -1530,8 +1530,10 @@ async def _process_root_weights(
self.root_weights = self._process_root_weights(raw_root_weights_data, "weights", subtensor)
"""
data_array = []
n_subnets = await subtensor.get_total_subnets() or 0
subnets = await subtensor.get_subnets()
n_subnets_, subnets = await asyncio.gather(
subtensor.get_total_subnets(block=block), subtensor.get_subnets(block=block)
)
n_subnets = n_subnets_ or 0
for item in data:
if len(item) == 0:
if use_torch():
Expand Down Expand Up @@ -1612,9 +1614,11 @@ async def _get_all_stakes_from_chain(self, block: int):
except (SubstrateRequestException, AttributeError) as e:
logging.debug(e)

async def _apply_metagraph_info(self):
async def _apply_metagraph_info(self, block: int):
"""Retrieves metagraph information for a specific subnet and applies it using a mixin."""
metagraph_info = await self.subtensor.get_metagraph_info(self.netuid)
metagraph_info = await self.subtensor.get_metagraph_info(
self.netuid, block=block
)
if metagraph_info:
self._apply_metagraph_info_mixin(metagraph_info=metagraph_info)

Expand Down Expand Up @@ -1711,13 +1715,13 @@ def sync(

# If not a 'lite' version, compute and set weights and bonds for each neuron
if not lite:
self._set_weights_and_bonds(subtensor=subtensor)
self._set_weights_and_bonds(subtensor=subtensor, block=block)

# Fills in the stake associated attributes of a class instance from a chain response.
self._get_all_stakes_from_chain(block=block)

# apply MetagraphInfo data to instance
self._apply_metagraph_info()
self._apply_metagraph_info(block=block)

def _initialize_subtensor(self, subtensor: "Subtensor") -> "Subtensor":
"""
Expand Down Expand Up @@ -1787,7 +1791,7 @@ def _assign_neurons(self, block: int, lite: bool, subtensor: "Subtensor"):
self.neurons = subtensor.neurons(block=block, netuid=self.netuid)
self.lite = lite

def _set_weights_and_bonds(self, subtensor: Optional["Subtensor"] = None):
def _set_weights_and_bonds(self, block: int, subtensor: "Subtensor"):
"""
Computes and sets the weights and bonds for each neuron in the metagraph. This method is responsible for
processing the raw weight and bond data obtained from the network and converting it into a structured format
Expand All @@ -1804,9 +1808,7 @@ def _set_weights_and_bonds(self, subtensor: Optional["Subtensor"] = None):
"""
if self.netuid == 0:
self.weights = self._process_root_weights(
[neuron.weights for neuron in self.neurons],
"weights",
subtensor,
[neuron.weights for neuron in self.neurons], "weights", subtensor, block
)
else:
self.weights = self._process_weights_or_bonds(
Expand All @@ -1817,7 +1819,7 @@ def _set_weights_and_bonds(self, subtensor: Optional["Subtensor"] = None):
)

def _process_root_weights(
self, data: list, attribute: str, subtensor: "Subtensor"
self, data: list, attribute: str, subtensor: "Subtensor", block: int
) -> Union[NDArray, "torch.nn.Parameter"]:
"""
Specifically processes the root weights data for the metagraph. This method is similar to :func:`_process_weights_or_bonds`
Expand All @@ -1838,8 +1840,8 @@ def _process_root_weights(
self.root_weights = self._process_root_weights(raw_root_weights_data, "weights", subtensor)
"""
data_array = []
n_subnets = subtensor.get_total_subnets() or 0
subnets = subtensor.get_subnets()
n_subnets = subtensor.get_total_subnets(block=block) or 0
subnets = subtensor.get_subnets(block=block)
for item in data:
if len(item) == 0:
if use_torch():
Expand Down Expand Up @@ -1920,9 +1922,9 @@ def _get_all_stakes_from_chain(self, block: int):
except (SubstrateRequestException, AttributeError) as e:
logging.debug(e)

def _apply_metagraph_info(self):
def _apply_metagraph_info(self, block: int):
"""Retrieves metagraph information for a specific subnet and applies it using a mixin."""
metagraph_info = self.subtensor.get_metagraph_info(self.netuid)
metagraph_info = self.subtensor.get_metagraph_info(self.netuid, block=block)
if metagraph_info:
self._apply_metagraph_info_mixin(metagraph_info=metagraph_info)

Expand Down
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