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import dataclasses
from typing import ClassVar, Optional, Type
import bittensor as bt
# The maximum bytes for metadata on the chain.
MAX_METADATA_BYTES = 128
# The length, in bytes, of a git commit hash.
GIT_COMMIT_LENGTH = 40
# The length, in bytes, of a base64 encoded sha256 hash.
SHA256_BASE_64_LENGTH = 44
# The max length, in characters, of the competition id
MAX_COMPETITION_ID_LENGTH = 2
NETUID = 80 # Replace with your specific netui
subtensor = bt.subtensor()
@dataclasses.dataclass(frozen=True)
class ModelId:
"""Uniquely identifies a trained model"""
MAX_REPO_ID_LENGTH: ClassVar[int] = (
MAX_METADATA_BYTES
- GIT_COMMIT_LENGTH
- SHA256_BASE_64_LENGTH
- MAX_COMPETITION_ID_LENGTH
- 4 # separators
)
# Namespace where the model can be found. ex. Hugging Face username/org.
namespace: str
# Name of the model.
name: str
# Identifier for competition
competition_id: int
# When handling a model locally the commit and hash are not necessary.
# Commit must be filled when trying to download from a remote store.
commit: Optional[str] = dataclasses.field(default=None)
# Hash is filled automatically when uploading to or downloading from a remote store.
hash: Optional[str] = dataclasses.field(default=None)
# The secure hash that's used for validation.
secure_hash: Optional[str] = dataclasses.field(default=None)
def to_compressed_str(self) -> str:
"""Returns a compressed string representation."""
return f"{self.namespace}:{self.name}:{self.commit}:{self.secure_hash}:{self.competition_id}"
@classmethod
def from_compressed_str(
cls, cs: str, default_competition_id: int = 0
) -> Type["ModelId"]:
"""Returns an instance of this class from a compressed string representation"""
tokens = cs.split(":")
# This case is for backward compatibility with SN9's 7B competition
# prior to multi-competition support was introduced
if len(tokens) < 5:
competition_id = default_competition_id
hash = tokens[3] if tokens[3] != "None" else None
else:
competition_id = int(tokens[4])
hash = None
return cls(
namespace=tokens[0],
name=tokens[1],
commit=tokens[2] if tokens[2] != "None" else None,
hash=hash,
secure_hash=tokens[3] if tokens[3] != "None" else None,
competition_id=competition_id,
)
def get_model_info(uid):
commitment_data = subtensor.get_commitment(netuid=NETUID, uid=uid)
model_id = ModelId.from_compressed_str(commitment_data)
return model_id.namespace + "/" + model_id.name
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