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import json
from collections import OrderedDict
from io import BytesIO
import safetensors
from safetensors import safe_open
from info import software_meta
from toolkit.train_tools import addnet_hash_legacy
from toolkit.train_tools import addnet_hash_safetensors
def get_meta_for_safetensors(meta: OrderedDict, name=None, add_software_info=True) -> OrderedDict:
# stringify the meta and reparse OrderedDict to replace [name] with name
meta_string = json.dumps(meta)
if name is not None:
meta_string = meta_string.replace("[name]", name)
save_meta = json.loads(meta_string, object_pairs_hook=OrderedDict)
if add_software_info:
save_meta["software"] = software_meta
# safetensors can only be one level deep
for key, value in save_meta.items():
# if not float, int, bool, or str, convert to json string
if not isinstance(value, str):
save_meta[key] = json.dumps(value)
# add the pt format
save_meta["format"] = "pt"
return save_meta
def add_model_hash_to_meta(state_dict, meta: OrderedDict) -> OrderedDict:
"""Precalculate the model hashes needed by sd-webui-additional-networks to
save time on indexing the model later."""
# Because writing user metadata to the file can change the result of
# sd_models.model_hash(), only retain the training metadata for purposes of
# calculating the hash, as they are meant to be immutable
metadata = {k: v for k, v in meta.items() if k.startswith("ss_")}
bytes = safetensors.torch.save(state_dict, metadata)
b = BytesIO(bytes)
model_hash = addnet_hash_safetensors(b)
legacy_hash = addnet_hash_legacy(b)
meta["sshs_model_hash"] = model_hash
meta["sshs_legacy_hash"] = legacy_hash
return meta
def add_base_model_info_to_meta(
meta: OrderedDict,
base_model: str = None,
is_v1: bool = False,
is_v2: bool = False,
is_xl: bool = False,
) -> OrderedDict:
if base_model is not None:
meta['ss_base_model'] = base_model
elif is_v2:
meta['ss_v2'] = True
meta['ss_base_model_version'] = 'sd_2.1'
elif is_xl:
meta['ss_base_model_version'] = 'sdxl_1.0'
else:
# default to v1.5
meta['ss_base_model_version'] = 'sd_1.5'
return meta
def parse_metadata_from_safetensors(meta: OrderedDict) -> OrderedDict:
parsed_meta = OrderedDict()
for key, value in meta.items():
try:
parsed_meta[key] = json.loads(value)
except json.decoder.JSONDecodeError:
parsed_meta[key] = value
return parsed_meta
def load_metadata_from_safetensors(file_path: str) -> OrderedDict:
try:
with safe_open(file_path, framework="pt") as f:
metadata = f.metadata()
return parse_metadata_from_safetensors(metadata)
except Exception as e:
print(f"Error loading metadata from {file_path}: {e}")
return OrderedDict()
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