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Make eqv2 old to hydra converter work with old old configs :'( #856

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merged 3 commits into from
Oct 25, 2024
Merged

Make eqv2 old to hydra converter work with old old configs :'( #856

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f489105
make it work with old checkpoints
misko Sep 17, 2024
93a40f0
Merge branch 'main' into support_old_equiv2_model_surgery_script
misko Oct 4, 2024
a1f646f
Merge branch 'main' into support_old_equiv2_model_surgery_script
misko Oct 23, 2024
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20 changes: 14 additions & 6 deletions src/fairchem/core/models/equiformer_v2/eqv2_to_eqv2_hydra.py
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Original file line number Diff line number Diff line change
Expand Up @@ -17,22 +17,30 @@ def convert_checkpoint_and_config_to_hydra(
new_checkpoint_fn
), "Output checkpoint cannot already exist!"

def remove_module_prefix(x):
while x[: len("module.")] == "module.":
x = x[len("module.") :]
return x

def eqv2_state_dict_to_hydra_state_dict(eqv2_state_dict):
hydra_state_dict = OrderedDict()
for og_key in list(eqv2_state_dict.keys()):
key_without_module = remove_module_prefix(og_key)
if "force_block" in og_key or "energy_block" in og_key:
key = og_key.replace(
key = "module." + key_without_module.replace(
"force_block", "output_heads.forces.force_block"
).replace("energy_block", "output_heads.energy.energy_block")
else:
offset = 0
if og_key[: len("module.")] == "module.":
offset += len("module.")
key = og_key[:offset] + "backbone." + og_key[offset:]
key = "module.backbone." + key_without_module
hydra_state_dict[key] = eqv2_state_dict[og_key]
return hydra_state_dict

def convert_configs_to_hydra(yaml_config, checkpoint_config):
if isinstance(checkpoint_config["model"], str):
name = checkpoint_config["model"]
checkpoint_config["model"] = checkpoint_config.pop("model_attributes")
checkpoint_config["model"]["name"] = name

new_model_config = {
"name": "hydra",
"backbone": checkpoint_config["model"].copy(),
Expand Down Expand Up @@ -80,7 +88,7 @@ def convert_configs_to_hydra(yaml_config, checkpoint_config):
checkpoint["state_dict"]
)
for key in ["ema", "optimizer", "scheduler"]:
new_checkpoint.pop(key)
new_checkpoint.pop(key, None)

# write output
torch.save(new_checkpoint, new_checkpoint_fn)
Expand Down