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Remove redundant config_name arg from JAX->Pytorch model conversion script #915

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Remove redundant config_name arg from JAX->Pytorch model conversion script #915

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28 changes: 15 additions & 13 deletions examples/convert_jax_model_to_pytorch.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,11 +9,9 @@
Usage:
# Just inspect keys:
python examples/convert_jax_model_to_pytorch.py --checkpoint_dir /path/to/checkpoint --inspect_only
python examples/convert_jax_model_to_pytorch.py --checkpoint_dir /path/to/checkpoint --inspect_only

# Convert to PyTorch:
python examples/convert_jax_model_to_pytorch.py --checkpoint_dir /path/to/checkpoint --output_path /path/to/output
python examples/convert_jax_model_to_pytorch.py --checkpoint_dir /path/to/checkpoint --output_path /path/to/output

Example:
# pi0_droid
Expand Down Expand Up @@ -44,7 +42,6 @@
import openpi.models.pi0_config
import openpi.models_pytorch.pi0_pytorch
from openpi.training import utils
import openpi.training.config as _config


def slice_paligemma_state_dict(state_dict, config):
Expand Down Expand Up @@ -419,24 +416,33 @@ def load_jax_model_and_print_keys(checkpoint_dir: str):
print(utils.array_tree_to_info(metadata))


def convert_pi0_checkpoint(
checkpoint_dir: str, precision: str, output_path: str, model_config: openpi.models.pi0_config.Pi0Config
):
def convert_pi0_checkpoint(checkpoint_dir: str, precision: str, output_path: str):
"""
Convert PI0 JAX checkpoint to PyTorch format.

Args:
checkpoint_dir: Path to the JAX checkpoint
precision: Model precision (float32, bfloat16, float16)
output_path: Path to save the converted PyTorch model
model_config: Model config
"""
print(f"Converting PI0 checkpoint from {checkpoint_dir} to {output_path}")
print(f"Model config: {model_config}")

# Break down orbax ckpts by restoring via JAX to respect dtype
initial_params = slice_initial_orbax_checkpoint(checkpoint_dir=checkpoint_dir, restore_precision="float32")

# Detect pi05 from checkpoint contents: pi05 uses time_mlp_in/out instead of state_proj
is_pi05 = "time_mlp_in" in initial_params["projection_params"]
print(f"Auto-detected model type: {'Pi0.5' if is_pi05 else 'Pi0'}")

# Infer action_dim from action_in_proj kernel shape: [action_dim, expert_hidden_size]
action_in_proj_kernel = initial_params["projection_params"]["action_in_proj"]["kernel"]
if isinstance(action_in_proj_kernel, dict):
action_in_proj_kernel = action_in_proj_kernel["value"]
action_dim = action_in_proj_kernel.shape[0]
print(f"Auto-detected action_dim: {action_dim}")

model_config = openpi.models.pi0_config.Pi0Config(pi05=is_pi05, action_dim=action_dim)

# Process projection params
if model_config.pi05:
keys = [
Expand Down Expand Up @@ -557,7 +563,6 @@ def __init__(self):

def main(
checkpoint_dir: str,
config_name: str,
output_path: str | None = None,
precision: Literal["float32", "bfloat16", "float16"] = "bfloat16",
*,
Expand All @@ -571,16 +576,13 @@ def main(
precision: Precision for model conversion
inspect_only: Only inspect parameter keys, don't convert
"""
model_config = _config.get_config(config_name).model
if not isinstance(model_config, openpi.models.pi0_config.Pi0Config):
raise ValueError(f"Config {config_name} is not a Pi0Config")
if inspect_only:
load_jax_model_and_print_keys(checkpoint_dir)
else:
if not output_path:
print("Error: --output_path is required for conversion. Use --inspect_only to only view keys.")
return
convert_pi0_checkpoint(checkpoint_dir, precision, output_path, model_config)
convert_pi0_checkpoint(checkpoint_dir, precision, output_path)


if __name__ == "__main__":
Expand Down