admin/lerobot
1
0
Fork 0
mirror of https://github.com/huggingface/lerobot.git synced 2026-07-25 02:36:11 +00:00
Code Issues Packages Projects Releases Wiki Activity

[HIL-SERL]Remove overstrict pre-commit modifications (#1028)

Browse Source
This commit is contained in:
Adil Zouitine
2025-04-24 13:48:52 +02:00
committed by GitHub
parent 671ac3411f
commit c58b504a9e
47 changed files with 163 additions and 757 deletions
Download Patch File Download Diff File Expand all files Collapse all files
lerobot/common/policies/diffusion/modeling_diffusion.py
+6 -21
View File
@@ -209,10 +209,7 @@ class DiffusionModel(nn.Module):
# ========= inference ============
def conditional_sample(
self,
batch_size: int,
global_cond: Tensor | None = None,
generator: torch.Generator | None = None,
self, batch_size: int, global_cond: Tensor | None = None, generator: torch.Generator | None = None
) -> Tensor:
device = get_device_from_parameters(self)
dtype = get_dtype_from_parameters(self)
@@ -257,10 +254,7 @@ class DiffusionModel(nn.Module):
# Separate batch and sequence dims back out. The camera index dim gets absorbed into the
# feature dim (effectively concatenating the camera features).
img_features = einops.rearrange(
img_features_list,
"(n b s) ... -> b s (n ...)",
b=batch_size,
s=n_obs_steps,
img_features_list, "(n b s) ... -> b s (n ...)", b=batch_size, s=n_obs_steps
)
else:
# Combine batch, sequence, and "which camera" dims before passing to shared encoder.
@@ -270,10 +264,7 @@ class DiffusionModel(nn.Module):
# Separate batch dim and sequence dim back out. The camera index dim gets absorbed into the
# feature dim (effectively concatenating the camera features).
img_features = einops.rearrange(
img_features,
"(b s n) ... -> b s (n ...)",
b=batch_size,
s=n_obs_steps,
img_features, "(b s n) ... -> b s (n ...)", b=batch_size, s=n_obs_steps
)
global_cond_feats.append(img_features)
@@ -524,9 +515,7 @@ class DiffusionRgbEncoder(nn.Module):
def _replace_submodules(
root_module: nn.Module,
predicate: Callable[[nn.Module], bool],
func: Callable[[nn.Module], nn.Module],
root_module: nn.Module, predicate: Callable[[nn.Module], bool], func: Callable[[nn.Module], nn.Module]
) -> nn.Module:
"""
Args:
@@ -644,14 +633,10 @@ class DiffusionConditionalUnet1d(nn.Module):
self.mid_modules = nn.ModuleList(
[
DiffusionConditionalResidualBlock1d(
config.down_dims[-1],
config.down_dims[-1],
**common_res_block_kwargs,
config.down_dims[-1], config.down_dims[-1], **common_res_block_kwargs
),
DiffusionConditionalResidualBlock1d(
config.down_dims[-1],
config.down_dims[-1],
**common_res_block_kwargs,
config.down_dims[-1], config.down_dims[-1], **common_res_block_kwargs
),
]
)