mirror of
https://github.com/huggingface/lerobot.git
synced 2026-07-07 18:11:50 +00:00
updating uv lock and linting
This commit is contained in:
Maxime Ellerbach
@@ -120,13 +120,17 @@ def _generate_robotwin_official_instruction(task_name: str, env: Any) -> str:
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fallback = task_name.replace("_", " ")
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episode_info = _robotwin_blocks_episode_info(task_name, env)
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if episode_info is None:
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logger.warning("Official RoboTwin instruction is not implemented for task=%s; using %r.", task_name, fallback)
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logger.warning(
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"Official RoboTwin instruction is not implemented for task=%s; using %r.", task_name, fallback
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)
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return fallback
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try:
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from description.utils.generate_episode_instructions import generate_episode_descriptions
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except Exception:
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logger.warning("Failed to import RoboTwin official instruction generator; using %r.", fallback, exc_info=True)
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logger.warning(
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"Failed to import RoboTwin official instruction generator; using %r.", fallback, exc_info=True
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)
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return fallback
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instruction_type = os.environ.get(OFFICIAL_INSTRUCTION_TYPE_ENV, "seen")
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@@ -137,7 +141,9 @@ def _generate_robotwin_official_instruction(task_name: str, env: Any) -> str:
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results = generate_episode_descriptions(task_name, [episode_info], max_descriptions=max_descriptions)
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if not results:
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logger.warning("RoboTwin generated no official instructions for task=%s; using %r.", task_name, fallback)
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logger.warning(
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"RoboTwin generated no official instructions for task=%s; using %r.", task_name, fallback
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)
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return fallback
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options = results[0].get(instruction_type) or results[0].get("seen") or results[0].get("unseen")
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@@ -1925,9 +1925,7 @@ class LingBotVAPolicy(PreTrainedPolicy):
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z_dim = vae.config.z_dim
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vae_device = next(vae.parameters()).device
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latents = latents.to(device=vae_device, dtype=vae.dtype)
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latents = denormalize_latents(
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latents, vae.config.latents_mean, vae.config.latents_std, z_dim
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)
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latents = denormalize_latents(latents, vae.config.latents_mean, vae.config.latents_std, z_dim)
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video = vae.decode(latents, return_dict=False)[0] # [B, C, F, H, W] in [-1, 1]
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video = (video.float().clamp(-1, 1) + 1.0) / 2.0
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video = (video[0].permute(1, 2, 3, 0) * 255.0).round().to(torch.uint8) # [F, H, W, C]
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@@ -320,7 +320,9 @@ def rollout(
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elif "is_success" in info:
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is_success = info["is_success"]
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successes = (
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is_success.tolist() if hasattr(is_success, "tolist") else [bool(is_success)] * env.num_envs
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is_success.tolist()
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if hasattr(is_success, "tolist")
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else [bool(is_success)] * env.num_envs
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)
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else:
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successes = [False] * env.num_envs
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@@ -59,7 +59,7 @@ wheels = [
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[[package]]
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version = "1.13.0"
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source = { registry = "https://pypi.org/simple" }
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dependencies = [
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{ name = "huggingface-hub" },
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@@ -71,9 +71,9 @@ dependencies = [
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{ name = "torch", version = "2.11.0", source = { registry = "https://pypi.org/simple" }, marker = "sys_platform != 'linux'" },
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{ name = "torch", version = "2.11.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "sys_platform == 'linux'" },
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]
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@@ -1777,7 +1786,7 @@ wheels = [
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@@ -1785,14 +1794,14 @@ dependencies = [
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@@ -3140,6 +3241,7 @@ requires-dist = [
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Reference in New Issue
Block a user