mirror of
https://github.com/huggingface/lerobot.git
synced 2026-07-24 18:26:11 +00:00
ZibinDong
255 lines
10 KiB
Python
255 lines
10 KiB
Python
#!/usr/bin/env python
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# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import inspect
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import typing
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from pathlib import Path
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import pytest
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import torch
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from torch import nn
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from lerobot.configs import FeatureType, PolicyFeature
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from lerobot.policies.fastwam.configuration_fastwam import FastWAMConfig
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from lerobot.policies.fastwam.modeling_fastwam import FastWAMPolicy
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from lerobot.policies.fastwam.processor_fastwam import make_fastwam_pre_post_processors
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from lerobot.utils.constants import OBS_STATE
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ROOT = Path(__file__).resolve().parents[3]
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def test_package_init_exports_required_symbols():
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init_source = (ROOT / "src" / "lerobot" / "policies" / "fastwam" / "__init__.py").read_text()
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assert "FastWAMConfig" in init_source
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assert "make_fastwam_pre_post_processors" in init_source
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def test_policy_config_is_exported_from_public_policies_package():
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import lerobot.policies as policies
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assert policies.FastWAMConfig is FastWAMConfig
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assert "FastWAMConfig" in policies.__all__
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def test_fastwam_policy_docs_are_registered():
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readme_path = ROOT / "src" / "lerobot" / "policies" / "fastwam" / "README.md"
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wan_readme_path = ROOT / "src" / "lerobot" / "policies" / "fastwam" / "wan" / "README.md"
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policy_readme_path = ROOT / "docs" / "source" / "policy_fastwam_README.md"
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guide_path = ROOT / "docs" / "source" / "fastwam.mdx"
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toctree_path = ROOT / "docs" / "source" / "_toctree.yml"
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assert readme_path.is_symlink()
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assert readme_path.resolve() == policy_readme_path.resolve()
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assert wan_readme_path.exists()
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wan_readme = wan_readme_path.read_text()
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assert "Wan-Video/Wan2.2" in wan_readme
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assert "42bf4cfaa384bc21833865abc2f9e6c0e67233dc" in wan_readme
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assert policy_readme_path.exists()
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assert guide_path.exists()
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assert "local: fastwam" in toctree_path.read_text()
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def test_wan_backbone_code_is_isolated_from_lerobot_adapter():
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wan_dir = ROOT / "src" / "lerobot" / "policies" / "fastwam" / "wan"
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assert (wan_dir / "modules" / "attention.py").exists()
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assert (wan_dir / "modules" / "model.py").exists()
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assert (wan_dir / "modules" / "t5.py").exists()
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assert (wan_dir / "modules" / "tokenizers.py").exists()
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assert (wan_dir / "modules" / "vae2_1.py").exists()
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assert (wan_dir / "modules" / "vae2_2.py").exists()
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assert (wan_dir / "utils" / "fm_solvers.py").exists()
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assert (wan_dir / "utils" / "fm_solvers_unipc.py").exists()
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assert (wan_dir.parent / "wan_video_dit.py").exists()
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assert (wan_dir.parent / "wan_adapters.py").exists()
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assert (wan_dir.parent / "wan_components.py").exists()
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assert not (wan_dir / "wan_video_dit.py").exists()
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assert not (wan_dir / "wan_adapters.py").exists()
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assert not (wan_dir / "wan_components.py").exists()
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def test_fastwam_text_encoder_uses_upstream_wan_modules_directly():
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fastwam_dir = ROOT / "src" / "lerobot" / "policies" / "fastwam"
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modular_source = (fastwam_dir / "modular_fastwam.py").read_text()
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components_source = (fastwam_dir / "wan_components.py").read_text()
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assert not (fastwam_dir / "wan_video_text_encoder.py").exists()
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assert "from .wan.modules.t5 import umt5_xxl" in components_source
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assert "from .wan.modules.tokenizers import HuggingfaceTokenizer" in components_source
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assert "WAN_T5_ENCODER_KWARGS" not in components_source
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assert "wan_video_text_encoder" not in modular_source
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def test_fastwam_vae_reuses_upstream_wan_modules():
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fastwam_dir = ROOT / "src" / "lerobot" / "policies" / "fastwam"
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vae_source = (fastwam_dir / "wan_adapters.py").read_text()
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assert not (fastwam_dir / "wan_video_vae.py").exists()
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assert "from .wan.modules.vae2_2 import Wan2_2_VAE" in vae_source
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assert "mean = [" not in vae_source
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assert "std = [" not in vae_source
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assert "class Encoder3d_38" not in vae_source
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assert "class Decoder3d_38" not in vae_source
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assert "class VideoVAE38_" not in vae_source
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def test_fastwam_component_loading_uses_fixed_wan_checkpoint_layout():
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modular_source = (ROOT / "src" / "lerobot" / "policies" / "fastwam" / "modular_fastwam.py").read_text()
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modeling_source = (ROOT / "src" / "lerobot" / "policies" / "fastwam" / "modeling_fastwam.py").read_text()
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components_source = (ROOT / "src" / "lerobot" / "policies" / "fastwam" / "wan_components.py").read_text()
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assert "class ModelConfig" not in modular_source
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assert "def load_state_dict" not in modular_source
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assert "WAN22_MODEL_REGISTRY" not in modular_source
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assert "class ModelConfig" not in components_source
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assert "class WanComponentSource" not in components_source
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assert "def load_state_dict" not in components_source
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assert "WAN22_MODEL_REGISTRY" not in components_source
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assert "hash_model_file" not in components_source
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assert "_resolve_component_sources" not in components_source
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assert "origin_file_pattern" not in components_source
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assert "inspect.signature" not in components_source
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assert "class FastWAMWanComponentPaths" not in modeling_source
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assert "def _first_existing" not in modeling_source
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assert "def _missing_wan_component_names" not in modeling_source
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assert "WAN_T5_CHECKPOINT" in components_source
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assert "WAN_VAE_CHECKPOINT" in components_source
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assert "WAN_DIT_PATTERN" in components_source
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def test_fastwam_dit_reuses_upstream_wan_primitives():
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dit_source = (ROOT / "src" / "lerobot" / "policies" / "fastwam" / "wan_video_dit.py").read_text()
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assert "from .wan.modules.model import" in dit_source
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assert "WanModel" in dit_source
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for duplicated_symbol in [
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"def flash_attention(",
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"def sinusoidal_embedding_1d(",
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"def rope_apply(",
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"def unpatchify(",
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"def _dense_video_freqs(",
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"class RMSNorm(",
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"class SelfAttention(",
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"class CrossAttention(",
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"class Head(",
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]:
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assert duplicated_symbol not in dit_source
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def test_fastwam_inference_schedule_reuses_upstream_wan_sigmas():
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modular_source = (ROOT / "src" / "lerobot" / "policies" / "fastwam" / "modular_fastwam.py").read_text()
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assert "def _get_wan_sampling_sigmas" in modular_source
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assert "from .wan.utils.fm_solvers import get_sampling_sigmas" in modular_source
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assert "_get_wan_sampling_sigmas(num_inference_steps, shift)" in modular_source
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def test_policy_config_rejects_missing_required_image_and_action_features():
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with pytest.raises(ValueError, match="image feature"):
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FastWAMConfig(
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input_features={OBS_STATE: PolicyFeature(type=FeatureType.STATE, shape=(8,))},
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)
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with pytest.raises(ValueError, match="action"):
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FastWAMConfig(
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output_features={"not_action": PolicyFeature(type=FeatureType.ACTION, shape=(7,))},
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)
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def test_policy_init_calls_validate_features_even_for_prebuilt_configs(monkeypatch):
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cfg = FastWAMConfig(action_dim=3, proprio_dim=2, action_horizon=4, n_action_steps=2)
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calls = []
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def record_validate_features():
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calls.append("called")
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monkeypatch.setattr(cfg, "validate_features", record_validate_features)
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monkeypatch.setattr(
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FastWAMPolicy,
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"_build_core_model",
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lambda self, config: nn.Linear(1, 1),
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)
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FastWAMPolicy(cfg)
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assert calls == ["called"]
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def test_required_policy_entrypoints_exist_with_discoverable_names():
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assert FastWAMPolicy.config_class is FastWAMConfig
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assert FastWAMPolicy.name == "fastwam"
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assert callable(FastWAMPolicy.reset)
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assert callable(FastWAMPolicy.get_optim_params)
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assert callable(FastWAMPolicy.predict_action_chunk)
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assert callable(FastWAMPolicy.select_action)
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assert callable(FastWAMPolicy.forward)
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assert callable(make_fastwam_pre_post_processors)
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assert make_fastwam_pre_post_processors.__name__ == "make_fastwam_pre_post_processors"
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def test_policy_constructor_and_forward_match_byo_template_contract():
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init_signature = inspect.signature(FastWAMPolicy.__init__)
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assert "dataset_stats" in init_signature.parameters
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assert "core_model" not in init_signature.parameters
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assert typing.get_type_hints(FastWAMPolicy.forward)["return"] == dict[str, torch.Tensor]
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def test_saved_config_round_trips_policy_features(tmp_path):
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cfg = FastWAMConfig(action_dim=7, proprio_dim=8, image_size=(224, 448))
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cfg.save_pretrained(tmp_path)
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loaded = FastWAMConfig.from_pretrained(tmp_path)
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assert loaded.type == "fastwam"
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assert loaded.image_features["observation.images.image"].type == FeatureType.VISUAL
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assert loaded.action_feature.shape == (7,)
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assert loaded.robot_state_feature.shape == (8,)
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def test_config_from_pretrained_ignores_unknown_fields(tmp_path):
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cfg = FastWAMConfig()
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cfg.save_pretrained(tmp_path)
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config_path = tmp_path / "config.json"
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payload = config_path.read_text()
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payload = payload.replace(
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'"torch_dtype": "bfloat16"',
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'"torch_dtype": "bfloat16",\n "unknown_fastwam_field": true',
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)
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config_path.write_text(payload)
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loaded = FastWAMConfig.from_pretrained(tmp_path)
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assert loaded.type == "fastwam"
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assert not hasattr(loaded, "unknown_fastwam_field")
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def test_config_from_pretrained_does_not_use_non_wan22_tokenizer_repo_id(tmp_path):
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cfg = FastWAMConfig()
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cfg.save_pretrained(tmp_path)
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config_path = tmp_path / "config.json"
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payload = config_path.read_text()
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payload = payload.replace(
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'"tokenizer_model_id": "Wan-AI/Wan2.2-TI2V-5B"',
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'"tokenizer_model_id": "somebody/old-tokenizer"',
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)
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config_path.write_text(payload)
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loaded = FastWAMConfig.from_pretrained(tmp_path)
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assert loaded.tokenizer_model_id == "Wan-AI/Wan2.2-TI2V-5B"
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