Merge pull request #10 from Cadene/user/rcadene/2024_03_06_fix_tests

Fix env tests

.github/workflows/test.yml

@@ -87,6 +87,10 @@ jobs:
       #----------------------------------------------
       #               run tests
       #----------------------------------------------
+      - name: Run tests
+        run: |
+          source .venv/bin/activate
+          pytest tests
       - name: Test train pusht end-to-end
         run: |
           source .venv/bin/activate

lerobot/common/datasets/pusht.py

@@ -8,13 +8,13 @@
 import torch
 import torchrl
 import tqdm
+from diffusion_policy.common.replay_buffer import ReplayBuffer as DiffusionPolicyReplayBuffer
+from diffusion_policy.env.pusht.pusht_env import pymunk_to_shapely
 from tensordict import TensorDict
 from torchrl.data.replay_buffers.samplers import SliceSampler
 from torchrl.data.replay_buffers.storages import TensorStorage
 from torchrl.data.replay_buffers.writers import Writer
 
-from diffusion_policy.common.replay_buffer import ReplayBuffer as DiffusionPolicyReplayBuffer
-from diffusion_policy.env.pusht.pusht_env import pymunk_to_shapely
 from lerobot.common.datasets.abstract import AbstractExperienceReplay
 from lerobot.common.datasets.utils import download_and_extract_zip
 
@@ -111,7 +111,7 @@ def __init__(
         )
 
     def _download_and_preproc(self):
-        raw_dir = self.data_dir / "raw"
+        raw_dir = self.data_dir.parent / f"{self.data_dir.name}_raw"
         zarr_path = (raw_dir / PUSHT_ZARR).resolve()
         if not zarr_path.is_dir():
             raw_dir.mkdir(parents=True, exist_ok=True)

lerobot/common/envs/factory.py

@@ -9,6 +9,7 @@ def make_env(cfg, transform=None):
         "image_size": cfg.env.image_size,
         # TODO(rcadene): do we want a specific eval_env_seed?
         "seed": cfg.seed,
+        "num_prev_obs": cfg.n_obs_steps - 1,
     }
 
     if cfg.env.name == "simxarm":

lerobot/common/envs/pusht.py

@@ -2,6 +2,7 @@
 from collections import deque
 from typing import Optional
 
+import einops
 import torch
 from tensordict import TensorDict
 from torchrl.data.tensor_specs import (
@@ -28,7 +29,7 @@ def __init__(
         image_size=None,
         seed=1337,
         device="cpu",
-        num_prev_obs=1,
+        num_prev_obs=0,
         num_prev_action=0,
     ):
         super().__init__(device=device, batch_size=[])
@@ -65,7 +66,8 @@ def __init__(
             self._prev_obs_image_queue = deque(maxlen=self.num_prev_obs)
             self._prev_obs_state_queue = deque(maxlen=self.num_prev_obs)
         if self.num_prev_action > 0:
-            self._prev_action_queue = deque(maxlen=self.num_prev_action)
+            raise NotImplementedError()
+            # self._prev_action_queue = deque(maxlen=self.num_prev_action)
 
     def render(self, mode="rgb_array", width=384, height=384):
         if width != height:
@@ -133,7 +135,7 @@ def _step(self, tensordict: TensorDict):
         sum_reward = 0
 
         if action.ndim == 1:
-            action = action.repeat(self.frame_skip, 1)
+            action = einops.repeat(action, "c -> t c", t=self.frame_skip)
         else:
             if self.frame_skip > 1:
                 raise NotImplementedError()
@@ -172,7 +174,7 @@ def _make_spec(self):
         if self.from_pixels:
             image_shape = (3, self.image_size, self.image_size)
             if self.num_prev_obs > 0:
-                image_shape = (self.num_prev_obs, *image_shape)
+                image_shape = (self.num_prev_obs + 1, *image_shape)
 
             obs["image"] = BoundedTensorSpec(
                 low=0,
@@ -184,24 +186,24 @@ def _make_spec(self):
             if not self.pixels_only:
                 state_shape = self._env.observation_space["agent_pos"].shape
                 if self.num_prev_obs > 0:
-                    state_shape = (self.num_prev_obs, *state_shape)
+                    state_shape = (self.num_prev_obs + 1, *state_shape)
 
                 obs["state"] = BoundedTensorSpec(
                     low=0,
                     high=512,
-                    shape=self._env.observation_space["agent_pos"].shape,
+                    shape=state_shape,
                     dtype=torch.float32,
                     device=self.device,
                 )
         else:
             # TODO(rcadene): add observation_space achieved_goal and desired_goal?
             state_shape = self._env.observation_space["observation"].shape
             if self.num_prev_obs > 0:
-                state_shape = (self.num_prev_obs, *state_shape)
+                state_shape = (self.num_prev_obs + 1, *state_shape)
 
             obs["state"] = UnboundedContinuousTensorSpec(
                 # TODO:
-                shape=self._env.observation_space["observation"].shape,
+                shape=state_shape,
                 dtype=torch.float32,
                 device=self.device,
             )

tests/test_datasets.py

@@ -6,12 +6,18 @@
 
 
 @pytest.mark.parametrize(
-    "env_name",
+    "env_name,dataset_id",
     [
-        "simxarm",
-        "pusht",
+        # TODO(rcadene): simxarm is depreciated for now
+        # ("simxarm", "lift"),
+        ("pusht", "pusht"),
+        # TODO(aliberts): add aloha when dataset is available on hub
+        # ("aloha", "sim_insertion_human"),
+        # ("aloha", "sim_insertion_scripted"),
+        # ("aloha", "sim_transfer_cube_human"),
+        # ("aloha", "sim_transfer_cube_scripted"),
     ],
 )
-def test_factory(env_name):
-    cfg = init_config(overrides=[f"env={env_name}"])
+def test_factory(env_name, dataset_id):
+    cfg = init_config(overrides=[f"env={env_name}", f"env.task={dataset_id}"])
     offline_buffer = make_offline_buffer(cfg)

tests/test_envs.py

@@ -36,6 +36,7 @@ def simple_rollout(steps=100):
     print("data from rollout:", simple_rollout(100))
 
 
+@pytest.mark.skip(reason="Simxarm is deprecated")
 @pytest.mark.parametrize(
     "task,from_pixels,pixels_only",
     [
@@ -80,7 +81,7 @@ def test_pusht(from_pixels, pixels_only):
 @pytest.mark.parametrize(
     "env_name",
     [
-        "simxarm",
+        # "simxarm",
         "pusht",
     ],
 )