fix tests

This commit is contained in:
Remi Cadene 2024-03-06 13:55:12 +00:00 committed by Simon Alibert
parent c2c0ef9927
commit 524d29aa80
4 changed files with 23 additions and 14 deletions

View File

@ -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":

View File

@ -2,6 +2,7 @@ import importlib
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 @@ class PushtEnv(EnvBase):
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 @@ class PushtEnv(EnvBase):
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 @@ class PushtEnv(EnvBase):
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 @@ class PushtEnv(EnvBase):
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,
@ -184,12 +186,12 @@ class PushtEnv(EnvBase):
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,
)
@ -197,11 +199,11 @@ class PushtEnv(EnvBase):
# 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,
)

View File

@ -6,12 +6,17 @@ from .utils import init_config
@pytest.mark.parametrize(
"env_name",
"env_name,dataset_id",
[
"simxarm",
"pusht",
# TODO(rcadene): simxarm is depreciated for now
# ("simxarm", "lift"),
("pusht", "pusht"),
("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)

View File

@ -36,6 +36,7 @@ def print_spec_rollout(env):
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",
],
)