fix tests
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c2c0ef9927
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@ -9,6 +9,7 @@ def make_env(cfg, transform=None):
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"image_size": cfg.env.image_size,
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# TODO(rcadene): do we want a specific eval_env_seed?
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"seed": cfg.seed,
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"num_prev_obs": cfg.n_obs_steps - 1,
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}
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if cfg.env.name == "simxarm":
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@ -2,6 +2,7 @@ import importlib
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from collections import deque
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from typing import Optional
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import einops
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import torch
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from tensordict import TensorDict
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from torchrl.data.tensor_specs import (
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@ -28,7 +29,7 @@ class PushtEnv(EnvBase):
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image_size=None,
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seed=1337,
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device="cpu",
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num_prev_obs=1,
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num_prev_obs=0,
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num_prev_action=0,
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):
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super().__init__(device=device, batch_size=[])
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@ -65,7 +66,8 @@ class PushtEnv(EnvBase):
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self._prev_obs_image_queue = deque(maxlen=self.num_prev_obs)
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self._prev_obs_state_queue = deque(maxlen=self.num_prev_obs)
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if self.num_prev_action > 0:
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self._prev_action_queue = deque(maxlen=self.num_prev_action)
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raise NotImplementedError()
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# self._prev_action_queue = deque(maxlen=self.num_prev_action)
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def render(self, mode="rgb_array", width=384, height=384):
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if width != height:
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@ -133,7 +135,7 @@ class PushtEnv(EnvBase):
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sum_reward = 0
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if action.ndim == 1:
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action = action.repeat(self.frame_skip, 1)
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action = einops.repeat(action, "c -> t c", t=self.frame_skip)
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else:
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if self.frame_skip > 1:
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raise NotImplementedError()
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@ -172,7 +174,7 @@ class PushtEnv(EnvBase):
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if self.from_pixels:
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image_shape = (3, self.image_size, self.image_size)
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if self.num_prev_obs > 0:
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image_shape = (self.num_prev_obs, *image_shape)
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image_shape = (self.num_prev_obs + 1, *image_shape)
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obs["image"] = BoundedTensorSpec(
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low=0,
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@ -184,12 +186,12 @@ class PushtEnv(EnvBase):
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if not self.pixels_only:
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state_shape = self._env.observation_space["agent_pos"].shape
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if self.num_prev_obs > 0:
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state_shape = (self.num_prev_obs, *state_shape)
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state_shape = (self.num_prev_obs + 1, *state_shape)
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obs["state"] = BoundedTensorSpec(
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low=0,
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high=512,
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shape=self._env.observation_space["agent_pos"].shape,
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shape=state_shape,
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dtype=torch.float32,
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device=self.device,
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)
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@ -197,11 +199,11 @@ class PushtEnv(EnvBase):
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# TODO(rcadene): add observation_space achieved_goal and desired_goal?
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state_shape = self._env.observation_space["observation"].shape
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if self.num_prev_obs > 0:
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state_shape = (self.num_prev_obs, *state_shape)
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state_shape = (self.num_prev_obs + 1, *state_shape)
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obs["state"] = UnboundedContinuousTensorSpec(
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# TODO:
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shape=self._env.observation_space["observation"].shape,
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shape=state_shape,
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dtype=torch.float32,
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device=self.device,
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)
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@ -6,12 +6,17 @@ from .utils import init_config
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@pytest.mark.parametrize(
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"env_name",
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"env_name,dataset_id",
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[
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"simxarm",
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"pusht",
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# TODO(rcadene): simxarm is depreciated for now
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# ("simxarm", "lift"),
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("pusht", "pusht"),
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("aloha", "sim_insertion_human"),
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("aloha", "sim_insertion_scripted"),
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("aloha", "sim_transfer_cube_human"),
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("aloha", "sim_transfer_cube_scripted"),
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],
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)
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def test_factory(env_name):
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cfg = init_config(overrides=[f"env={env_name}"])
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def test_factory(env_name, dataset_id):
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cfg = init_config(overrides=[f"env={env_name}", f"env.task={dataset_id}"])
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offline_buffer = make_offline_buffer(cfg)
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@ -36,6 +36,7 @@ def print_spec_rollout(env):
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print("data from rollout:", simple_rollout(100))
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@pytest.mark.skip(reason="Simxarm is deprecated")
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@pytest.mark.parametrize(
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"task,from_pixels,pixels_only",
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[
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@ -80,7 +81,7 @@ def test_pusht(from_pixels, pixels_only):
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@pytest.mark.parametrize(
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"env_name",
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[
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"simxarm",
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# "simxarm",
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"pusht",
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],
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)
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