All attempts to get a Google authentication bearer token failed

[cjybupt]

I have already gotten the access to Waymo Open Motion Dataset. However, when I run the demo like
`import jax
from jax import numpy as jnp
import numpy as np
import mediapy
from tqdm import tqdm
import dataclasses

from waymax import config as _config
from waymax import dataloader
from waymax import datatypes
from waymax import dynamics
from waymax import env as _env
from waymax import agents
from waymax import visualization

Config dataset:

max_num_objects = 32

config = dataclasses.replace(_config.WOD_1_0_0_VALIDATION, max_num_objects=max_num_objects)
data_iter = dataloader.simulator_state_generator(config=config)
scenario = next(data_iter)

Config the multi-agent environment:

init_steps = 11

Set the dynamics model the environment is using.

Note each actor interacting with the environment needs to provide action

compatible with this dynamics model.

dynamics_model = dynamics.StateDynamics()

Expect users to control all valid object in the scene.

env = _env.MultiAgentEnvironment(
dynamics_model=dynamics_model,
config=dataclasses.replace(
_config.EnvironmentConfig(),
max_num_objects=max_num_objects,
controlled_object=_config.ObjectType.VALID,
),
)

Setup a few actors, see visualization below for how each actor behaves.

An actor that doesn't move, controlling all objects with index > 4

obj_idx = jnp.arange(max_num_objects)
static_actor = agents.create_constant_speed_actor(
speed=0.0,
dynamics_model=dynamics_model,
is_controlled_func=lambda state: obj_idx > 4,
)

IDM actor/policy controlling both object 0 and 1.

Note IDM policy is an actor hard-coded to use dynamics.StateDynamics().

actor_0 = agents.IDMRoutePolicy(
is_controlled_func=lambda state: (obj_idx == 0) | (obj_idx == 1)
)

Constant speed actor with predefined fixed speed controlling object 2.

actor_1 = agents.create_constant_speed_actor(
speed=5.0,
dynamics_model=dynamics_model,
is_controlled_func=lambda state: obj_idx == 2,
)

Exper/log actor controlling objects 3 and 4.

actor_2 = agents.create_expert_actor(
dynamics_model=dynamics_model,
is_controlled_func=lambda state: (obj_idx == 3) | (obj_idx == 4),
)

actors = [static_actor, actor_0, actor_1, actor_2]

jit_step = jax.jit(env.step)
jit_select_action_list = [jax.jit(actor.select_action) for actor in actors]

states = [env.reset(scenario)]
for _ in range(states[0].remaining_timesteps):
current_state = states[-1]

outputs = [
jit_select_action({}, current_state, None, None)
for jit_select_action in jit_select_action_list
]
action = agents.merge_actions(outputs)
next_state = jit_step(current_state, action)

states.append(next_state)

imgs = []
for state in states:
imgs.append(visualization.plot_simulator_state(state, use_log_traj=False))
mediapy.show_video(imgs, fps=10)`

I got this error
All attempts to get a Google authentication bearer token failed, returning an empty token. Retrieving token from files failed with "NOT_FOUND: Could not locate the credentials file.". Retrieving token from GCE failed with "FAILED_PRECONDITION: Error executing an HTTP request: libcurl code 6 meaning 'Couldn't resolve host name', error details: Could not resolve host: metadata.google.internal". Traceback (most recent call last):

It would be great if you can help me out there! Thx

[cjybupt]

I would appreciate it if you could give me a simple demo which can run on my local machine.

[justinjfu]

Could you try some of the steps in #30 (comment) and see if they resolve the issue? And it would be appreciated if you report back if they work so we can compile an FAQ for these access issues.