Status keeps PENDING while training

[Fishermanykx]

Hello, I set up the environment as the README says and do the training, but the trainer keeps in PENDING status and does not require any CPU or GPU resources like the image shown below. Is the code complete enough to reproduce the result shown in your paper? Is there some way to solve this problem? I'm waiting for your answer.

This is my train.yaml

local_dir: "./ray_results"

env_config: {
        FILENAME: /home/fisher/data/sim/goseek-allscenes-v0.1.4.x86_64,
        SCENES: [1, 2, 3, 4],
        episode_length: 400,
        video_log_path: "./videos",
        collision_reward: 0,
        target_found_reward: 1,
        success_dist: 2,
        no_collisions: False,
        modalities: ["RGB_LEFT", "SEGMENTATION", "DEPTH"],
        visible_targets: False,
        use_esdf_data: True,
        esdf_data: {'1': /home/fisher/data/esdf/scene_1_esdf_slices.npy,
                    '2': /home/fisher/data/esdf/scene_2_esdf_slices.npy,
                    '3': /home/fisher/data/esdf/scene_3_esdf_slices.npy,
                    '4': /home/fisher/data/esdf/scene_4_esdf_slices.npy,
                    },
        scene_graph: {"1": /home/fisher/data/dsgs/dsg_dict_scene_1.pkl,
                      "2": /home/fisher/data/dsgs/dsg_dict_scene_2.pkl,
                      "3": /home/fisher/data/dsgs/dsg_dict_scene_3.pkl,
                      "4": /home/fisher/data/dsgs/dsg_dict_scene_4.pkl,
                    },
    }

model: {
        custom_model: gnn_actor_critic,
        custom_model_config: {
            fields: {
                nodes: GRAPH_NODES,
                edges: GRAPH_EDGES,
                node_shapes: GRAPH_NODE_SHAPE,
                edge_shapes: GRAPH_EDGE_SHAPE,
            },
            in_features: 10,
            graph_conv_features: [64, 64, 64],
            n_layer_nodes: 8,
            embedding_size: [512],
        },
        max_seq_len: 400,
        vf_share_layers : false
    }

# training
lr : 1.0e-4
gamma : 0.99
lambda : .9
vf_loss_coeff : 0.25
clip_param : 0.3
vf_clip_param : 25
entropy_coeff : 0.01

# batch
train_batch_size : 1024 # 4096
sgd_minibatch_size : 128
num_sgd_iter : 30
rollout_fragment_length: 400

# env
env : goseek
framework : torch
num_workers : 0
num_gpus : 1
num_envs_per_worker : 1
num_gpus_per_worker: 0.25
log_level : INFO

ckpt_save_freq_timesteps: 10000

evaluation_interval : 50
evaluation_num_episodes : 50
evaluation_num_workers: 1
evaluation_config: {
    env_config: {
            SCENES: [5],
            RANK: 3,
            FILENAME: /home/fisher/data/sim/goseek-allscenes-v0.1.4.x86_64,
            esdf_data: {'5': /home/fisher/data/esdf/scene_5_esdf_slices.npy},
            scene_graph: {"5": /home/fisher/data/dsgs/dsg_dict_scene_5.pkl},
        }
    }