cant save checkpoint

W0117 14:48:50.972433 140051385186112 experiment.py:220] Your experiment's self.CHECKPOINT_ATTRS and self.NON_BROADCAST_CHECKPOINT_ATTRS are empty. Your job will not checkpoint any state or parameters.
I0117 14:48:50.972585 140051385186112 utils.py:615] Saved checkpoint latest with id 0.
I0117 14:48:50.973322 140051385186112 utils.py:316] [jaxline] training loop finished.
I0117 14:48:50.974981 140051385186112 utils.py:309] [jaxline] final checkpoint starting...
W0117 14:48:50.975140 140051385186112 experiment.py:220] Your experiment's self.CHECKPOINT_ATTRS and self.NON_BROADCAST_CHECKPOINT_ATTRS are empty. Your job will not checkpoint any state or parameters.
I0117 14:48:50.975250 140051385186112 utils.py:615] Saved checkpoint latest with id 1.
I0117 14:48:50.975420 140051385186112 utils.py:316] [jaxline] final checkpoint finished.
I0117 14:48:50.975657 140051385186112 utils.py:498] Waiting for a periodic action to finish...
I0117 14:49:06.433700 140051385186112 utils.py:309] [jaxline] rendezvous starting...
I0117 14:49:06.486311 140051385186112 utils.py:316] [jaxline] rendezvous finished.

train config as follow:
I0117 14:44:59.102810 140051385186112 train.py:76] Training with config:
best_checkpoint_all_hosts: false
best_model_eval_metric: ''
best_model_eval_metric_higher_is_better: true
binary_args:
- !!python/tuple
- --define cudnn_embed_so
- 1
- !!python/tuple
- --define=cuda_compress
- 1
checkpoint_dir: /workplace/0_code/2_Game/2025/ai-imgbit/training/
checkpoint_interval_type: null
eval_initial_weights: false
eval_modes: !!python/tuple []
eval_specific_checkpoint_dir: /workplace/0_code/2_Game/2025/ai-imgbit/eval/
experiment_kwargs:
config:
dataset:
name: clic2020
num_examples: 1
num_frames: null
root_dir: /workplace/0_code/2_Game/2025/ai-imgbit/clic2020
skip_examples: 0
spatial_patch_size: null
video_idx: null
eval: {}
log_gradient_norms: false
log_per_datum_metrics: true
loss:
rd_weight: 0.001
rd_weight_warmup_steps: 0
model:
entropy:
activation_fn: gelu
clip_like_cool_chic: true
conditional_spec:
interpolation: bilinear
prev_kernel_shape: &id001 !!python/tuple
- 3
- 3
use_conditioning: true
use_prev_grid: true
context_num_rows_cols: *id001
layers: &id002 !!python/tuple
- 24
- 24
scale_range: !!python/tuple
- 0.001
- 150
shift_log_scale: 8.0
use_linear_w_init: true
latents:
add_gains: true
downsampling_exponents: !!python/tuple
- 0
- 1
- 2
- 3
- 4
- 5
- 6
downsampling_factor: 2.0
gain_factor: null
gain_values: null
learnable_gains: false
num_grids: 7
q_step: 0.4
quant:
q_steps_bias:
- 5.0e-05
- 0.0001
- 0.0005
- 0.001
- 0.003
- 0.006
- 0.01
q_steps_weight:
- 5.0e-05
- 0.0001
- 0.0005
- 0.001
- 0.003
- 0.006
- 0.01
synthesis:
activation_fn: gelu
add_activation_before_residual: false
add_layer_norm: false
b_last_init_input_mean: false
clip_range: !!python/tuple
- 0.0
- 1.0
kernel_shape: 1
layers: *id002
num_residual_layers: 2
residual_kernel_shape: 3
upsampling:
kwargs:
interpolation_method: bilinear
type: image_resize
opt:
cosine_decay_schedule: true
cosine_decay_schedule_kwargs:
alpha: 0.0
decay_steps: 100
init_value: 0.01
grad_norm_clip: 0.1
max_num_ste_steps: 100
noise_log_every: 100
num_noise_steps: 100
ste_break_at_lr: 1.0e-08
ste_init_lr: 0.0001
ste_log_every: 50
ste_lr_decay_factor: 0.8
ste_num_steps_not_improved: 20
ste_reset_params_at_lr_decay: true
ste_uses_cosine_decay: false
quant:
kumaraswamy_decay_steps: 100
kumaraswamy_end_value: 1.0
kumaraswamy_init_value: 2.0
noise_quant_type: soft_round
soft_round_temp_end: 0.1
soft_round_temp_start: 0.3
ste_quant_type: ste_soft_round
ste_soft_round_temp: 0.0001
use_kumaraswamy_noise: true
interval_type: steps
legacy_random_seed_behavior: false
log_all_hosts: false
log_all_train_data: false
log_async: true
log_tensors_interval: 1
log_train_data_interval: 1.0
logging_interval_type: null
max_checkpoints_to_keep: 5
one_off_evaluate: false
periodic_action_growth_ratios: null
random_mode_eval: same_host_same_device
random_mode_train: unique_host_unique_device
random_seed: 0
save_checkpoint_interval: 1
save_initial_train_checkpoint: false
train_checkpoint_all_hosts: false
training_steps: 1