I used the following script to test the reconstruction metrics. The IS is much lower. Also, the PSNR is not reported in the paper. I want to confirm if it is similar to the 24.8 I measured?
Test Script:
eval_resconstruct0-1 (1).py
evaluator.py
Test cmd：
python -m accelerate.commands.launch \
--num_processes=$(nvidia-smi --list-gpus | wc -l) \
--num_machines=$NUM_MACHINES \
--machine_rank=$MACHINE_RANK \
--main_process_ip=$MAIN_PROCESS_IP \
--main_process_port=$MAIN_PROCESS_PORT \
--mixed_precision=bf16 \
eval_resconstruct0-1py \
--eval_data_dir imagenet/CLS-LOC/val \
--model_name turkeyju/tokenizer_tatitok_sl128_vae \
--class_file imagenet_1k_class.txt \
--batch_size 64 \
--model_image_size 256 \
--eval_image_size 256 \
--buffer_size 8 \
--enable_rfid \
--enable_inception_score
I used the following script to test the reconstruction metrics. The IS is much lower. Also, the PSNR is not reported in the paper. I want to confirm if it is similar to the 24.8 I measured?
Test Script:
eval_resconstruct0-1 (1).py
evaluator.py
Test cmd：
python -m accelerate.commands.launch \ --num_processes=$(nvidia-smi --list-gpus | wc -l) \ --num_machines=$NUM_MACHINES \ --machine_rank=$MACHINE_RANK \ --main_process_ip=$MAIN_PROCESS_IP \ --main_process_port=$MAIN_PROCESS_PORT \ --mixed_precision=bf16 \ eval_resconstruct0-1py \ --eval_data_dir imagenet/CLS-LOC/val \ --model_name turkeyju/tokenizer_tatitok_sl128_vae \ --class_file imagenet_1k_class.txt \ --batch_size 64 \ --model_image_size 256 \ --eval_image_size 256 \ --buffer_size 8 \ --enable_rfid \ --enable_inception_score