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#!/bin/bash
# MemGen VIS Training Multi - Math Vision
# Based on mm_math training configuration
# Change to project directory
cd /root/CVPR/MemGen
# Set environment variables
export DEBUG_MODE="true"
export LOG_PATH="./test_output/debug_log_math_vision.txt"
export CUDA_VISIBLE_DEVICES="0,1,2,3,4,5,6,7"
export MAIN_PROCESS_PORT="29508"
export NCCL_DEBUG="WARN"
export NCCL_IB_DISABLE="1"
export NCCL_P2P_DISABLE="0"
export NCCL_ASYNC_DISABLE="1"
export TORCH_DISTRIBUTED_DEBUG="OFF"
# Run with accelerate (using uv run to manage Python environment)
uv run python -m accelerate.commands.launch \
--num_processes=8 \
--main_process_port=29508 \
--config_file=configs/zero2.yaml \
main.py \
--cfg-path configs/latent_memory/math_vision.yaml \
--options \
model.reasoner_model_name "Qwen/Qwen2.5-VL-7B-Instruct" \
model.weaver.weaver_model_name "Qwen/Qwen2.5-1.5B-Instruct" \
model.trigger.trigger_model_name "null" \
model.weaver.prompt_latents_len "6" \
model.weaver.inference_latents_len "6" \
model.max_prompt_aug_num "1" \
model.max_inference_aug_num "2" \
model.load_model_path "null" \
run.mode "train" \
run.train_weaver "True" \
run.train_trigger "False" \
run.train_weaver_method "grpo" \
run.generation.do_sample "True" \
run.generation.temperature "1.0" \
run.generation.max_response_length "1024" \
run.weaver.grpo.batch_size "4" \
run.output_dir "/root/CVPR/MemGen/test_output/math_vision" \
datasets.math_vision.mode "grpo"
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