# CODI MATH-dataset Evaluation Configuration
# Used by test_math.py / test_math.sh

# ==================== Model Arguments ====================
model_name_or_path: /data/oss_bucket_0/liqi/models/Llama-3.2-3B-Instruct
# model_name_or_path: /data/oss_bucket_0/liqi/models/Qwen3-4B-Instruct-2507
# model_name_or_path: /data/oss_bucket_0/liqi/models/gpt2
lora_r: 128
lora_alpha: 32
lora_init: True
use_lora: True
ckpt_dir: /data/oss_bucket_0/liqi/larger_model/llama-3b/math/k32_t0.1_mt0.1_fac0.3_l8_lr5e4_btz256_nopos_ep300/gsm8k_gpt_pmps/
# ckpt_dir: /data/oss_bucket_0/liqi/larger_model/qwen-4b/math/k32_t0.1_mt0.1_fac0.3_l8_lr8e4_btz256_pos6_ep300/gsm8k_gpt_pmps/
# ckpt_dir: /data/oss_bucket_0/liqi/codi_pmps/math/k24_t0.1_mt0.1_fac0.5_l6_lr3e3_btz256_ep300/gsm8k_gpt_pmps/

# ==================== Data Arguments ====================
data_name: math
# Path to the MATH test JSON. Each entry must contain `problem` and `answer`.
# `data_path` is read by test_math.py; falls back to the default path below if unset.
# data_path: /data/oss_bucket_0/liqi/dataset/MATH/test.json
batch_size: 16

enable_top_k: False
latent_top_k: 20
latent_top_k_temperature: 1.0

# ==================== Training Arguments (for inference) ====================
output_dir: /data/oss_bucket_0/liqi/larger_model/llama-3b/math/k32_t0.1_mt0.1_fac0.3_l8_lr5e4_btz256_nopos_ep300/output_math
# output_dir: /data/oss_bucket_0/liqi/larger_model/qwen-4b/math/k32_t0.1_mt0.1_fac0.3_l8_lr8e4_btz256_pos6_ep300/output_math
# output_dir: /data/oss_bucket_0/liqi/codi_pmps/math/k24_t0.1_mt0.1_fac0.5_l6_lr3e3_btz256_ep300/output_math
model_max_length: 64
bf16: True

# ==================== CODI Specific Arguments ====================
pmps_nmb_prototypes: 32
inf_latent_iterations: 8
use_prj: True
prj_dim: 3072
prj_dropout: 0.0
prj_no_ln: False
inf_num_iterations: 1
remove_eos: True
greedy: True