generate_ideas.py

code:first_idea_input.py

[

{

"Name": "learning_rate_schedule",

"Title": "Adaptive Learning Rate Schedules: Comparing different learning rate schedules for diffusion models.",

"Experiment": "In this experiment, we compare the performance of different learning rate schedules on diffusion model performance. We use the final estimated KL as the evaluation metric.",

"Interestingness": 4,

"Feasibility": 10,

"Novelty": 3

}

]

----------------------------------------------------------------------------------------------------

idea_str_archive = []

with open(osp.join(base_dir, "seed_ideas.json"), "r") as f:

seed_ideas = json.load(f)

for seed_idea in seed_ideas:

idea_str_archive.append(json.dumps(seed_idea))

with open(osp.join(base_dir, "experiment.py"), "r") as f:

code = f.read()

with open(osp.join(base_dir, "prompt.json"), "r") as f:

prompt = json.load(f)

idea_system_prompt = prompt"system"

for _ in range(max_num_generations):

print()

print(f"Generating idea {_ + 1}/{max_num_generations}")

try:

prev_ideas_string = "\n\n".join(idea_str_archive)

msg_history = []

print(f"Iteration 1/{num_reflections}")

text, msg_history = get_response_from_llm(

idea_first_prompt.format(

task_description=prompt"task_description",

code=code,

prev_ideas_string=prev_ideas_string,

num_reflections=num_reflections,

client=client,

model=model,

system_message=idea_system_prompt,

msg_history=msg_history,

)

code:how to input LLM?.py