wehub-resource-sync
229 lines
12 KiB
Python
229 lines
12 KiB
Python
import collections
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import json
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import os.path
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from argparse import ArgumentParser
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from glob import glob
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import random
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from tqdm import tqdm
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def sample_step(response: str, upper_step_ratio: float, sample_ratio: float):
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orig_lines = response.split("\n")
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lines = [(i, line) for i, line in enumerate(orig_lines)]
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lines = [(i, line) for i, line in lines if line.strip()]
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if len(lines) < 5:
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return []
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upper_step = int(len(lines) * upper_step_ratio)
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if upper_step == 0:
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return []
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sample_step_num = int(upper_step * sample_ratio)
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if sample_step_num == 0:
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return []
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sample_steps = random.sample(lines[:upper_step], sample_step_num)
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if len(sample_steps) == 0:
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return []
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step_prefixes = []
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for i, line in sample_steps:
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step_prefixes.append("\n".join(orig_lines[:(i + 1)]))
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return step_prefixes
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def get_pred_set(preds):
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if isinstance(preds[0], list):
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tmp = []
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for pred in preds:
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tmp.append(str(sorted(pred)))
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tmp = set(tmp)
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elif isinstance(preds[0], str):
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tmp = set(preds)
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else:
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raise ValueError(f"Unknown type {type(preds[0])}")
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return tmp
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def main():
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parser = ArgumentParser()
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parser.add_argument("--input_file", type=str)
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parser.add_argument("--output_file", type=str)
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parser.add_argument("--upper_step_ratio", type=float, default=0.6)
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parser.add_argument("--sample_ratio", type=float, default=0.3)
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parser.add_argument("--filter_all_correct", action="store_true", default=False)
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parser.add_argument("--filter_all_same", action="store_true", default=False)
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parser.add_argument("--sample_over_p", default=-1, type=int)
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args = parser.parse_args()
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if os.path.exists(args.input_file):
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if args.input_file.endswith(".json"):
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data = json.load(open(args.input_file))
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else:
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data = [json.loads(line) for line in open(args.input_file).readlines()]
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else:
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data = []
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for file in sorted(glob(args.input_file)):
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if ".metrics" in file:
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continue
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print(file)
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if file.endswith(".json"):
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data += json.load(open(file))
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else:
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data += [json.loads(line) for line in open(file).readlines()]
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# # First use self-consistency to construct pseudo labels
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# for item in data:
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# all_preds = collections.Counter()
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# for pred in item["pred"]:
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# if isinstance(pred, list):
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# all_preds.update(pred)
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# else:
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# all_preds[pred] += 1
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#
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# pseudo_label = all_preds.most_common(1)[0][0]
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# item["sc_label_0"] = pseudo_label
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outputs = []
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num = 0
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for item in tqdm(data):
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if args.filter_all_correct and all(item["res"]):
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continue
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if args.filter_all_same and len(set(item["pred"])) == 1:
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continue
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prefixes = []
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prefix_ids = []
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if not item["response"]:
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item["prefix"] = []
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continue
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for resp_id, resp in enumerate(item["response"]):
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response_prefixes = sample_step(resp, args.upper_step_ratio, args.sample_ratio)
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prefixes.extend(response_prefixes)
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prefix_ids.extend([f"{item['id']}_{resp_id}_{i}" for i in range(len(response_prefixes))])
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if args.sample_over_p > 0:
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if len(prefixes) > args.sample_over_p:
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prefixes = random.sample(prefixes, args.sample_over_p)
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prefix_ids = random.sample(prefix_ids, args.sample_over_p)
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item["prefix"] = prefixes
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item["prefix_id"] = prefix_ids
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item.pop("response")
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item.pop("pred")
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item.pop("res")
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item.pop("sc_pred")
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item.pop("sc_res")
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outputs.append(item)
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num += len(prefixes)
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json.dump(outputs, open(args.output_file, "w"), indent=2)
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print(f"Number of prefixes: {num}")
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print(len(outputs))
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if __name__ == "__main__":
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main()
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"""
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>>> python ~/gpt-chat-examples/scripts/math/deepseek_math_sample_steps.py \
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--input_file "math.test.v1.1.0shot.n10.tem1.0.p0.9.8-of-?.json" \
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--output_file math.test.v1.1.0shot.n10.tem1.0.p0.9.prefix.upper0.6.r0.3.json --upper_step_ratio 0.6 --sample_ratio 0.3
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>>> python scripts/math/deepseek_math_sample_steps.py --input_file "../msranlpintern/share/models/deepseek-math-7b-instruct/meta_math/sub_math.cot.train.0shot.n10.tem1.0.p0.9.v1.0.?-of-24.json" --output_file "../msranlpintern/share/models/deepseek-math-7b-instruct/meta_math/sub_math.cot.train.0shot.n10.tem1.0.p0.9.v1.0.upper0.7.r0.3.inter_step.filter_all_true.json" --upper_step_ra
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tio 0.7 --sample_ratio 0.3 --filter_all_correct
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>>> python scripts/math/deepseek_math_sample_steps.py \
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--input_file "../msranlpintern/share/models/mathstral-7B-v0.1/mathscale4o/split-0-of-11/train.330k.boxed.v1.0.0-of-11.0shot.n20.tem1.0.p0.9.[0-9]*-of-64.json" \
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--output_file "../msranlpintern/share/models/mathstral-7B-v0.1/mathscale4o/split-0-of-11/train.330k.boxed.v1.0.0-of-11.0shot.n20.tem1.0.p0.9.upper0.7.r0.3.inter_step.json" \
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--upper_step_ratio 0.7 --sample_ratio 0.3
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>>> python scripts/math/deepseek_math_sample_steps.py \
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--input_file "../msranlpintern/share/models/mathstral-7B-v0.1/mathscale4o/split-0-of-11/train.330k.boxed.v1.0.0-of-11.0shot.n20.tem1.0.p0.9.[0-9]*-of-64.json" \
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--output_file "../msranlpintern/share/models/mathstral-7B-v0.1/mathscale4o/split-0-of-11/train.330k.boxed.v1.0.0-of-11.0shot.n20.tem1.0.p0.9.upper0.7.r0.3.filter_same.json" \
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--upper_step_ratio 0.7 --sample_ratio 0.3 --filter_all_same
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>>> python scripts/math/deepseek_math_sample_steps.py \
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--input_file "../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.sft.V100.tp2dp8.v2.0.s42/checkpoint-800/mathscale4o/500k-split-*-of-20/train.500k.de_con.boxed.v1.0.*-of-20.0shot.n10.tem1.0.p0.9.?-of-8.json" \
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--output_file "../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.sft.V100.tp2dp8.v2.0.s42/checkpoint-800/mathscale4o/500k-split-*-of-20/train.500k.de_con.boxed.v1.0.n10.tem1.0.p0.9.upper0.7.r0.3.filter_same.json" \
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--upper_step_ratio 0.7 --sample_ratio 0.3 --filter_all_same
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Number of prefixes: 19521786
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309876
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>>> python scripts/math/deepseek_math_sample_steps.py \
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--input_file "../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.sft.V100.tp2dp8.v2.0.s42/checkpoint-800/mathscale4o/500k-split-*-of-20/train.500k.de_con.boxed.v1.0.*-of-20.0shot.n10.tem1.0.p0.9.?-of-8.json" \
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--output_file "../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.sft.V100.tp2dp8.v2.0.s42/checkpoint-800/mathscale4o/train.500k.de_con.boxed.v1.0.n10.tem1.0.p0.9.upper0.7.r0.3.sample10.filter_same.json" \
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--upper_step_ratio 0.7 --sample_ratio 0.3 --filter_all_same --sample_over_p 10
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Number of prefixes: 3098719
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309876
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>>> python scripts/math/deepseek_math_sample_steps.py \
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--input_file "../msranlpintern/share/models/llama3.1_8b_mathscale4o/model_lr1e-5_batch512_epochs3_gpus8_linearSchedule/mathscale4o/500k-split-*-of-20/train.500k.de_con.boxed.v1.0.*-of-20.0shot.n10.tem1.0.p0.9.*-of-32.json" \
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--output_file "../msranlpintern/share/models/llama3.1_8b_mathscale4o/model_lr1e-5_batch512_epochs3_gpus8_linearSchedule/mathscale4o/train.500k.de_con.boxed.v1.0.n10.tem1.0.p0.9.upper0.7.r0.3.sample10.filter_same.json" \
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--upper_step_ratio 0.7 --sample_ratio 0.3 --filter_all_same --sample_over_p 10
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Number of prefixes: 2879063
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287913
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############################################################ ITERATION 1 #######################################################
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>>> python scripts/math/deepseek_math_sample_steps.py \
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--input_file "../msranlpintern/reward_modeling/experiments/llama3.1.8b.mathscale4o.process-dpo.iter0.A100.dp8.v2.2.s42/checkpoint-1200/mathscale4o/500k-split-*-of-20/train.500k.de_con.boxed.v1.0.*-of-20.0shot.n10.tem1.0.p0.9.*-of-8.json" \
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--output_file ../msranlpintern/reward_modeling/experiments/llama3.1.8b.mathscale4o.process-dpo.iter0.A100.dp8.v2.2.s42/checkpoint-1200/mathscale4o/train.500k.de_con.boxed.v1.0.n10.tem1.0.p0.9.upper0.7.r0.3.sample10.filter_same.json \
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--upper_step_ratio 0.7 --sample_ratio 0.3 --filter_all_same --sample_over_p 10
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Number of prefixes: 2389255
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238928
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>>> python scripts/math/deepseek_math_sample_steps.py \
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--input_file "../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.process-dpo.iter0.V100.tp8dp48.v2.2.fix.s42/checkpoint-600/mathscale4o/500k-split-*-of-20/train.500k.de_con.boxed.v1.0.*-of-20.0shot.n10.tem1.0.p0.9.*-of-8.json" \
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--output_file ../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.process-dpo.iter0.V100.tp8dp48.v2.2.fix.s42/checkpoint-600/mathscale4o/train.500k.de_con.boxed.v1.0.n10.tem1.0.p0.9.upper0.7.r0.3.sample10.filter_same.json \
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--upper_step_ratio 0.7 --sample_ratio 0.3 --filter_all_same --sample_over_p 10
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Number of prefixes: 2389255
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238928
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>>> python scripts/math/deepseek_math_sample_steps.py \
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--input_file "../msranlpintern/reward_modeling/experiments/llama3.1.8b.mathscale4o.process-dpo.iter0.A100.dp8.v2.2.s42/checkpoint-1200/mathscale4o/500k-split-*-of-20/train.500k.de_con.boxed.v1.0.*-of-20.0shot.n10.tem1.0.p0.9.*-of-8.json" \
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--output_file ../msranlpintern/reward_modeling/experiments/llama3.1.8b.mathscale4o.process-dpo.iter0.A100.dp8.v2.2.s42/checkpoint-1200/mathscale4o/train.500k.de_con.boxed.v1.0.n10.tem1.0.p0.9.upper0.7.r0.3.sample32.filter_same.json \
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--upper_step_ratio 0.7 --sample_ratio 0.3 --filter_all_same --sample_over_p 32
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Number of prefixes: 7512389
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238928
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>>> python scripts/math/deepseek_math_sample_steps.py \
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--input_file "../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.process-dpo.iter0.V100.tp8dp48.v2.2.fix.s42/checkpoint-600/mathscale4o/500k-split-*-of-20/train.500k.de_con.boxed.v1.0.*-of-20.0shot.n10.tem1.0.p0.9.*-of-8.json" \
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--output_file ../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.process-dpo.iter0.V100.tp8dp48.v2.2.fix.s42/checkpoint-600/mathscale4o/train.500k.de_con.boxed.v1.0.n10.tem1.0.p0.9.upper0.7.r0.3.sample32.filter_same.json \
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--upper_step_ratio 0.7 --sample_ratio 0.3 --filter_all_same --sample_over_p 32
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>>> python scripts/math/deepseek_math_sample_steps.py \
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--input_file "../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.process-dpo.iter0.V100.tp8dp48.v2.2.fix.s42/checkpoint-600/numina/830k-split-[0-9]-of-10/cot.de_con.[0-9]-of-10.n8.tem1.0.p1.0.*-of-16.s0.json" \
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--output_file ../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.process-dpo.iter0.V100.tp8dp48.v2.2.fix.s42/checkpoint-600/numina/cot.de_con.n8.tem1.0.p1.0.s0.upper0.7.r0.3.sample16.filter_same.json \
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--upper_step_ratio 0.7 --sample_ratio 0.3 --filter_all_same --sample_over_p 16
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>>> python scripts/math/deepseek_math_sample_steps.py \
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--input_file "../msranlpintern/share/models/mathstral-7B-v0.1/mathscale4o/500k-split-*-of-20/train.500k.de_con.boxed.v1.0.*-of-20.0shot.n10.tem1.0.p0.9.*-of-64.*json" \
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--output_file ../msranlpintern/share/models/mathstral-7B-v0.1/mathscale4o/train.500k.de_con.boxed.v1.0.n10.tem1.0.p0.9.upper0.7.r0.3.sample16.filter_same.json \
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--upper_step_ratio 0.7 --sample_ratio 0.3 --filter_all_same --sample_over_p 16
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Number of prefixes: 5053462
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345626
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>>> python scripts/math/deepseek_math_sample_steps.py \
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--input_file "../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.process-dpo.iter0.V100.tp8dp48.v2.2.fix.s42/checkpoint-600/numina/830k-split-0-of-10/cot.de_con.0-of-10.n8.tem1.0.p1.0.*-of-8.s0.json" \
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--output_file ../msranlpintern/reward_modeling/experiments/mathstral.mathscale4o.process-dpo.iter0.V100.tp8dp48.v2.2.fix.s42/checkpoint-600/numina/cot.de_con.n8.tem1.0.p1.0.orig_0-of-8.s0.upper0.7.r0.3.sample32.filter_same.json \
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--upper_step_ratio 0.7 --sample_ratio 0.3 --filter_all_same --sample_over_p 32
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"""
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