update preprocess format

This commit is contained in:
LiangSong 2023-05-05 18:20:59 +08:00
parent 85caa97a6a
commit d24b4cce54

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@ -15,221 +15,54 @@ from datasets import load_dataset
root_dir = "data"
write_path = "data/instruction_data/part-{}-{}.jsonl.zst"
dataset_map = {
"yizhongw/self_instruct": "self_instruct",
"BelleGroup/train_0.5M_CN": "belle_0.5M",
"BelleGroup/train_1M_CN": "belle_1M",
"BelleGroup/train_2M_CN": "belle_2M",
"BelleGroup/school_math_0.25M": "belle_school_math_0.25M",
"BelleGroup/multiturn_chat_0.8M": "belle_multiturn_chat_0.8M",
"Graverman/Instruct-to-Code": "instruct_to_code",
("bigscience/xP3mt", "code"): "xP3mt_code",
("bigscience/xP3mt", "zh"): "xP3mt_zh",
}
dataset = load_dataset("yizhongw/self_instruct")
write_path = root_dir + "/instruction_data/part-self_instruct-{}.jsonl.zst"
total_num = 0
file_num = 1
wfp = zstd.open(write_path.format(file_num), "wb", encoding="utf-8")
for line in tqdm(dataset["train"]):
line = json.dumps(line)
if total_num % 1024 == 0 and total_num > 0:
file_num += 1
wfp.close()
wfp = zstd.open(write_path.format(file_num), "wb", encoding="utf-8")
wfp.write(line.encode("utf-8"))
wfp.write(b"\n")
total_num += 1
wfp.close()
print(
"yizhongw/self_instruct preprocess done. Total line: {}, Total file: {}".format(
total_num, file_num
def process_hf_dataset(name, local_name):
if isinstance(name, str):
dataset = load_dataset(name)
else:
dataset = load_dataset(*name)
total_num = 0
file_num = 1
wfp = zstd.open(write_path.format(local_name, file_num), "wb", encoding="utf-8")
for line in tqdm(dataset["train"]):
line = json.dumps(line)
if total_num % 1024 == 0 and total_num > 0:
file_num += 1
wfp.close()
wfp = zstd.open(
write_path.format(local_name, file_num), "wb", encoding="utf-8"
)
wfp.write(line.encode("utf-8"))
wfp.write(b"\n")
total_num += 1
wfp.close()
print(
"{} preprocess done. Total line: {}, Total file: {}".format(
name, total_num, file_num
)
)
)
dataset = load_dataset("BelleGroup/train_0.5M_CN")
write_path = root_dir + "/instruction_data/part-belle_0.5M-{}.jsonl.zst"
for k, v in dataset_map.items():
process_hf_dataset(k, v)
local_name = "sharegpt_90K"
total_num = 0
file_num = 1
wfp = zstd.open(write_path.format(file_num), "wb", encoding="utf-8")
for line in tqdm(dataset["train"]):
line = json.dumps(line)
if total_num % 1024 == 0 and total_num > 0:
file_num += 1
wfp.close()
wfp = zstd.open(write_path.format(file_num), "wb", encoding="utf-8")
wfp.write(line.encode("utf-8"))
wfp.write(b"\n")
total_num += 1
wfp.close()
print(
"BelleGroup/train_0.5M_CN preprocess done. Total line: {}, Total file: {}".format(
total_num, file_num
)
)
dataset = load_dataset("BelleGroup/train_1M_CN")
write_path = root_dir + "/instruction_data/part-belle_1M-{}.jsonl.zst"
total_num = 0
file_num = 1
wfp = zstd.open(write_path.format(file_num), "wb", encoding="utf-8")
for line in tqdm(dataset["train"]):
line = json.dumps(line)
if total_num % 1024 == 0 and total_num > 0:
file_num += 1
wfp.close()
wfp = zstd.open(write_path.format(file_num), "wb", encoding="utf-8")
wfp.write(line.encode("utf-8"))
wfp.write(b"\n")
total_num += 1
wfp.close()
print(
"BelleGroup/train_1M_CN preprocess done. Total line: {}, Total file: {}".format(
total_num, file_num
)
)
dataset = load_dataset("BelleGroup/train_2M_CN")
write_path = root_dir + "/instruction_data/part-belle_2M-{}.jsonl.zst"
total_num = 0
file_num = 1
wfp = zstd.open(write_path.format(file_num), "wb", encoding="utf-8")
for line in tqdm(dataset["train"]):
line = json.dumps(line)
if total_num % 1024 == 0 and total_num > 0:
file_num += 1
wfp.close()
wfp = zstd.open(write_path.format(file_num), "wb", encoding="utf-8")
wfp.write(line.encode("utf-8"))
wfp.write(b"\n")
total_num += 1
wfp.close()
print(
"BelleGroup/train_2M_CN preprocess done. Total line: {}, Total file: {}".format(
total_num, file_num
)
)
dataset = load_dataset("BelleGroup/school_math_0.25M")
write_path = root_dir + "/instruction_data/part-belle_school_math_0.25M-{}.jsonl.zst"
total_num = 0
file_num = 1
wfp = zstd.open(write_path.format(file_num), "wb", encoding="utf-8")
for line in tqdm(dataset["train"]):
line = json.dumps(line)
if total_num % 1024 == 0 and total_num > 0:
file_num += 1
wfp.close()
wfp = zstd.open(write_path.format(file_num), "wb", encoding="utf-8")
wfp.write(line.encode("utf-8"))
wfp.write(b"\n")
total_num += 1
wfp.close()
print(
"BelleGroup/school_math_0.25M preprocess done. Total line: {}, Total file: {}".format(
total_num, file_num
)
)
dataset = load_dataset("BelleGroup/multiturn_chat_0.8M")
write_path = root_dir + "/instruction_data/part-belle_multiturn_chat_0.8M-{}.jsonl.zst"
total_num = 0
file_num = 1
wfp = zstd.open(write_path.format(file_num), "wb", encoding="utf-8")
for line in tqdm(dataset["train"]):
line = json.dumps(line)
if total_num % 1024 == 0 and total_num > 0:
file_num += 1
wfp.close()
wfp = zstd.open(write_path.format(file_num), "wb", encoding="utf-8")
wfp.write(line.encode("utf-8"))
wfp.write(b"\n")
total_num += 1
wfp.close()
print(
"BelleGroup/multiturn_chat_0.8M preprocess done. Total line: {}, Total file: {}".format(
total_num, file_num
)
)
dataset = load_dataset("Graverman/Instruct-to-Code")
write_path = root_dir + "/instruction_data/part-instruct_to_code-{}.jsonl.zst"
total_num = 0
file_num = 1
wfp = zstd.open(write_path.format(file_num), "wb", encoding="utf-8")
for line in tqdm(dataset["train"]):
line = json.dumps(line)
if total_num % 1024 == 0 and total_num > 0:
file_num += 1
wfp.close()
wfp = zstd.open(write_path.format(file_num), "wb", encoding="utf-8")
wfp.write(line.encode("utf-8"))
wfp.write(b"\n")
total_num += 1
wfp.close()
print(
"Graverman/Instruct-to-Code preprocess done. Total line: {}, Total file: {}".format(
total_num, file_num
)
)
# dataset = load_dataset("bigscience/xP3mt", "en")
# write_path = root_dir + "/instruction_data/part-bigscience/xP3mt_en-{}.jsonl.zst"
# total_num = 0
# file_num = 1
# wfp = zstd.open(write_path.format(file_num), "wb", encoding="utf-8")
# for line in tqdm(dataset["train"]):
# line = json.dumps(line)
# if total_num % 1024 == 0 and total_num > 0:
# file_num += 1
# wfp.close()
# wfp = zstd.open(write_path.format(file_num), "wb", encoding="utf-8")
# wfp.write(line.encode("utf-8"))
# wfp.write(b"\n")
# total_num += 1
# wfp.close()
# print(
# "bigscience/xP3mt_en preprocess done. Total line: {}, Total file: {}".format(
# total_num, file_num
# )
# )
dataset = load_dataset("bigscience/xP3mt", "code")
write_path = root_dir + "/instruction_data/part-xP3mt_code-{}.jsonl.zst"
total_num = 0
file_num = 1
wfp = zstd.open(write_path.format(file_num), "wb", encoding="utf-8")
for line in tqdm(dataset["train"]):
line = json.dumps(line)
if total_num % 1024 == 0 and total_num > 0:
file_num += 1
wfp.close()
wfp = zstd.open(write_path.format(file_num), "wb", encoding="utf-8")
wfp.write(line.encode("utf-8"))
wfp.write(b"\n")
total_num += 1
wfp.close()
print(
"bigscience/xP3mt_code preprocess done. Total line: {}, Total file: {}".format(
total_num, file_num
)
)
dataset = load_dataset("bigscience/xP3mt", "zh")
write_path = root_dir + "/instruction_data/part-xP3mt_zh-{}.jsonl.zst"
total_num = 0
file_num = 1
wfp = zstd.open(write_path.format(file_num), "wb", encoding="utf-8")
for line in tqdm(dataset["train"]):
line = json.dumps(line)
if total_num % 1024 == 0 and total_num > 0:
file_num += 1
wfp.close()
wfp = zstd.open(write_path.format(file_num), "wb", encoding="utf-8")
wfp.write(line.encode("utf-8"))
wfp.write(b"\n")
total_num += 1
wfp.close()
print(
"bigscience/xP3mt_zh preprocess done. Total line: {}, Total file: {}".format(
total_num, file_num
)
)
write_path = root_dir + "/instruction_data/part-sharegpt_90K-{}.jsonl.zst"
total_num = 0
file_num = 1
wfp = zstd.open(write_path.format(file_num), "wb", encoding="utf-8")
wfp = zstd.open(write_path.format(local_name, file_num), "wb", encoding="utf-8")
with open("{}/sg_90k_part1_html_cleaned.json".format(root_dir), "r") as fp:
data1 = json.load(fp)
with open("{}/sg_90k_part2_html_cleaned.json".format(root_dir), "r") as fp:
@ -240,7 +73,7 @@ for line in tqdm(data):
if total_num % 1024 == 0 and total_num > 0:
file_num += 1
wfp.close()
wfp = zstd.open(write_path.format(file_num), "wb", encoding="utf-8")
wfp = zstd.open(write_path.format(local_name, file_num), "wb", encoding="utf-8")
wfp.write(line.encode("utf-8"))
wfp.write(b"\n")
total_num += 1