Commit
·
44bfcd5
1
Parent(s):
b356e6e
Track lfs
Browse filesThis view is limited to 50 files because it contains too many changes.
See raw diff
- .gitattributes +1024 -0
- inference_c4.py +166 -0
- inference_c4.sh +26 -0
- preptasky.sh +29 -0
- tr13f-6b3-mtf-tasky.sh +211 -0
- train/{c4tasky_00000_to_356317.jsonl → c4tasky_00000-of-01024.jsonl} +2 -2
- train/c4tasky_00001-of-01024.jsonl +3 -0
- train/c4tasky_00002-of-01024.jsonl +3 -0
- train/c4tasky_00003-of-01024.jsonl +3 -0
- train/c4tasky_00004-of-01024.jsonl +3 -0
- train/c4tasky_00005-of-01024.jsonl +3 -0
- train/c4tasky_00006-of-01024.jsonl +3 -0
- train/c4tasky_00007-of-01024.jsonl +3 -0
- train/c4tasky_00008-of-01024.jsonl +3 -0
- train/c4tasky_00009-of-01024.jsonl +3 -0
- train/c4tasky_00010-of-01024.jsonl +3 -0
- train/c4tasky_00011-of-01024.jsonl +3 -0
- train/c4tasky_00012-of-01024.jsonl +3 -0
- train/c4tasky_00013-of-01024.jsonl +3 -0
- train/c4tasky_00014-of-01024.jsonl +3 -0
- train/c4tasky_00015-of-01024.jsonl +3 -0
- train/c4tasky_00016-of-01024.jsonl +3 -0
- train/c4tasky_00017-of-01024.jsonl +3 -0
- train/c4tasky_00018-of-01024.jsonl +3 -0
- train/c4tasky_00019-of-01024.jsonl +3 -0
- train/c4tasky_00020-of-01024.jsonl +3 -0
- train/c4tasky_00021-of-01024.jsonl +3 -0
- train/c4tasky_00022-of-01024.jsonl +3 -0
- train/c4tasky_00023-of-01024.jsonl +3 -0
- train/c4tasky_00024-of-01024.jsonl +3 -0
- train/c4tasky_00025-of-01024.jsonl +3 -0
- train/c4tasky_00026-of-01024.jsonl +3 -0
- train/c4tasky_00027-of-01024.jsonl +3 -0
- train/c4tasky_00028-of-01024.jsonl +3 -0
- train/c4tasky_00029-of-01024.jsonl +3 -0
- train/c4tasky_00030-of-01024.jsonl +3 -0
- train/c4tasky_00031-of-01024.jsonl +3 -0
- train/c4tasky_00032-of-01024.jsonl +3 -0
- train/c4tasky_00033-of-01024.jsonl +3 -0
- train/c4tasky_00034-of-01024.jsonl +3 -0
- train/c4tasky_00035-of-01024.jsonl +3 -0
- train/c4tasky_00036-of-01024.jsonl +3 -0
- train/c4tasky_00037-of-01024.jsonl +3 -0
- train/c4tasky_00038-of-01024.jsonl +3 -0
- train/c4tasky_00039-of-01024.jsonl +3 -0
- train/c4tasky_00040-of-01024.jsonl +3 -0
- train/c4tasky_00041-of-01024.jsonl +3 -0
- train/c4tasky_00042-of-01024.jsonl +3 -0
- train/c4tasky_00043-of-01024.jsonl +3 -0
- train/c4tasky_00044-of-01024.jsonl +3 -0
.gitattributes
CHANGED
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@@ -56,3 +56,1027 @@ train/taskyc4_00000_to_356317.jsonl filter=lfs diff=lfs merge=lfs -text
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| 56 |
train/taskyc4_356317_to_712634.jsonl filter=lfs diff=lfs merge=lfs -text
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| 57 |
train/c4tasky_00000_to_356317.jsonl filter=lfs diff=lfs merge=lfs -text
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| 58 |
train/c4tasky_356317_to_712634.jsonl filter=lfs diff=lfs merge=lfs -text
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inference_c4.py
ADDED
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# !pip install -q transformers datasets sentencepiece
|
| 2 |
+
import argparse
|
| 3 |
+
import gc
|
| 4 |
+
import json
|
| 5 |
+
import os
|
| 6 |
+
|
| 7 |
+
import datasets
|
| 8 |
+
import pandas as pd
|
| 9 |
+
import torch
|
| 10 |
+
from tqdm import tqdm
|
| 11 |
+
from transformers import AutoModelForSequenceClassification, AutoTokenizer
|
| 12 |
+
|
| 13 |
+
TOTAL_NUM_FILES_C4_TRAIN = 1024
|
| 14 |
+
|
| 15 |
+
|
| 16 |
+
def parse_args():
|
| 17 |
+
parser = argparse.ArgumentParser()
|
| 18 |
+
|
| 19 |
+
parser.add_argument(
|
| 20 |
+
"--start",
|
| 21 |
+
type=int,
|
| 22 |
+
required=True,
|
| 23 |
+
help="Starting file number to download. Valid values: 0 - 1023",
|
| 24 |
+
)
|
| 25 |
+
parser.add_argument(
|
| 26 |
+
"--end",
|
| 27 |
+
type=int,
|
| 28 |
+
required=True,
|
| 29 |
+
help="Ending file number to download. Valid values: 0 - 1023",
|
| 30 |
+
)
|
| 31 |
+
parser.add_argument("--batch_size", type=int, default=16, help="Batch size")
|
| 32 |
+
parser.add_argument(
|
| 33 |
+
"--model_name",
|
| 34 |
+
type=str,
|
| 35 |
+
default="taskydata/deberta-v3-base_10xp3nirstbbflanseuni_10xc4",
|
| 36 |
+
help="Model name",
|
| 37 |
+
)
|
| 38 |
+
parser.add_argument(
|
| 39 |
+
"--local_cache_location",
|
| 40 |
+
type=str,
|
| 41 |
+
default="c4_download",
|
| 42 |
+
help="local cache location from where the dataset will be loaded",
|
| 43 |
+
)
|
| 44 |
+
parser.add_argument(
|
| 45 |
+
"--use_local_cache_location",
|
| 46 |
+
type=bool,
|
| 47 |
+
default=True,
|
| 48 |
+
help="Set True if you want to load the dataset from local cache.",
|
| 49 |
+
)
|
| 50 |
+
parser.add_argument(
|
| 51 |
+
"--clear_dataset_cache",
|
| 52 |
+
type=bool,
|
| 53 |
+
default=False,
|
| 54 |
+
help="Set True if you want to delete the dataset files from the cache after inference.",
|
| 55 |
+
)
|
| 56 |
+
parser.add_argument(
|
| 57 |
+
"--release_memory",
|
| 58 |
+
type=bool,
|
| 59 |
+
default=True,
|
| 60 |
+
help="Set True if you want to release the memory of used variables.",
|
| 61 |
+
)
|
| 62 |
+
|
| 63 |
+
args = parser.parse_args()
|
| 64 |
+
return args
|
| 65 |
+
|
| 66 |
+
|
| 67 |
+
def chunks(l, n):
|
| 68 |
+
for i in range(0, len(l), n):
|
| 69 |
+
yield l[i : i + n]
|
| 70 |
+
|
| 71 |
+
|
| 72 |
+
def batch_tokenize(data, batch_size):
|
| 73 |
+
batches = list(chunks(data, batch_size))
|
| 74 |
+
tokenized_batches = []
|
| 75 |
+
for batch in batches:
|
| 76 |
+
# max_length will automatically be set to the max length of the model (512 for deberta)
|
| 77 |
+
tensor = tokenizer(
|
| 78 |
+
batch,
|
| 79 |
+
return_tensors="pt",
|
| 80 |
+
padding="max_length",
|
| 81 |
+
truncation=True,
|
| 82 |
+
max_length=512,
|
| 83 |
+
)
|
| 84 |
+
tokenized_batches.append(tensor)
|
| 85 |
+
return tokenized_batches, batches
|
| 86 |
+
|
| 87 |
+
|
| 88 |
+
def batch_inference(data, batch_size=16):
|
| 89 |
+
preds = []
|
| 90 |
+
tokenized_batches, batches = batch_tokenize(data, batch_size)
|
| 91 |
+
for i in tqdm(range(len(batches))):
|
| 92 |
+
with torch.no_grad():
|
| 93 |
+
logits = model(**tokenized_batches[i].to(device)).logits.cpu()
|
| 94 |
+
preds.extend(logits)
|
| 95 |
+
return preds
|
| 96 |
+
|
| 97 |
+
|
| 98 |
+
if __name__ == "__main__":
|
| 99 |
+
args = parse_args()
|
| 100 |
+
|
| 101 |
+
tokenizer = AutoTokenizer.from_pretrained(args.model_name)
|
| 102 |
+
model = AutoModelForSequenceClassification.from_pretrained(args.model_name)
|
| 103 |
+
device = torch.device("cuda") if torch.cuda.is_available() else torch.device("cpu")
|
| 104 |
+
model.to(device)
|
| 105 |
+
model.eval()
|
| 106 |
+
|
| 107 |
+
for file_number in range(args.start, args.end + 1):
|
| 108 |
+
global_id = (
|
| 109 |
+
str(file_number).zfill(5) + "-of-" + str(TOTAL_NUM_FILES_C4_TRAIN).zfill(5)
|
| 110 |
+
)
|
| 111 |
+
c4taskyprobas_path = f"c4taskyprobas_{global_id}.jsonl"
|
| 112 |
+
c4tasky_path = f"c4tasky_{global_id}.jsonl"
|
| 113 |
+
|
| 114 |
+
if os.path.exists(c4taskyprobas_path) and os.path.exists(c4tasky_path):
|
| 115 |
+
print(f"Already done: {c4taskyprobas_path} & {c4tasky_path}")
|
| 116 |
+
exit()
|
| 117 |
+
|
| 118 |
+
if args.use_local_cache_location:
|
| 119 |
+
file_name = f"c4-train.{global_id}.json.gz"
|
| 120 |
+
data_files = {"train": f"{args.local_cache_location}/{file_name}"}
|
| 121 |
+
c4 = datasets.load_dataset("json", data_files=data_files, split="train")
|
| 122 |
+
else:
|
| 123 |
+
file_name = f"en/c4-train.{global_id}.json.gz"
|
| 124 |
+
data_files = {"train": file_name}
|
| 125 |
+
c4 = datasets.load_dataset(
|
| 126 |
+
"allenai/c4", data_files=data_files, split="train"
|
| 127 |
+
)
|
| 128 |
+
df = pd.DataFrame(c4, index=None)
|
| 129 |
+
texts = df["text"].to_list()
|
| 130 |
+
preds = batch_inference(texts, batch_size=args.batch_size)
|
| 131 |
+
|
| 132 |
+
assert len(preds) == len(texts)
|
| 133 |
+
|
| 134 |
+
# Write two jsonl files:
|
| 135 |
+
# 1) Probas for all of C4
|
| 136 |
+
# 2) Probas + texts for samples predicted as tasky
|
| 137 |
+
df['timestamp'] = df['timestamp'].astype(str)
|
| 138 |
+
with open(c4taskyprobas_path, "w") as f, open(c4tasky_path, "w") as g:
|
| 139 |
+
for i in range(len(preds)):
|
| 140 |
+
predicted_class_id = preds[i].argmax().item()
|
| 141 |
+
pred = model.config.id2label[predicted_class_id]
|
| 142 |
+
tasky_proba = torch.softmax(preds[i], dim=-1)[-1].item()
|
| 143 |
+
f.write(json.dumps({"proba": tasky_proba}) + "\n")
|
| 144 |
+
# If it's tasky, save!
|
| 145 |
+
if int(predicted_class_id) == 1:
|
| 146 |
+
g.write(
|
| 147 |
+
json.dumps(
|
| 148 |
+
{
|
| 149 |
+
"proba": tasky_proba,
|
| 150 |
+
"text": texts[i],
|
| 151 |
+
"timestamp": df["timestamp"][i],
|
| 152 |
+
"url": df["url"][i],
|
| 153 |
+
}
|
| 154 |
+
)
|
| 155 |
+
+ "\n"
|
| 156 |
+
)
|
| 157 |
+
# release memory
|
| 158 |
+
if args.release_memory:
|
| 159 |
+
del preds
|
| 160 |
+
del texts
|
| 161 |
+
del df
|
| 162 |
+
gc.collect()
|
| 163 |
+
|
| 164 |
+
# Delete the processed dataset file from the cache
|
| 165 |
+
if args.clear_dataset_cache:
|
| 166 |
+
os.remove(f"{args.local_cache_location}/{file_name}")
|
inference_c4.sh
ADDED
|
@@ -0,0 +1,26 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#!/bin/bash
|
| 2 |
+
#SBATCH --job-name=inferencec4
|
| 3 |
+
#SBATCH --partition=gpu_p5
|
| 4 |
+
#SBATCH --constraint=a100
|
| 5 |
+
#SBATCH --nodes=1
|
| 6 |
+
#SBATCH --ntasks-per-node=1 # crucial - only 1 task per dist per node!
|
| 7 |
+
#SBATCH --cpus-per-task=8 # number of cores per tasks
|
| 8 |
+
#SBATCH --hint=nomultithread # we get physical cores not logical
|
| 9 |
+
#SBATCH --gres=gpu:1 # number of gpus
|
| 10 |
+
#SBATCH --time 12:00:00 # maximum execution time (HH:MM:SS)
|
| 11 |
+
#SBATCH --output=%x-%j.out # output file name
|
| 12 |
+
#SBATCH --account=ajs@a100
|
| 13 |
+
|
| 14 |
+
set -x -e
|
| 15 |
+
|
| 16 |
+
source $six_ALL_CCFRWORK/start-tr13f-6B3-ml-t0
|
| 17 |
+
echo "START TIME: $(date)"
|
| 18 |
+
|
| 19 |
+
NUM_SAMPLES=1024
|
| 20 |
+
NUM_SAMPLES_PER_JOB=1
|
| 21 |
+
|
| 22 |
+
TASK_START=$((($SLURM_ARRAY_TASK_ID) * $NUM_SAMPLES_PER_JOB))
|
| 23 |
+
TASK_END=$(($TASK_START + $NUM_SAMPLES_PER_JOB))
|
| 24 |
+
|
| 25 |
+
echo "Starting task $SLURM_ARRAY_TASK_ID with start $TASK_START and end $TASK_END"
|
| 26 |
+
python inference_c4.py --start $TASK_START --end $TASK_END
|
preptasky.sh
ADDED
|
@@ -0,0 +1,29 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#!/bin/bash
|
| 2 |
+
#SBATCH --job-name=tasky # job name
|
| 3 |
+
#SBATCH --ntasks=1 # number of MP tasks
|
| 4 |
+
#SBATCH --nodes=1
|
| 5 |
+
#SBATCH --cpus-per-task=40 # number of cores per tasks
|
| 6 |
+
#SBATCH --hint=nomultithread # we get physical cores not logical
|
| 7 |
+
#SBATCH --time=20:00:00 # maximum execution time (HH:MM:SS)
|
| 8 |
+
#SBATCH --output=%x-%j.out # output file name
|
| 9 |
+
#SBATCH --account=ajs@cpu
|
| 10 |
+
#SBATCH --partition=cpu_p1
|
| 11 |
+
#SBATCH --qos=qos_cpu-t3
|
| 12 |
+
|
| 13 |
+
set -x -e
|
| 14 |
+
source $six_ALL_CCFRWORK/start-tr13f-6B3-ml-t0
|
| 15 |
+
MEGATRON_DEEPSPEED_REPO=$six_ALL_CCFRWORK/code/tr13f-6B3-ml-t0/Megatron-DeepSpeed
|
| 16 |
+
TOKENIZER_PATH="bigscience/tokenizer"
|
| 17 |
+
|
| 18 |
+
cat c4tasky_*.jsonl > merged_dups_c4tasky.jsonl
|
| 19 |
+
sort -u merged_dups_c4tasky.jsonl | shuf > merged_c4tasky.jsonl
|
| 20 |
+
|
| 21 |
+
cd $MEGATRON_DEEPSPEED_REPO
|
| 22 |
+
python tools/preprocess_data.py \
|
| 23 |
+
--input /gpfswork/rech/six/commun/code/turku/tasky/merged_c4tasky.jsonl \
|
| 24 |
+
--output-prefix /gpfswork/rech/six/commun/code/turku/tasky/tasky_bloom \
|
| 25 |
+
--dataset-impl mmap \
|
| 26 |
+
--json-key text \
|
| 27 |
+
--tokenizer-type PretrainedFromHF \
|
| 28 |
+
--tokenizer-name-or-path $TOKENIZER_PATH \
|
| 29 |
+
--workers 35
|
tr13f-6b3-mtf-tasky.sh
ADDED
|
@@ -0,0 +1,211 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#!/bin/bash
|
| 2 |
+
#SBATCH --job-name=tr13f-6b3-mtf-tasky
|
| 3 |
+
#SBATCH --partition=gpu_p5
|
| 4 |
+
#SBATCH --constraint=a100
|
| 5 |
+
#SBATCH --nodes=8
|
| 6 |
+
#SBATCH --ntasks-per-node=1 # crucial - only 1 task per dist per node!
|
| 7 |
+
#SBATCH --cpus-per-task=64 # number of cores per tasks
|
| 8 |
+
#SBATCH --hint=nomultithread # we get physical cores not logical
|
| 9 |
+
#SBATCH --gres=gpu:8 # number of gpus
|
| 10 |
+
#SBATCH --time 12:00:00 # maximum execution time (HH:MM:SS)
|
| 11 |
+
#SBATCH --output=%x-%j.out # output file name
|
| 12 |
+
#SBATCH --account=ajs@a100
|
| 13 |
+
|
| 14 |
+
set -x -e
|
| 15 |
+
|
| 16 |
+
source $six_ALL_CCFRWORK/start-tr13f-6B3-ml-t0
|
| 17 |
+
echo "START TIME: $(date)"
|
| 18 |
+
|
| 19 |
+
variant=tasky
|
| 20 |
+
|
| 21 |
+
DATA_OUTPUT_PATH=$six_ALL_CCFRSCRATCH/checkpoints/tr13f-6B3-ml-t0
|
| 22 |
+
CHECKPOINT_PATH=$DATA_OUTPUT_PATH/checkpoints/$variant
|
| 23 |
+
REPO_PATH=$DATA_OUTPUT_PATH/tr13f-6B3-ml-t0-logs
|
| 24 |
+
TENSORBOARD_PATH=$REPO_PATH/tensorboard/$variant
|
| 25 |
+
LOGS_PATH=$REPO_PATH/logs/$variant
|
| 26 |
+
mkdir -p $LOGS_PATH
|
| 27 |
+
mkdir -p $TENSORBOARD_PATH
|
| 28 |
+
|
| 29 |
+
MEGATRON_DEEPSPEED_REPO=/gpfswork/rech/six/commun/code/tr13f-6B3-ml-t0/megdslossseq/Megatron-DeepSpeed
|
| 30 |
+
cd $MEGATRON_DEEPSPEED_REPO
|
| 31 |
+
|
| 32 |
+
KILL_SWITCH_PATH=$MEGATRON_DEEPSPEED_REPO/kill-switch-tr13f-6B3-mtf
|
| 33 |
+
|
| 34 |
+
TRAIN_DATA_PATH=$six_ALL_CCFRWORK/code/tr13f-6B3-ml-t0/Megatron-DeepSpeed/data/tasky_train.txt
|
| 35 |
+
#VALID_DATA_PATH=$six_ALL_CCFRWORK/code/tr13f-6B3-ml-t0/Megatron-DeepSpeed/data/p31_validation.txt
|
| 36 |
+
VALID_DATA_PATH=$six_ALL_CCFRWORK/code/tr13f-6B3-ml-t0/Megatron-DeepSpeed/data/tasky_validation.txt
|
| 37 |
+
|
| 38 |
+
TOKENIZER_NAME_OR_PATH=bigscience/tokenizer
|
| 39 |
+
|
| 40 |
+
# defining the right environment variables
|
| 41 |
+
export TRANSFORMERS_CACHE=$six_ALL_CCFRWORK/models
|
| 42 |
+
export HF_DATASETS_CACHE=$six_ALL_CCFRWORK/datasets
|
| 43 |
+
export HF_MODULES_CACHE=$six_ALL_CCFRWORK/modules
|
| 44 |
+
export HF_METRICS_CACHE=$six_ALL_CCFRWORK/metrics
|
| 45 |
+
export HF_DATASETS_OFFLINE=1
|
| 46 |
+
export TRANSFORMERS_OFFLINE=1
|
| 47 |
+
|
| 48 |
+
# testing for potential faulty nodes
|
| 49 |
+
# srun --jobid $SLURM_JOBID bash -c 'python -c "import torch, socket; print(socket.gethostname(), torch.cuda.is_available())"'
|
| 50 |
+
|
| 51 |
+
# so processes know who to talk to
|
| 52 |
+
MASTER_ADDR=$(scontrol show hostnames $SLURM_JOB_NODELIST | head -n 1)
|
| 53 |
+
MASTER_PORT=6001
|
| 54 |
+
|
| 55 |
+
GPUS_PER_NODE=8
|
| 56 |
+
NNODES=$SLURM_NNODES
|
| 57 |
+
|
| 58 |
+
PP_SIZE=1
|
| 59 |
+
TP_SIZE=1
|
| 60 |
+
|
| 61 |
+
# T0 paper:
|
| 62 |
+
# ...truncate input and target sequences to 1024 and 256 tokens...
|
| 63 |
+
# ...use a batch size of 1024 sequences ... 2^20 total input tokens per batch...
|
| 64 |
+
# We use 2048 total tokens and 512 batch size = 2**20
|
| 65 |
+
MICRO_BATCH_SIZE=4
|
| 66 |
+
GLOBAL_BATCH_SIZE=2048
|
| 67 |
+
|
| 68 |
+
NLAYERS=30
|
| 69 |
+
NHIDDEN=4096
|
| 70 |
+
NHEADS=32
|
| 71 |
+
SEQ_LEN=2048
|
| 72 |
+
|
| 73 |
+
SAVE_INTERVAL=250
|
| 74 |
+
|
| 75 |
+
TRAIN_SAMPLES=6_348_800
|
| 76 |
+
|
| 77 |
+
# T0 paper:
|
| 78 |
+
# "...we use a learning rate of 1e-3..."
|
| 79 |
+
# However, they use Adafactor, which adapts the LR
|
| 80 |
+
# For Adam we likely want a lower one
|
| 81 |
+
# FLAN:
|
| 82 |
+
# "...decay of 1e-4..""
|
| 83 |
+
|
| 84 |
+
# Uncomment for the first step
|
| 85 |
+
# --no-load-optim \
|
| 86 |
+
OPTIMIZER_ARGS=" \
|
| 87 |
+
--optimizer adam \
|
| 88 |
+
--adam-beta1 0.9 \
|
| 89 |
+
--adam-beta2 0.95 \
|
| 90 |
+
--adam-eps 1e-8 \
|
| 91 |
+
--lr 2e-5 \
|
| 92 |
+
--lr-decay-style constant \
|
| 93 |
+
--lr-warmup-samples 0 \
|
| 94 |
+
--clip-grad 1.0 \
|
| 95 |
+
--weight-decay 1e-4 \
|
| 96 |
+
--no-load-optim \
|
| 97 |
+
--reset-progress \
|
| 98 |
+
"
|
| 99 |
+
# for 20h 1190, for 100h 5990
|
| 100 |
+
# --exit-duration-in-mins 1190 \
|
| 101 |
+
EXIT_OPTS=" \
|
| 102 |
+
--exit-duration-in-mins 5990 \
|
| 103 |
+
"
|
| 104 |
+
|
| 105 |
+
GPT_ARGS=" \
|
| 106 |
+
--pp-partition-method 'type:transformer|embedding' \
|
| 107 |
+
--num-layers $NLAYERS \
|
| 108 |
+
--hidden-size $NHIDDEN \
|
| 109 |
+
--num-attention-heads $NHEADS \
|
| 110 |
+
--seq-length $SEQ_LEN \
|
| 111 |
+
--max-position-embeddings $SEQ_LEN \
|
| 112 |
+
--micro-batch-size $MICRO_BATCH_SIZE \
|
| 113 |
+
--global-batch-size $GLOBAL_BATCH_SIZE \
|
| 114 |
+
--train-samples $TRAIN_SAMPLES \
|
| 115 |
+
--tokenizer-type PretrainedFromHF \
|
| 116 |
+
--tokenizer-name-or-path $TOKENIZER_NAME_OR_PATH \
|
| 117 |
+
--init-method-std 0.0048 \
|
| 118 |
+
--embed-layernorm \
|
| 119 |
+
--fp16 \
|
| 120 |
+
--seed 42 \
|
| 121 |
+
--position-embedding-type alibi \
|
| 122 |
+
--checkpoint-activations \
|
| 123 |
+
--abort-on-unmet-fused-kernel-constraints \
|
| 124 |
+
--kill-switch-path $KILL_SWITCH_PATH \
|
| 125 |
+
--pad-vocab-size-to 250880 \
|
| 126 |
+
$OPTIMIZER_ARGS \
|
| 127 |
+
$EXIT_OPTS \
|
| 128 |
+
"
|
| 129 |
+
|
| 130 |
+
OUTPUT_ARGS=" \
|
| 131 |
+
--log-interval 1 \
|
| 132 |
+
--save-interval $SAVE_INTERVAL \
|
| 133 |
+
--eval-interval 250 \
|
| 134 |
+
--eval-iters 50 \
|
| 135 |
+
--tensorboard-dir $TENSORBOARD_PATH \
|
| 136 |
+
--tensorboard-queue-size 5 \
|
| 137 |
+
--log-timers-to-tensorboard \
|
| 138 |
+
--log-batch-size-to-tensorboard \
|
| 139 |
+
--log-validation-ppl-to-tensorboard \
|
| 140 |
+
"
|
| 141 |
+
|
| 142 |
+
ZERO_STAGE=1
|
| 143 |
+
|
| 144 |
+
config_json="./ds_config.$SLURM_JOBID.json"
|
| 145 |
+
|
| 146 |
+
# Deepspeed figures out GAS dynamically from dynamic GBS via set_train_batch_size()
|
| 147 |
+
cat <<EOT > $config_json
|
| 148 |
+
{
|
| 149 |
+
"train_micro_batch_size_per_gpu": $MICRO_BATCH_SIZE,
|
| 150 |
+
"train_batch_size": $GLOBAL_BATCH_SIZE,
|
| 151 |
+
"gradient_clipping": 1.0,
|
| 152 |
+
"zero_optimization": {
|
| 153 |
+
"stage": $ZERO_STAGE
|
| 154 |
+
},
|
| 155 |
+
"fp16": {
|
| 156 |
+
"enabled": true,
|
| 157 |
+
"loss_scale": 0,
|
| 158 |
+
"loss_scale_window": 500,
|
| 159 |
+
"hysteresis": 2,
|
| 160 |
+
"min_loss_scale": 1,
|
| 161 |
+
"initial_scale_power": 12
|
| 162 |
+
},
|
| 163 |
+
"steps_per_print": 2000,
|
| 164 |
+
"wall_clock_breakdown": false
|
| 165 |
+
}
|
| 166 |
+
EOT
|
| 167 |
+
|
| 168 |
+
|
| 169 |
+
DEEPSPEED_ARGS=" \
|
| 170 |
+
--deepspeed \
|
| 171 |
+
--deepspeed_config ${config_json} \
|
| 172 |
+
--zero-stage ${ZERO_STAGE} \
|
| 173 |
+
--deepspeed-activation-checkpointing \
|
| 174 |
+
"
|
| 175 |
+
|
| 176 |
+
export LAUNCHER="python -u -m torch.distributed.run \
|
| 177 |
+
--nproc_per_node $GPUS_PER_NODE \
|
| 178 |
+
--nnodes $NNODES \
|
| 179 |
+
--rdzv_endpoint $MASTER_ADDR:$MASTER_PORT \
|
| 180 |
+
--rdzv_backend c10d \
|
| 181 |
+
--max_restarts 0 \
|
| 182 |
+
--tee 3 \
|
| 183 |
+
"
|
| 184 |
+
|
| 185 |
+
export CMD=" \
|
| 186 |
+
`pwd`/finetune_t0.py \
|
| 187 |
+
--tensor-model-parallel-size $TP_SIZE \
|
| 188 |
+
--pipeline-model-parallel-size $PP_SIZE \
|
| 189 |
+
$GPT_ARGS \
|
| 190 |
+
$OUTPUT_ARGS \
|
| 191 |
+
--save $CHECKPOINT_PATH \
|
| 192 |
+
--load $CHECKPOINT_PATH \
|
| 193 |
+
--train-weighted-split-paths-path $TRAIN_DATA_PATH \
|
| 194 |
+
--valid-weighted-split-paths-path $VALID_DATA_PATH \
|
| 195 |
+
--dataloader-type single \
|
| 196 |
+
--data-impl mmap \
|
| 197 |
+
--distributed-backend nccl \
|
| 198 |
+
$DEEPSPEED_ARGS \
|
| 199 |
+
"
|
| 200 |
+
|
| 201 |
+
echo $CMD
|
| 202 |
+
|
| 203 |
+
# do not remove or the training will hang and nodes will be lost w/o this workaround
|
| 204 |
+
export CUDA_LAUNCH_BLOCKING=1
|
| 205 |
+
|
| 206 |
+
# hide duplicated errors using this hack - will be properly fixed in pt-1.12
|
| 207 |
+
export TORCHELASTIC_ERROR_FILE=/tmp/torch-elastic-error.json
|
| 208 |
+
|
| 209 |
+
clear; srun --jobid $SLURM_JOBID bash -c "$LAUNCHER --node_rank \$SLURM_PROCID $CMD" 2>&1 | tee -a $LOGS_PATH/main_log.txt
|
| 210 |
+
|
| 211 |
+
echo "END TIME: $(date)"
|
train/{c4tasky_00000_to_356317.jsonl → c4tasky_00000-of-01024.jsonl}
RENAMED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:0ff7cd48692517413365daecb7a914d5252f3b77ae5c67e66613ee4e2ca5cbfa
|
| 3 |
+
size 9145244
|
train/c4tasky_00001-of-01024.jsonl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:f3057bc20b8e04973ba1f839866d3e7334eb9190a07bd86e123c54648e3817bc
|
| 3 |
+
size 8910777
|
train/c4tasky_00002-of-01024.jsonl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:9946b6210a545bc9c5eace96ec34ec76a36ee1cc567fc281fe4285893427357f
|
| 3 |
+
size 9162034
|
train/c4tasky_00003-of-01024.jsonl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:0b94f4d74559835995ec7ce7cf40563eae393a922a0f3fee1d0c1adc944651c8
|
| 3 |
+
size 8992826
|
train/c4tasky_00004-of-01024.jsonl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:4d5312878d68b3b5706bccbc0d6e3a240d581a87104e8f0d4be908ef6835eb4c
|
| 3 |
+
size 9012500
|
train/c4tasky_00005-of-01024.jsonl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:439e7d52d2c770daaa8ccbb18da6bb73852f3aa5fa1a3c977b720d96b6c517a5
|
| 3 |
+
size 9147489
|
train/c4tasky_00006-of-01024.jsonl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:b51cade7350fef77f1d998e22cc03c04422484c6202fa862dc9a9d70e347a30a
|
| 3 |
+
size 8903917
|
train/c4tasky_00007-of-01024.jsonl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:da219d7b5a64f761b2bf4e1618962461fda52b804566e6afe98cb44305292e12
|
| 3 |
+
size 9818037
|
train/c4tasky_00008-of-01024.jsonl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:55c5f1e312c4741872e956b2ab692a6ed52ea0697da3df407b5bc6eb933c015f
|
| 3 |
+
size 8745909
|
train/c4tasky_00009-of-01024.jsonl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:eda43412be8f663bdb4f01455ad5545b06dfa89bf092f0be9bbfe5672346e10f
|
| 3 |
+
size 9160663
|
train/c4tasky_00010-of-01024.jsonl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
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oid sha256:83651956a55e0ffa07db424ea94206ee927bc6729e1395d6a6f7a3f53399e5f6
|
| 3 |
+
size 9513213
|
train/c4tasky_00011-of-01024.jsonl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:30894582cbd8d107bb93472d13e6226e5cd29918f939ddc386440aca7d965d93
|
| 3 |
+
size 8267410
|
train/c4tasky_00012-of-01024.jsonl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
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oid sha256:23c6dd22017501ee2e614f1e2f5c29fcb5e478d4bdebc3f16203d0055b56c290
|
| 3 |
+
size 9167728
|
train/c4tasky_00013-of-01024.jsonl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:a4a08b0f3b9f89beb33ade0976c95c2e726e3e067b50b11060cf4c41e874ccad
|
| 3 |
+
size 9461706
|
train/c4tasky_00014-of-01024.jsonl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:39f2a335aae170b1474f97e7135637a376970f714af3136843aea56088921b9a
|
| 3 |
+
size 9357248
|
train/c4tasky_00015-of-01024.jsonl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:788c5f8a65222d06802b2550164273c5216a745938cd44d6e52a002dccc01552
|
| 3 |
+
size 8858805
|
train/c4tasky_00016-of-01024.jsonl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:887b678518431a3db37f6f23cdbabde9a4a531009255f0f6c2a8b8e125a94f3a
|
| 3 |
+
size 8999456
|
train/c4tasky_00017-of-01024.jsonl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:98aaf683baadb8bfaf79e68f33faaab51d658b73d5474d46ac604376aeae9188
|
| 3 |
+
size 9262309
|
train/c4tasky_00018-of-01024.jsonl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:1987ab96558aad172f05cf1ef0a37b8d739a36f63f21f1237f09f5c387f18f73
|
| 3 |
+
size 9718373
|
train/c4tasky_00019-of-01024.jsonl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:1457433f1b5f025378692f12daabb298dc3701078fe0bfb15dbd80805fa6ff3e
|
| 3 |
+
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