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Enable greedy sampling #70

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merged 8 commits into from
Jun 5, 2023
Merged

Enable greedy sampling #70

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16edd63
Enable greedy sampling
May 24, 2023
de9f4de
Refactored based on comments in revision 1
May 25, 2023
f299fb7
Merge branch 'huggingface:main' into main
aashiqmuhamed Jun 3, 2023
7704dbe
Supporting decoder model sampling
Jun 3, 2023
0d16bc6
Addressed comments in rev2
Jun 3, 2023
94c90fe
Merge branch 'huggingface:main' into main
aashiqmuhamed Jun 5, 2023
d60d3e7
Formatted files with make style
Jun 5, 2023
cc878dc
Reformatting after rebase
Jun 5, 2023
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30 changes: 15 additions & 15 deletions notebooks/text-classification/scripts/train.py
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Original file line number Diff line number Diff line change
@@ -1,19 +1,18 @@
import os
import argparse
import logging
import os

import evaluate
import numpy as np
from datasets import load_from_disk
from huggingface_hub import HfFolder
from transformers import (
AutoModelForSequenceClassification,
DataCollatorForSeq2Seq,
AutoTokenizer,
TrainingArguments,
set_seed,
)
from datasets import load_from_disk
import torch
import evaluate
import numpy as np
import logging
from huggingface_hub import HfFolder
from transformers import TrainingArguments

from optimum.neuron import TrainiumTrainer as Trainer


Expand All @@ -22,15 +21,14 @@

print(f"is precompilation: {os.environ.get('NEURON_PARALLEL_COMPILE')}")


def parse_args():
"""Parse the arguments."""
parser = argparse.ArgumentParser()
# add model id and dataset path argument
parser.add_argument("--model_id", type=str, default="bert-large-uncased", help="Model id to use for training.")
parser.add_argument("--dataset_path", type=str, default="dataset", help="Path to the already processed dataset.")
parser.add_argument(
"--output_dir", type=str, default=None, help="Hugging Face Repository id for uploading models"
)
parser.add_argument("--output_dir", type=str, default=None, help="Hugging Face Repository id for uploading models")
parser.add_argument(
"--repository_id", type=str, default=None, help="Hugging Face Repository id for uploading models"
)
Expand All @@ -55,9 +53,11 @@ def parse_args():
args = parser.parse_known_args()
return args


# Metric Id
metric = evaluate.load("f1")


# Metric helper method
def compute_metrics(eval_pred):
predictions, labels = eval_pred
Expand All @@ -73,11 +73,11 @@ def training_function(args):
train_dataset = load_from_disk(os.path.join(args.dataset_path, "train"))
eval_dataset = load_from_disk(os.path.join(args.dataset_path, "eval"))
tokenizer = AutoTokenizer.from_pretrained(args.model_id)

# Prepare model labels - useful for inference
labels = train_dataset.features["labels"].names
num_labels = len(labels)
label2id, id2label = dict(), dict()
label2id, id2label = {}, {}
for i, label in enumerate(labels):
label2id[label] = str(i)
id2label[str(i)] = label
Expand Down Expand Up @@ -143,4 +143,4 @@ def main():


if __name__ == "__main__":
main()
main()