From ce2d802dc75e6922b2a292519cdb3a5ee9a61501 Mon Sep 17 00:00:00 2001
From: zqwerty <zhuq96@hotmail.com>
Date: Tue, 28 Dec 2021 04:04:21 +0000
Subject: [PATCH] clean up run_seq2seq.py
---
convlab2/base_models/t5/run_seq2seq.py | 16 ++++++----------
1 file changed, 6 insertions(+), 10 deletions(-)
diff --git a/convlab2/base_models/t5/run_seq2seq.py b/convlab2/base_models/t5/run_seq2seq.py
index 30e2b1d5..0679e367 100644
--- a/convlab2/base_models/t5/run_seq2seq.py
+++ b/convlab2/base_models/t5/run_seq2seq.py
@@ -1,4 +1,4 @@
-#!python
+#!/usr/bin/env python
# coding=utf-8
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
@@ -27,12 +27,10 @@ from dataclasses import dataclass, field
from typing import Optional
import datasets
-import nltk # Here to have a nice missing dependency error message early on
import numpy as np
-from datasets import load_dataset, load_metric
+from datasets import load_dataset
import transformers
-from filelock import FileLock
from transformers import (
AutoConfig,
AutoModelForSeq2SeqLM,
@@ -43,7 +41,6 @@ from transformers import (
Seq2SeqTrainingArguments,
set_seed,
)
-from transformers.file_utils import is_offline_mode
from transformers.trainer_utils import EvalPrediction, get_last_checkpoint
from transformers.utils import check_min_version
from transformers.utils.versions import require_version
@@ -109,7 +106,7 @@ class DataTrainingArguments:
task_name: Optional[str] = field(
- default=None, metadata={"help": "The name of the task, e.g., response generation."}
+ default=None, metadata={"help": "The name of the task, e.g., rg (for rgresponse generation)."}
)
dataset_name: Optional[str] = field(
default=None, metadata={"help": "The name of the dataset to use (via the datasets library)."}
@@ -223,7 +220,7 @@ class DataTrainingArguments:
and self.validation_file is None
and self.test_file is None
):
- raise ValueError("Need either a dataset name or a training/validation file/test_file.")
+ raise ValueError("Need either a dataset name or a training/validation/testing file.")
else:
if self.train_file is not None:
extension = self.train_file.split(".")[-1]
@@ -238,8 +235,6 @@ class DataTrainingArguments:
self.val_max_target_length = self.max_target_length
-
-
def main():
# See all possible arguments in src/transformers/training_args.py
# or by passing the --help flag to this script.
@@ -586,6 +581,7 @@ def main():
trainer.log_metrics("eval", metrics)
trainer.save_metrics("eval", metrics)
+ # Predict
if training_args.do_predict:
logger.info("*** Predict ***")
@@ -636,4 +632,4 @@ def _mp_fn(index):
if __name__ == "__main__":
- main()
\ No newline at end of file
+ main()
--
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