diff --git a/audio/speech_synthesis/tacotron2/pytorch/requirements.txt b/audio/speech_synthesis/tacotron2/pytorch/requirements.txt
index 77c339624d127a5f30e2d4520202e619911ac837..71435a5dbbef18d608ce2cf3af400a4ad8286564 100644
--- a/audio/speech_synthesis/tacotron2/pytorch/requirements.txt
+++ b/audio/speech_synthesis/tacotron2/pytorch/requirements.txt
@@ -1,4 +1,4 @@
-matplotlib==3.7.0
+matplotlib==3.8.0
 numpy
 inflect==0.2.5
 scipy
diff --git a/cv/classification/resnet101/pytorch/dataloader/dali_classification.py b/cv/classification/resnet101/pytorch/dataloader/dali_classification.py
index 4c92283b234ceb8d9932eabd1bb1bb01d467fefb..faf9c8cbe4993540b5c5928f856f0d54afb4c3e6 100644
--- a/cv/classification/resnet101/pytorch/dataloader/dali_classification.py
+++ b/cv/classification/resnet101/pytorch/dataloader/dali_classification.py
@@ -14,7 +14,7 @@ import nvidia.dali.ops as ops
 import nvidia.dali.types as types
 from nvidia.dali.pipeline import Pipeline
 from nvidia.dali.plugin.pytorch import DALIClassificationIterator, DALIGenericIterator
-
+from nvidia.dali.plugin.base_iterator import LastBatchPolicy
 class HybridTrainPipe(Pipeline):
     def __init__(self, batch_size, num_threads, device_id, data_dir, size):
         super(HybridTrainPipe, self).__init__(batch_size, num_threads, device_id)
@@ -66,14 +66,14 @@ def get_imagenet_iter_dali(type, image_dir, batch_size, num_threads, device_id,
                                     data_dir = os.path.join(image_dir, "train"),
                                     size=size)
         pip_train.build()
-        dali_iter_train = DALIClassificationIterator(pip_train, size=pip_train.epoch_size("Reader"))
+        dali_iter_train = DALIClassificationIterator(pip_train, size=pip_train.epoch_size("Reader"), last_batch_policy = LastBatchPolicy.DROP)
         return dali_iter_train
     elif type == 'val':
         pip_val = HybridValPipe(batch_size=batch_size, num_threads=num_threads, device_id=device_id,
                                     data_dir = os.path.join(image_dir, "val"),
                                     size=size)
         pip_val.build()
-        dali_iter_val = DALIClassificationIterator(pip_val, size=pip_val.epoch_size("Reader"))
+        dali_iter_val = DALIClassificationIterator(pip_val, size=pip_val.epoch_size("Reader"), last_batch_policy = LastBatchPolicy.DROP)
         return dali_iter_val
 
 
diff --git a/cv/classification/resnet50/pytorch/dataloader/dali_classification.py b/cv/classification/resnet50/pytorch/dataloader/dali_classification.py
index 4c92283b234ceb8d9932eabd1bb1bb01d467fefb..faf9c8cbe4993540b5c5928f856f0d54afb4c3e6 100644
--- a/cv/classification/resnet50/pytorch/dataloader/dali_classification.py
+++ b/cv/classification/resnet50/pytorch/dataloader/dali_classification.py
@@ -14,7 +14,7 @@ import nvidia.dali.ops as ops
 import nvidia.dali.types as types
 from nvidia.dali.pipeline import Pipeline
 from nvidia.dali.plugin.pytorch import DALIClassificationIterator, DALIGenericIterator
-
+from nvidia.dali.plugin.base_iterator import LastBatchPolicy
 class HybridTrainPipe(Pipeline):
     def __init__(self, batch_size, num_threads, device_id, data_dir, size):
         super(HybridTrainPipe, self).__init__(batch_size, num_threads, device_id)
@@ -66,14 +66,14 @@ def get_imagenet_iter_dali(type, image_dir, batch_size, num_threads, device_id,
                                     data_dir = os.path.join(image_dir, "train"),
                                     size=size)
         pip_train.build()
-        dali_iter_train = DALIClassificationIterator(pip_train, size=pip_train.epoch_size("Reader"))
+        dali_iter_train = DALIClassificationIterator(pip_train, size=pip_train.epoch_size("Reader"), last_batch_policy = LastBatchPolicy.DROP)
         return dali_iter_train
     elif type == 'val':
         pip_val = HybridValPipe(batch_size=batch_size, num_threads=num_threads, device_id=device_id,
                                     data_dir = os.path.join(image_dir, "val"),
                                     size=size)
         pip_val.build()
-        dali_iter_val = DALIClassificationIterator(pip_val, size=pip_val.epoch_size("Reader"))
+        dali_iter_val = DALIClassificationIterator(pip_val, size=pip_val.epoch_size("Reader"), last_batch_policy = LastBatchPolicy.DROP)
         return dali_iter_val
 
 
diff --git a/cv/ocr/satrn/pytorch/base/requirements.txt b/cv/ocr/satrn/pytorch/base/requirements.txt
index a6ff6227ea682100d8cabfc0c0e3335e3a62ea58..b3390ac488b752361755a09bf4346d2544861749 100755
--- a/cv/ocr/satrn/pytorch/base/requirements.txt
+++ b/cv/ocr/satrn/pytorch/base/requirements.txt
@@ -1,5 +1,5 @@
 addict==2.4.0
-yapf==0.32.0
+yapf==0.40.1
 lmdb==1.3.0
-rapidfuzz==2.0.7
+rapidfuzz==2.2.0
 shapely
diff --git a/nlp/translation/t5/pytorch/train.py b/nlp/translation/t5/pytorch/train.py
index 047438c37548a60d0918bbfa3e18afb668c372cc..ea62996f06d6d7539600e4e60c4d97a6a617dc2a 100644
--- a/nlp/translation/t5/pytorch/train.py
+++ b/nlp/translation/t5/pytorch/train.py
@@ -18,8 +18,8 @@ from transformers import (HfArgumentParser,
                           default_data_collator,
                           DataCollatorForSeq2Seq,
                           )
-from trainer_seq2seq import Seq2SeqTrainer
-from training_args_seq2seq import Seq2SeqTrainingArguments
+from transformers.trainer_seq2seq import Seq2SeqTrainer
+from transformers.training_args_seq2seq import Seq2SeqTrainingArguments
 
 logger = logging.getLogger(__name__)