run the command “python train.py”, the issues “OpenBLAS blas_thread_init: pthread_create failed for thread 6 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 7 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 8 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 9 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 10 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 11 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 12 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 13 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 14 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 15 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 16 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 17 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 18 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 19 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 20 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 21 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 22 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 23 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 24 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 25 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 26 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 27 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 28 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 29 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 30 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 31 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 32 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 33 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 34 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 35 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 36 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 37 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 38 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 39 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 40 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 41 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 42 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 43 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 44 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 45 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 46 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 47 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 48 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 49 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 50 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 51 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 52 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 53 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 54 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 55 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 56 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 57 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 58 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 59 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 60 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 61 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 62 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
OpenBLAS blas_thread_init: pthread_create failed for thread 63 of 64: Resource temporarily unavailable
OpenBLAS blas_thread_init: RLIMIT_NPROC 4096 current, 1156891 max
Traceback (most recent call last):
File “train.py”, line 16, in
from transformers import get_linear_schedule_with_warmup
File “”, line 1032, in _handle_fromlist
File “/homes/jl007/.conda/envs/torch/lib/python3.7/site-packages/transformers/utils/import_utils.py”, line 847, in getattr
module = self._get_module(self._class_to_module[name])
File “/homes/jl007/.conda/envs/torch/lib/python3.7/site-packages/transformers/utils/import_utils.py”, line 857, in _get_module
return importlib.import_module(”." + module_name, self.name)
File “/homes/jl007/.conda/envs/torch/lib/python3.7/importlib/init.py”, line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File “/homes/jl007/.conda/envs/torch/lib/python3.7/site-packages/transformers/optimization.py”, line 26, in
from .trainer_utils import SchedulerType
File “/homes/jl007/.conda/envs/torch/lib/python3.7/site-packages/transformers/trainer_utils.py”, line 46, in
import tensorflow as tf
File “/homes/jl007/.conda/envs/torch/lib/python3.7/site-packages/tensorflow/init.py”, line 473, in
keras._load()
File “/homes/jl007/.conda/envs/torch/lib/python3.7/site-packages/tensorflow/python/util/lazy_loader.py”, line 41, in _load
module = importlib.import_module(self.name)
File “/homes/jl007/.conda/envs/torch/lib/python3.7/importlib/init.py”, line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File “/homes/jl007/.conda/envs/torch/lib/python3.7/site-packages/keras/init.py”, line 25, in
from keras import models
File “/homes/jl007/.conda/envs/torch/lib/python3.7/site-packages/keras/models.py”, line 20, in
from keras import metrics as metrics_module
File “/homes/jl007/.conda/envs/torch/lib/python3.7/site-packages/keras/metrics.py”, line 24, in
from keras import activations
File “/homes/jl007/.conda/envs/torch/lib/python3.7/site-packages/keras/activations.py”, line 20, in
from keras.layers import advanced_activations
File “/homes/jl007/.conda/envs/torch/lib/python3.7/site-packages/keras/layers/init.py”, line 30, in
from keras.layers.preprocessing.image_preprocessing import CenterCrop
File “/homes/jl007/.conda/envs/torch/lib/python3.7/site-packages/keras/layers/preprocessing/image_preprocessing.py”, line 24, in
from keras.preprocessing.image import smart_resize
File “/homes/jl007/.conda/envs/torch/lib/python3.7/site-packages/keras/preprocessing/init.py”, line 22, in
from keras.preprocessing import image
File “/homes/jl007/.conda/envs/torch/lib/python3.7/site-packages/keras/preprocessing/image.py”, line 22, in
from keras_preprocessing import image
File “/homes/jl007/.conda/envs/torch/lib/python3.7/site-packages/keras_preprocessing/image/init.py”, line 5, in
from .affine_transformations import *
File “/homes/jl007/.conda/envs/torch/lib/python3.7/site-packages/keras_preprocessing/image/affine_transformations.py”, line 15, in
from scipy import ndimage
File “/homes/jl007/.conda/envs/torch/lib/python3.7/site-packages/scipy/ndimage/init.py”, line 153, in
from .interpolation import *
File “/homes/jl007/.conda/envs/torch/lib/python3.7/site-packages/scipy/ndimage/interpolation.py”, line 37, in
from scipy import special
File “/homes/jl007/.conda/envs/torch/lib/python3.7/site-packages/scipy/special/init.py”, line 643, in
from . import _ufuncs
File “”, line 416, in parent
KeyboardInterrupt
Segmentation fault (core dumped)", how to solve it? thanks.
the train.py as follows “# -- coding: utf-8 --
import os
os.environ[“CUDA_VISIBLE_DEVICES”]= ‘2’
from tqdm import tqdm
import os
import random
import torch
import torch.nn as nn
from transformers import RobertaTokenizer
from ERC_dataset import MELD_loader, Emory_loader, IEMOCAP_loader, DD_loader
from model import ERC_model
from ERCcombined import ERC_model
from torch.utils.data import Dataset, DataLoader
from transformers import get_linear_schedule_with_warmup
import pdb
import argparse, logging
from sklearn.metrics import precision_recall_fscore_support
from utils import make_batch_roberta, make_batch_bert, make_batch_gpt
def CELoss(pred_outs, labels):
“”"
pred_outs: [batch, clsNum]
labels: [batch]
“”"
loss = nn.CrossEntropyLoss()
loss_val = loss(pred_outs, labels)
return loss_val
finetune RoBETa-large
def main():
“”“Dataset Loading”“”
batch_size = args.batch
dataset = args.dataset
dataclass = args.cls
sample = args.sample
model_type = args.pretrained
freeze = args.freeze
initial = args.initial
dataType = 'multi'
if dataset == 'MELD':
if args.dyadic:
dataType = 'dyadic'
else:
dataType = 'multi'
data_path = './dataset/MELD/'+dataType+'/'
DATA_loader = MELD_loader
elif dataset == 'EMORY':
data_path = './dataset/EMORY/'
DATA_loader = Emory_loader
elif dataset == 'iemocap':
data_path = './dataset/iemocap/'
DATA_loader = IEMOCAP_loader
elif dataset == 'dailydialog':
data_path = './dataset/dailydialog/'
DATA_loader = DD_loader
if 'roberta' in model_type:
make_batch = make_batch_roberta
elif model_type == 'bert-large-uncased':
make_batch = make_batch_bert
else:
make_batch = make_batch_gpt
if freeze:
freeze_type = 'freeze'
else:
freeze_type = 'no_freeze'
train_path = data_path + dataset+'_train.txt'
dev_path = data_path + dataset+'_dev.txt'
test_path = data_path + dataset+'_test.txt'
train_dataset = DATA_loader(train_path, dataclass)
if sample < 1.0:
train_dataloader = DataLoader(train_dataset, batch_size=batch_size, shuffle=False, num_workers=4, collate_fn=make_batch)
else:
train_dataloader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True, num_workers=4, collate_fn=make_batch)
train_sample_num = int(len(train_dataloader)*sample)
dev_dataset = DATA_loader(dev_path, dataclass)
dev_dataloader = DataLoader(dev_dataset, batch_size=1, shuffle=False, num_workers=4, collate_fn=make_batch)
test_dataset = DATA_loader(test_path, dataclass)
test_dataloader = DataLoader(test_dataset, batch_size=1, shuffle=False, num_workers=4, collate_fn=make_batch)
"""logging and path"""
save_path = os.path.join(dataset+'_models', model_type, initial, freeze_type, dataclass, str(sample))
print("###Save Path### ", save_path)
log_path = os.path.join(save_path, 'train.log')
if not os.path.exists(save_path):
os.makedirs(save_path)
fileHandler = logging.FileHandler(log_path)
logger.addHandler(streamHandler)
logger.addHandler(fileHandler)
logger.setLevel(level=logging.DEBUG)
"""Model Loading"""
if 'gpt2' in model_type:
last = True
else:
last = False
print('DataClass: ', dataclass, '!!!') # emotion
clsNum = len(train_dataset.labelList)
model = ERC_model(model_type, clsNum, last, freeze, initial)
model = model.cuda()
model.train()
"""Training Setting"""
training_epochs = args.epoch
save_term = int(training_epochs/5)
max_grad_norm = args.norm
lr = args.lr
num_training_steps = len(train_dataset)*training_epochs
num_warmup_steps = len(train_dataset)
# optimizer = torch.optim.AdamW(model.parameters(), lr=lr) # , eps=1e-06, weight_decay=0.01
optimizer = torch.optim.AdamW(model.train_params, lr=lr) # , eps=1e-06, weight_decay=0.01
scheduler = get_linear_schedule_with_warmup(optimizer, num_warmup_steps=num_warmup_steps, num_training_steps=num_training_steps)
"""Input & Label Setting"""
best_dev_fscore, best_test_fscore = 0, 0
best_dev_fscore_macro, best_dev_fscore_micro, best_test_fscore_macro, best_test_fscore_micro = 0, 0, 0, 0
best_epoch = 0
for epoch in tqdm(range(training_epochs)):
model.train()
for i_batch, data in enumerate(train_dataloader):
if i_batch > train_sample_num:
print(i_batch, train_sample_num)
break
"""Prediction"""
batch_input_tokens, batch_labels, batch_speaker_tokens = data
batch_input_tokens, batch_labels = batch_input_tokens.cuda(), batch_labels.cuda()
pred_logits = model(batch_input_tokens, batch_speaker_tokens)
"""Loss calculation & training"""
loss_val = CELoss(pred_logits, batch_labels)
loss_val.backward()
torch.nn.utils.clip_grad_norm_(model.parameters(), max_grad_norm) # Gradient clipping is not in AdamW anymore (so you can use amp without issue)
optimizer.step()
scheduler.step()
optimizer.zero_grad()
"""Dev & Test evaluation"""
model.eval()
if dataset == 'dailydialog': # micro & macro
dev_acc, dev_pred_list, dev_label_list = _CalACC(model, dev_dataloader)
dev_pre_macro, dev_rec_macro, dev_fbeta_macro, _ = precision_recall_fscore_support(dev_label_list, dev_pred_list, average='macro')
dev_pre_micro, dev_rec_micro, dev_fbeta_micro, _ = precision_recall_fscore_support(dev_label_list, dev_pred_list, labels=[0,1,2,3,5,6], average='micro') # neutral x
dev_fscore = dev_fbeta_macro+dev_fbeta_micro
"""Best Score & Model Save"""
if dev_fscore > best_dev_fscore_macro + best_dev_fscore_micro:
best_dev_fscore_macro = dev_fbeta_macro
best_dev_fscore_micro = dev_fbeta_micro
test_acc, test_pred_list, test_label_list = _CalACC(model, test_dataloader)
test_pre_macro, test_rec_macro, test_fbeta_macro, _ = precision_recall_fscore_support(test_label_list, test_pred_list, average='macro')
test_pre_micro, test_rec_micro, test_fbeta_micro, _ = precision_recall_fscore_support(test_label_list, test_pred_list, labels=[0,1,2,3,5,6], average='micro') # neutral x
best_epoch = epoch
_SaveModel(model, save_path)
else: # weight
dev_acc, dev_pred_list, dev_label_list = _CalACC(model, dev_dataloader)
dev_pre, dev_rec, dev_fbeta, _ = precision_recall_fscore_support(dev_label_list, dev_pred_list, average='weighted')
"""Best Score & Model Save"""
if dev_fbeta > best_dev_fscore:
best_dev_fscore = dev_fbeta
test_acc, test_pred_list, test_label_list = _CalACC(model, test_dataloader)
test_pre, test_rec, test_fbeta, _ = precision_recall_fscore_support(test_label_list, test_pred_list, average='weighted')
best_epoch = epoch
_SaveModel(model, save_path)
if epoch % 5 == 0:
logger.info('Epoch: {}'.format(epoch))
if dataset == 'dailydialog': # micro & macro
logger.info('Devleopment ## accuracy: {}, macro-fscore: {}, micro-fscore: {}'.format(dev_acc, dev_fbeta_macro, dev_fbeta_micro))
logger.info('')
else:
logger.info('Devleopment ## accuracy: {}, precision: {}, recall: {}, fscore: {}'.format(dev_acc, dev_pre, dev_rec, dev_fbeta))
logger.info('')
if dataset == 'dailydialog': # micro & macro
logger.info('Final Fscore ## test-accuracy: {}, test-macro: {}, test-micro: {}, test_epoch: {}'.format(test_acc, test_fbeta_macro, test_fbeta_micro, best_epoch))
else:
logger.info('Final Fscore ## test-accuracy: {}, test-fscore: {}, test_epoch: {}'.format(test_acc, test_fbeta, best_epoch))
def _CalACC(model, dataloader):
model.eval()
correct = 0
label_list = []
pred_list = []
# label arragne
with torch.no_grad():
for i_batch, data in enumerate(dataloader):
"""Prediction"""
batch_input_tokens, batch_labels, batch_speaker_tokens = data
batch_input_tokens, batch_labels = batch_input_tokens.cuda(), batch_labels.cuda()
pred_logits = model(batch_input_tokens, batch_speaker_tokens) # (1, clsNum)
"""Calculation"""
pred_label = pred_logits.argmax(1).item()
true_label = batch_labels.item()
pred_list.append(pred_label)
label_list.append(true_label)
if pred_label == true_label:
correct += 1
acc = correct/len(dataloader)
return acc, pred_list, label_list
def _SaveModel(model, path):
if not os.path.exists(path):
os.makedirs(path)
torch.save(model.state_dict(), os.path.join(path, ‘model.bin’))
if name == ‘main’:
torch.cuda.empty_cache()
"""Parameters"""
parser = argparse.ArgumentParser(description = "Emotion Classifier" )
parser.add_argument( "--batch", type=int, help = "batch_size", default = 1)
parser.add_argument( "--epoch", type=int, help = 'training epohcs', default = 10) # 12 for iemocap
parser.add_argument( "--norm", type=int, help = "max_grad_norm", default = 10)
parser.add_argument( "--lr", type=float, help = "learning rate", default = 1e-6) # 1e-5
parser.add_argument( "--sample", type=float, help = "sampling trainign dataset", default = 1.0) #
parser.add_argument( "--dataset", help = 'MELD or EMORY or iemocap or dailydialog', default = 'MELD')
parser.add_argument( "--pretrained", help = 'roberta-large or bert-large-uncased or gpt2 or gpt2-large or gpt2-medium', default = 'roberta-large')
parser.add_argument( "--initial", help = 'pretrained or scratch', default = 'pretrained')
parser.add_argument('-dya', '--dyadic', action='store_true', help='dyadic conversation')
parser.add_argument('-fr', '--freeze', action='store_true', help='freezing PM')
parser.add_argument( "--cls", help = 'emotion or sentiment', default = 'emotion')
args = parser.parse_args()
logger = logging.getLogger(__name__)
streamHandler = logging.StreamHandler()
main()
”