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Implemented notebook tqdm support #7

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Implemented notebook tqdm support #7

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10 changes: 9 additions & 1 deletion src/NERDA/predictions.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,12 +6,20 @@
from .preprocessing import create_dataloader
import torch
import numpy as np
from tqdm import tqdm
from nltk.tokenize import sent_tokenize, word_tokenize
from typing import List, Callable
import transformers
import sklearn.preprocessing

try:
from IPython import get_ipython
if 'IPKernelApp' in get_ipython().config:
from tqdm.notebook import tqdm
else:
from tqdm import tqdm
except:
from tqdm import tqdm

def predict(network: torch.nn.Module,
sentences: List[List[str]],
transformer_tokenizer: transformers.PreTrainedTokenizer,
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10 changes: 9 additions & 1 deletion src/NERDA/training.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,15 @@
from transformers import AdamW, get_linear_schedule_with_warmup
import random
import torch
from tqdm import tqdm

try:
from IPython import get_ipython
if 'IPKernelApp' in get_ipython().config:
from tqdm.notebook import tqdm
else:
from tqdm import tqdm
except:
from tqdm import tqdm

def train(model, data_loader, optimizer, device, scheduler, n_tags):
"""One Iteration of Training"""
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