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import pandas as pd
import os
import subprocess
from transformers import AutoTokenizer, AutoModelForCausalLM
# Format sequence inputs based on ProtGPT fine-tuning requirements
def modify_sequences(sequence):
modified_sequence = sequence.upper()
modified_sequence = '\n'.join([modified_sequence[i:i+60] for i in range(0, len(modified_sequence), 60)])
fasta = "<|endoftext|>"
modified_sequence = fasta + "\n" + modified_sequence
return modified_sequence
# Function to save sequences to txt files
def to_txt_file(df, filename):
with open(filename, 'w') as f:
for sequence in df['Sequence']:
f.write(sequence + '\n')
# Modify the sequences
path = "/workspace/sg666/MDpLM"
train = pd.read_csv(path + "/data/membrane/train.csv")
val = pd.read_csv(path + "/data/membrane/val.csv")
test = pd.read_csv(path + "/data/membrane/test.csv")
train = pd.concat([train, val])
train['Sequence'] = train['Sequence'].apply(modify_sequences)
test['Sequence'] = test['Sequence'].apply(modify_sequences)
# Save the modified sequences as txt files
to_txt_file(train, path + '/benchmarks/Generation/ProtGPT2/protgpt2_train.txt')
to_txt_file(test, path + '/benchmarks/Generation/ProtGPT2/protgpt2_test.txt')
tokenizer = AutoTokenizer.from_pretrained("nferruz/ProtGPT2")
model = AutoModelForCausalLM.from_pretrained("nferruz/ProtGPT2")
finetune_protgpt2_command = [
"python", "run_clm.py",
"--model_name_or_path", "nferruz/ProtGPT2",
"--train_file", "protgpt2_train.txt",
"--validation_file", "protgpt2_test.txt",
"--tokenizer_name", "nferruz/ProtGPT2",
"--num_train_epochs", "10",
"--logging_steps", "1",
"--logging_dir", "test",
"--do_train",
"--do_eval",
"--output_dir", "/workspace/sg666/MDpLM/benchmarks/Generation/ProtGPT2/finetuned_models",
"--overwrite_output_dir",
"--learning_rate", "3e-04",
"--per_device_train_batch_size", "2",
"--evaluation_strategy", "epoch"
]
try:
result = subprocess.run(finetune_protgpt2_command, check=True, text=True, capture_output=True)
except subprocess.CalledProcessError as e:
print("Command failed with the following error:")
print(e.stderr) # Print standard error output
print("Command output:")
print(e.stdout) # Print standard output if needed
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