from datasets import concatenate_datasets, load_dataset, load_from_disk
import argparse
from tokenizers import Tokenizer, decoders, models, pre_tokenizers, processors, trainers
from transformers import GPT2TokenizerFast, AutoTokenizer
from datasets import config
from datasets import DatasetDict, Dataset

code_dataset_go= load_dataset('code_x_glue_ct_code_to_text','go',split='train', cache_dir='/sml2/atul/CENTRAL_CACHE')['code']
code_dataset_java= load_dataset('code_x_glue_ct_code_to_text','java',split='train', cache_dir='/sml2/atul/CENTRAL_CACHE')['code']
code_dataset_javascript= load_dataset('code_x_glue_ct_code_to_text','javascript',split='train', cache_dir='/sml2/atul/CENTRAL_CACHE')['code']
code_dataset_php= load_dataset('code_x_glue_ct_code_to_text','php',split='train', cache_dir='/sml2/atul/CENTRAL_CACHE')['code']
code_dataset_python= load_dataset('code_x_glue_ct_code_to_text','python',split='train', cache_dir='/sml2/atul/CENTRAL_CACHE')['code']
code_dataset_ruby= load_dataset('code_x_glue_ct_code_to_text','ruby',split='train', cache_dir='/sml2/atul/CENTRAL_CACHE')['code']

indic_datasets_hi= load_dataset('ai4bharat/sangraha', data_dir="verified/hin", cache_dir='/sml2/atul/CENTRAL_CACHE')['train']['type'][:1000000]
indic_datasets_bn= load_dataset('ai4bharat/sangraha', data_dir="verified/ben", cache_dir='/sml2/atul/CENTRAL_CACHE')['train']['type'][:1000000]
wikipedia_en = load_dataset("wikipedia", "20220301.en", cache_dir='/sml2/atul/CENTRAL_CACHE')['train']['text'][:1000000]
    

combined_train_set=code_dataset_go+code_dataset_java+code_dataset_javascript+code_dataset_php+code_dataset_python+code_dataset_ruby+indic_datasets_hi + indic_datasets_bn + wikipedia_en

data = {
        "train":{"text": combined_train_set},
        "validation": {"text": []},
        "test": {"text": []},
    }
    # print(data)
custom_dataset = DatasetDict()
for split in data:
    custom_dataset[split] = Dataset.from_dict(data[split])
print(custom_dataset)