python_code stringlengths 0 679k | repo_name stringlengths 9 41 | file_path stringlengths 6 149 |
|---|---|---|
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""GLUE dataset."""
from abc import ABC
from abc import abstractmethod
from torch.utils.data import Dataset
from megatron import print_rank_0
from tasks.data_utils import build_sample
from tasks.data_utils import build_tokens_types_paddings_from_text
... | Megatron-LM-master | tasks/glue/data.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""MNLI dataset."""
from megatron import print_rank_0
from tasks.data_utils import clean_text
from .data import GLUEAbstractDataset
LABELS = {'contradiction': 0, 'entailment': 1, 'neutral': 2}
class MNLIDataset(GLUEAbstractDataset):
def __init__(... | Megatron-LM-master | tasks/glue/mnli.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Detokenization."""
import re
def ptb_detokenizer(string):
string = string.replace(" '", "'")
string = string.replace(" \n", "\n")
string = string.replace("\n ", "\n")
string = string.replace(" n't", "n't")
string = string.replace(... | Megatron-LM-master | tasks/zeroshot_gpt/detokenizer.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Zero-shot datasets."""
import json
import math
import numpy as np
import torch
from megatron import get_args
from megatron import print_rank_0
from megatron import get_tokenizer
from .detokenizer import get_detokenizer
def build_dataset(task):
... | Megatron-LM-master | tasks/zeroshot_gpt/datasets.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""GPT zero-shot evaluation."""
import math
import torch
from megatron import get_args
from megatron import print_rank_0, is_last_rank
from megatron import get_tokenizer
from megatron.core import parallel_state, tensor_parallel
from megatron.checkpointi... | Megatron-LM-master | tasks/zeroshot_gpt/evaluate.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Finetune utilities."""
import torch
import torch.nn.functional as F
from megatron import get_args
from megatron import print_rank_0
from megatron import get_timers
from megatron import utils
from megatron.core import mpu
from megatron.checkpointing imp... | Megatron-LM-master | tasks/vision/finetune_utils.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Main tasks functionality."""
import os
import sys
sys.path.append(
os.path.abspath(
os.path.join(
os.path.join(os.path.dirname(__file__), os.path.pardir),
os.path.pardir,
)
)
)
from megatron import get_a... | Megatron-LM-master | tasks/vision/main.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Vision-classification finetuning/evaluation."""
import torch.nn.functional as F
from functools import partial
from megatron import get_args, get_timers
from megatron import print_rank_0
from megatron.model.vision.classification import VitClassification... | Megatron-LM-master | tasks/vision/classification/classification.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Evaluation utilities."""
import os
from functools import partial
import torch
from megatron import get_args
from megatron import print_rank_0, print_rank_last
from megatron.core import mpu
from megatron.schedules import get_forward_backward_func
from... | Megatron-LM-master | tasks/vision/classification/eval_utils.py |
# BSD 3-Clause License
#
# Copyright (c) Soumith Chintala 2016,
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# * Redistributions of source code must retain the above copyright notice, this
#... | Megatron-LM-master | tasks/vision/segmentation/cityscapes.py |
#!/usr/bin/env python
# -*- coding: UTF-8 -*-
#copyright (c) go-hiroaki & Chokurei
#email: guangmingwu2010@gmail.com
# guozhilingty@gmail.com
#
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import math
import torch
import torch.nn as... | Megatron-LM-master | tasks/vision/segmentation/metrics.py |
# Copyright (c) 2020 The MMSegmenation Authors.
#
# This source code is licensed under the Apache license found in the
# LICENSE file in the root directory of this source tree.
import random
import os
import math
import mmcv
import torch
import numpy as np
import torchvision.transforms as T
from torchvision import dat... | Megatron-LM-master | tasks/vision/segmentation/transforms.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import math
import einops
import torch
import apex
import torch.nn.functional as F
from megatron import get_args
from megatron.model.module import MegatronModule
from megatron.model.vision.vit_backbone import VitBackbone, VitMlpHead
from megatron.model.visi... | Megatron-LM-master | tasks/vision/segmentation/seg_models.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Vision-classification finetuning/evaluation."""
import torch
import torch.nn.functional as F
from functools import partial
from megatron import get_args, get_timers
from megatron import print_rank_0, print_rank_last
from megatron.core import mpu
from t... | Megatron-LM-master | tasks/vision/segmentation/finetune_setr.py |
import math
import torch
import numpy as np
from megatron import get_args
def slidingcrops(img, mask):
# img: [b c h w]
# mask: [b h w]
args = get_args()
assert args.img_h == args.img_w
crop_size = args.img_h
stride = args.seg_stride
ignore_index = args.ignore_index
n, c, h, w = img.sha... | Megatron-LM-master | tasks/vision/segmentation/utils.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Vision-classification finetuning/evaluation."""
import numpy as np
import torch
import torch.nn.functional as F
from functools import partial
from megatron import get_args, get_timers
from megatron import print_rank_0, print_rank_last
from megatron.cor... | Megatron-LM-master | tasks/vision/segmentation/finetune_segformer.py |
import random
import os
import math
import mmcv
import torch
import numpy as np
import torchvision.transforms as T
from torchvision import datasets
from torch.utils.data import Dataset
from megatron.data.autoaugment import ImageNetPolicy
from tasks.vision.segmentation.cityscapes import Cityscapes
import tasks.vision.se... | Megatron-LM-master | tasks/vision/segmentation/data.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import math
import einops
import torch
import apex
import torch.nn.functional as F
from megatron import get_args
from megatron.model import LayerNorm
from megatron.model.module import MegatronModule
from megatron.model.vision.utils import resize
class Set... | Megatron-LM-master | tasks/vision/segmentation/seg_heads.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Race."""
from megatron import get_args
from megatron import print_rank_0
from megatron import get_tokenizer
from megatron.model.multiple_choice import MultipleChoice
from tasks.eval_utils import accuracy_func_provider
from tasks.finetune_utils import f... | Megatron-LM-master | tasks/race/finetune.py |
import glob
import json
import os
import time
from torch.utils.data import Dataset
from megatron import print_rank_0
from tasks.data_utils import build_sample
from tasks.data_utils import build_tokens_types_paddings_from_ids
from tasks.data_utils import clean_text
NUM_CHOICES = 4
MAX_QA_LENGTH = 128
class RaceDa... | Megatron-LM-master | tasks/race/data.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import torch
from megatron import get_args, print_rank_0
from megatron.checkpointing import load_biencoder_checkpoint
from megatron.data.orqa_wiki_dataset import get_open_retrieval_wiki_dataset
from megatron.data.realm_index import OpenRetreivalDataStore,... | Megatron-LM-master | tasks/orqa/evaluate_utils.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Main tasks functionality."""
from megatron import get_args, print_rank_0
from megatron.indexer import IndexBuilder
from tasks.orqa.evaluate_utils import ORQAEvaluator
def main():
"""
Main program
"""
args = get_args()
"""
Cre... | Megatron-LM-master | tasks/orqa/evaluate_orqa.py |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# The following code has been taken from
# https://github.com/facebookresearch/DPR, which is CC-BY-NC 4.0
# licensed as of now. More details on the license can be found
# at https://github.com/facebookresearch/DPR/blob/m... | Megatron-LM-master | tasks/orqa/unsupervised/qa_utils.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""
Data Loader for Google NQ dataset
"""
from abc import ABC
import csv
from collections import OrderedDict
import numpy as np
import torch
from torch.utils.data import DataLoader
from torch.utils.data import Dataset, BatchSampler
from megatron import... | Megatron-LM-master | tasks/orqa/unsupervised/nq.py |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# The following code has been taken from
# https://github.com/facebookresearch/DPR, which is CC-BY-NC 4.0
# licensed as of now. More details on the license can be found
# at https://github.com/facebookresearch/DPR/blob/m... | Megatron-LM-master | tasks/orqa/unsupervised/tokenizers.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Evaluation utilities."""
from collections import OrderedDict
import math
import numpy as np
import time
import torch
import torch.nn.functional as F
from torch.utils.data import DataLoader
from megatron import get_args, print_rank_0
from megatron.core ... | Megatron-LM-master | tasks/orqa/supervised/eval_utils.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""ORQA finetuning/evaluation."""
from functools import partial
import sys
import math
import torch
import torch.nn.functional as F
from megatron import get_args, get_timers, get_tokenizer, print_rank_0
from megatron.core import mpu
from megatron.indexe... | Megatron-LM-master | tasks/orqa/supervised/finetune.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""ORQA dataset."""
import json
import random
from abc import ABC
from abc import abstractmethod
import numpy as np
from torch.utils.data import Dataset
from megatron import print_rank_0, get_args
from megatron.data.biencoder_dataset_utils import make_a... | Megatron-LM-master | tasks/orqa/supervised/data.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Processing large data for pretraining."""
import argparse
import math
import json
import os
import sys
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__),
os.path.pardir)))
import time
imp... | Megatron-LM-master | tools/preprocess_data.py |
import os
import sys
import json
import argparse
sys.path.append(
os.path.abspath(os.path.join(os.path.dirname(__file__), os.path.pardir))
)
from megatron.data.indexed_dataset import (
MMapIndexedDataset,
MMapIndexedDatasetBuilder,
get_bin_path,
get_idx_path,
)
def get_args():
parser = argpa... | Megatron-LM-master | tools/merge_datasets.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Processing nmt data for finetuning."""
import argparse
import json
import multiprocessing
import os
import sys
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__),
os.path.pardir)))
import... | Megatron-LM-master | tools/preprocess_data_nmt.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import sys
import json
import requests
if __name__ == "__main__":
url = sys.argv[1]
url = 'http://' + url + '/api'
headers = {'Content-Type': 'application/json'}
while True:
sentence = input("Enter prompt: ")
tokens_to_gen... | Megatron-LM-master | tools/text_generation_cli.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Sample Generate GPT"""
import os
import sys
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__),
os.path.pardir)))
import socket
from megatron import get_args
from megatron import print_ran... | Megatron-LM-master | tools/run_text_generation_server.py |
import os
import os.path as osp
import pathlib
import subprocess
def recursively_lint_files():
"""Recursively lint all python files in chosen subdirectories of megatron-lm"""
try:
import autopep8
except ModuleNotFoundError:
print("Please first install autopep8 via `pip install autopep8`")... | Megatron-LM-master | tools/linter.py |
# coding=utf-8
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
"""Processing text modality data for MultiModal pretraining."""
import argparse
import json
import multiprocessing
import os
import sys
import numpy as np
from torchvision.transforms import ToTensor
sys.path.append(os.path.abspath(os.path.... | Megatron-LM-master | tools/preprocess_mmdata.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import json
import os
import sys
import types
import torch
def add_arguments(parser):
group = parser.add_argument_group(title='Megatron loader')
group.add_argument('--true-vocab-size', type=int, default=None,
help='origina... | Megatron-LM-master | tools/checkpoint/loader_megatron.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import argparse
import importlib
import torch.multiprocessing as mp
import os
import sys
# A loader is a python file with at least two functions
# - add_arguments - takes in a parser and adds any arguments needed
# - load_checkpoint - takes in the queue a... | Megatron-LM-master | tools/checkpoint/util.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import argparse
from collections.abc import Mapping
import concurrent.futures
import os
import sys
import torch
def add_arguments(parser):
group = parser.add_argument_group(title='Megatron saver')
group.add_argument('--megatron-path', type=str,... | Megatron-LM-master | tools/checkpoint/saver_megatron.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import json
import os
import sys
import torch
import transformers
from tqdm import tqdm
import types
def add_arguments(parser):
group = parser.add_argument_group(title='Llama-2 HF loader.')
group.add_argument('--true-vocab-size', type=int, defau... | Megatron-LM-master | tools/checkpoint/loader_llama2_hf.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import json
import time
import sys
if __name__ == '__main__':
url_filename = sys.argv[1]
data_filename = sys.argv[2]
output_filename = sys.argv[3]
urls = set()
with open(url_filename, 'r') as f:
for line in f:
m... | Megatron-LM-master | tools/openwebtext/remove_group_duplicates.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import argparse
import json
import os
import time
"""
This code adds id to each json object in a json file. User can add prefix
to the ids.
"""
if __name__ == '__main__':
print('parsing the arguments ...')
parser = argparse.ArgumentParser()
... | Megatron-LM-master | tools/openwebtext/add_id.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import glob
import sys
import json
import argparse
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument("--json_path", type=str, default=".",
help="path where all the json files are located")
parser.add_... | Megatron-LM-master | tools/openwebtext/merge_jsons.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
# WARNING! This file contains a blacklist of known malicious sites and thus contains some NSFW language.
import glob
import re
import time
import tldextract
import sys
# List of the domains to blacklist.
domain_blacklist = set([
'500px',
'aapks... | Megatron-LM-master | tools/openwebtext/blacklist_urls.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""
Filter and clean documents:
Capable to clean docs with less than 512 characters, less than
256 characters and contains javascript, fix text and dataset specific
cleaning like stories and realnews datasets.
Program arguments have the details.
"""
impor... | Megatron-LM-master | tools/openwebtext/cleanup_fix_dataset.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import json
import time
import sys
if __name__ == '__main__':
print('grouping duplicate urls ...')
input = sys.argv[1]
output = sys.argv[2]
if len(sys.argv) > 3:
jaccard_similarity_threshold = float(sys.argv[3])
else:
... | Megatron-LM-master | tools/openwebtext/group_duplicate_url.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import argparse
from functools import partial
import itertools
import json
from lsh import cache, minhash
import multiprocessing
import numpy as np
import time
import pickle
import sys
import os
# This function is adapted from:
# https://github.com/matt... | Megatron-LM-master | tools/openwebtext/find_duplicates.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import ftfy
import json
from langdetect import detect
import numpy as np
import time
import os
import sys
from tokenizer import Tokenizer
MIN_DOCUMENT_LENGHT = 128
def print_progress(prefix, start_time, num_docs, num_fixed_text,
num... | Megatron-LM-master | tools/openwebtext/cleanup_dataset.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""
Deduplicate downstream tasks from training dataset. 13-grams have been used.
All split documents with less than 200 characters got filtered. Any document
with more than 10 splits got filtered as well.
"""
import argparse
from functools import partial
... | Megatron-LM-master | tools/openwebtext/filter_ngrams.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import importlib
required_libs = [
"faiss",
"h5py",
"transformers", # for huggingface bert
]
for lib in required_libs:
try:
globals()[lib] = importlib.import_module(lib)
except ImportError as e:
raise Exception(f"Miss... | Megatron-LM-master | tools/retro/external_libs.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import os
import torch
import types
from megatron import get_retro_args
from megatron.tokenizer.tokenizer import (
_BertWordPieceTokenizer,
_GPT2BPETokenizer,
_GPTSentencePieceTokenizer,
)
def get_args_path(workdir):
'''Argument copy st... | Megatron-LM-master | tools/retro/utils.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
"""Preprocess data for Retro.
Stages (see argument '--retro-tasks'):
- Build chunk database (DB).
- Build index (train, add).
- Query pretraining neighbors.
"""
import json
import os
import torch
from megatron import get_args, initialize_megatron, prin... | Megatron-LM-master | tools/retro/main.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
from .cli import retro
| Megatron-LM-master | tools/retro/cli/__init__.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import json
import numpy as np
import os
import torch
import types
from megatron.global_vars import set_global_variables, set_retro_args
from megatron.initialize import (
initialize_megatron,
_initialize_distributed,
_set_random_seed,
_co... | Megatron-LM-master | tools/retro/cli/cli.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import os
from . import retro
if __name__ == "__main__":
retro.init(os.environ["RETRO_WORKDIR"])
| Megatron-LM-master | tools/retro/cli/__main__.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
from collections import defaultdict
from concurrent.futures import as_completed, ProcessPoolExecutor
from functools import reduce
import glob
import json
import numpy as np
import os
from pathlib import Path
import threading
import torch
from tqdm import ... | Megatron-LM-master | tools/retro/db/build.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
from .build import build_db
| Megatron-LM-master | tools/retro/db/__init__.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import json
import numpy as np
import torch
from tqdm import tqdm
from megatron import get_args, print_rank_0
from tools.retro.external_libs import h5py
from tools.retro.utils import get_gpt_tokenizer
class DBDataset(torch.utils.data.Dataset):
'''D... | Megatron-LM-master | tools/retro/db/dataset.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
from collections import defaultdict
import glob
import json
import numpy as np
import os
from tqdm import tqdm
from megatron import get_retro_args, print_rank_0
from megatron.data.indexed_dataset import MMapIndexedDataset
from tools.retro.external_libs i... | Megatron-LM-master | tools/retro/db/utils.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import numpy as np
import os
import shutil
import torch
from tqdm import tqdm
from megatron import get_retro_args, print_rank_0
from tools.bert_embedding import DiskDataParallelBertEmbedder
from tools.retro.db.utils import (
get_indexed_dataset_infos... | Megatron-LM-master | tools/retro/index/build.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import abc
import numpy as np
import os
import torch
from megatron import get_retro_args
from tools.retro.external_libs import faiss
from .utils import get_index_dir
class Index(abc.ABC):
'''Abstract base class for indexes.
*Note* : While cu... | Megatron-LM-master | tools/retro/index/index.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
from .build import add_to_index, build_index, train_index
# from .index import Index
| Megatron-LM-master | tools/retro/index/__init__.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
from .indexes import FaissBaseIndex, FaissParallelAddIndex
class IndexFactory:
'''Get index.
Index type generally read from argument '--retro-index-ty'.
'''
@classmethod
def get_index_class(cls, index_type):
return {
... | Megatron-LM-master | tools/retro/index/factory.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import concurrent
import gc
import glob
import numpy as np
import os
import psutil
import time
import torch
from tqdm import tqdm
from megatron import get_retro_args, print_rank_0
from tools.retro.db.utils import get_indexed_dataset_infos
from tools.retr... | Megatron-LM-master | tools/retro/index/utils.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
"""Multi-process & multi-node version of Faiss's index.add().
This class inherits from FaissBaseIndex, and optimizes the 'add()' method by
making it multi-node and multi-process, with bit-wise equivalence to
FaissBaseIndex. This allows 'add()' to scale o... | Megatron-LM-master | tools/retro/index/indexes/faiss_par_add.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
"""
This class implements a simple, un-optimized wrapper around a Faiss index, that
implements the Index interface (see ..index.py). While this class is
instantiable, it is meant to be extended with optimizations in classes that
inherit from this class (s... | Megatron-LM-master | tools/retro/index/indexes/faiss_base.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
from .faiss_base import FaissBaseIndex
from .faiss_par_add import FaissParallelAddIndex
| Megatron-LM-master | tools/retro/index/indexes/__init__.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import os
import torch
from megatron import get_retro_args, print_rank_0
from megatron.data.gpt_dataset import build_train_valid_test_datasets \
as build_gpt_train_valid_test_datasets
from megatron.training import (
build_train_valid_test_dataset... | Megatron-LM-master | tools/retro/query/chunk_dataset.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import numpy as np
import os
import torch
from megatron import get_args, get_retro_args
from tools.bert_embedding.utils import BlockPathMap
from tools.retro.db.utils import get_merged_train_dataset as get_db_dataset
from tools.retro.external_libs import ... | Megatron-LM-master | tools/retro/query/retro_dataset.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import numpy as np
import os
import psutil
import time
import torch
from tqdm import tqdm
from megatron import get_retro_args, print_rank_0
from tools.bert_embedding import BertEmbedder
from tools.bert_embedding.utils import get_missing_blocks_by_rank
fr... | Megatron-LM-master | tools/retro/query/query.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
from .query import query_pretraining_neighbors
| Megatron-LM-master | tools/retro/query/__init__.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import hashlib
import os
from megatron import get_retro_args
def get_query_workdir():
args = get_retro_args()
return os.path.join(args.retro_workdir, "query")
def get_neighbor_dirname(key, dataset):
hashes = ",".join([ d.desc_hash for d i... | Megatron-LM-master | tools/retro/query/utils.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import importlib
required_libs = [
"h5py",
"transformers", # for huggingface bert
]
for lib in required_libs:
try:
globals()[lib] = importlib.import_module(lib)
except ImportError as e:
raise Exception(f"Missing one or mo... | Megatron-LM-master | tools/bert_embedding/external_libs.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
from functools import partial
import numpy as np
import os
import time
import torch
from torch.utils.data import BatchSampler, DataLoader, SequentialSampler, Subset
from torch.utils.data._utils.collate import default_collate
from tqdm import tqdm
from me... | Megatron-LM-master | tools/bert_embedding/embed.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
from .embed import BertEmbedder, DiskDataParallelBertEmbedder
| Megatron-LM-master | tools/bert_embedding/__init__.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import numpy as np
import torch
from megatron import get_args, get_tokenizer
from megatron.data.bert_dataset import build_training_sample
class BertEmbeddingDataset(torch.utils.data.Dataset):
'''Dataset to convert a text dataset to Bert tokens.'''
... | Megatron-LM-master | tools/bert_embedding/dataset.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
from collections import defaultdict
import glob
import numpy as np
import os
import torch
from tqdm import tqdm
from megatron import print_rank_0
from megatron.core import parallel_state
from .external_libs import h5py
def save_data(data_map, *args):
... | Megatron-LM-master | tools/bert_embedding/utils.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import numpy as np
import torch
from tqdm import tqdm
from .external_libs import transformers
class IterableTextDataset(torch.utils.data.IterableDataset):
'''Iterable over a text dataset.'''
def __init__(self, text_dataset):
self.text_... | Megatron-LM-master | tools/bert_embedding/huggingface.py |
Megatron-LM-master | tests/__init__.py | |
def test_import():
import megatron
| Megatron-LM-master | tests/unit_tests/test_basic.py |
import pytest
import torch
import megatron.core.utils as util
import numpy as np
def test_divide_properly():
assert util.divide(4,2) == 2
def test_divide_improperly():
with pytest.raises(AssertionError):
util.divide(4,5)
def test_global_memory_buffer():
global_memory_buffer = util.GlobalMemoryBuf... | Megatron-LM-master | tests/unit_tests/test_utils.py |
import os
import torch
import megatron.core.parallel_state as ps
class Utils:
world_size = torch.cuda.device_count()
rank = int(os.environ['LOCAL_RANK'])
@staticmethod
def initialize_distributed():
print(f'Initializing torch.distributed with rank: {Utils.rank}, world_size: {Utils.world_size}'... | Megatron-LM-master | tests/unit_tests/test_utilities.py |
Megatron-LM-master | tests/unit_tests/__init__.py | |
import torch
import megatron.core.parallel_state as ps
import pytest
from tests.unit_tests.test_utilities import Utils
import os
rank = Utils.rank
world_size = Utils.world_size
def test_initialize__and_destroy_model_parallel():
with pytest.raises(AssertionError):
assert(ps.initialize_model_parallel())
... | Megatron-LM-master | tests/unit_tests/test_parallel_state.py |
from megatron.core.tensor_parallel.cross_entropy import vocab_parallel_cross_entropy
import torch
from tests.unit_tests.test_utilities import Utils
import numpy as np
def test_vocab_parallel_cross_entropy():
Utils.initialize_model_parallel(4,2)
vocab_parallel_logits = torch.range(0,7).repeat(16,4).cuda()
t... | Megatron-LM-master | tests/unit_tests/tensor_parallel/test_cross_entropy.py |
import torch
import megatron.core.tensor_parallel.utils as util
import megatron.core.parallel_state as ps
from tests.unit_tests.test_utilities import Utils
rank = Utils.rank
def test_split_tensor_along_last_dim():
input_tensor = torch.rand((3,4))
torch.equal(input_tensor[0:2,0:2], util.split_tensor_along_last... | Megatron-LM-master | tests/unit_tests/tensor_parallel/test_tensor_parallel_utils.py |
from megatron.core.tensor_parallel import mappings
from tests.unit_tests.test_utilities import Utils
import torch
def test_CopyToModelParallelRegion():
Utils.initialize_model_parallel(4,2)
input_data = torch.ones((1)).cuda()*Utils.rank
output_data = mappings._CopyToModelParallelRegion.backward(None, input_... | Megatron-LM-master | tests/unit_tests/tensor_parallel/test_mappings.py |
from megatron.core.tensor_parallel.data import broadcast_data
import torch
from tests.unit_tests.test_utilities import Utils
def test_broadcast_data():
Utils.initialize_model_parallel(2,4)
input_data = {
0 : torch.ones((8,8)).cuda() * 0.0,
1 : torch.ones((8,8)).cuda() * 1.0,
2 : torch.o... | Megatron-LM-master | tests/unit_tests/tensor_parallel/test_data.py |
from megatron.core.tensor_parallel.random import CudaRNGStatesTracker
from megatron.core.tensor_parallel.random import model_parallel_cuda_manual_seed
from megatron.core.tensor_parallel.random import _CUDA_RNG_STATE_TRACKER
from megatron.core.tensor_parallel.random import checkpoint
from tests.unit_tests.test_utilities... | Megatron-LM-master | tests/unit_tests/tensor_parallel/test_random.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import pytest
import torch
from megatron.core.transformer.mlp import MLP
from tests.unit_tests.test_utilities import Utils
from megatron.core.tensor_parallel.random import model_parallel_cuda_manual_seed
from megatron.core.transformer.transformer_config ... | Megatron-LM-master | tests/unit_tests/transformer/test_mlp.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import pytest
import torch
from megatron.core.transformer.module import Float16Module, MegatronModule
from megatron.core.transformer.transformer_config import TransformerConfig
from tests.unit_tests.test_utilities import Utils
from megatron.core.tensor_p... | Megatron-LM-master | tests/unit_tests/transformer/test_module.py |
Megatron-LM-master | tests/unit_tests/transformer/__init__.py | |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import pytest
import torch
from megatron.core.transformer.attention import CrossAttention
"""
@pytest.fixture
def core_attention(transformer_config):
return CrossAttention(transformer_config)
class TestCoreAttention:
def test_constructor(sel... | Megatron-LM-master | tests/unit_tests/transformer/test_core_attention.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import os
import pytest
import torch
from megatron.core import dist_checkpointing
from megatron.core.transformer.transformer_config import TransformerConfig
from megatron.core.transformer.transformer_layer import TransformerLayer
from megatron.core.trans... | Megatron-LM-master | tests/unit_tests/transformer/test_transformer_block.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import pytest
import torch
from megatron.core.transformer.attention import SelfAttention
from tests.unit_tests.test_utilities import Utils
from megatron.core.tensor_parallel.random import model_parallel_cuda_manual_seed
from megatron.core.transformer.tra... | Megatron-LM-master | tests/unit_tests/transformer/test_attention.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import pytest
import torch
from megatron.core.transformer.transformer_config import TransformerConfig
from megatron.core.transformer.transformer_layer import TransformerLayer
from tests.unit_tests.test_utilities import Utils
from megatron.core.tensor_pa... | Megatron-LM-master | tests/unit_tests/transformer/test_transformer_layer.py |
import torch
from tests.unit_tests.test_utilities import Utils
from megatron.core import ModelParallelConfig
import megatron.core.pipeline_parallel.schedules as schedule
from pytest_mock import mocker
import pytest
rank = Utils.rank
def test_get_forward_backward_func():
Utils.initialize_model_parallel(tensor_mo... | Megatron-LM-master | tests/unit_tests/pipeline_parallel/test_schedules.py |
Megatron-LM-master | tests/unit_tests/pipeline_parallel/__init__.py | |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import pytest
import torch
from megatron.core.transformer.transformer_config import TransformerConfig
from megatron.core.models.gpt.gpt_model import GPTModel
from tests.unit_tests.test_utilities import Utils
from megatron.core.tensor_parallel.random impo... | Megatron-LM-master | tests/unit_tests/models/test_gpt_model.py |
Megatron-LM-master | tests/unit_tests/models/__init__.py | |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import pytest
import torch
from megatron.core.transformer.transformer_config import TransformerConfig
from megatron.core.models.gpt.gpt_embedding import GPTEmbedding
from tests.unit_tests.test_utilities import Utils
class TestGPTEmbedding:
def setu... | Megatron-LM-master | tests/unit_tests/models/test_gpt_embedding.py |
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