python_code stringlengths 0 290k | repo_name stringclasses 30
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# SPDX-License-Identifier: Apache-2.0
# Copyright 2022 The HuggingFace Authors.
import logging
from http import HTTPStatus
from typing import Any
from libcommon.constants import PROCESSING_STEP_DATASET_INFO_VERSION
from libcommon.exceptions import PreviousStepFormatError
from libcommon.simple_cache import (
Cache... | datasets-server-main | services/worker/src/worker/job_runners/dataset/info.py |
# SPDX-License-Identifier: Apache-2.0
# Copyright 2022 The HuggingFace Authors.
import logging
from typing import Optional
from datasets import get_dataset_config_names
from datasets.data_files import EmptyDatasetError as _EmptyDatasetError
from libcommon.constants import PROCESSING_STEP_DATASET_CONFIG_NAMES_VERSION
... | datasets-server-main | services/worker/src/worker/job_runners/dataset/config_names.py |
import argparse
import glob
import multiprocessing as mp
import os
import pickle
import random
import struct
import numpy as np
from datasets import load_from_disk
from tqdm import tqdm
from transformers import GPT2Tokenizer, T5Tokenizer
parser = argparse.ArgumentParser(description="Load a dataset.")
parser.add_argum... | datablations-main | filtering/deduplication/hf_dataset_to_file.py |
import argparse
import glob
import os
from functools import partial
from multiprocessing import Pool, cpu_count
from datasets import DatasetDict, load_from_disk
def save_dataset(dataset_name, base_dir, sample_size=100000, token=None):
print("Processing", dataset_name)
ds = load_from_disk(base_dir + dataset_n... | datablations-main | filtering/deduplication/save_dataset_sample.py |
import os
from multiprocessing import cpu_count
from datasets import load_dataset
HUGGINGFACE_TOKEN = os.environ.get("HUGGINGFACE_TOKEN")
print(HUGGINGFACE_TOKEN)
oscar = load_dataset(
"oscar-corpus/OSCAR-2201", "en", use_auth_token=HUGGINGFACE_TOKEN, num_proc=cpu_count(), ignore_verifications=True
)
oscar.save_... | datablations-main | filtering/deduplication/save_dataset.py |
import os
from collections import Counter
from datasets import load_dataset
HUGGINGFACE_TOKEN = os.environ.get("HUGGINGFACE_TOKEN")
oscar = load_dataset(
"oscar-corpus/OSCAR-2201",
"en",
use_auth_token=HUGGINGFACE_TOKEN,
num_proc=128,
ignore_verifications=True,
)
# oscar.save_to_disk("/home/piktu... | datablations-main | filtering/deduplication/download_oscar.py |
import jsonlines
from collections import defaultdict
from datasets import load_from_disk, load_dataset, concatenate_datasets
from multiprocessing import Pool, cpu_count
from tqdm import tqdm
oscar = load_from_disk("/home/piktus_huggingface_co/lumi/preprocessed_data/oscar-dedup-exapanded/")
# oscar = load_dataset("ola1... | datablations-main | filtering/deduplication/filter_oscar_jsonl.py |
import argparse
import os
import sys
from datasets import load_dataset
sys.path.append("/home/piktus_huggingface_co/lumi/text-dedup")
print(sys.path)
from text_dedup.suffix_array import suffix_array
def get_args():
"""
parser = argparse.ArgumentParser()
parser.add_argument('--name', type=str, require... | datablations-main | filtering/deduplication/suffix_dedup.py |
from datasets import load_from_disk
import string
def find_whitespace(text):
for i, c in enumerate(text):
if c in string.whitespace:
yield i
def
def get_segmentation(text, passage_tokens, overlap_tokens):
whitespace_idx = [-1] + list(find_whitespace(text))
unique_tokens = passage_tok... | datablations-main | filtering/deduplication/dedup_oscar.py |
import argparse
import ast
import glob
import os
from datasets import DatasetDict, concatenate_datasets, load_from_disk
def get_perplexity(meta):
meta = ast.literal_eval(meta) if isinstance(meta, str) else meta
perplexity_score = meta["perplexity_score"]
return float(perplexity_score)
if __name__ == "_... | datablations-main | filtering/deduplication/save_roots_sample.py |
import argparse
import os
import pickle
from bisect import bisect_right
from collections import defaultdict
from multiprocessing import cpu_count
from datasets import load_from_disk
from tqdm import tqdm
def get_pairs(byterange):
"""
Returns pairs generated by
https://github.com/google-research/deduplica... | datablations-main | filtering/deduplication/add_dedup_info.py |
# import csv
import pandas as pd
import string
from datasets import load_dataset
from tqdm import tqdm
def find_whitespace(text):
for i, c in enumerate(text):
if c in string.whitespace:
yield i
oscar_small = pd.DataFrame(load_dataset("ola13/small-oscar")["train"][:10])
query_length = 100
... | datablations-main | filtering/deduplication/save_rust_format.py |
"""
muP Preparation from https://github.com/microsoft/mutransformers#basic-usage-of-models
!git clone https://github.com/microsoft/mutransformers.git
%cd mutransformers
!pip install -r requirements.txt
!pip install -e .
!pip install -q datasets
With our CC-like architectures we found that
7m params & 100M tokens -> 8... | datablations-main | training/mup.py |
import os
import shutil
# shutil.rmtree()
checkpoint_dirs = [dir_name for dir_name in os.listdir() if dir_name.startswith('checkpoint')]
for dir_name in checkpoint_dirs:
latest_file_path = os.path.join(dir_name, 'latest')
with open(latest_file_path, 'r') as f:
latest_checkpoint = f.read().strip()
... | datablations-main | utils/cleandirs.py |
#!/usr/bin/env python
# this script converts results.json:
#
# "results": {
# "arc_challenge": {
# "acc": 0.24232081911262798,
# "acc_stderr": 0.01252159329580012,
# "acc_norm": 0.2764505119453925,
# "acc_norm_stderr": 0.013069662474252425
# },
#
# into a format expected by a spreadsh... | datablations-main | utils/csv_generative.py |
def full_flops(dataset_size, hidden_size, num_heads, num_layers, seq_len=2048, vocab_size=32000, ffw_size=None):
if ffw_size is None:
ffw_size = 4 * hidden_size
embeddings_flops = 2 * seq_len * vocab_size * hidden_size
attention_kqv_proj = 2 * 3 * seq_len * hidden_size * hidden_size
attention_kq... | datablations-main | utils/flops-params_py.py |
"""
Saves a merged.json file in the provided directory
python merge_all_json.py DIRECTORY
"""
import json
import os
from pathlib import Path
import sys
from typing import Dict
def find_all_json(root_dir: Path):
if root_dir.is_file():
if root_dir.name.endswith(".json"):
return [root_dir]
... | datablations-main | utils/merge_generative.py |
#!/usr/bin/env python
# creates a local auth token file which can then be safely used by other programs without leaking
# the password in public git
import getpass
import json
from pathlib import Path
from huggingface_hub import HfApi
HUB_DATA_PATH_SHARED = "/pfs/lustrep4/scratch/project_462000119/muennighoff/nov-20... | datablations-main | utils/hub_auth.py |
"""
Script for searching through logs to look for failing nodes.
"""
import sys
import re
NODE_RANK_RE = re.compile(r'Launching on (\S+) \((\d+)/(\d+)\)')
ERROR_STRINGS = [
'Segmentation fault',
'Failed to initialize RSMI device mutex',
'ERROR:torch.distributed.elastic.multiprocessing.api:failed',
]
... | datablations-main | utils/errornodes.py |
#!/usr/bin/env python
#
# This tool automatically pushes newly added and modified files into the hub repo, if they match the
# provided one or more patterns.
#
# If the program fails to run the first time make sure to run `hub-auth.py` to authenticate and save
# the token, and user name/email locally which will then b... | datablations-main | utils/hub_sync.py |
import argparse
import os
from typing import List, Dict
import subprocess
import shlex
import numpy as np
import pyarrow as pa
from datasets import load_dataset, Dataset, concatenate_datasets
from tqdm import tqdm
def get_args():
parser = argparse.ArgumentParser()
parser.add_argument('--name', type=str, requ... | datablations-main | utils/hf_dataset_subsampling.py |
###############################################################################
# Language Modeling on Penn Tree Bank
#
# This file generates new sentences sampled from the language model
#
###############################################################################
import argparse
import torch
from torch.autograd... | awd-lstm-lm-master | generate.py |
import torch
import torch.nn as nn
from torch.autograd import Variable
from embed_regularize import embedded_dropout
from locked_dropout import LockedDropout
from weight_drop import WeightDrop
class RNNModel(nn.Module):
"""Container module with an encoder, a recurrent module, and a decoder."""
def __init__(s... | awd-lstm-lm-master | model.py |
from torch.autograd import Variable
def repackage_hidden(h):
"""Wraps hidden states in new Variables, to detach them from their history."""
if type(h) == Variable:
return Variable(h.data)
else:
return tuple(repackage_hidden(v) for v in h)
def batchify(data, bsz, args):
# Work out how c... | awd-lstm-lm-master | utils.py |
import argparse
import time
import math
import numpy as np
import torch
import torch.nn as nn
from torch.autograd import Variable
import data
import model
from utils import batchify, get_batch, repackage_hidden
parser = argparse.ArgumentParser(description='PyTorch PennTreeBank RNN/LSTM Language Model')
parser.add_ar... | awd-lstm-lm-master | pointer.py |
import numpy as np
import torch
from torch.autograd import Variable
def embedded_dropout(embed, words, dropout=0.1, scale=None):
if dropout:
mask = embed.weight.data.new().resize_((embed.weight.size(0), 1)).bernoulli_(1 - dropout).expand_as(embed.weight) / (1 - dropout)
mask = Variable(mask)
masked_embe... | awd-lstm-lm-master | embed_regularize.py |
import torch
from torch.nn import Parameter
from functools import wraps
class WeightDrop(torch.nn.Module):
def __init__(self, module, weights, dropout=0, variational=False):
super(WeightDrop, self).__init__()
self.module = module
self.weights = weights
self.dropout = dropout
... | awd-lstm-lm-master | weight_drop.py |
import argparse
import time
import math
import numpy as np
import torch
import torch.nn as nn
from torch.autograd import Variable
import data
import model
from utils import batchify, get_batch, repackage_hidden
parser = argparse.ArgumentParser(description='PyTorch PennTreeBank RNN/LSTM Language Model')
parser.add_ar... | awd-lstm-lm-master | main.py |
from collections import defaultdict
import torch
import torch.nn as nn
import numpy as np
class SplitCrossEntropyLoss(nn.Module):
r'''SplitCrossEntropyLoss calculates an approximate softmax'''
def __init__(self, hidden_size, splits, verbose=False):
# We assume splits is [0, split1, split2, N] where ... | awd-lstm-lm-master | splitcross.py |
import argparse
import time
import math
import numpy as np
np.random.seed(331)
import torch
import torch.nn as nn
from torch.autograd import Variable
import data
import model
from utils import batchify, get_batch, repackage_hidden
parser = argparse.ArgumentParser(description='PyTorch PennTreeBank RNN/LSTM Language M... | awd-lstm-lm-master | finetune.py |
import torch
import torch.nn as nn
from torch.autograd import Variable
class LockedDropout(nn.Module):
def __init__(self):
super().__init__()
def forward(self, x, dropout=0.5):
if not self.training or not dropout:
return x
m = x.data.new(1, x.size(1), x.size(2)).bernoulli_(... | awd-lstm-lm-master | locked_dropout.py |
import os
import torch
from collections import Counter
class Dictionary(object):
def __init__(self):
self.word2idx = {}
self.idx2word = []
self.counter = Counter()
self.total = 0
def add_word(self, word):
if word not in self.word2idx:
self.idx2word.append(... | awd-lstm-lm-master | data.py |
#!/usr/bin/env python
# coding=utf-8
import os
import sys
import zipfile
if os.path.exists('train.txt'):
print('Tokenized enwik8 already exists - skipping processing')
sys.exit()
data = zipfile.ZipFile('enwik8.zip').read('enwik8')
print('Length of enwik8: {}'.format(len(data)))
num_test_chars = 5000000
tr... | awd-lstm-lm-master | data/enwik8/prep_enwik8.py |
import os
import deepspeed
import torch.distributed as dist
from distill_bloom import build_train_val_test_dataset
from distill_bloom import parse_args
args = parse_args()
local_rank = int(os.getenv("LOCAL_RANK", "0"))
world_size = int(os.getenv("WORLD_SIZE", "1"))
deepspeed.init_distributed("nccl")
rank = dist.... | distill-bloom-deepspeed-main | test_dataset.py |
# usage:
# deepspeed --num_gpus 8 teacher-inference-script.py --name bigscience/bloom
#
# to run benchmarks:
# deepspeed --num_gpus 8 teacher-inference-script.py --name bigscience/bloom --benchmark
#
# This is going to improve, but at the moment, the process is a bit cumbersome - we first use
# 1. use Deepspeed-ZeRO ... | distill-bloom-deepspeed-main | teacher-inference-script.py |
# Dataset imports
from .arguments.arguments import parse_args
from .dataset.get_dataset import build_train_val_test_dataset
from .dataset.dataloader import DistributedDataset, DistributedDataLoader
# Arguments import
from .init_wrapper import DeepSpeedInitWrapper, print_rank0 | distill-bloom-deepspeed-main | distill_bloom/__init__.py |
# usage:
# deepspeed --num_gpus 8 teacher-inference-script.py --name bigscience/bloom
#
# to run benchmarks:
# deepspeed --num_gpus 8 teacher-inference-script.py --name bigscience/bloom --benchmark
#
# This is going to improve, but at the moment, the process is a bit cumbersome - we first use
# 1. use Deepspeed-ZeRO ... | distill-bloom-deepspeed-main | distill_bloom/teacher-inference-script.py |
import io, json
from pathlib import Path
import torch
import torch.distributed as dist
from transformers.models.bloom.modeling_bloom import BloomBlock as BloomBlock
class DeepSpeedInitWrapper(object):
r"""
This is a wrapper around DeepSpeed inference / training script initialisation.
It is used ... | distill-bloom-deepspeed-main | distill_bloom/init_wrapper.py |
import torch.distributed as dist
from .utils import build_dataset_group
def build_train_val_test_dataset(args):
r"""
This function wraps all the dataset building functions from megatron.
"""
if args.train_samples:
train_samples = args.train_samples
else:
train_samples = args.trai... | distill-bloom-deepspeed-main | distill_bloom/dataset/get_dataset.py |
import os
import time
import numpy as np
import torch
from .megatron import mpu
def print_rank_0(message):
"""If distributed is initialized, print only on rank 0."""
if torch.distributed.is_initialized():
if torch.distributed.get_rank() == 0:
print(message, flush=True)
else:
... | distill-bloom-deepspeed-main | distill_bloom/dataset/gpt_dataset.py |
import time
import numpy as np
import torch
from .gpt_dataset import GPTDataset
from .indexed_dataset import (IndexedDataset, MMapIndexedDataset,
create_doc_idx, data_file_path, index_file_path)
def print_rank_0(message):
"""If distributed is initialized, print only on rank 0."""
... | distill-bloom-deepspeed-main | distill_bloom/dataset/utils.py |
import torch
class DistributedDataset(torch.utils.data.Dataset):
r"""
Wrapper for torch.utils.data.Dataset to make it distributed.
Args:
dataset (torch.utils.data.Dataset): Dataset to be distributed.
rank (int): Rank of the current process.
world_size (int): Num... | distill-bloom-deepspeed-main | distill_bloom/dataset/dataloader.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# copied from fairseq/fairseq/data/indexed_dataset.py
# Removed IndexedRawTextDataset since it relied on Fairseq dictionary
# other slight mo... | distill-bloom-deepspeed-main | distill_bloom/dataset/indexed_dataset.py |
# coding=utf-8
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... | distill-bloom-deepspeed-main | distill_bloom/dataset/megatron/mpu/cross_entropy.py |
# coding=utf-8
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... | distill-bloom-deepspeed-main | distill_bloom/dataset/megatron/mpu/initialize.py |
# coding=utf-8
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... | distill-bloom-deepspeed-main | distill_bloom/dataset/megatron/mpu/__init__.py |
# coding=utf-8
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... | distill-bloom-deepspeed-main | distill_bloom/dataset/megatron/mpu/random.py |
# coding=utf-8
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... | distill-bloom-deepspeed-main | distill_bloom/dataset/megatron/mpu/utils.py |
# coding=utf-8
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... | distill-bloom-deepspeed-main | distill_bloom/dataset/megatron/mpu/layers.py |
# coding=utf-8
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... | distill-bloom-deepspeed-main | distill_bloom/dataset/megatron/mpu/data.py |
# coding=utf-8
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... | distill-bloom-deepspeed-main | distill_bloom/dataset/megatron/mpu/mappings.py |
# coding=utf-8
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... | distill-bloom-deepspeed-main | distill_bloom/dataset/megatron/mpu/tests/test_cross_entropy.py |
# coding=utf-8
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... | distill-bloom-deepspeed-main | distill_bloom/dataset/megatron/mpu/tests/test_layers.py |
distill-bloom-deepspeed-main | distill_bloom/dataset/megatron/mpu/tests/__init__.py | |
# coding=utf-8
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... | distill-bloom-deepspeed-main | distill_bloom/dataset/megatron/mpu/tests/commons.py |
# coding=utf-8
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... | distill-bloom-deepspeed-main | distill_bloom/dataset/megatron/mpu/tests/test_data.py |
# coding=utf-8
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... | distill-bloom-deepspeed-main | distill_bloom/dataset/megatron/mpu/tests/test_initialize.py |
# coding=utf-8
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... | distill-bloom-deepspeed-main | distill_bloom/dataset/megatron/mpu/tests/test_random.py |
# coding=utf-8
# Copyright 2020 Optuna, Hugging Face
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law o... | distill-bloom-deepspeed-main | distill_bloom/arguments/logging.py |
# Arguments for distillation
import argparse
import collections
import os
import re
import time
import deepspeed
from .logging import log_levels
def parse_args(extra_args_provider=None, defaults={}, ignore_unknown_args=False):
r"""
Helper function to parse all necessarly arguments to perform teacher / stud... | distill-bloom-deepspeed-main | distill_bloom/arguments/arguments.py |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate-wip-main | setup.py |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate-wip-main | tests/test_big_modeling.py |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate-wip-main | tests/test_optimizer.py |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate-wip-main | tests/test_data_loader.py |
import unittest
from dataclasses import dataclass
import pytest
from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict
@dataclass
class MockLaunchConfig(SageMakerConfig):
compute_environment = ... | accelerate-wip-main | tests/test_sagemaker.py |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate-wip-main | tests/test_utils.py |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate-wip-main | tests/test_cpu.py |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate-wip-main | tests/test_memory_utils.py |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate-wip-main | tests/test_metrics.py |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate-wip-main | tests/test_kwargs_handlers.py |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate-wip-main | tests/test_scheduler.py |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate-wip-main | tests/test_modeling_utils.py |
import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state import GradientState, PartialState
from accele... | accelerate-wip-main | tests/test_accelerator.py |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate-wip-main | tests/test_tracking.py |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate-wip-main | tests/test_hooks.py |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate-wip-main | tests/test_multigpu.py |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate-wip-main | tests/test_grad_sync.py |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate-wip-main | tests/xla_spawn.py |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate-wip-main | tests/test_offload.py |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate-wip-main | tests/test_cli.py |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate-wip-main | tests/test_tpu.py |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate-wip-main | tests/test_examples.py |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate-wip-main | tests/test_state_checkpointing.py |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate-wip-main | tests/deepspeed/test_deepspeed.py |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate-wip-main | tests/fsdp/test_fsdp.py |
# Copyright 2022 The HuggingFace Team, the AllenNLP library authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
... | accelerate-wip-main | utils/stale.py |
import json
import os
from datetime import date
from pathlib import Path
from tabulate import DataRow, TableFormat, tabulate
hf_table_format = TableFormat(
lineabove=None,
linebelowheader=None,
linebetweenrows=None,
linebelow=None,
headerrow=DataRow("", "|", "|"),
datarow=DataRow("", "|", "|"... | accelerate-wip-main | utils/log_reports.py |
# coding=utf-8
# Copyright 2021 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless r... | accelerate-wip-main | examples/nlp_example.py |
import argparse
import runhouse as rh
import torch
from nlp_example import training_function
from accelerate.utils import PrepareForLaunch, patch_environment
def launch_train(*args):
num_processes = torch.cuda.device_count()
print(f"Device count: {num_processes}")
with patch_environment(
world_s... | accelerate-wip-main | examples/multigpu_remote_launcher.py |
# coding=utf-8
# Copyright 2021 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless r... | accelerate-wip-main | examples/complete_cv_example.py |
# coding=utf-8
# Copyright 2021 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless r... | accelerate-wip-main | examples/complete_nlp_example.py |
# coding=utf-8
# Copyright 2021 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless r... | accelerate-wip-main | examples/cv_example.py |
# coding=utf-8
# Copyright 2021 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless r... | accelerate-wip-main | examples/by_feature/gradient_accumulation.py |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate-wip-main | examples/by_feature/memory.py |
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless r... | accelerate-wip-main | examples/by_feature/local_sgd.py |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate-wip-main | examples/by_feature/automatic_gradient_accumulation.py |
#!/usr/bin/env python
# coding=utf-8
# Copyright 2022 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LI... | accelerate-wip-main | examples/by_feature/deepspeed_with_config_support.py |
# coding=utf-8
# Copyright 2022 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless r... | accelerate-wip-main | examples/by_feature/multi_process_metrics.py |
#!/usr/bin/env python
# coding=utf-8
# Copyright 2021 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LI... | accelerate-wip-main | examples/by_feature/megatron_lm_gpt_pretraining.py |
# coding=utf-8
# Copyright 2021 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless r... | accelerate-wip-main | examples/by_feature/fsdp_with_peak_mem_tracking.py |
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