python_code stringlengths 0 679k | repo_name stringlengths 9 41 | file_path stringlengths 6 149 |
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# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import json
import os
import sys
import tempfile
import requests
from megatron.data.indexed_dataset import MMapIndexedDataset
from megatron.tokenizer.gpt2_tokenization import (
PRETRAINED_MERGES_ARCHIVE_MAP,
PRETRAINED_VOCAB_ARCHIVE_MAP,
)
from t... | Megatron-LM-master | tests/unit_tests/data/test_preprocess_data.py |
Megatron-LM-master | tests/functional_tests/__init__.py | |
import os
import json
import pytest
import sys
import glob
from tensorboard.backend.event_processing import event_accumulator
LOGS_DIR = os.getenv('LOGS_DIR')
EXPECTED_METRICS_FILE = os.getenv('EXPECTED_METRICS_FILE')
import enum
class TypeOfTest(enum.Enum):
APPROX = 1
DETERMINISTIC = 2
def read_tb_logs_as... | Megatron-LM-master | tests/functional_tests/python_test_utils/test_ci_pipeline.py |
"""Check if a given slurm job id completed successfully
Usage:
python3 check_slurm_job_completion.py <JOB_ID>
"""
import sys
import subprocess
cmd = f"sacct -j {sys.argv[1]}"
result = subprocess.check_output(cmd, shell=True).decode().split()
assert len(result) > 14, "JOB state not available."
status = res... | Megatron-LM-master | tests/functional_tests/python_test_utils/check_slurm_job_completion.py |
Megatron-LM-master | tests/functional_tests/python_test_utils/__init__.py | |
import os
os.environ['OPENBLAS_NUM_THREADS'] = '1'
import sys
import json
import shutil
import glob
from tensorboard.backend.event_processing import event_accumulator
LOGS_DIR = os.getenv('LOGS_DIR')
def read_tb_logs_as_list(path, summary_name, index):
files = glob.glob(f"{path}/events*tfevents*")
files += gl... | Megatron-LM-master | tests/functional_tests/python_test_utils/test_resume_checkpoint_pipeline.py |
import os
os.environ['OPENBLAS_NUM_THREADS'] = '1'
import sys
import glob
from tensorboard.backend.event_processing import event_accumulator
def read_tb_logs_as_list(path, summary_name):
"""Reads a TensorBoard Events file from the input path, and returns the
summary specified as input as a list.
Argument... | Megatron-LM-master | tests/functional_tests/python_test_utils/get_test_results_from_tensorboard_logs.py |
# coding=utf-8
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
"""Sample Generate GPT"""
import json
import os
import sys
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__),
os.path.pardir, os.path.pardir)))
import torch
from megatron im... | Megatron-LM-master | examples/detxoify_lm/generate_samples_gpt.py |
# coding=utf-8
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
"""Fine-tune GPT"""
import torch
from functools import partial
import os
import sys
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__),
os.path.pardir, os.path.pardir)))
fro... | Megatron-LM-master | examples/detxoify_lm/finetune_gpt.py |
import json
import time
from typing import Dict, Optional, List
import joblib
from googleapiclient import discovery
from googleapiclient.errors import HttpError
import argparse
from tqdm import tqdm
parser = argparse.ArgumentParser(description='Process some integers.')
parser.add_argument('--data-path', type=str, d... | Megatron-LM-master | examples/detxoify_lm/perspective_api.py |
import json
import time
from typing import Dict, Optional, List
import joblib
from googleapiclient import discovery
from googleapiclient.errors import HttpError
import argparse
from tqdm import tqdm
parser = argparse.ArgumentParser(description='Process some integers.')
parser.add_argument('--data-path', type=str, d... | Megatron-LM-master | examples/detxoify_lm/annotations/perspective_api_annotate.py |
import json
import time
from typing import Dict, Optional, List
import joblib
from googleapiclient import discovery
from googleapiclient.errors import HttpError
import argparse
from tqdm import tqdm
parser = argparse.ArgumentParser(description='Process some integers.')
parser.add_argument('--data-path', type=str, d... | Megatron-LM-master | examples/detxoify_lm/annotations/filter-selfgeneration.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import torch
# A dictionary of all the memory buffers allocated.
_MEM_BUFFS = dict()
def allocate_mem_buff(name, numel, dtype, track_usage):
"""Allocate a memory buffer."""
assert name not in _MEM_BUFFS, \
'memory buffer {} already all... | Megatron-LM-master | megatron/memory.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Megatron initialization."""
import random
import os
import time
import numpy as np
import torch
from datetime import timedelta
from megatron import fused_kernels
from megatron import get_adlr_autoresume
from megatron import get_args
from megatron imp... | Megatron-LM-master | megatron/initialize.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
"""Megatron arguments."""
import argparse
import dataclasses
import json
import os
import torch
import types
import torch.nn.functional as F
from megatron.global_vars import set_retro_args, get_retro_args
from tools.retro.utils import get_args_path as ge... | Megatron-LM-master | megatron/arguments.py |
import signal
import torch
def get_world_size():
if torch.distributed.is_available() and torch.distributed.is_initialized():
world_size = torch.distributed.get_world_size()
else:
world_size = 1
return world_size
def get_device(local_rank=None):
backend = torch.distributed.get_backen... | Megatron-LM-master | megatron/dist_signal_handler.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import torch
from .global_vars import get_args, get_retro_args
from .global_vars import get_current_global_batch_size
from .global_vars import get_num_microbatches
from .global_vars import get_signal_handler
from .global_vars import update_num_microbatche... | Megatron-LM-master | megatron/__init__.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import datetime
import torch
import json
import threading
from flask import Flask, request, jsonify, current_app
from flask_restful import Resource, Api
from megatron import get_args
from megatron.text_generation import generate_and_post_process
from megatr... | Megatron-LM-master | megatron/text_generation_server.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Learning rate decay and weight decay incr functions."""
import math
from megatron import print_rank_0
class OptimizerParamScheduler(object):
"""Anneals learning rate and weight decay"""
def __init__(self, optimizer, init_lr, max_lr, min_lr,
... | Megatron-LM-master | megatron/optimizer_param_scheduler.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""General utilities."""
import sys
import torch
try:
from apex.multi_tensor_apply import multi_tensor_applier
except ImportError:
multi_tensor_applier = None
try:
import amp_C
except ImportError:
amp_C = None
from megatron import (
... | Megatron-LM-master | megatron/utils.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Megatron number of micro-batches calculators."""
from abc import ABC
from abc import abstractmethod
def build_num_microbatches_calculator(args):
# Constant num micro-batches.
if args.rampup_batch_size is None:
num_microbatches_calcul... | Megatron-LM-master | megatron/microbatches.py |
import sys
import time
import torch
import torch.distributed as dist
from megatron import get_args, print_rank_0
from megatron.core import mpu
from megatron.checkpointing import load_biencoder_checkpoint
from megatron.data.orqa_wiki_dataset import get_open_retrieval_wiki_dataset
from megatron.data.orqa_wiki_dataset im... | Megatron-LM-master | megatron/indexer.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Megatron timers."""
from abc import ABC
from abc import abstractmethod
import time
import torch
class TimerBase(ABC):
def __init__(self, name):
self.name = name
@abstractmethod
def start(self, barrier=False):
pass
... | Megatron-LM-master | megatron/timers.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
"""Pretrain utilities."""
from datetime import datetime
import math
import sys
import time
# The earliest we can measure the start time.
_TRAIN_START_TIME = time.time()
import torch
from megatron import get_args
from megatron import get_signal_handler
fr... | Megatron-LM-master | megatron/training.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Megatron global variables."""
import os
import sys
import torch
from megatron import dist_signal_handler
from megatron.tokenizer import build_tokenizer
from .microbatches import build_num_microbatches_calculator
from .timers import Timers
_GLOBAL_ARG... | Megatron-LM-master | megatron/global_vars.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
"""Input/output checkpointing."""
import os
import random
import sys
import numpy as np
import torch
from megatron import update_num_microbatches
from megatron.core import mpu, tensor_parallel
from .global_vars import get_args
from .utils import (unwrap... | Megatron-LM-master | megatron/checkpointing.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Generation utilities."""
import torch
import torch.nn.functional as F
from megatron import get_args, get_tokenizer
from megatron.core import mpu
from megatron.utils import get_ltor_masks_and_position_ids
from .communication import (
copy_from_last... | Megatron-LM-master | megatron/text_generation/generation.py |
# coding=utf-8
# Copyright 2018 The Google AI Language Team Authors, Facebook AI Research authors and The HuggingFace Inc. team.
# Copyright (c) 2018, 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 L... | Megatron-LM-master | megatron/text_generation/beam_utils.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
from .api import (
generate,
generate_and_post_process,
beam_search_and_post_process)
| Megatron-LM-master | megatron/text_generation/__init__.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Tokenization utilities."""
import torch
from megatron import get_tokenizer, get_args
from .communication import broadcast_int_list, broadcast_tensor
def detokenize_generations(tokens_gpu_tensor,
lengths_gpu_tensor,
... | Megatron-LM-master | megatron/text_generation/tokenization.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Forward step utilities."""
from collections.abc import Iterable
import torch
from megatron import get_args
from megatron.core import mpu, InferenceParams
from .communication import (
send_to_next_pipeline_rank,
recv_from_prev_pipeline_rank_)
... | Megatron-LM-master | megatron/text_generation/forward_step.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Inference API."""
import torch
from megatron.core import mpu
from .communication import broadcast_float_list
from .generation import (
generate_tokens_probs_and_return_on_first_stage,
score_and_return_on_first_stage,
beam_sear... | Megatron-LM-master | megatron/text_generation/api.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Communications utilities."""
import torch
from megatron.core import mpu
# TODO: use functions from megatron/p2p
def recv_from_prev_pipeline_rank_(recv_buffer=None):
"""Receive from previous pipeline stage and update the
input buffer inplac... | Megatron-LM-master | megatron/text_generation/communication.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Sampling utilities.
Part of this code is inspired by:
- https://github.com/ari-holtzman/degen/blob/master/gen.py
- https://huggingface.co/transformers/_modules/transformers/generation_logits_process.html
"""
import torch
def modify_logits_for_top... | Megatron-LM-master | megatron/text_generation/sampling.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
from commons import set_random_seed
from commons import IdentityLayer
from commons import print_separator
from commons import initialize_distributed
from mpu.cross_entropy import vocab_parallel_cross_entropy
import mpu
import torch.nn.functional as F
impor... | Megatron-LM-master | megatron/mpu/tests/test_cross_entropy.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
from mpu import layers
from commons import set_random_seed
from commons import print_separator
from commons import initialize_distributed
import mpu
from torch.nn.parameter import Parameter
import torch.nn.init as init
import torch
import random
import sys... | Megatron-LM-master | megatron/mpu/tests/test_layers.py |
Megatron-LM-master | megatron/mpu/tests/__init__.py | |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import argparse
import os
import random
import numpy
import torch
import mpu
class IdentityLayer(torch.nn.Module):
def __init__(self, size, scale=1.0):
super(IdentityLayer, self).__init__()
self.weight = torch.nn.Parameter(scale * to... | Megatron-LM-master | megatron/mpu/tests/commons.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
from commons import print_separator
from commons import initialize_distributed
from mpu import data as data_utils
import mpu
import torch
import functools
import operator
import sys
sys.path.append("../..")
def test_broadcast_data(tensor_model_parallel_s... | Megatron-LM-master | megatron/mpu/tests/test_data.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
from commons import print_separator
from commons import initialize_distributed
import mpu
import torch
import sys
sys.path.append("../..")
def test_initialize_model_parallel(tensor_model_parallel_size):
if torch.distributed.get_rank() == 0:
... | Megatron-LM-master | megatron/mpu/tests/test_initialize.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
from commons import print_separator
from commons import initialize_distributed
import mpu
import torch
import sys
sys.path.append("../..")
def test_set_cuda_rng_state(tensor_model_parallel_size):
if torch.distributed.get_rank() == 0:
print('... | Megatron-LM-master | megatron/mpu/tests/test_random.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
from dataclasses import dataclass
from typing import Callable, Optional
import torch
@dataclass
class ModelParallelConfig:
"""Base configuration for Megatron Core
Model Parallelism
-----------------
tensor_model_parallel_size (int): In... | Megatron-LM-master | megatron/core/model_parallel_config.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
MAJOR = 0
MINOR = 4
PATCH = 0
PRE_RELEASE = 'rc0'
# Use the following formatting: (major, minor, patch, pre-release)
VERSION = (MAJOR, MINOR, PATCH, PRE_RELEASE)
__shortversion__ = '.'.join(map(str, VERSION[:3]))
__version__ = '.'.join(map(str, VERSION... | Megatron-LM-master | megatron/core/package_info.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import enum
class ModelType(enum.Enum):
encoder_or_decoder = 1
encoder_and_decoder = 2
retro_encoder = 3
retro_decoder = 4
| Megatron-LM-master | megatron/core/enums.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Model and data parallel groups."""
import os
from typing import Optional
import torch
from .utils import GlobalMemoryBuffer
# Intra-layer model parallel group that the current rank belongs to.
_TENSOR_MODEL_PARALLEL_GROUP = None
# Inter-layer model ... | Megatron-LM-master | megatron/core/parallel_state.py |
import megatron.core.parallel_state
import megatron.core.tensor_parallel
import megatron.core.utils
from .inference_params import InferenceParams
from .model_parallel_config import ModelParallelConfig
# Alias parallel_state as mpu, its legacy name
mpu = parallel_state
__all__ = ["parallel_state", "tensor_parallel", ... | Megatron-LM-master | megatron/core/__init__.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
"""Utility functions used throughout Megatron core"""
import math
import operator
from functools import reduce
import torch
from megatron.core import parallel_state
from megatron.core.dist_checkpointing.mapping import ShardedTensor
def ensure_divisibil... | Megatron-LM-master | megatron/core/utils.py |
class InferenceParams:
"""Inference parameters that are passed to the main model in order
to efficienly calculate and store the context during inference."""
def __init__(self, max_batch_size, max_sequence_length):
self.max_sequence_length = max_sequence_length
self.max_batch_size = max_batc... | Megatron-LM-master | megatron/core/inference_params.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import importlib
import numbers
import torch
from torch.nn import init
from torch.nn.parameter import Parameter
from megatron.core.utils import make_viewless_tensor
try:
from apex.contrib.layer_norm.layer_norm import FastLayerNormFN
HAVE_PERSIS... | Megatron-LM-master | megatron/core/fusions/fused_layer_norm.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import torch
import torch.nn as nn
from megatron.core.transformer.enums import AttnMaskType
class ScaledUpperTriangMaskedSoftmax(torch.autograd.Function):
"""
Fused operation which performs following three operations in sequence
1. Scale th... | Megatron-LM-master | megatron/core/fusions/fused_softmax.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
from typing import Optional, Tuple
import torch
def _bias_dropout_add_func(x, bias, residual, prob, training):
# type: (Tensor, Optional[Tensor], Tensor, float, bool) -> Tensor
# NOTE: Previously, the argument `bias` used to be passed as
# `... | Megatron-LM-master | megatron/core/fusions/fused_bias_dropout.py |
Megatron-LM-master | megatron/core/fusions/__init__.py | |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import torch
###### BIAS GELU FUSION/ NO AUTOGRAD ################
# 1/sqrt(2*pi)-> 0.3989423
# 1/sqrt(2) -> 0.70710678
# sqrt(2/pi) -> 0.79788456
# this function is tanh approximation of gelu
# actual gelu is:
# x * 0.5 * (1.0 + torch.erf(x * 0.707106... | Megatron-LM-master | megatron/core/fusions/fused_bias_gelu.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import torch
from megatron.core.parallel_state import (
get_tensor_model_parallel_group,
get_tensor_model_parallel_rank,
get_tensor_model_parallel_world_size,
)
from .utils import VocabUtility
class _VocabParallelCrossEntropy(torch.autograd... | Megatron-LM-master | megatron/core/tensor_parallel/cross_entropy.py |
from .cross_entropy import vocab_parallel_cross_entropy
from .data import broadcast_data
from .layers import (
ColumnParallelLinear,
RowParallelLinear,
VocabParallelEmbedding,
copy_tensor_model_parallel_attributes,
linear_with_grad_accumulation_and_async_allreduce,
param_is_not_tensor_parallel_d... | Megatron-LM-master | megatron/core/tensor_parallel/__init__.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
# Parts of the code here are adapted from PyTorch
# repo: https://github.com/pytorch/pytorch
import contextlib
import torch
from torch import _C
from torch.cuda import _lazy_call
from torch.cuda import device as device_ctx_manager
from torch.utils.checkp... | Megatron-LM-master | megatron/core/tensor_parallel/random.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
from typing import List, Sequence
import torch
from megatron.core import parallel_state
from megatron.core.utils import divide
def split_tensor_along_last_dim(
tensor: torch.Tensor, num_partitions: int, contiguous_split_chunks: bool = False,
) -> L... | Megatron-LM-master | megatron/core/tensor_parallel/utils.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
# Parts of the code here are adapted from PyTorch
# repo: https://github.com/pytorch/pytorch
import math
import os
import warnings
from typing import Callable, Optional
import torch
import torch.nn.functional as F
import torch.nn.init as init
from torch.... | Megatron-LM-master | megatron/core/tensor_parallel/layers.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import torch
from megatron.core.parallel_state import (
get_tensor_model_parallel_group,
get_tensor_model_parallel_rank,
get_tensor_model_parallel_src_rank,
)
_MAX_DATA_DIM = 5
def _check_data_types(keys, data, target_dtype):
"""Check t... | Megatron-LM-master | megatron/core/tensor_parallel/data.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import torch
from megatron.core.parallel_state import (
get_tensor_model_parallel_group,
get_tensor_model_parallel_rank,
get_tensor_model_parallel_world_size,
)
from .utils import split_tensor_along_last_dim
def _reduce(input_):
"""All-... | Megatron-LM-master | megatron/core/tensor_parallel/mappings.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import re
from contextlib import nullcontext
import torch
from megatron.core import parallel_state, tensor_parallel
from megatron.core.fusions.fused_layer_norm import FusedLayerNorm
from megatron.core.transformer.custom_layers.transformer_engine import T... | Megatron-LM-master | megatron/core/transformer/transformer_block.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
from dataclasses import dataclass
from typing import Callable
import torch
import torch.nn.functional as F
from megatron.core import ModelParallelConfig
from megatron.core.utils import init_method_normal, scaled_init_method_normal
@dataclass
class Tran... | Megatron-LM-master | megatron/core/transformer/transformer_config.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
from abc import ABC, abstractmethod
import torch
from megatron.core import parallel_state, tensor_parallel
from megatron.core.models.common.rotary_pos_embedding import apply_rotary_pos_emb
from megatron.core.transformer.custom_layers.transformer_engine i... | Megatron-LM-master | megatron/core/transformer/attention.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import enum
# can we get rid of this?
# it's being used in pipeline schedules
class ModelType(enum.Enum):
encoder_or_decoder = 1
encoder_and_decoder = 2
# class LayerType(enum.Enum):
# encoder = 1
# decoder = 2
class AttnType(enum.Enu... | Megatron-LM-master | megatron/core/transformer/enums.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
from .transformer_config import TransformerConfig
| Megatron-LM-master | megatron/core/transformer/__init__.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import re
import torch
from megatron.core import parallel_state
from megatron.core.dist_checkpointing.mapping import ShardedObject, ShardedTensor
from megatron.core.fusions.fused_bias_dropout import get_bias_dropout_add
from megatron.core.transformer.att... | Megatron-LM-master | megatron/core/transformer/transformer_layer.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import torch
import torch.nn.functional as F
from megatron.core import tensor_parallel
from megatron.core.fusions.fused_bias_gelu import bias_gelu_impl
from megatron.core.transformer.custom_layers.transformer_engine import (
TELayerNormColumnParallelL... | Megatron-LM-master | megatron/core/transformer/mlp.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import math
import torch
from torch import Tensor
from megatron.core import parallel_state, tensor_parallel
from megatron.core.fusions.fused_softmax import FusedScaleMaskSoftmax
from megatron.core.transformer.enums import AttnMaskType
from megatron.core... | Megatron-LM-master | megatron/core/transformer/dot_product_attention.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Utilities for transformer layers."""
import torch
from megatron import get_args
def attention_mask_func(attention_scores, attention_mask):
attention_scores.masked_fill_(attention_mask, -10000.0)
return attention_scores
def get_linear_layer... | Megatron-LM-master | megatron/core/transformer/utils.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import torch
class IdentityOp(torch.nn.Module):
"""
This is a placeholder for IdentityOp (NoOp)
"""
def __init__(self, *args, **kwargs):
super(IdentityOp, self).__init__()
def forward(self, x, *args, **kwargs):
return... | Megatron-LM-master | megatron/core/transformer/identity_op.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
"""Megatron Module"""
import torch
from torch.autograd import Variable
from torch.nn.parameter import Parameter
from megatron.core import parallel_state, tensor_parallel
from megatron.core.transformer.transformer_config import TransformerConfig
_FLOAT_T... | Megatron-LM-master | megatron/core/transformer/module.py |
from importlib.metadata import version
from typing import Callable
import torch
import transformer_engine as te
from pkg_resources import packaging
from megatron.core.parallel_state import get_tensor_model_parallel_group
from megatron.core.tensor_parallel import get_cuda_rng_tracker
from megatron.core.transformer.enu... | Megatron-LM-master | megatron/core/transformer/custom_layers/transformer_engine.py |
from .schedules import get_forward_backward_func
| Megatron-LM-master | megatron/core/pipeline_parallel/__init__.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import contextlib
from typing import Callable, Iterator, List, Optional, Union
import torch
from torch.autograd.variable import Variable
from torch.nn.parallel.distributed import DistributedDataParallel as torchDDP
from megatron import core
from megatron... | Megatron-LM-master | megatron/core/pipeline_parallel/schedules.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import operator
from functools import reduce
from typing import Callable, List, Optional, Tuple, Union
import torch
from megatron import core
from megatron.core import ModelParallelConfig
from megatron.core.parallel_state import (
get_pipeline_model_... | Megatron-LM-master | megatron/core/pipeline_parallel/p2p_communication.py |
Megatron-LM-master | megatron/core/models/__init__.py | |
from .gpt_model import GPTModel
| Megatron-LM-master | megatron/core/models/gpt/__init__.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import logging
from typing import Literal, Optional
import torch
from torch import Tensor
from megatron.core import parallel_state, tensor_parallel
from megatron.core.models.common.rotary_pos_embedding import RotaryEmbedding
from megatron.core.models.gpt... | Megatron-LM-master | megatron/core/models/gpt/gpt_model.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import torch
from megatron.core import tensor_parallel
from megatron.core.transformer.module import MegatronModule
from megatron.core.transformer.transformer_config import TransformerConfig
from megatron.core.utils import (
make_sharded_tensor_for_che... | Megatron-LM-master | megatron/core/models/gpt/gpt_embedding.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import importlib.util
import torch
from torch import einsum, nn
__all__ = ['RotaryEmbedding', 'apply_rotary_pos_emb']
class RotaryEmbedding(nn.Module):
def __init__(self, dim, seq_len_interpolation_factor=None):
super().__init__()
s... | Megatron-LM-master | megatron/core/models/common/rotary_pos_embedding.py |
# Copyright (c) 2022-2023, NVIDIA CORPORATION. All rights reserved.
""" Utilities for operating with dicts and lists. """
from collections import defaultdict
from typing import Any, Callable, Iterable, Optional, Tuple, Union
import torch
def extract_matching_values(
x: Union[dict, list], predicate: Callable
)... | Megatron-LM-master | megatron/core/dist_checkpointing/dict_utils.py |
# Copyright (c) 2022-2023, NVIDIA CORPORATION. All rights reserved.
from .core import check_is_distributed_checkpoint
from .mapping import LocalNonpersitentObject, ShardedTensor
from .serialization import load, load_common_state_dict, save
| Megatron-LM-master | megatron/core/dist_checkpointing/__init__.py |
# Copyright (c) 2022-2023, NVIDIA CORPORATION. All rights reserved.
import json
from dataclasses import asdict, dataclass
from pathlib import Path
from typing import Optional
CONFIG_FNAME = 'metadata.json'
class CheckpointingException(Exception):
pass
@dataclass
class CheckpointingConfig:
""" Documents b... | Megatron-LM-master | megatron/core/dist_checkpointing/core.py |
# Copyright (c) 2022-2023, NVIDIA CORPORATION. All rights reserved.
from typing import Tuple
from .dict_utils import dict_list_map_inplace, extract_matching_values
from .mapping import LocalNonpersitentObject, ShardedStateDict, ShardedTensor, StateDict
def extract_sharded_tensors(
sharded_state_dict: ShardedSt... | Megatron-LM-master | megatron/core/dist_checkpointing/utils.py |
# Copyright (c) 2022-2023, NVIDIA CORPORATION. All rights reserved.
""" Optimizer related helpers. """
import logging
from copy import deepcopy
from dataclasses import replace
from itertools import chain
from typing import Dict, Iterable, List
logger = logging.getLogger(__name__)
import torch
from .dict_utils imp... | Megatron-LM-master | megatron/core/dist_checkpointing/optimizer.py |
# Copyright (c) 2022-2023, NVIDIA CORPORATION. All rights reserved.
""" Core library classes. """
from dataclasses import dataclass, replace
from itertools import chain
from typing import Any, Dict, Optional, Tuple, Union
import numpy as np
import torch
from .core import CheckpointingException
# These type defini... | Megatron-LM-master | megatron/core/dist_checkpointing/mapping.py |
# Copyright (c) 2022-2023, NVIDIA CORPORATION. All rights reserved.
import logging
import os
from collections import Counter, defaultdict
from itertools import chain
from pathlib import Path
from typing import Iterable, List, Tuple, Union
import numpy as np
import torch
from .core import CheckpointingConfig, maybe_... | Megatron-LM-master | megatron/core/dist_checkpointing/serialization.py |
# Copyright (c) 2022-2023, NVIDIA CORPORATION. All rights reserved.
""" Various loading and saving strategies """
import logging
logger = logging.getLogger(__name__)
try:
import tensorstore
import zarr
from .tensorstore import _import_trigger
from .zarr import _import_trigger
except ImportError:
... | Megatron-LM-master | megatron/core/dist_checkpointing/strategies/__init__.py |
# Copyright (c) 2022-2023, NVIDIA CORPORATION. All rights reserved.
""" 2-stage checkpoint loading. """
import os
import time
from collections import defaultdict
from dataclasses import dataclass
from functools import partial, wraps
from itertools import chain
from logging import DEBUG, INFO, StreamHandler, getLogger... | Megatron-LM-master | megatron/core/dist_checkpointing/strategies/two_stage.py |
# Copyright (c) 2022-2023, NVIDIA CORPORATION. All rights reserved.
""" Strategies using Zarr as an underlying format. """
import os
from functools import partial
from pathlib import Path
from typing import List
import numpy as np
import torch
import zarr
from ..core import CheckpointingException
from ..dict_utils ... | Megatron-LM-master | megatron/core/dist_checkpointing/strategies/zarr.py |
# Copyright (c) 2022-2023, NVIDIA CORPORATION. All rights reserved.
from abc import ABC, abstractmethod
from collections import defaultdict
from enum import Enum
from pathlib import Path
from typing import Dict, List, Optional
from ..mapping import CheckpointingException, ShardedStateDict, ShardedTensor, StateDict
... | Megatron-LM-master | megatron/core/dist_checkpointing/strategies/base.py |
# Copyright (c) 2022-2023, NVIDIA CORPORATION. All rights reserved.
""" Strategies using TensorStore to load and save Zarr arrays. """
from functools import partial
from itertools import starmap
from pathlib import Path
import tensorstore as ts
import torch
from ..core import CheckpointingException
from ..dict_uti... | Megatron-LM-master | megatron/core/dist_checkpointing/strategies/tensorstore.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Gradient clipping."""
import os
import torch
from torch import inf
from apex.multi_tensor_apply import multi_tensor_applier
import amp_C
from megatron.model.module import param_is_not_shared
from megatron.core.tensor_parallel import param_is_not_ten... | Megatron-LM-master | megatron/optimizer/clip_grads.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Megatron grad scaler."""
from abc import ABC
from abc import abstractmethod
import torch
class MegatronGradScaler(ABC):
def __init__(self, initial_scale):
"""Initialize scale value with the input initial scale."""
assert initial... | Megatron-LM-master | megatron/optimizer/grad_scaler.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
from apex.optimizers import FusedAdam as Adam
from apex.optimizers import FusedSGD as SGD
from megatron import get_args
from .distrib_optimizer import DistributedOptimizer
from .grad_scaler import ConstantGradScaler, DynamicGradScaler
from .optimizer imp... | Megatron-LM-master | megatron/optimizer/__init__.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
"""Megatron distributed optimizer."""
from apex.optimizers import FusedAdam as Adam
import math
import torch
from megatron import get_args
from megatron import get_timers
from megatron import print_rank_0
from megatron.core import mpu, tensor_parallel
f... | Megatron-LM-master | megatron/optimizer/distrib_optimizer.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
"""Megatron optimizer."""
from abc import ABC
from abc import abstractmethod
from apex.multi_tensor_apply import multi_tensor_applier
import amp_C
import torch
from torch._utils import _flatten_dense_tensors, _unflatten_dense_tensors
from megatron import... | Megatron-LM-master | megatron/optimizer/optimizer.py |
# coding=utf-8
# Copyright 2018 The Google AI Language Team Authors.
#
# 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 ... | Megatron-LM-master | megatron/tokenizer/bert_tokenization.py |
# coding=utf-8
# Copyright 2018 The Open AI Team Authors and The HuggingFace Inc. team.
#
# 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
#
# ... | Megatron-LM-master | megatron/tokenizer/gpt2_tokenization.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
from .tokenizer import build_tokenizer
| Megatron-LM-master | megatron/tokenizer/__init__.py |
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