repo stringlengths 1 99 | file stringlengths 13 215 | code stringlengths 12 59.2M | file_length int64 12 59.2M | avg_line_length float64 3.82 1.48M | max_line_length int64 12 2.51M | extension_type stringclasses 1
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AMP | AMP-main/DeepSpeed/setup.py | """
Copyright 2020 The Microsoft DeepSpeed Team
DeepSpeed library
Create a new wheel via the following command: python setup.py bdist_wheel
The wheel will be located at: dist/*.whl
"""
import os
import shutil
import subprocess
import warnings
from setuptools import setup, find_packages
import time
try:
import ... | 7,036 | 33.836634 | 99 | py |
AMP | AMP-main/DeepSpeed/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... | 8,315 | 35.634361 | 100 | py |
AMP | AMP-main/DeepSpeed/deepspeed/env_report.py | import torch
import deepspeed
import subprocess
from .ops.op_builder import ALL_OPS
from .git_version_info import installed_ops, torch_info
from .ops import __compatible_ops__ as compatible_ops
GREEN = '\033[92m'
RED = '\033[91m'
YELLOW = '\033[93m'
END = '\033[0m'
SUCCESS = f"{GREEN} [SUCCESS] {END}"
OKAY = f"{GREEN}... | 3,668 | 32.354545 | 136 | py |
AMP | AMP-main/DeepSpeed/deepspeed/git_version_info.py | try:
# This is populated by setup.py
from .git_version_info_installed import *
except ModuleNotFoundError:
import os
if os.path.isfile('version.txt'):
# Will be missing from checkouts that haven't been installed (e.g., readthedocs)
version = open('version.txt', 'r').read().strip()
e... | 616 | 33.277778 | 88 | py |
AMP | AMP-main/DeepSpeed/deepspeed/__init__.py | '''
Copyright 2020 The Microsoft DeepSpeed Team
'''
import sys
import types
from . import ops
from .runtime.engine import DeepSpeedEngine
from .runtime.engine import ADAM_OPTIMIZER, LAMB_OPTIMIZER
from .runtime.pipe.engine import PipelineEngine
from .runtime.lr_schedules import add_tuning_arguments
from .runtime.conf... | 8,369 | 37.930233 | 121 | py |
AMP | AMP-main/DeepSpeed/deepspeed/profiling/flops_profiler/profiler.py | import time
import torch
import torch.nn as nn
import torch.nn.functional as F
from functools import partial
module_flop_count = []
old_functions = {}
class FlopsProfiler(object):
"""Measures the latency, number of estimated floating point operations and parameters of each module in a PyTorch model.
The flo... | 33,137 | 37.133487 | 468 | py |
AMP | AMP-main/DeepSpeed/deepspeed/runtime/lr_schedules.py | """
Copyright 2019 The Microsoft DeepSpeed Team
Implementation of learning rate schedules.
Taken and modified from PyTorch v1.0.1 source
https://github.com/pytorch/pytorch/blob/v1.1.0/torch/optim/lr_scheduler.py
"""
import argparse
from torch.optim import Optimizer
from typing import Union, List
import math
from de... | 33,521 | 40.385185 | 164 | py |
AMP | AMP-main/DeepSpeed/deepspeed/runtime/engine.py | '''
Copyright 2019 The Microsoft DeepSpeed Team
'''
import os
import time
import torch
import warnings
import hashlib
import torch.distributed as dist
from torch.nn.modules import Module
from torch.distributed.distributed_c10d import _get_global_rank
from tensorboardX import SummaryWriter
from deepspeed.runtime.uti... | 72,641 | 41.505559 | 227 | py |
AMP | AMP-main/DeepSpeed/deepspeed/runtime/csr_tensor.py | """
Copyright 2020 The Microsoft DeepSpeed Team
Implementation of a compressed sparse row (CSR) tensor. Similar in
functionality to TensorFlow's IndexedSlices implementation.
"""
import torch
class CSRTensor(object):
""" Compressed Sparse Row (CSR) Tensor """
def __init__(self, dense_tensor=None):
s... | 1,999 | 32.333333 | 80 | py |
AMP | AMP-main/DeepSpeed/deepspeed/runtime/engine_back.py | '''
Copyright 2019 The Microsoft DeepSpeed Team
'''
import os
import torch
import warnings
import hashlib
import time
import numpy as np
import torch.distributed as dist
from torch.nn.modules import Module
from torch.distributed.distributed_c10d import _get_global_rank
from tensorboardX import SummaryWriter
from dee... | 72,496 | 41.371128 | 227 | py |
AMP | AMP-main/DeepSpeed/deepspeed/runtime/dataloader.py | '''
Copyright 2019 The Microsoft DeepSpeed Team
'''
import torch
from torch.utils.data import DataLoader, RandomSampler
from torch.utils.data.distributed import DistributedSampler
class RepeatingLoader:
def __init__(self, loader):
"""Wraps an iterator to allow for infinite iteration. This is especially u... | 3,623 | 33.188679 | 88 | py |
AMP | AMP-main/DeepSpeed/deepspeed/runtime/utils.py | '''
Copyright 2019 The Microsoft DeepSpeed Team
Copyright NVIDIA/Megatron
Helper functions and classes from multiple sources.
'''
import os
import psutil
from math import ceil
from math import floor
from bisect import bisect_left, bisect_right
import torch
import torch.distributed as dist
from torch._six import inf... | 20,489 | 33.846939 | 115 | py |
AMP | AMP-main/DeepSpeed/deepspeed/runtime/config.py | """
Copyright (c) Microsoft Corporation
Licensed under the MIT license.
"""
import torch
import json
import copy
from .constants import *
from .fp16.loss_scaler import INITIAL_LOSS_SCALE, SCALE_WINDOW, DELAYED_SHIFT, MIN_LOSS_SCALE
from .config_utils import get_scalar_param, dict_raise_error_on_duplicate_keys
from .z... | 32,096 | 39.373585 | 178 | py |
AMP | AMP-main/DeepSpeed/deepspeed/runtime/activation_checkpointing/checkpointing.py | '''
Copyright (c) Microsoft Corporation
Licensed under the MIT license.
Use to partition the activations stored for backward propagation
Therefore reduces the memory consumption
Also implements CPU checkpointing and contiguous memory checkpointing
Reduces memory consumption and memory fragmentation
Code for rng check... | 32,387 | 35.804545 | 185 | py |
AMP | AMP-main/DeepSpeed/deepspeed/runtime/fp16/fused_optimizer.py | '''
Copyright 2019 The Microsoft DeepSpeed Team
Copyright NVIDIA/apex
This file is adapted from FP16_Optimizer in NVIDIA/apex
'''
import torch
import math
from torch._utils import _flatten_dense_tensors, _unflatten_dense_tensors
from deepspeed.runtime.utils import get_grad_norm, CheckOverflow, get_weight_norm
from d... | 17,643 | 40.032558 | 126 | py |
AMP | AMP-main/DeepSpeed/deepspeed/runtime/fp16/loss_scaler.py | # Copyright 2019 The Microsoft DeepSpeed Team
# Copyright (c) 2019, 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/lic... | 9,018 | 39.626126 | 325 | py |
AMP | AMP-main/DeepSpeed/deepspeed/runtime/fp16/unfused_optimizer.py | '''
Copyright 2019 The Microsoft DeepSpeed Team
Copyright NVIDIA/apex
This file is adapted from FP16_Optimizer in NVIDIA/apex
'''
import torch
from torch._utils import _flatten_dense_tensors, _unflatten_dense_tensors
import math
from deepspeed.runtime.utils import get_grad_norm, CheckOverflow, get_weight_norm
from d... | 15,378 | 39.793103 | 126 | py |
AMP | AMP-main/DeepSpeed/deepspeed/runtime/fp16/onebit/adam.py | '''
Copyright 2020 The Microsoft DeepSpeed Team
'''
import types
import torch
import importlib
import numpy as np
import time
import torch.distributed as dist
from deepspeed.utils.logging import logger
class OnebitAdam(torch.optim.Optimizer):
"""Implements the 1-bit Adam algorithm. Currently GPU-only.
For us... | 14,912 | 47.106452 | 239 | py |
AMP | AMP-main/DeepSpeed/deepspeed/runtime/compression/cupy.py | '''
Copyright 2020 The Microsoft DeepSpeed Team
'''
import cupy
from torch.utils.dlpack import to_dlpack
from torch.utils.dlpack import from_dlpack
class CupyBackend(object):
def __init__(self):
pass
def torch2cupy(self, tensor):
return cupy.fromDlpack(to_dlpack(tensor))
def cupy2torch(... | 657 | 25.32 | 62 | py |
AMP | AMP-main/DeepSpeed/deepspeed/runtime/comm/nccl.py | '''
Copyright 2020 The Microsoft DeepSpeed Team
'''
import torch
import torch.distributed as dist
import time
import cupy
import numpy as np
from deepspeed.runtime.compression.cupy import CupyBackend
class NcclBackend(object):
def __init__(self):
self.world_group = dist.new_group(ranks=range(dist.get_wo... | 7,089 | 38.608939 | 107 | py |
AMP | AMP-main/DeepSpeed/deepspeed/runtime/comm/mpi.py | '''
Copyright 2020 The Microsoft DeepSpeed Team
'''
import torch
import cupy
import time
import numpy as np
from mpi4py import MPI
from deepspeed.runtime.compression.cupy import CupyBackend
class MpiBackend(object):
def __init__(self, cuda_aware):
self.comm = MPI.COMM_WORLD
self.rank = self.comm... | 11,838 | 39.683849 | 110 | py |
AMP | AMP-main/DeepSpeed/deepspeed/runtime/zero/test.py | import torch
from deepspeed.runtime.zero.contiguous_memory_allocator import ContiguousMemoryAllocator
def test1():
mem = ContiguousMemoryAllocator(1024, torch.half, 'cpu')
mem.print_allocation(resolution=100)
a1 = mem.allocate_tensor(64).mul_(0.0).add_(1.0)
mem.print_allocation(resolution=100)
mem... | 2,631 | 35.054795 | 97 | py |
AMP | AMP-main/DeepSpeed/deepspeed/runtime/zero/contiguous_memory_allocator.py | import torch
def print_rank_0(message):
if torch.distributed.get_rank() == 0:
print(message)
class ContiguousMemoryAllocator(object):
def __init__(self, size, dtype, device):
self.buffer = torch.zeros(size, dtype=dtype, device=device)
#address to contiguous size avaialble
se... | 10,906 | 37.40493 | 147 | py |
AMP | AMP-main/DeepSpeed/deepspeed/runtime/zero/partition_parameters.py | import os
import time
import types
from enum import Enum
import functools
import itertools
import torch
from torch.distributed.distributed_c10d import _get_global_rank
from deepspeed.runtime.zero.linear import LinearModuleForZeroStage3, LinearFunctionForZeroStage3
from deepspeed.runtime.utils import see_memory_usage
... | 38,459 | 40.002132 | 185 | py |
AMP | AMP-main/DeepSpeed/deepspeed/runtime/zero/stage1.py | import math
import torch
import torch.distributed as dist
from torch._utils import _flatten_dense_tensors, _unflatten_dense_tensors
from collections import defaultdict
from deepspeed.runtime.zero.utils import _initialize_parameter_parallel_groups
from deepspeed.runtime.fp16.loss_scaler import LossScaler, DynamicLossSc... | 52,581 | 45.864528 | 155 | py |
AMP | AMP-main/DeepSpeed/deepspeed/runtime/zero/stage3.py | from deepspeed.utils.logging import logger
'''
Copyright 2020 The Microsoft DeepSpeed Team
'''
import os
import torch
from torch._utils import _flatten_dense_tensors, _unflatten_dense_tensors
from torch.distributed.distributed_c10d import _get_global_rank
import torch.distributed as dist
import math
from torch._six i... | 120,468 | 41.299508 | 255 | py |
AMP | AMP-main/DeepSpeed/deepspeed/runtime/zero/utils.py | import torch
import torch.distributed as dist
from deepspeed.utils import logger
from deepspeed.ops.adam import DeepSpeedCPUAdam
from deepspeed.ops.adam import FusedAdam
def _initialize_parameter_parallel_groups(parameter_parallel_size=None):
data_parallel_size = int(dist.get_world_size())
parameter_parallel_... | 1,530 | 31.574468 | 104 | py |
AMP | AMP-main/DeepSpeed/deepspeed/runtime/zero/linear.py | #Linear Module to use with ZeRO Stage 3 to allow for parameter memory release
#after the module execution during forward
#Instead of saving variables using save_for_backward, we save variable ids
#Allowing us to retrive the variable without creating pointer to it
#Which allows for underlying tensor to be garbage collec... | 7,018 | 42.06135 | 162 | py |
AMP | AMP-main/DeepSpeed/deepspeed/runtime/zero/stage2.py | '''
Copyright 2019 The Microsoft DeepSpeed Team
'''
import torch
from torch._utils import _flatten_dense_tensors, _unflatten_dense_tensors
from torch.distributed.distributed_c10d import _get_global_rank
import torch.distributed as dist
import math
from torch._six import inf
from torch.autograd import Variable
import ... | 79,711 | 41.422565 | 185 | py |
AMP | AMP-main/DeepSpeed/deepspeed/runtime/pipe/engine.py | # Copyright 2019 The Microsoft DeepSpeed Team
import time
import logging
import copy
import os
import sys
from types import MethodType
from numpy import prod
import torch
import torch.nn as nn
import torch.optim as optim
import torch.distributed as dist
from deepspeed.utils.logging import logger
from deepspeed.uti... | 50,797 | 40.671862 | 133 | py |
AMP | AMP-main/DeepSpeed/deepspeed/runtime/pipe/p2p.py | '''
Copyright 2019 The Microsoft DeepSpeed Team
'''
import torch.distributed as dist
_groups = None
_grid = None
#initializes adjacent process groups
#run this only after torch.distributed.init_process_group() has been called
def init_process_groups(grid):
global _groups, _grid
_grid = grid
assert _gri... | 2,698 | 28.659341 | 85 | py |
AMP | AMP-main/DeepSpeed/deepspeed/runtime/pipe/topology.py | # Copyright 2019 The Microsoft DeepSpeed Team
from deepspeed.utils import logger
import torch.distributed as dist
import sys
from collections import namedtuple
from itertools import product as cartesian_product
class ProcessTopology:
""" Manages the mapping of n-dimensional Cartesian coordinates to linear
... | 17,297 | 36.768559 | 116 | py |
AMP | AMP-main/DeepSpeed/deepspeed/runtime/pipe/module.py | import os
import enum
import json
import time
import re as regex
from collections import defaultdict
from functools import partial
import torch
import torch.nn as nn
import torch.distributed as dist
import numpy as np
import torch.distributed as dist
from deepspeed.utils import logger
from .. import utils as ds_uti... | 27,350 | 40.949387 | 167 | py |
AMP | AMP-main/DeepSpeed/deepspeed/runtime/pipe/schedule.py | from ..utils import call_to_str
from abc import ABC, abstractmethod
class PipeSchedule(ABC):
"""Directs the execution of a pipeline engine by generating sequences of
:class:`PipeInstruction`.
Schedules are generators that yield sequences of
:class:`PipeInstruction` to process the micro-batches in on... | 15,250 | 30.575569 | 98 | py |
AMP | AMP-main/DeepSpeed/deepspeed/launcher/launch.py | # Copyright 2020 The Microsoft DeepSpeed Team
"""
DeepSpeed launcher, this is similar to torch.distributed.launch but supports
additional features such as abitrary gpu exclusion.
deepspeed.launcher.launch is intended to be run on a single worker node and
will spawn several worker sub-processes depending on how many de... | 7,555 | 35.502415 | 89 | py |
AMP | AMP-main/DeepSpeed/deepspeed/launcher/runner.py | # Copyright 2020 The Microsoft DeepSpeed Team
"""
DeepSpeed runner is the main front-end to launching multi-worker
training jobs with DeepSpeed. By default this uses pdsh to parallel
ssh into multiple worker nodes and launch all the neccisary processes
per rank for training.
"""
import os
import sys
import json
import... | 14,347 | 37.466488 | 99 | py |
AMP | AMP-main/DeepSpeed/deepspeed/launcher/launch_amp.py | # Copyright 2020 The Microsoft DeepSpeed Team
"""
DeepSpeed launcher, this is similar to torch.distributed.launch but supports
additional features such as abitrary gpu exclusion.
deepspeed.launcher.launch is intended to be run on a single worker node and
will spawn several worker sub-processes depending on how many de... | 6,842 | 36.190217 | 89 | py |
AMP | AMP-main/DeepSpeed/deepspeed/module_inject/inject.py | import copy
import torch
from deepspeed.ops.transformer import DeepSpeedTransformerLayer, DeepSpeedTransformerConfig
def module_inject(layer_obj,
model,
config,
micro_batch_size,
max_seq_length,
seed,
preln,
... | 4,578 | 36.227642 | 101 | py |
AMP | AMP-main/DeepSpeed/deepspeed/module_inject/replace_module.py | import copy
import torch
import deepspeed
def replace_transformer_layer(orig_layer_impl,
model,
micro_batch_size,
bert_config,
seed=-1,
preln=True,
... | 8,210 | 41.324742 | 107 | py |
AMP | AMP-main/DeepSpeed/deepspeed/utils/timer.py | '''
Copyright 2019 The Microsoft DeepSpeed Team
'''
import time
import torch
import numpy as np
from deepspeed.utils.logging import log_dist
from deepspeed.utils import logger
try:
import psutil
PSUTILS_INSTALLED = True
except ImportError:
PSUTILS_INSTALLED = False
pass
class SynchronizedWallClockT... | 6,410 | 34.032787 | 90 | py |
AMP | AMP-main/DeepSpeed/deepspeed/utils/logging.py | import logging
import sys
import torch.distributed as dist
class LoggerFactory:
@staticmethod
def create_logger(name=None, level=logging.INFO):
"""create a logger
Args:
name (str): name of the logger
level: level of logger
Raises:
ValueError is na... | 1,619 | 25.557377 | 74 | py |
AMP | AMP-main/DeepSpeed/deepspeed/utils/distributed.py | '''
Copyright 2020 The Microsoft DeepSpeed Team
'''
import os
import torch
from datetime import timedelta
from .logging import logger
from ..constants import TORCH_DISTRIBUTED_DEFAULT_PORT, default_pg_timeout
def init_distributed(dist_backend="nccl",
auto_mpi_discovery=True,
... | 5,905 | 40.300699 | 171 | py |
AMP | AMP-main/DeepSpeed/deepspeed/ops/module_inject.py | import copy
import torch
import deepspeed
from deepspeed.ops import DeepSpeedTransformerConfig
def _copy_child_transformer_state(new_module, orig_child, pre_layer_norm):
# copy relevant state from original child -> new module
qw = orig_child.attention.self.query.weight
qb = orig_child.attention.self.quer... | 9,314 | 41.926267 | 115 | py |
AMP | AMP-main/DeepSpeed/deepspeed/ops/sparse_attention/softmax.py | # DeepSpeed note, code taken & adapted from commit 9aa94789f13ada713af36cfd8cca2fc9a7f6b79a
# https://github.com/ptillet/torch-blocksparse/blob/master/torch_blocksparse/matmul.py
import warnings
import importlib
import torch
import math
from .trsrc import softmax_fwd, softmax_bwd
fwd_kernels = dict()
bwd_kernels = di... | 11,901 | 38.022951 | 154 | py |
AMP | AMP-main/DeepSpeed/deepspeed/ops/sparse_attention/sparse_attention_utils.py | """
Copyright 2020 The Microsoft DeepSpeed Team
"""
from torch import nn
from torch.nn import functional as F
from deepspeed.ops.sparse_attention import BertSparseSelfAttention, SparsityConfig
'''
This file contains few utility functions to handle adapting pretrained model with sparse self-attention module.
'''
clas... | 12,533 | 54.460177 | 335 | py |
AMP | AMP-main/DeepSpeed/deepspeed/ops/sparse_attention/sparsity_config.py | """
Copyright 2020 The Microsoft DeepSpeed Team
"""
import torch
import random
class SparsityConfig:
"""Abstract Configuration class to store `sparsity configuration of a self attention layer`.
It contains shared property of different block-sparse sparsity patterns. However, each class needs to extend it bas... | 37,461 | 55.418675 | 668 | py |
AMP | AMP-main/DeepSpeed/deepspeed/ops/sparse_attention/sparse_self_attention.py | """
Copyright 2020 The Microsoft DeepSpeed Team
"""
import torch.nn as nn
from torch.nn.functional import *
import torch
from torch import distributed as dist
from collections import namedtuple
from deepspeed.ops.sparse_attention import MatMul, Softmax, SparsityConfig
import sys
class SparseSelfAttention(nn.Module):... | 6,794 | 40.181818 | 163 | py |
AMP | AMP-main/DeepSpeed/deepspeed/ops/sparse_attention/matmul.py | # DeepSpeed note, code taken & adapted from commit 9aa94789f13ada713af36cfd8cca2fc9a7f6b79a
# https://github.com/ptillet/torch-blocksparse/blob/master/torch_blocksparse/matmul.py
import importlib
import warnings
import torch
import math
from .trsrc import matmul
from ..op_builder import SparseAttnBuilder
triton = None... | 29,367 | 38.105193 | 160 | py |
AMP | AMP-main/DeepSpeed/deepspeed/ops/sparse_attention/bert_sparse_self_attention.py | """
Copyright 2020 The Microsoft DeepSpeed Team
"""
from torch import nn
from deepspeed.ops.sparse_attention import SparseSelfAttention, FixedSparsityConfig
class BertSparseSelfAttention(nn.Module):
"""Implements Sparse Self Attention layer of Bert model based on https://github.com/microsoft/DeepSpeedExamples/bl... | 3,492 | 43.21519 | 166 | py |
AMP | AMP-main/DeepSpeed/deepspeed/ops/op_builder/stochastic_transformer.py | """
Copyright 2020 The Microsoft DeepSpeed Team
"""
import torch
from .transformer import TransformerBuilder
class StochasticTransformerBuilder(TransformerBuilder):
BUILD_VAR = "DS_BUILD_STOCHASTIC_TRANSFORMER"
NAME = "stochastic_transformer"
def __init__(self):
super().__init__(name=self.NAME)
... | 534 | 23.318182 | 58 | py |
AMP | AMP-main/DeepSpeed/deepspeed/ops/op_builder/cpu_adam.py | """
Copyright 2020 The Microsoft DeepSpeed Team
"""
import os
import torch
import subprocess
from .builder import CUDAOpBuilder
class CPUAdamBuilder(CUDAOpBuilder):
BUILD_VAR = "DS_BUILD_CPU_ADAM"
NAME = "cpu_adam"
def __init__(self):
super().__init__(name=self.NAME)
def absolute_name(self):... | 2,074 | 27.819444 | 84 | py |
AMP | AMP-main/DeepSpeed/deepspeed/ops/op_builder/transformer.py | """
Copyright 2020 The Microsoft DeepSpeed Team
"""
import torch
from .builder import CUDAOpBuilder
class TransformerBuilder(CUDAOpBuilder):
BUILD_VAR = "DS_BUILD_TRANSFORMER"
NAME = "transformer"
def __init__(self, name=None):
name = self.NAME if name is None else name
super().__init__(n... | 1,347 | 27.083333 | 58 | py |
AMP | AMP-main/DeepSpeed/deepspeed/ops/op_builder/fused_lamb.py | """
Copyright 2020 The Microsoft DeepSpeed Team
"""
import torch
from .builder import CUDAOpBuilder
class FusedLambBuilder(CUDAOpBuilder):
BUILD_VAR = 'DS_BUILD_FUSED_LAMB'
NAME = "fused_lamb"
def __init__(self):
super().__init__(name=self.NAME)
def absolute_name(self):
return f'deep... | 805 | 24.1875 | 87 | py |
AMP | AMP-main/DeepSpeed/deepspeed/ops/op_builder/fused_adam.py | """
Copyright 2020 The Microsoft DeepSpeed Team
"""
import torch
from .builder import CUDAOpBuilder
class FusedAdamBuilder(CUDAOpBuilder):
BUILD_VAR = "DS_BUILD_FUSED_ADAM"
NAME = "fused_adam"
def __init__(self):
super().__init__(name=self.NAME)
def absolute_name(self):
return f'deep... | 804 | 24.15625 | 86 | py |
AMP | AMP-main/DeepSpeed/deepspeed/ops/op_builder/builder.py | """
Copyright 2020 The Microsoft DeepSpeed Team
"""
import os
import time
import torch
import importlib
from pathlib import Path
import subprocess
from abc import ABC, abstractmethod
YELLOW = '\033[93m'
END = '\033[0m'
WARNING = f"{YELLOW} [WARNING] {END}"
DEFAULT_TORCH_EXTENSION_PATH = "/tmp/torch_extensions"
DEFAUL... | 13,065 | 37.316716 | 147 | py |
AMP | AMP-main/DeepSpeed/deepspeed/ops/op_builder/sparse_attn.py | """
Copyright 2020 The Microsoft DeepSpeed Team
"""
import torch
import warnings
from .builder import OpBuilder
class SparseAttnBuilder(OpBuilder):
BUILD_VAR = "DS_BUILD_SPARSE_ATTN"
NAME = "sparse_attn"
def __init__(self):
super().__init__(name=self.NAME)
def absolute_name(self):
re... | 1,811 | 33.188679 | 104 | py |
AMP | AMP-main/DeepSpeed/deepspeed/ops/adam/cpu_adam.py | '''
Copyright 2020 The Microsoft DeepSpeed Team
'''
import math
import torch
import time
from pathlib import Path
from ..op_builder import CPUAdamBuilder
class DeepSpeedCPUAdam(torch.optim.Optimizer):
optimizer_id = 0
def __init__(self,
model_params,
lr=1e-3,
... | 7,563 | 42.976744 | 113 | py |
AMP | AMP-main/DeepSpeed/deepspeed/ops/adam/fused_adam.py | '''
Copyright 2020 The Microsoft DeepSpeed Team
Copyright NVIDIA/apex
This file is adapted from fused adam in NVIDIA/apex, commit a109f85
'''
import torch
import importlib
from .multi_tensor_apply import MultiTensorApply
multi_tensor_applier = MultiTensorApply(2048 * 32)
from ..op_builder import FusedAdamBuilder
cl... | 7,445 | 39.688525 | 145 | py |
AMP | AMP-main/DeepSpeed/deepspeed/ops/adam/multi_tensor_apply.py | '''
Copyright 2020 The Microsoft DeepSpeed Team
Copyright NVIDIA/apex
This file is adapted from NVIDIA/apex, commit a109f85
'''
import torch
class MultiTensorApply(object):
def __init__(self, chunk_size):
self.chunk_size = chunk_size
def __call__(self, op, noop_flag_buffer, tensor_lists, *args):
... | 391 | 23.5 | 73 | py |
AMP | AMP-main/DeepSpeed/deepspeed/ops/transformer/transformer.py | '''
Copyright 2020 The Microsoft DeepSpeed Team
'''
import json
import math
import importlib
import torch
from torch import nn
from torch.autograd import Function
from ..op_builder import TransformerBuilder, StochasticTransformerBuilder
# Cuda modules will be imported if needed
transformer_cuda_module = None
stochast... | 25,457 | 40.395122 | 136 | py |
AMP | AMP-main/DeepSpeed/deepspeed/ops/lamb/fused_lamb.py | '''
Copyright 2019 The Microsoft DeepSpeed Team
Copyright NVIDIA/apex
This file is adapted from NVIDIA/apex/optimizer/fused_adam and implements the LAMB optimizer
'''
import types
import torch
from ..op_builder import FusedLambBuilder
class FusedLamb(torch.optim.Optimizer):
"""Implements the LAMB algorithm. Curr... | 8,469 | 43.578947 | 151 | py |
AMP | AMP-main/DeepSpeed/op_builder/stochastic_transformer.py | """
Copyright 2020 The Microsoft DeepSpeed Team
"""
import torch
from .transformer import TransformerBuilder
class StochasticTransformerBuilder(TransformerBuilder):
BUILD_VAR = "DS_BUILD_STOCHASTIC_TRANSFORMER"
NAME = "stochastic_transformer"
def __init__(self):
super().__init__(name=self.NAME)
... | 534 | 23.318182 | 58 | py |
AMP | AMP-main/DeepSpeed/op_builder/cpu_adam.py | """
Copyright 2020 The Microsoft DeepSpeed Team
"""
import os
import torch
import subprocess
from .builder import CUDAOpBuilder
class CPUAdamBuilder(CUDAOpBuilder):
BUILD_VAR = "DS_BUILD_CPU_ADAM"
NAME = "cpu_adam"
def __init__(self):
super().__init__(name=self.NAME)
def absolute_name(self):... | 2,074 | 27.819444 | 84 | py |
AMP | AMP-main/DeepSpeed/op_builder/transformer.py | """
Copyright 2020 The Microsoft DeepSpeed Team
"""
import torch
from .builder import CUDAOpBuilder
class TransformerBuilder(CUDAOpBuilder):
BUILD_VAR = "DS_BUILD_TRANSFORMER"
NAME = "transformer"
def __init__(self, name=None):
name = self.NAME if name is None else name
super().__init__(n... | 1,347 | 27.083333 | 58 | py |
AMP | AMP-main/DeepSpeed/op_builder/fused_lamb.py | """
Copyright 2020 The Microsoft DeepSpeed Team
"""
import torch
from .builder import CUDAOpBuilder
class FusedLambBuilder(CUDAOpBuilder):
BUILD_VAR = 'DS_BUILD_FUSED_LAMB'
NAME = "fused_lamb"
def __init__(self):
super().__init__(name=self.NAME)
def absolute_name(self):
return f'deep... | 805 | 24.1875 | 87 | py |
AMP | AMP-main/DeepSpeed/op_builder/fused_adam.py | """
Copyright 2020 The Microsoft DeepSpeed Team
"""
import torch
from .builder import CUDAOpBuilder
class FusedAdamBuilder(CUDAOpBuilder):
BUILD_VAR = "DS_BUILD_FUSED_ADAM"
NAME = "fused_adam"
def __init__(self):
super().__init__(name=self.NAME)
def absolute_name(self):
return f'deep... | 804 | 24.15625 | 86 | py |
AMP | AMP-main/DeepSpeed/op_builder/builder.py | """
Copyright 2020 The Microsoft DeepSpeed Team
"""
import os
import time
import torch
import importlib
from pathlib import Path
import subprocess
from abc import ABC, abstractmethod
YELLOW = '\033[93m'
END = '\033[0m'
WARNING = f"{YELLOW} [WARNING] {END}"
DEFAULT_TORCH_EXTENSION_PATH = "/tmp/torch_extensions"
DEFAUL... | 13,065 | 37.316716 | 147 | py |
AMP | AMP-main/DeepSpeed/op_builder/sparse_attn.py | """
Copyright 2020 The Microsoft DeepSpeed Team
"""
import torch
import warnings
from .builder import OpBuilder
class SparseAttnBuilder(OpBuilder):
BUILD_VAR = "DS_BUILD_SPARSE_ATTN"
NAME = "sparse_attn"
def __init__(self):
super().__init__(name=self.NAME)
def absolute_name(self):
re... | 1,811 | 33.188679 | 104 | py |
AMP | AMP-main/DeepSpeed/tests/unit/test_topology.py | import pytest
import torch
import torch.distributed as dist
from deepspeed.runtime.pipe.topology import PipelineParallelGrid as Grid
from deepspeed.runtime.pipe.topology import ProcessTopology as Topo
from deepspeed.runtime.pipe.topology import _prime_factors
from common import distributed_test
def test_topology_2... | 7,960 | 34.699552 | 87 | py |
AMP | AMP-main/DeepSpeed/tests/unit/test_dist.py | import torch
import torch.distributed as dist
from common import distributed_test
import pytest
@distributed_test(world_size=3)
def test_init():
assert dist.is_initialized()
assert dist.get_world_size() == 3
assert dist.get_rank() < 3
# Demonstration of pytest's paramaterization
@pytest.mark.parametri... | 1,140 | 28.25641 | 89 | py |
AMP | AMP-main/DeepSpeed/tests/unit/test_sparse_attention.py | # DeepSpeed note, some parts of code taken & adapted from commit c368a9fd1b2c9dee4cc94de9a6bb0be3d447be41
# https://github.com/ptillet/torch-blocksparse/blob/master/tests/test_softmax.py
# https://github.com/ptillet/torch-blocksparse/blob/master/tests/test_matmul.py
# https://github.com/ptillet/torch-blocksparse/blob/m... | 12,236 | 33.962857 | 129 | py |
AMP | AMP-main/DeepSpeed/tests/unit/test_cpu_adam.py | import argparse
import torch
import time
import numpy as np
import pytest
import copy
import deepspeed
from deepspeed.ops.adam import FusedAdam
from deepspeed.ops.op_builder import CPUAdamBuilder
if not deepspeed.ops.__compatible_ops__[CPUAdamBuilder.NAME]:
pytest.skip("cpu-adam is not compatible")
def check_eq... | 2,090 | 32.190476 | 81 | py |
AMP | AMP-main/DeepSpeed/tests/unit/test_flops_profiler.py | import torch
import deepspeed
import deepspeed.runtime.utils as ds_utils
from deepspeed.profiling.flops_profiler import FlopsProfiler, get_model_profile
from simple_model import SimpleModel, SimpleOptimizer, random_dataloader, args_from_dict
from common import distributed_test
def test_flops_profiler_in_ds_trainning(... | 3,724 | 31.112069 | 88 | py |
AMP | AMP-main/DeepSpeed/tests/unit/test_cuda_forward.py | import argparse
import numpy as np
import torch
import torch.nn.functional as F
import pytest
import json
import random
import time
import copy
from torch import nn
from modelingpreln import BertEncoder as BertEncoderPreln
from modeling import BertEncoder as BertEncoderPostln
from modeling import BertLayerNorm, BertCon... | 12,907 | 38.234043 | 110 | py |
AMP | AMP-main/DeepSpeed/tests/unit/test_config.py | # A test on its own
import torch
import pytest
import json
import argparse
from common import distributed_test
from simple_model import SimpleModel, create_config_from_dict, random_dataloader
import torch.distributed as dist
# A test on its own
import deepspeed
from deepspeed.runtime.config import DeepSpeedConfig
de... | 10,326 | 32.420712 | 96 | py |
AMP | AMP-main/DeepSpeed/tests/unit/modeling.py | # DeepSpeed note, code taken from commit 3d59216cec89a363649b4fe3d15295ba936ced0f
# https://github.com/NVIDIA/DeepLearningExamples/blob/master/PyTorch/LanguageModeling/BERT/modeling.py
# coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HugginFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORA... | 72,000 | 44.599113 | 141 | py |
AMP | AMP-main/DeepSpeed/tests/unit/test_lr_schedulers.py | import torch
import deepspeed
import argparse
import pytest
import json
import os
from common import distributed_test
from simple_model import SimpleModel, SimpleOptimizer, random_dataloader, args_from_dict
from deepspeed.runtime.lr_schedules import LR_RANGE_TEST, LR_RANGE_TEST_MIN_LR, LR_RANGE_TEST_STEP_RATE, LR_RANGE... | 19,416 | 35.774621 | 153 | py |
AMP | AMP-main/DeepSpeed/tests/unit/test_csr.py | import torch
import random
from deepspeed.runtime.csr_tensor import CSRTensor
def test_csr_addition_self():
row_count = 10
random.seed(1234)
x = torch.ones(1, 5)
for i in range(row_count - 1):
if random.random() > 0.75:
x = torch.cat([x, torch.ones(1, 5)])
else:
... | 1,215 | 22.843137 | 56 | py |
AMP | AMP-main/DeepSpeed/tests/unit/test_pipe_module.py | import copy
import torch
import torch.nn as nn
import torch.distributed as dist
import pytest
import deepspeed
from deepspeed.runtime.pipe.topology import PipeDataParallelTopology, PipeModelDataParallelTopology
PipeTopo = PipeDataParallelTopology
from deepspeed.pipe import PipelineModule, LayerSpec
from deepspeed.... | 2,887 | 27.313725 | 99 | py |
AMP | AMP-main/DeepSpeed/tests/unit/test_zero.py | import torch
import pytest
import json
import argparse
import os
from common import distributed_test
from simple_model import SimpleModel, random_dataloader, args_from_dict
import deepspeed
def run_unbalanced_gradients(model, data_loader):
def drop_some_gradients(model, iter):
odd_iteration = iter % 2
... | 2,068 | 28.557143 | 82 | py |
AMP | AMP-main/DeepSpeed/tests/unit/test_dynamic_loss_scale.py | import torch
import deepspeed
import argparse
import pytest
import json
import os
import numpy as np
from common import distributed_test
from simple_model import SimpleModel, args_from_dict
def run_model_step(model, gradient_list):
for value in gradient_list:
for p in model.parameters():
p.gra... | 10,949 | 33.651899 | 87 | py |
AMP | AMP-main/DeepSpeed/tests/unit/test_checkpointing.py | import torch
import torch.distributed as dist
import deepspeed
from deepspeed.runtime.zero.stage2 import FP16_DeepSpeedZeroOptimizer
from deepspeed.runtime.zero.stage1 import FP16_DeepSpeedZeroOptimizer_Stage1
from deepspeed.runtime.fp16.fused_optimizer import FP16_Optimizer
from deepspeed.runtime.fp16.unfused_optim... | 33,676 | 36.627933 | 161 | py |
AMP | AMP-main/DeepSpeed/tests/unit/test_activation_checkpointing.py | # TODO: add tests with model parallelism for activation partitioning and other features.
from copy import deepcopy
import pytest
import torch
import deepspeed
ckpt = deepspeed.checkpointing.checkpoint
from common import distributed_test
def _compute(module, *inputs, do_checkpoint=False):
if do_checkpoint:
... | 8,225 | 27.365517 | 89 | py |
AMP | AMP-main/DeepSpeed/tests/unit/simple_model.py | import os
import json
import argparse
import torch
from deepspeed.pipe import PipelineModule, LayerSpec
class SimpleModel(torch.nn.Module):
def __init__(self, hidden_dim, empty_grad=False):
super(SimpleModel, self).__init__()
self.linear = torch.nn.Linear(hidden_dim, hidden_dim)
if empty_... | 6,068 | 32.905028 | 86 | py |
AMP | AMP-main/DeepSpeed/tests/unit/common.py | import os
import time
import torch
import torch.distributed as dist
from torch.multiprocessing import Process
import deepspeed
import pytest
# Worker timeout *after* the first worker has completed.
DEEPSPEED_UNIT_WORKER_TIMEOUT = 120
def distributed_test(world_size=2, backend='nccl'):
"""A decorator for execu... | 3,991 | 37.019048 | 88 | py |
AMP | AMP-main/DeepSpeed/tests/unit/test_multi_output_model.py | import torch
import deepspeed
import argparse
import pytest
from pytest import approx
import json
import os
from common import distributed_test
from simple_model import args_from_dict
from multi_output_model import MultiOutputModel, multi_output_dataloader
def create_config_dict(micro_batch_size, grad_accumulation_st... | 5,594 | 38.964286 | 103 | py |
AMP | AMP-main/DeepSpeed/tests/unit/test_zero_context.py | import os
import torch
import pytest
import deepspeed
from deepspeed.runtime.zero.partition_parameters import ZeroParamStatus
from common import distributed_test
def setup_serial_env():
# Setup for a serial run
os.environ['MASTER_ADDR'] = '127.0.0.1'
os.environ['MASTER_PORT'] = '29503'
os.environ['L... | 4,018 | 31.152 | 84 | py |
AMP | AMP-main/DeepSpeed/tests/unit/modelingpreln.py | # DeepSpeed note, code taken from commit 3d59216cec89a363649b4fe3d15295ba936ced0f
# https://github.com/NVIDIA/DeepLearningExamples/blob/master/PyTorch/LanguageModeling/BERT/modeling.py
# coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HugginFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORA... | 76,440 | 44.66368 | 141 | py |
AMP | AMP-main/DeepSpeed/tests/unit/test_onebit.py | import torch
import torch.distributed as dist
import deepspeed
import argparse
import pytest
import json
import os
import numpy as np
import time
from common import distributed_test
from simple_model import SimpleModel, SimpleOptimizer, random_dataloader, args_from_dict, create_deepspeed_args
TORCH_MAJOR = int(torch._... | 15,640 | 41.387534 | 162 | py |
AMP | AMP-main/DeepSpeed/tests/unit/test_partition.py | import pytest
import torch
import torch.distributed as dist
from deepspeed.runtime.utils import partition_uniform
from deepspeed.runtime.utils import partition_balanced
from deepspeed.runtime.utils import prefix_sum_inc
from deepspeed.runtime.utils import PartitionedTensor
from common import distributed_test
@dist... | 4,620 | 23.193717 | 91 | py |
AMP | AMP-main/DeepSpeed/tests/unit/test_cuda_backward.py | import argparse
import numpy as np
import torch
import torch.nn.functional as F
import pytest
import json
import random
import time
import copy
from torch import nn
from modelingpreln import BertEncoder as BertEncoderPreln
from modeling import BertEncoder as BertEncoderPostln
from modeling import BertConfig, BertLayerN... | 12,173 | 35.558559 | 106 | py |
AMP | AMP-main/DeepSpeed/tests/unit/multi_output_model.py | import os
import json
import argparse
import torch
class MultiOutputModel(torch.nn.Module):
def __init__(self, hidden_dim, weight_value):
super(MultiOutputModel, self).__init__()
self.linear = torch.nn.Linear(hidden_dim, hidden_dim, bias=False)
self.linear.weight.data.fill_(weight_value)
... | 1,440 | 31.022222 | 87 | py |
AMP | AMP-main/DeepSpeed/tests/unit/test_adamw.py | import deepspeed
import torch
import pytest
from common import distributed_test
from deepspeed.ops.adam import FusedAdam
from deepspeed.ops.adam import DeepSpeedCPUAdam
from simple_model import SimpleModel, args_from_dict
# yapf: disable
#'optimizer, zero_offload, torch_adam, adam_w_mode, resulting_optimizer
adam_con... | 2,962 | 39.040541 | 82 | py |
AMP | AMP-main/DeepSpeed/tests/unit/test_pipe.py | import os
import copy
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.distributed as dist
import pytest
import deepspeed
import deepspeed.runtime.utils as ds_utils
from deepspeed.runtime.pipe.topology import PipeDataParallelTopology, PipeModelDataParallelTopology
PipeTopo = PipeData... | 8,798 | 31.83209 | 129 | py |
AMP | AMP-main/DeepSpeed/tests/unit/test_fp16.py | import torch
import deepspeed
import argparse
import pytest
import json
import os
from deepspeed.ops.adam import FusedAdam
from common import distributed_test
from simple_model import SimpleModel, SimpleOptimizer, random_dataloader, args_from_dict, create_deepspeed_args
from deepspeed.ops.op_builder import CPUAdamBuild... | 29,434 | 32.91129 | 111 | py |
AMP | AMP-main/DeepSpeed/tests/perf/adam_test1.py | import torch
from deepspeed.ops.adam import DeepSpeedCPUAdam
import time
device = 'cpu'
model_size = 1 * 1024**3
param = torch.nn.Parameter(torch.ones(model_size, device=device))
param_fp16 = torch.nn.Parameter(torch.ones(model_size,
dtype=torch.half,
... | 724 | 30.521739 | 65 | py |
AMP | AMP-main/DeepSpeed/tests/perf/adam_test.py | import torch
from deepspeed.ops.adam import DeepSpeedCPUAdam
import time
device = 'cpu'
model_size = 1 * 1024**3
group_size = [model_size, 274432]
param = [torch.nn.Parameter(torch.ones(size, device=device)) for size in group_size]
optimizer = DeepSpeedCPUAdam(param)
#torch.set_num_threads(128)
for i, p in enumerate(... | 750 | 29.04 | 84 | py |
AMP | AMP-main/DeepSpeed/tests/small_model_debugging/test.py | import torch
from deepspeed.pt.deepspeed_linear import LinearModuleForZeroStage3
from deepspeed.pt.deepspeed_utils import see_memory_usage
from deepspeed.pt.log_utils import logger
import deepspeed
def see_memory_usage(message):
# Print message except when distributed but not rank 0
logger.info(message)
... | 1,379 | 27.163265 | 93 | py |
AMP | AMP-main/DeepSpeed/tests/small_model_debugging/test_model.py | import os
import json
import argparse
import torch
import deepspeed
from torch.utils.data.distributed import DistributedSampler
class SimpleModel(torch.nn.Module):
def __init__(self, hidden_dim, empty_grad=False):
super(SimpleModel, self).__init__()
self.linear = torch.nn.Linear(hidden_dim, hidden... | 3,641 | 30.396552 | 89 | py |
AMP | AMP-main/DeepSpeed/tests/small_model_debugging/stage3_test.py | import torch
import deepspeed
###################################
# Setup
###################################
class VerboseLinear(torch.nn.Linear):
def __init__(self, **kwargs):
print(f'Begin VerboseLinear.__init__')
super().__init__(**kwargs)
print(f'End VerboseLinear.__init__')
class... | 2,425 | 26.885057 | 89 | py |
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