python_code stringlengths 0 187k | repo_name stringlengths 8 46 | file_path stringlengths 6 135 |
|---|---|---|
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Core code for sequence length warmup."""
import logging
import textwrap
from typing import Dict, Mapping, Optional
import torch
import torch.utils.data
from composer.core import Algorithm, Batch, Event, State, TimeUnit, get_precisio... | composer-dev | composer/algorithms/seq_length_warmup/seq_length_warmup.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Sequence length warmup progressively increases the sequence length during training of NLP models.
See the :doc:`Method Card </method_cards/seq_length_warmup>` for more details.
"""
from composer.algorithms.seq_length_warmup.seq_lengt... | composer-dev | composer/algorithms/seq_length_warmup/__init__.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import logging
from typing import Optional, Sequence, Union
import torch
from torch.optim import Optimizer
from composer.core import Algorithm, Event, State
from composer.loggers import Logger
from co... | composer-dev | composer/algorithms/squeeze_excite/squeeze_excite.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Adds Squeeze-and-Excitation blocks (`Hu et al, 2019 <https://arxiv.org/abs/1709.01507>`_) after the
:class:`~torch.nn.Conv2d` modules in a neural network.
See :class:`~composer.algorithms.SqueezeExcite` or the :doc:`Method Card </meth... | composer-dev | composer/algorithms/squeeze_excite/__init__.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Replaces all instances of :class:`torch.nn.LayerNorm` with a low precision :class:`torch.nn.LayerNorm` (either float16 or bfloat16).
By default, torch.autocast always runs torch.nn.LayerNorm in float32, so this surgery forces a lower p... | composer-dev | composer/algorithms/low_precision_layernorm/__init__.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Low Precision LayerNorm."""
from __future__ import annotations
import logging
import warnings
from typing import Dict, Optional, Sequence, Type, Union
import torch
import torch.nn.functional as F
from packaging import version
from t... | composer-dev | composer/algorithms/low_precision_layernorm/low_precision_layernorm.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Replaces all instances of `torch.nn.Dropout` with a `GyroDropout`.
By masking Dropout layer, this usually improves accuracy.
"""
from composer.algorithms.gyro_dropout.gyro_dropout import GyroDropout, GyroDropoutLayer, apply_gyro_drop... | composer-dev | composer/algorithms/gyro_dropout/__init__.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
# Written by Gihyun Park, Junyeol Lee, and Jiwon Seo
import logging
import warnings
from typing import Dict, Optional, Type
import numpy as np
import torch
from composer.algorithms.warnings import NoEffectWarning
from composer.core imp... | composer-dev | composer/algorithms/gyro_dropout/gyro_dropout.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Replaces the Linear layers in the feed-forward network with `Gated Linear Units <https://arxiv.org/abs/2002.05202>`_.
This leads to improved convergence with a slight drop in throughput. Using no bias terms in the GLU is highly recomm... | composer-dev | composer/algorithms/gated_linear_units/__init__.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
from typing import Callable
import torch
class BERTGatedFFOutput(torch.nn.Module):
"""
Defines a single feed-forward block that uses `Gated Linear Units <https://arxiv.org/abs/2002.05202>`_.
Args:
d_embed (int): Th... | composer-dev | composer/algorithms/gated_linear_units/gated_linear_unit_layers.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
# Copyright 2022 MosaicML. All Rights Reserved.
from __future__ import annotations
import logging
import warnings
from typing import Callable, Dict, Optional, Sequence, Type, Union
import torch
from composer.models.huggingface import ... | composer-dev | composer/algorithms/gated_linear_units/gated_linear_units.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Core code for Stochastic Weight Averaging."""
from __future__ import annotations
import logging
import warnings
from typing import Any, Dict, List, Optional
import torch
from torch.optim.swa_utils import SWALR, AveragedModel
from c... | composer-dev | composer/algorithms/swa/swa.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Stochastic Weight Averaging (SWA; `Izmailov et al, 2018 <https://arxiv.org/abs/1803.05407>`_) averages model weights
sampled at different times near the end of training.
This leads to better generalization than just using the final tr... | composer-dev | composer/algorithms/swa/__init__.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Core AugMix classes and functions."""
import functools
import textwrap
import weakref
from typing import List, TypeVar
import numpy as np
import torch
import torch.utils.data
from PIL import Image
from PIL.Image import Image as Pillo... | composer-dev | composer/algorithms/augmix/augmix.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""AugMix (`Hendrycks et al, 2020 <http://arxiv.org/abs/1912.02781>`_) creates multiple independent realizations of
sequences of image augmentations, applies each sequence with random intensity, and returns a convex combination of the
aug... | composer-dev | composer/algorithms/augmix/__init__.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
# type: ignore
from typing import Optional
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.common_types import _size_2_t
from torch.nn.modules.utils import _pair
def _default_2d_filte... | composer-dev | composer/algorithms/blurpool/blurpool_layers.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""`BlurPool <http://proceedings.mlr.press/v97/zhang19a.html>`_ adds anti-aliasing filters to convolutional layers to
increase accuracy and invariance to small shifts in the input.
See :class:`~composer.algorithms.BlurPool` or the :doc:`... | composer-dev | composer/algorithms/blurpool/__init__.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import functools
import logging
import warnings
from typing import Optional, Sequence, Union
import numpy as np
import torch
from torch.optim import Optimizer
from composer.algorithms.blurpool.blurpoo... | composer-dev | composer/algorithms/blurpool/blurpool.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Core ColOut classes and functions."""
from __future__ import annotations
import logging
import textwrap
import weakref
from typing import Any, Callable, Tuple, TypeVar, Union
import torch
import torch.utils.data
from PIL.Image impor... | composer-dev | composer/algorithms/colout/colout.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Drops a fraction of the rows and columns of an input image. If the fraction of rows/columns dropped isn't too large,
this does not significantly alter the content of the image, but reduces its size and provides extra variability.
See ... | composer-dev | composer/algorithms/colout/__init__.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Optimizers and learning rate schedulers.
Composer is compatible with optimizers based off of PyTorch's native :class:`~torch.optim.Optimizer` API, and common
optimizers such
However, where applicable, it is recommended to use the opti... | composer-dev | composer/optim/__init__.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Optimizers with weight decay decoupled from the learning rate.
These optimizers are based off of `Decoupled Weight Decay Regularization <https://arxiv.org/abs/1711.05101>`_, which
proposes this decoupling. In general, it is recommende... | composer-dev | composer/optim/decoupled_weight_decay.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Stateless learning rate schedulers.
Stateless schedulers solve some of the problems associated with PyTorch's built-in schedulers provided in
:mod:`torch.optim.lr_scheduler`. The primary design goal of the schedulers provided in this ... | composer-dev | composer/optim/scheduler.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Retry helper."""
from __future__ import annotations
import collections.abc
import functools
import random
import time
from typing import Any, Callable, Sequence, Type, TypeVar, Union, cast, overload
TCallable = TypeVar('TCallable', ... | composer-dev | composer/utils/retrying.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Miscellaneous Helpers."""
import socket
from contextlib import contextmanager
from typing import Type
import torch
from packaging import version
from torch.nn.parallel import DistributedDataParallel
__all__ = [
'is_model_deepspe... | composer-dev | composer/utils/misc.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
# To keep the typing organized for this file, see iter_helpers.pyi
# All typing annotations are in there
# All methods signatures must be defined in there.
"""Utilities for iterating over collections."""
import collections.abc
import io
... | composer-dev | composer/utils/iter_helpers.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Dynamically import a Python object (e.g. module, class, function, ...)."""
import importlib
from typing import Any, Optional
__all__ = ['MissingConditionalImportError', 'import_object']
class MissingConditionalImportError(ImportErr... | composer-dev | composer/utils/import_helpers.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Utilities for working with training checkpoints."""
from __future__ import annotations
import contextlib
import fnmatch
import logging
import os
import shutil
import tarfile
import tempfile
import textwrap
import warnings
from pathli... | composer-dev | composer/utils/checkpoint.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Device-related helper methods and utilities."""
from typing import TYPE_CHECKING, Optional, Union
import torch.cuda
if TYPE_CHECKING:
from composer.devices import Device
__all__ = ['get_device', 'is_tpu_installed']
def get_de... | composer-dev | composer/utils/device.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Helpers to get items and set items in a batch."""
from operator import attrgetter, itemgetter
from typing import Any, Callable, Sequence, Union, cast
__all__ = ['batch_get', 'batch_set']
def batch_get(batch: Any, key: Union[str, in... | composer-dev | composer/utils/batch_helpers.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Helpers to gather system information for debugging and bug reporting.
Leverages PyTorch's :mod:`torch.utils.collect_env` package to gather pertinent system information.
The following information is additionally collected to faciliate ... | composer-dev | composer/utils/collect_env.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Helper utilities for configuring deterministic training to ensure reproducibility.
.. note::
For deterministic model initialization, :func:`~.seed_all` and/or
:func:`~.configure_deterministic_mode` should be
invoked befor... | composer-dev | composer/utils/reproducibility.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Helper utilities."""
from composer.utils.auto_log_hparams import (convert_flat_dict_to_nested_dict, convert_nested_dict_to_flat_dict,
extract_hparams)
from composer.utils.batch_helpers impo... | composer-dev | composer/utils/__init__.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Contains helper functions for auto-logging hparams."""
from typing import Any, Dict, List, Tuple
__all__ = ['extract_hparams', 'convert_nested_dict_to_flat_dict', 'convert_flat_dict_to_nested_dict']
def extract_hparams(locals_dict:... | composer-dev | composer/utils/auto_log_hparams.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""FX-based model transformation and optimization.
Provides utilities to do FX-based model transformations.
"""
import logging
import operator
import re
from typing import Any, Callable, Dict, List, Mapping, Optional, Tuple, Union
impo... | composer-dev | composer/utils/fx_utils.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Inference-related utility functions for model export and optimizations.
Used for exporting models into various formats such ONNX, torchscript etc. and apply optimizations such as fusion.
"""
from __future__ import annotations
import ... | composer-dev | composer/utils/inference.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Base class for Enums containing string values."""
from __future__ import annotations
import textwrap
import warnings
from enum import Enum
class StringEnum(Enum):
"""Base class for Enums containing string values.
This class... | composer-dev | composer/utils/string_enum.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Modify model architectures.
Algorithms, such as :class:`~composer.algorithms.blurpool.BlurPool`, replace model parameters in-place.
This module contains helper functions to replace parameters in :class:`~torch.nn.Module` and
:class:`~... | composer-dev | composer/utils/module_surgery.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Helper methods for :mod:`torch.distributed`.
To use :mod:`torch.distributed`, launch your training script with the
:ref:`composer launcher for distributed training <distributed-training>`. For example,
the following command launches a... | composer-dev | composer/utils/dist.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Helpers for working with files."""
from __future__ import annotations
import logging
import os
import pathlib
import re
import tempfile
import uuid
import warnings
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, U... | composer-dev | composer/utils/file_helpers.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""OCI-Compatible object store."""
from __future__ import annotations
import os
import pathlib
import uuid
from typing import Callable, Optional, Union
from composer.utils.import_helpers import MissingConditionalImportError
from compos... | composer-dev | composer/utils/object_store/oci_object_store.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Utility for uploading to and downloading from cloud object stores."""
import io
import os
import pathlib
import uuid
from typing import Any, Callable, Dict, Optional, Union
from requests.exceptions import ConnectionError
from urllib3.... | composer-dev | composer/utils/object_store/libcloud_object_store.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""S3-Compatible object store."""
from __future__ import annotations
import os
import pathlib
import uuid
from typing import Any, Callable, Dict, Optional, Union
from composer.utils.import_helpers import MissingConditionalImportError
f... | composer-dev | composer/utils/object_store/s3_object_store.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Object store base class and implementations."""
from composer.utils.object_store.libcloud_object_store import LibcloudObjectStore
from composer.utils.object_store.object_store import ObjectStore, ObjectStoreTransientError
from compose... | composer-dev | composer/utils/object_store/__init__.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Utility for uploading to and downloading from cloud object stores."""
from __future__ import annotations
import contextlib
import os
import pathlib
import urllib.parse
import uuid
from typing import Any, Callable, Dict, Optional, Uni... | composer-dev | composer/utils/object_store/sftp_object_store.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Abstract class for utilities that upload to and download from object stores."""
import abc
import pathlib
from types import TracebackType
from typing import Callable, Optional, Type, Union
__all__ = ['ObjectStore', 'ObjectStoreTransi... | composer-dev | composer/utils/object_store/object_store.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""The models module contains the :class:`.ComposerModel` base class along with reference
implementations of many common models. Additionally, it includes task-specific convenience
:class:`.ComposerModel`\\s that wrap existing Pytorch mod... | composer-dev | composer/models/__init__.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Module Initializers."""
from typing import Callable
import torch
from torch import nn as nn
from composer.utils import StringEnum
class Initializer(StringEnum):
"""Sets the initialization scheme for different layers of a PyTor... | composer-dev | composer/models/initializers.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""A wrapper class that converts 🤗 Transformers models to composer models"""
from __future__ import annotations
import inspect
import json
import logging
import tempfile
import textwrap
from collections import UserDict
from pathlib imp... | composer-dev | composer/models/huggingface.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""A wrapper class that converts mmdet detection models to composer models"""
from __future__ import annotations
from typing import TYPE_CHECKING, Any, List, Optional
import numpy as np
import torch
from torchmetrics import Metric
from... | composer-dev | composer/models/mmdetection.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""The ComposerModel base interface."""
from __future__ import annotations
import abc
import copy
import warnings
from typing import Any, Dict, Optional, Sequence, Union
import torch
from torch import Tensor
from torchmetrics import Met... | composer-dev | composer/models/base.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""A convenience class that creates a :class:`.ComposerModel` for classification tasks from a vanilla PyTorch model.
:class:`.ComposerClassifier` requires batches in the form: (``input``, ``target``) and includes a basic
classification t... | composer-dev | composer/models/tasks/classification.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Model tasks are ComposerModels with forward passes and logging built-in for many common deep learning tasks."""
from composer.models.tasks.classification import ComposerClassifier as ComposerClassifier
__all__ = ['ComposerClassifier'... | composer-dev | composer/models/tasks/__init__.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""The ResNet model family is a set of convolutional neural networks described in `Deep Residual Learning for Image
Recognition <https://arxiv.org/abs/1512.03385>`_ (He et al, 2015). ResNets can be used as the base for a variety of
vision... | composer-dev | composer/models/resnet/__init__.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""A :class:`.ComposerClassifier` wrapper around the torchvision implementations of the ResNet model family."""
import logging
import textwrap
import warnings
from typing import List, Optional
import torchvision
from packaging import ve... | composer-dev | composer/models/resnet/model.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""ViT Small Patch 16 for image classification."""
from composer.models.vit_small_patch16.model import vit_small_patch16 as vit_small_patch16
__all__ = ['vit_small_patch16']
_task = 'Image Classification'
_dataset = 'ImageNet'
_name = ... | composer-dev | composer/models/vit_small_patch16/__init__.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Implements ViT-S/16 as a :class:`.ComposerClassifier`."""
from composer.models.tasks import ComposerClassifier
__all__ = ['vit_small_patch16']
def vit_small_patch16(num_classes: int = 1000,
image_size: int = 2... | composer-dev | composer/models/vit_small_patch16/model.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
## Code adapted from https://github.com/NVIDIA/DeepLearningExamples/blob/master/PyTorch/Segmentation/nnUNet/
import numpy as np
import torch
import torch.nn as nn
normalizations = {
'instancenorm3d': nn.InstanceNorm3d,
'instance... | composer-dev | composer/models/unet/_layers.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""A U-Net model extending :class:`.ComposerModel`."""
import logging
from typing import Any, Dict, Optional, Sequence, Union
import torch
import torch.nn as nn
from torchmetrics import Metric
from composer.metrics.metrics import Dice
... | composer-dev | composer/models/unet/unet.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""The Unet architecture used in image segmentation. The example we are using is for BRATS medical brain tumor dataset.
See the :doc:`Model Card </model_cards/unet>` for more details.
"""
from composer.models.unet.unet import UNet as UN... | composer-dev | composer/models/unet/__init__.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""The Unet architecture used in image segmentation. The example we are using is for BRATS medical brain tumor dataset.
See the :doc:`Model Card </model_cards/unet>` for more details.
"""
import torch.nn as nn
from composer.models.unet... | composer-dev | composer/models/unet/model.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""A wrapper around `timm.create_model() <https://rwightman.github.io/pytorch-image-models/#load-a-pretrained-model>`_
used to create :class:`.ComposerClassifier`."""
from composer.models.timm.model import composer_timm as composer_timm
... | composer-dev | composer/models/timm/__init__.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""A wrapper around `timm.create_model() <https://rwightman.github.io/pytorch-image-models/#load-a-pretrained-model>`_
used to create :class:`.ComposerClassifier`."""
from typing import Optional
from composer.models.tasks import Compose... | composer-dev | composer/models/timm/model.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
from typing import Callable, Optional
import torch
from torch import nn as nn
def round_channels(
channels: float,
width_multiplier: float,
divisor: int = 8,
min_value: Optional[int] = None,
) -> int:
"""Round numbe... | composer-dev | composer/models/efficientnetb0/_layers.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""The EfficientNet model family is a set of convolutional neural networks that can be used as the basis for a variety
of vision tasks, but were initially designed for image classification. The model family was designed to reach the
highe... | composer-dev | composer/models/efficientnetb0/__init__.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""A :class:`.ComposerClassifier` wrapper around the EfficientNet-b0 architecture."""
from composer.models.efficientnetb0.efficientnets import EfficientNet
from composer.models.tasks import ComposerClassifier
__all__ = ['composer_efficie... | composer-dev | composer/models/efficientnetb0/model.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""EfficientNet model.
Adapted from `(Generic) EfficientNets for PyTorch. <https://github.com/rwightman/gen-efficientnet-pytorch>`_.
"""
import math
import re
from typing import Callable, Optional
import torch
import torch.nn as nn
fr... | composer-dev | composer/models/efficientnetb0/efficientnets.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""The `BERT <https://huggingface.co/docs/transformers/master/en/model_doc/bert>`_ model family using `Hugging Face
Transformers <https://huggingface.co/transformers/>`_."""
from composer.models.bert.model import create_bert_classificati... | composer-dev | composer/models/bert/__init__.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Implements a BERT wrapper around a :class:`.ComposerTransformer`."""
from __future__ import annotations
from typing import Optional
from torchmetrics import MeanSquaredError
from torchmetrics.classification import MatthewsCorrCoef, ... | composer-dev | composer/models/bert/model.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""A simple example convolutional neural network which can be used to classify MNIST data."""
from composer.models.classify_mnist.model import mnist_model as mnist_model
__all__ = ['mnist_model']
_task = 'Image Classification'
_dataset ... | composer-dev | composer/models/classify_mnist/__init__.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""A simple convolutional neural network extending :class:`.ComposerClassifier`."""
from typing import List, Optional, Sequence, Union
import torch
import torch.nn as nn
from torch.nn import functional as F
from composer.models.initial... | composer-dev | composer/models/classify_mnist/model.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""A ResNet model family adapted for CIFAR10 image sizes.
See the :doc:`Model Card </model_cards/cifar_resnet>` for more details.
"""
from composer.models.resnet_cifar.model import composer_resnet_cifar as composer_resnet_cifar
__all__... | composer-dev | composer/models/resnet_cifar/__init__.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""ResNet models for CIFAR extending :class:`.ComposerClassifier`."""
from typing import List, Optional
from composer.models.initializers import Initializer
from composer.models.resnet_cifar.resnets import ResNet9, ResNetCIFAR
from comp... | composer-dev | composer/models/resnet_cifar/model.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""The CIFAR ResNet torch module.
See the :doc:`Model Card </model_cards/resnet>` for more details.
"""
# Code below adapted from https://github.com/facebookresearch/open_lth
# and https://github.com/pytorch/vision
from typing import L... | composer-dev | composer/models/resnet_cifar/resnets.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""The GPT-2 model family is set of transformer-based networks for autoregressive language modeling at various scales.
This family was originally proposed by OpenAI, and is trained on the OpenWebText dataset. It is useful for downstream
l... | composer-dev | composer/models/gpt2/__init__.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""GPT-2 model based on `Hugging Face GPT-2 <https://huggingface.co/docs/transformers/master/en/model_doc/gpt2>`_.
Implemented as a wrapper using :class:`.ComposerTrainer`.
"""
from __future__ import annotations
from typing import Opti... | composer-dev | composer/models/gpt2/model.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""DeepLabV3 for image segmentation."""
from composer.models.deeplabv3.model import composer_deeplabv3 as composer_deeplabv3
__all__ = ['composer_deeplabv3']
| composer-dev | composer/models/deeplabv3/__init__.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""DeepLabV3 model extending :class:`.ComposerClassifier`."""
import functools
import textwrap
import warnings
from typing import Dict, Optional, Sequence
import torch
import torch.distributed as torch_dist
import torch.nn.functional as... | composer-dev | composer/models/deeplabv3/model.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Composer CLI."""
| composer-dev | composer/cli/__init__.py |
#!/usr/bin/env python3
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""The Composer CLI launcher for distributed training."""
import contextlib
import datetime
import logging
import os
import signal
import subprocess
import sys
import tempfile
import time
import traceback
from argp... | composer-dev | composer/cli/launcher.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Runs the Composer CLI."""
import sys
from composer.cli.launcher import main
sys.exit(main())
| composer-dev | composer/cli/__main__.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Profiler Schedules."""
from typing import Callable
from composer.core.state import State
from composer.profiler.profiler_action import ProfilerAction
__all__ = ['cyclic_schedule']
def cyclic_schedule(
skip_first: int = 0,
... | composer-dev | composer/profiler/profiler_schedule.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Outputs profiling data in JSON trace format."""
from __future__ import annotations
import gzip
import json
import os
import pathlib
import queue
import tempfile
import textwrap
import time
from typing import TYPE_CHECKING, Dict, List... | composer-dev | composer/profiler/json_trace_handler.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Profiler to collect :mod:`torch` performance metrics during training."""
from __future__ import annotations
import json
import os
import textwrap
from typing import TYPE_CHECKING, Optional, OrderedDict
import torch.profiler
from tor... | composer-dev | composer/profiler/torch_profiler.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Performance profiling tools.
The profiler gathers performance metrics during a training run that can be used to diagnose bottlenecks and
facilitate model development.
The metrics gathered include:
* Duration of each :class:`.Event` ... | composer-dev | composer/profiler/__init__.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Action states for the :class:`Profiler` that define whether or not events are being recorded to the trace file."""
from composer.utils import StringEnum
__all__ = ['ProfilerAction']
class ProfilerAction(StringEnum):
"""Action s... | composer-dev | composer/profiler/profiler_action.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Profiler Marker."""
from __future__ import annotations
import functools
import time
from types import TracebackType
from typing import TYPE_CHECKING, Any, Callable, Dict, List, Optional, Sequence, Tuple, Type, Union
from composer.pr... | composer-dev | composer/profiler/marker.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Merge trace files together.
To run:
.. code-block::
python -m composer.profiler.json_trace_merger -o merged_trace_output.json path/to/input_file_1.json path/to/input_file_2.json ...
To view the traces, open a Google Chrome brow... | composer-dev | composer/profiler/json_trace_merger.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Profiler to record system level metrics."""
from __future__ import annotations
import threading
import time
from typing import TYPE_CHECKING, Dict, cast
import psutil
from composer.core import Callback
if TYPE_CHECKING:
from c... | composer-dev | composer/profiler/system_profiler.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Profiler Trace Handler."""
from __future__ import annotations
import abc
import pathlib
from typing import TYPE_CHECKING, Dict, List, Tuple, Union
from composer.core.callback import Callback
if TYPE_CHECKING:
from composer.core... | composer-dev | composer/profiler/trace_handler.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Composer Profiler."""
from __future__ import annotations
import logging
import pathlib
from typing import TYPE_CHECKING, Callable, Dict, List, Sequence, Tuple, Union
from composer.profiler.marker import Marker
from composer.profiler... | composer-dev | composer/profiler/profiler.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Functional API for applying algorithms in your own training loop.
.. code-block:: python
from composer import functional as cf
from torchvision import models
model = models.resnet50()
# replace some layers with blur... | composer-dev | composer/functional/__init__.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Helpers for running distributed data parallel training."""
import collections
import logging
import warnings
from contextlib import contextmanager, nullcontext
from typing import Any, Callable, ContextManager, Dict, Optional, Sequence... | composer-dev | composer/trainer/dist_strategy.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
# Released under BSD 3-Clause License,
# Copyright (c) Facebook, Inc. and its affiliates.
"""Updates FSDPs _auto_wrap to enable module_kwargs and custom process_group cache."""
import functools
import warnings
from typing import Any, Ca... | composer-dev | composer/trainer/mosaic_fsdp.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Helpers for the `DeepSpeed <https://www.deepspeed.ai>`_ integration with Composer."""
import copy
import warnings
from typing import Any, Dict, cast
import torch
import torch.utils.data
from composer.core import Batch, Precision, St... | composer-dev | composer/trainer/_deepspeed.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Train models with flexible insertion of algorithms."""
from composer.trainer.trainer import Trainer
__all__ = ['Trainer']
| composer-dev | composer/trainer/__init__.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
# Source code is compiled from a modified version of:
# https://github.com/pytorch/pytorch/blob/v1.13.0/torch/nn/modules/module.py
# Link to PyTorch License File: https://github.com/pytorch/pytorch/blob/master/LICENSE
# TODO: This code wi... | composer-dev | composer/trainer/meta_safe_apply.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
from collections import defaultdict
from typing import Optional, Union
import torch
from torch.cuda.amp.grad_scaler import GradScaler, OptState, _refresh_per_optimizer_state
from torch.optim import Optimizer
from composer.utils import d... | composer-dev | composer/trainer/_scaler.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
from collections import Counter
from torch.optim.lr_scheduler import CosineAnnealingLR, CosineAnnealingWarmRestarts, ExponentialLR, MultiStepLR, StepLR
from composer.core import PyTorchScheduler
def scale_pytorch_scheduler(scheduler: ... | composer-dev | composer/trainer/_scale_schedule.py |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Train models."""
from __future__ import annotations
import collections.abc
import contextlib
import datetime
import itertools
import logging
import os
import random
import re
import time
import warnings
from collections import defaul... | composer-dev | composer/trainer/trainer.py |
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