From 1baada9b9cff4fb38af1093388772bce16398be3 Mon Sep 17 00:00:00 2001
From: Mihir Patel <mihir.v.patel7@gmail.com>
Date: Thu, 5 Oct 2023 18:26:43 -0400
Subject: [PATCH] deprecate (#2605)

---
 composer/callbacks/mlperf.py                    |  2 ++
 composer/datasets/ade20k.py                     | 15 +++++++++++++++
 composer/datasets/brats.py                      |  3 +++
 composer/datasets/c4.py                         |  2 ++
 composer/datasets/cifar.py                      |  5 +++++
 composer/datasets/ffcv_utils.py                 |  3 +++
 composer/datasets/imagenet.py                   | 11 +++++++++++
 composer/datasets/lm_dataset.py                 |  3 +++
 composer/datasets/mnist.py                      |  3 +++
 composer/datasets/synthetic.py                  |  4 ++++
 composer/datasets/utils.py                      |  4 ++++
 composer/models/bert/model.py                   |  5 +++++
 composer/models/classify_mnist/model.py         |  3 +++
 composer/models/deeplabv3/model.py              |  4 ++++
 composer/models/efficientnetb0/efficientnets.py |  3 +++
 composer/models/efficientnetb0/model.py         |  4 ++++
 composer/models/gpt2/model.py                   |  3 +++
 composer/models/mmdetection.py                  |  2 ++
 composer/models/resnet/model.py                 |  2 ++
 composer/models/resnet_cifar/model.py           |  2 ++
 composer/models/timm/model.py                   |  2 ++
 composer/models/unet/model.py                   |  3 +++
 composer/models/unet/unet.py                    |  3 +++
 composer/models/vit_small_patch16/model.py      |  3 +++
 24 files changed, 94 insertions(+)

diff --git a/composer/callbacks/mlperf.py b/composer/callbacks/mlperf.py
index e5752c2a80..ddd2f02a76 100644
--- a/composer/callbacks/mlperf.py
+++ b/composer/callbacks/mlperf.py
@@ -267,6 +267,8 @@ def _get_dataloader_stats(self, dataloader: Iterable):
             # attempt to import ffcv and test if its an ffcv loader.
             import ffcv  # type: ignore
 
+            warnings.warn(DeprecationWarning('ffcv is deprecated and will be removed in v0.18'))
+
             if isinstance(dataloader, ffcv.loader.Loader):
                 # Use the cached attribute ffcv.init_traversal_order to compute number of samples
                 return (
diff --git a/composer/datasets/ade20k.py b/composer/datasets/ade20k.py
index 82603a59d2..23f801c485 100644
--- a/composer/datasets/ade20k.py
+++ b/composer/datasets/ade20k.py
@@ -8,6 +8,7 @@
 """
 
 import os
+import warnings
 from math import ceil
 from typing import Any, Dict, Optional, Tuple, Union
 
@@ -50,6 +51,8 @@ def build_ade20k_transformations(split,
            image_transforms (torch.nn.Module): Transformations to apply to the input image only.
            target_transforms (torch.nn.Module): Transformations to apply to the target semantic segmentation mask only.
     """
+    warnings.warn(DeprecationWarning('build_ade20k_transformations is deprecated and will be removed in v0.18'))
+
     if split == 'train':
         both_transforms = torch.nn.Sequential(
             RandomResizePair(
@@ -110,6 +113,8 @@ def build_ade20k_dataloader(
             Default: ``true``.
         **dataloader_kwargs (Dict[str, Any]): Additional settings for the dataloader (e.g. num_workers, etc.)
     """
+    warnings.warn(DeprecationWarning('build_ade20k_dataloader is deprecated and will be removed in v0.18'))
+
     if global_batch_size % dist.get_world_size() != 0:
         raise ValueError(
             f'global_batch_size ({global_batch_size}) must be divisible by world_size ({dist.get_world_size()}).')
@@ -195,6 +200,8 @@ def build_streaming_ade20k_dataloader(
             Defaults to ``None``, which is interpreted as the number of nodes of the initial run.
         **dataloader_kwargs (Dict[str, Any]): Additional settings for the dataloader (e.g. num_workers, etc.)
     """
+    warnings.warn(DeprecationWarning('build_streaming_ade20k_dataloader is deprecated and will be removed in v0.18'))
+
     if global_batch_size % dist.get_world_size() != 0:
         raise ValueError(
             f'global_batch_size ({global_batch_size}) must be divisible by world_size ({dist.get_world_size()}).')
@@ -274,6 +281,8 @@ def build_synthetic_ade20k_dataloader(
         memory_format (:class:`composer.core.MemoryFormat`): Memory format of the tensors. Default: ``CONTIGUOUS_FORMAT``.
         **dataloader_kwargs (Dict[str, Any]): Additional settings for the dataloader (e.g. num_workers, etc.)
     """
+    warnings.warn(DeprecationWarning('build_synthetic_ade20k_dataloader is deprecated and will be removed in v0.18'))
+
     if global_batch_size % dist.get_world_size() != 0:
         raise ValueError(
             f'global_batch_size ({global_batch_size}) must be divisible by world_size ({dist.get_world_size()}).')
@@ -321,6 +330,7 @@ def __init__(self, min_scale: float, max_scale: float, base_size: Optional[Tuple
         self.min_scale = min_scale
         self.max_scale = max_scale
         self.base_size = base_size
+        warnings.warn(DeprecationWarning('RandomResizePair is deprecated and will be removed in v0.18'))
 
     def forward(self, sample: Tuple[Image.Image, Image.Image]):
         image, target = sample
@@ -348,6 +358,7 @@ def __init__(self, crop_size: Tuple[int, int], class_max_percent: float = 1.0, n
         self.crop_size = crop_size
         self.class_max_percent = class_max_percent
         self.num_retry = num_retry
+        warnings.warn(DeprecationWarning('RandomCropPair is deprecated and will be removed in v0.18'))
 
     def forward(self, sample: Tuple[Image.Image, Image.Image]):
         image, target = sample
@@ -392,6 +403,7 @@ class RandomHFlipPair(torch.nn.Module):
     def __init__(self, probability: float = 0.5):
         super().__init__()
         self.probability = probability
+        warnings.warn(DeprecationWarning('RandomHFlipPair is deprecated and will be removed in v0.18'))
 
     def forward(self, sample: Tuple[Image.Image, Image.Image]):
         image, target = sample
@@ -413,6 +425,7 @@ def __init__(self, size: Tuple[int, int], fill: Union[int, Tuple[int, int, int]]
         super().__init__()
         self.size = size
         self.fill = fill
+        warnings.warn(DeprecationWarning('PadToSize is deprecated and will be removed in v0.18'))
 
     def forward(self, image: Image.Image):
         padding = max(self.size[0] - image.height, 0), max(self.size[1] - image.width, 0)
@@ -440,6 +453,7 @@ def __init__(self, brightness: float, contrast: float, saturation: float, hue: f
         self.contrast = contrast
         self.saturation = saturation
         self.hue = hue
+        warnings.warn(DeprecationWarning('PhotometricDistoration is deprecated and will be removed in v0.18'))
 
     def forward(self, image: Image.Image):
         if np.random.randint(2):
@@ -490,6 +504,7 @@ def __init__(self,
                  both_transforms: Optional[torch.nn.Module] = None,
                  image_transforms: Optional[torch.nn.Module] = None,
                  target_transforms: Optional[torch.nn.Module] = None):
+        warnings.warn(DeprecationWarning('ADE20k is deprecated and will be removed in v0.18'))
         super().__init__()
         self.datadir = datadir
         self.split = split
diff --git a/composer/datasets/brats.py b/composer/datasets/brats.py
index 096a4bd7e5..9356bdfb66 100644
--- a/composer/datasets/brats.py
+++ b/composer/datasets/brats.py
@@ -10,6 +10,7 @@
 import glob
 import os
 import random
+import warnings
 
 import numpy as np
 import torch
@@ -36,6 +37,8 @@ def build_brats_dataloader(datadir: str,
         global_batch_size (int): Global batch size.
         **dataloader_kwargs (Dict[str, Any]): Additional settings for the dataloader (e.g. num_workers, etc.)
     """
+    warnings.warn(DeprecationWarning('build_brats_dataloader is deprecated and will be removed in v0.18'))
+
     if global_batch_size % dist.get_world_size() != 0:
         raise ValueError(
             f'global_batch_size ({global_batch_size}) must be divisible by world_size ({dist.get_world_size()}).')
diff --git a/composer/datasets/c4.py b/composer/datasets/c4.py
index a9eb1d6e85..4402134a98 100644
--- a/composer/datasets/c4.py
+++ b/composer/datasets/c4.py
@@ -7,6 +7,7 @@
 <https://commoncrawl.org>`_ dataset.
 """
 import logging
+import warnings
 from typing import Any, Dict, Optional
 
 from torch.utils.data import DataLoader
@@ -74,6 +75,7 @@ def build_streaming_c4_dataloader(
             Defaults to ``None``, which is interpreted as the number of nodes of the initial run.
         **dataloader_kwargs (Dict[str, Any]): Additional settings for the dataloader (e.g. num_workers, etc.)
     """
+    warnings.warn(DeprecationWarning('build_streaming_c4_dataloader is deprecated and will be removed in v0.18'))
 
     try:
         import transformers
diff --git a/composer/datasets/cifar.py b/composer/datasets/cifar.py
index 3a2aad45fc..f866c5be1b 100644
--- a/composer/datasets/cifar.py
+++ b/composer/datasets/cifar.py
@@ -9,6 +9,7 @@
 
 import os
 import textwrap
+import warnings
 from typing import Any, Dict, List, Optional, Union
 
 import torch
@@ -52,6 +53,8 @@ def build_cifar10_dataloader(
         shuffle (bool): Shuffle the dataset. Default: ``True``.
         **dataloader_kwargs (Any): Additional settings for the dataloader (e.g. num_workers, etc.)
     """
+    warnings.warn(DeprecationWarning('build_cifar10_dataloader is deprecated and will be removed in v0.18'))
+
     if global_batch_size % dist.get_world_size() != 0:
         raise ValueError(
             f'global_batch_size ({global_batch_size}) must be divisible by world_size ({dist.get_world_size()}).')
@@ -119,6 +122,8 @@ def build_ffcv_cifar10_dataloader(
         ``False``.
         datadir (str | None, optional): Path to the non-FFCV data directory.
     """
+    warnings.warn(DeprecationWarning('build_ffcv_cifar10_dataloader is deprecated and will be removed in v0.18'))
+
     try:
         import ffcv
         from ffcv.fields.decoders import IntDecoder, SimpleRGBImageDecoder
diff --git a/composer/datasets/ffcv_utils.py b/composer/datasets/ffcv_utils.py
index 0a2bcc61dd..cdf7616d47 100644
--- a/composer/datasets/ffcv_utils.py
+++ b/composer/datasets/ffcv_utils.py
@@ -2,6 +2,7 @@
 # SPDX-License-Identifier: Apache-2.0
 
 import logging
+import warnings
 from typing import Optional
 
 import numpy as np
@@ -26,6 +27,7 @@ def _require_ffcv():
 
 
 def ffcv_monkey_patches():
+    warnings.warn(DeprecationWarning('ffcv_monkey_patches is deprecated and will be removed in v0.18'))
     _require_ffcv()
 
     # ffcv's __len__ function is expensive as it always calls self.next_traversal_order which does shuffling.
@@ -62,6 +64,7 @@ def write_ffcv_dataset(dataset: Optional[Dataset] = None,
         jpeg_quality (float): Quality to use for jpeg compression. Default: ``90``.
         chunk_size (int): Size of chunks processed by each worker during conversion. Default: ``100``.
     """
+    warnings.warn(DeprecationWarning('write_ffcv_dataset is deprecated and will be removed in v0.18'))
 
     _require_ffcv()
     if dataset is None:
diff --git a/composer/datasets/imagenet.py b/composer/datasets/imagenet.py
index 4533af208f..80d0f8c05d 100644
--- a/composer/datasets/imagenet.py
+++ b/composer/datasets/imagenet.py
@@ -8,6 +8,7 @@
 """
 
 import os
+import warnings
 from typing import Any, Dict, List, Optional
 
 import numpy as np
@@ -57,6 +58,8 @@ def build_imagenet_dataloader(
         crop size (int): The crop size to use. Default: ``224``.
         **dataloader_kwargs (Dict[str, Any]): Additional settings for the dataloader (e.g. num_workers, etc.)
     """
+    warnings.warn(DeprecationWarning('build_imagenet_dataloader is deprecated and will be removed in v0.18'))
+
     if global_batch_size % dist.get_world_size() != 0:
         raise ValueError(
             f'global_batch_size ({global_batch_size}) must be divisible by world_size ({dist.get_world_size()}).')
@@ -126,6 +129,8 @@ def build_synthetic_imagenet_dataloader(
         shuffle (bool): whether to shuffle the dataset. Default: ``True``.
         **dataloader_kwargs (Dict[str, Any]): Additional settings for the dataloader (e.g. num_workers, etc.)
     """
+    warnings.warn(DeprecationWarning('build_synthetic_imagenet_dataloader is deprecated and will be removed in v0.18'))
+
     if global_batch_size % dist.get_world_size() != 0:
         raise ValueError(
             f'global_batch_size ({global_batch_size}) must be divisible by world_size ({dist.get_world_size()}).')
@@ -166,6 +171,7 @@ def write_ffcv_imagenet(
         split (str): 'train' or 'val'. Default: ``train``.
         num_workers (int): Number of workers to use for conversion. Default: ``8``.
     """
+    warnings.warn(DeprecationWarning('write_ffcv_imagenet is deprecated and will be removed in v0.18'))
 
     if dist.get_local_rank() == 0:
         ds = ImageFolder(os.path.join(datadir, split))
@@ -205,6 +211,8 @@ def build_ffcv_imagenet_dataloader(
         prefetch_factor (int): Number of batches to prefect. Default: ``2``.
         num_workers (int): Number of workers. Default: ``8``.
     """
+    warnings.warn(DeprecationWarning('build_ffcv_imagenet_dataloader is deprecated and will be removed in v0.18'))
+
     try:
         import ffcv
         from ffcv.fields.decoders import CenterCropRGBImageDecoder, IntDecoder, RandomResizedCropRGBImageDecoder
@@ -317,6 +325,9 @@ def build_streaming_imagenet1k_dataloader(
             Defaults to ``None``, which is interpreted as the number of nodes of the initial run.
         **dataloader_kwargs (Dict[str, Any]): Additional settings for the dataloader (e.g. num_workers, etc.)
     """
+    warnings.warn(
+        DeprecationWarning('build_streaming_imagenet1k_dataloader is deprecated and will be removed in v0.18'))
+
     if global_batch_size % dist.get_world_size() != 0:
         raise ValueError(
             f'global_batch_size ({global_batch_size}) must be divisible by world_size ({dist.get_world_size()}).')
diff --git a/composer/datasets/lm_dataset.py b/composer/datasets/lm_dataset.py
index 1d2aed1ffc..aa752d0b2a 100644
--- a/composer/datasets/lm_dataset.py
+++ b/composer/datasets/lm_dataset.py
@@ -2,6 +2,7 @@
 # SPDX-License-Identifier: Apache-2.0
 
 import logging
+import warnings
 from typing import List, cast
 
 from torch.utils.data import DataLoader, Dataset
@@ -48,6 +49,8 @@ def build_lm_dataloader(
             ``1.0``.
         **dataloader_kwargs (Dict[str, Any]): Additional settings for the dataloader (e.g. num_workers, etc.)
     """
+    warnings.warn(DeprecationWarning('build_lm_dataloader is deprecated and will be removed in v0.18'))
+
     if global_batch_size % dist.get_world_size() != 0:
         raise ValueError(
             f'global_batch_size ({global_batch_size}) must be divisible by world_size ({dist.get_world_size()}).')
diff --git a/composer/datasets/mnist.py b/composer/datasets/mnist.py
index e54067cc39..4ec9601da4 100644
--- a/composer/datasets/mnist.py
+++ b/composer/datasets/mnist.py
@@ -1,6 +1,7 @@
 # Copyright 2022 MosaicML Composer authors
 # SPDX-License-Identifier: Apache-2.0
 
+import warnings
 from typing import Any
 
 from torch.utils.data import DataLoader
@@ -33,6 +34,8 @@ def build_mnist_dataloader(
         shuffle (bool): Shuffle the dataset. Default: ``True``.
         **dataloader_kwargs (Any): Additional settings for the dataloader (e.g. num_workers, etc.)
     """
+    warnings.warn(DeprecationWarning('build_mnist_dataloader is deprecated and will be removed in v0.18'))
+
     if global_batch_size % dist.get_world_size() != 0:
         raise ValueError(
             f'global_batch_size ({global_batch_size}) must be divisible by world_size ({dist.get_world_size()}).')
diff --git a/composer/datasets/synthetic.py b/composer/datasets/synthetic.py
index a660f85946..37d2e0f52c 100644
--- a/composer/datasets/synthetic.py
+++ b/composer/datasets/synthetic.py
@@ -5,6 +5,7 @@
 
 from __future__ import annotations
 
+import warnings
 from typing import Callable, Optional, Sequence, Union
 
 import torch
@@ -79,6 +80,8 @@ def __init__(self,
                  device: str = 'cpu',
                  memory_format: Union[str, MemoryFormat] = MemoryFormat.CONTIGUOUS_FORMAT,
                  transform: Optional[Callable] = None):
+        warnings.warn(DeprecationWarning('SyntheticBatchPairDataset is deprecated and will be removed in v0.18'))
+
         self.total_dataset_size = total_dataset_size
         self.data_shape = data_shape
         self.num_unique_samples_to_create = num_unique_samples_to_create
@@ -187,6 +190,7 @@ def __init__(self,
                  num_classes: Optional[int] = None,
                  label_shape: Optional[Sequence[int]] = None,
                  transform: Optional[Callable] = None):
+        warnings.warn(DeprecationWarning('SyntheticPILDataset is deprecated and will be removed in v0.18'))
         super().__init__(root='', transform=transform)
         self._dataset = SyntheticBatchPairDataset(
             total_dataset_size=total_dataset_size,
diff --git a/composer/datasets/utils.py b/composer/datasets/utils.py
index f873e5a860..9f6b2aac4e 100644
--- a/composer/datasets/utils.py
+++ b/composer/datasets/utils.py
@@ -5,6 +5,7 @@
 
 import logging
 import textwrap
+import warnings
 from typing import Callable, List, Tuple, Union
 
 import numpy as np
@@ -44,6 +45,7 @@ def __init__(self,
                  mean: Tuple[float, float, float],
                  std: Tuple[float, float, float],
                  ignore_background: bool = False):
+        warnings.warn(DeprecationWarning('NormalizationFn is deprecated and will be removed in v0.18'))
         self.mean = mean
         self.std = std
         self.ignore_background = ignore_background
@@ -87,6 +89,7 @@ def pil_image_collate(
         (torch.Tensor, torch.Tensor): Tuple of (image tensor, target tensor)
             The image tensor will be four-dimensional (NCHW or NHWC, depending on the ``memory_format``).
     """
+    warnings.warn(DeprecationWarning('pil_image_collate is deprecated and will be removed in v0.18'))
     imgs = [sample[0] for sample in batch]
     w, h = imgs[0].size
     image_tensor = torch.zeros((len(imgs), 3, h, w), dtype=torch.uint8).contiguous(memory_format=memory_format)
@@ -137,6 +140,7 @@ def add_vision_dataset_transform(dataset: VisionDataset, transform: Callable, is
     Returns:
         None: The ``dataset`` is modified in-place.
     """
+    warnings.warn(DeprecationWarning('add_vision_dataset_transform is deprecated and will be removed in v0.18'))
 
     transform_added_logstring = textwrap.dedent(f"""\
         Transform {transform} added to dataset.
diff --git a/composer/models/bert/model.py b/composer/models/bert/model.py
index 5e1a64edb8..7c79ef109b 100644
--- a/composer/models/bert/model.py
+++ b/composer/models/bert/model.py
@@ -5,6 +5,7 @@
 
 from __future__ import annotations
 
+import warnings
 from typing import Optional
 
 from torchmetrics import MeanSquaredError
@@ -70,6 +71,8 @@ def create_bert_mlm(use_pretrained: Optional[bool] = False,
         model = create_bert_mlm()
 
     """
+    warnings.warn(DeprecationWarning('create_bert_mlm is deprecated and will be removed in v0.18'))
+
     try:
         import transformers
     except ImportError as e:
@@ -175,6 +178,8 @@ def create_bert_classification(num_labels: int = 2,
         For the classification case (when ``num_labels > 1``), the training loss is :class:`~torch.nn.CrossEntropyLoss`, and the train/validation
         metrics are :class:`~torchmetrics.MulticlassAccuracy` and :class:`~torchmetrics.MatthewsCorrCoef`, as well as :class:`.BinaryF1Score` if ``num_labels == 2``.
     """
+    warnings.warn(DeprecationWarning('create_bert_classification is deprecated and will be removed in v0.18'))
+
     try:
         import transformers
     except ImportError as e:
diff --git a/composer/models/classify_mnist/model.py b/composer/models/classify_mnist/model.py
index e16af30916..708196af5b 100644
--- a/composer/models/classify_mnist/model.py
+++ b/composer/models/classify_mnist/model.py
@@ -3,6 +3,7 @@
 
 """A simple convolutional neural network extending :class:`.ComposerClassifier`."""
 
+import warnings
 from typing import List, Optional, Sequence, Union
 
 import torch
@@ -19,6 +20,7 @@ class Model(nn.Module):
     """Toy convolutional neural network architecture in pytorch for MNIST."""
 
     def __init__(self, initializers: Sequence[Union[str, Initializer]], num_classes: int = 10):
+        warnings.warn(DeprecationWarning('Model is deprecated and will be removed in v0.18'))
         super().__init__()
 
         self.num_classes = num_classes
@@ -65,6 +67,7 @@ def mnist_model(num_classes: int = 10, initializers: Optional[List[Initializer]]
 
         model = mnist_model()
     """
+    warnings.warn(DeprecationWarning('mnist_model is deprecated and will be removed in v0.18'))
 
     if initializers is None:
         initializers = []
diff --git a/composer/models/deeplabv3/model.py b/composer/models/deeplabv3/model.py
index 4d1ff6d591..7e58847708 100644
--- a/composer/models/deeplabv3/model.py
+++ b/composer/models/deeplabv3/model.py
@@ -28,6 +28,8 @@
 class SimpleSegmentationModel(torch.nn.Module):
 
     def __init__(self, backbone, classifier):
+        warnings.warn(DeprecationWarning('SimpleSegmentationModel is deprecated and will be removed in v0.18'))
+
         super().__init__()
         self.backbone = backbone
         self.classifier = classifier
@@ -75,6 +77,7 @@ def deeplabv3(num_classes: int,
 
         pytorch_model = deeplabv3(num_classes=150, backbone_arch='resnet101', backbone_weights=None)
     """
+    warnings.warn(DeprecationWarning('deeplabv3 is deprecated and will be removed in v0.18'))
 
     # check that the specified architecture is in the resnet module
     if not hasattr(resnet, backbone_arch):
@@ -217,6 +220,7 @@ def composer_deeplabv3(num_classes: int,
 
         model = composer_deeplabv3(num_classes=150, backbone_arch='resnet101', backbone_weights=None)
     """
+    warnings.warn(DeprecationWarning('composer_deeplabv3 is deprecated and will be removed in v0.18'))
 
     model = deeplabv3(backbone_arch=backbone_arch,
                       backbone_weights=backbone_weights,
diff --git a/composer/models/efficientnetb0/efficientnets.py b/composer/models/efficientnetb0/efficientnets.py
index 2b4e6bb1a5..7c544a5143 100644
--- a/composer/models/efficientnetb0/efficientnets.py
+++ b/composer/models/efficientnetb0/efficientnets.py
@@ -8,6 +8,7 @@
 
 import math
 import re
+import warnings
 from typing import Callable, Optional
 
 import torch
@@ -59,6 +60,8 @@ def __init__(self,
                  act_layer: Callable[..., nn.Module] = nn.SiLU,
                  norm_kwargs: Optional[dict] = None,
                  norm_layer: Callable[..., nn.Module] = nn.BatchNorm2d):
+        warnings.warn(DeprecationWarning('EfficientNet is deprecated and will be removed in v0.18'))
+
         super(EfficientNet, self).__init__()
         self.num_classes = num_classes
 
diff --git a/composer/models/efficientnetb0/model.py b/composer/models/efficientnetb0/model.py
index b6f177ad85..67ae193895 100644
--- a/composer/models/efficientnetb0/model.py
+++ b/composer/models/efficientnetb0/model.py
@@ -2,6 +2,9 @@
 # SPDX-License-Identifier: Apache-2.0
 
 """A :class:`.ComposerClassifier` wrapper around the EfficientNet-b0 architecture."""
+
+import warnings
+
 from composer.models.efficientnetb0.efficientnets import EfficientNet
 from composer.models.tasks import ComposerClassifier
 
@@ -31,6 +34,7 @@ def composer_efficientnetb0(num_classes: int = 1000, drop_connect_rate: float =
 
         model = composer_efficientnetb0()  # creates EfficientNet-b0 for image classification
     """
+    warnings.warn(DeprecationWarning('composer_efficientnetb0 is deprecated and will be removed in v0.18'))
     model = EfficientNet.get_model_from_name(model_name='efficientnet-b0',
                                              num_classes=num_classes,
                                              drop_connect_rate=drop_connect_rate)
diff --git a/composer/models/gpt2/model.py b/composer/models/gpt2/model.py
index ebb2606baa..ea924b7b99 100644
--- a/composer/models/gpt2/model.py
+++ b/composer/models/gpt2/model.py
@@ -8,6 +8,7 @@
 
 from __future__ import annotations
 
+import warnings
 from typing import Optional
 
 from composer.metrics.nlp import LanguageCrossEntropy, LanguagePerplexity
@@ -83,6 +84,8 @@ def create_gpt2(use_pretrained: Optional[bool] = False,
         composer_model = create_gpt2()
 
     """
+    warnings.warn(DeprecationWarning('create_gpt2 is deprecated and will be removed in v0.18'))
+
     try:
         import transformers
     except ImportError as e:
diff --git a/composer/models/mmdetection.py b/composer/models/mmdetection.py
index 837b991cf3..2e53aac543 100644
--- a/composer/models/mmdetection.py
+++ b/composer/models/mmdetection.py
@@ -5,6 +5,7 @@
 
 from __future__ import annotations
 
+import warnings
 from typing import TYPE_CHECKING, Any, List, Optional
 
 import numpy as np
@@ -56,6 +57,7 @@ def __init__(
             self,
             model: mmdet.models.detectors.BaseDetector,  # type: ignore
             metrics: Optional[List[Metric]] = None) -> None:
+        warnings.warn(DeprecationWarning('MMDetModel is deprecated and will be removed in v0.18'))
         super().__init__()
         self.model = model
 
diff --git a/composer/models/resnet/model.py b/composer/models/resnet/model.py
index 621fe772b9..5b023fabcf 100644
--- a/composer/models/resnet/model.py
+++ b/composer/models/resnet/model.py
@@ -4,6 +4,7 @@
 """A :class:`.ComposerClassifier` wrapper around the torchvision implementations of the ResNet model family."""
 
 import logging
+import warnings
 from typing import List, Optional
 
 from torchmetrics import MetricCollection
@@ -57,6 +58,7 @@ def composer_resnet(model_name: str,
 
         model = composer_resnet(model_name='resnet18')  # creates a torchvision resnet18 for image classification
     """
+    warnings.warn(DeprecationWarning('composer_resnet is deprecated and will be removed in v0.18'))
 
     valid_model_names = ['resnet18', 'resnet34', 'resnet50', 'resnet101', 'resnet152']
     if model_name not in valid_model_names:
diff --git a/composer/models/resnet_cifar/model.py b/composer/models/resnet_cifar/model.py
index 59e471d8bd..5bb8660b56 100644
--- a/composer/models/resnet_cifar/model.py
+++ b/composer/models/resnet_cifar/model.py
@@ -3,6 +3,7 @@
 
 """ResNet models for CIFAR extending :class:`.ComposerClassifier`."""
 
+import warnings
 from typing import List, Optional
 
 from composer.models.initializers import Initializer
@@ -39,6 +40,7 @@ def composer_resnet_cifar(model_name: str,
 
     .. _blog: https://myrtle.ai/learn/how-to-train-your-resnet-4-architecture/
     """
+    warnings.warn(DeprecationWarning('composer_resnet_cifar is deprecated and will be removed in v0.18'))
     if initializers is None:
         initializers = []
 
diff --git a/composer/models/timm/model.py b/composer/models/timm/model.py
index 8414646a9e..df0ffbca91 100644
--- a/composer/models/timm/model.py
+++ b/composer/models/timm/model.py
@@ -4,6 +4,7 @@
 """A wrapper around `timm.create_model() <https://rwightman.github.io/pytorch-image-models/#load-a-pretrained-model>`_
 used to create :class:`.ComposerClassifier`."""
 
+import warnings
 from typing import Optional
 
 from composer.models.tasks import ComposerClassifier
@@ -47,6 +48,7 @@ def composer_timm(model_name: str,
 
         model = composer_timm(model_name='resnet18')  # creates a timm resnet18
     """
+    warnings.warn(DeprecationWarning('composer_timm is deprecated and will be removed in v0.18'))
     try:
         import timm
     except ImportError as e:
diff --git a/composer/models/unet/model.py b/composer/models/unet/model.py
index 8b1c6a0c1e..08c49ff57c 100644
--- a/composer/models/unet/model.py
+++ b/composer/models/unet/model.py
@@ -6,6 +6,8 @@
 See the :doc:`Model Card </model_cards/unet>` for more details.
 """
 
+import warnings
+
 import torch.nn as nn
 
 from composer.models.unet._layers import ConvBlock, OutputBlock, ResidBlock, UpsampleBlock
@@ -40,6 +42,7 @@ def __init__(
         residual,
         dimension,
     ):
+        warnings.warn(DeprecationWarning('UNet is deprecated and will be removed in v0.18'))
         super(UNet, self).__init__()
         self.dim = dimension
         self.n_class = n_class
diff --git a/composer/models/unet/unet.py b/composer/models/unet/unet.py
index 80241ac351..dde555bb4f 100644
--- a/composer/models/unet/unet.py
+++ b/composer/models/unet/unet.py
@@ -4,6 +4,7 @@
 """A U-Net model extending :class:`.ComposerModel`."""
 
 import logging
+import warnings
 from typing import Any, Dict, Optional, Sequence, Union
 
 import torch
@@ -33,6 +34,8 @@ class UNet(ComposerModel):
     """
 
     def __init__(self, num_classes: int = 3) -> None:
+        warnings.warn(DeprecationWarning('UNet is deprecated and will be removed in v0.18'))
+
         super().__init__()
         try:
             from monai.losses import DiceLoss
diff --git a/composer/models/vit_small_patch16/model.py b/composer/models/vit_small_patch16/model.py
index 2bd6a8e6cd..dacb9db56a 100644
--- a/composer/models/vit_small_patch16/model.py
+++ b/composer/models/vit_small_patch16/model.py
@@ -3,6 +3,8 @@
 
 """Implements ViT-S/16 as a :class:`.ComposerClassifier`."""
 
+import warnings
+
 from composer.models.tasks import ComposerClassifier
 
 __all__ = ['vit_small_patch16']
@@ -29,6 +31,7 @@ def vit_small_patch16(num_classes: int = 1000,
     Returns:
         ComposerModel: instance of :class:`.ComposerClassifier` with a ViT-S/16 model.
     """
+    warnings.warn(DeprecationWarning('vit_small_patch16 is deprecated and will be removed in v0.18'))
 
     from vit_pytorch import ViT
     model = ViT(