From 9600f40285a05336f90e0de9aae8b0ddc6d26b32 Mon Sep 17 00:00:00 2001
From: Patrick von Platen <patrick.v.platen@gmail.com>
Date: Mon, 17 Apr 2023 11:06:18 +0000
Subject: [PATCH 01/16] Better deprecation message

---
 src/diffusers/configuration_utils.py | 23 +++++++++++++++++++++++
 1 file changed, 23 insertions(+)

diff --git a/src/diffusers/configuration_utils.py b/src/diffusers/configuration_utils.py
index 45930431351a..28cd2bb50ff5 100644
--- a/src/diffusers/configuration_utils.py
+++ b/src/diffusers/configuration_utils.py
@@ -118,6 +118,29 @@ def register_to_config(self, **kwargs):
 
         self._internal_dict = FrozenDict(internal_dict)
 
+    def __getattr__(self, name):
+        try:
+            getattr(super(), name)
+        except AttributeError as e:
+            try:
+                is_in_config = self._safe_hasattr("_internal_dict") and hasattr(self._internal_dict, name)
+                is_attribute = self._safe_hasattr(name)
+
+                if is_in_config and not is_attribute:
+                    return self._internal_dict[name]
+            except AttributeError as e:
+                raise AttributeError(str(e).replace("super", self.__class__.__name__))
+
+            raise AttributeError(str(e).replace("super", self.__class__.__name__))
+
+    def _safe_hasattr(self, name):
+        try:
+            self.__getattribute__(name)
+        except AttributeError:
+            return False
+
+        return True
+
     def save_config(self, save_directory: Union[str, os.PathLike], push_to_hub: bool = False, **kwargs):
         """
         Save a configuration object to the directory `save_directory`, so that it can be re-loaded using the

From eab27d4985e171418bdfa45fa6e6e7b4c244167d Mon Sep 17 00:00:00 2001
From: Patrick von Platen <patrick.v.platen@gmail.com>
Date: Mon, 17 Apr 2023 11:06:26 +0000
Subject: [PATCH 02/16] Better deprecation message

---
 src/diffusers/configuration_utils.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/src/diffusers/configuration_utils.py b/src/diffusers/configuration_utils.py
index 28cd2bb50ff5..3ede931944e2 100644
--- a/src/diffusers/configuration_utils.py
+++ b/src/diffusers/configuration_utils.py
@@ -127,6 +127,8 @@ def __getattr__(self, name):
                 is_attribute = self._safe_hasattr(name)
 
                 if is_in_config and not is_attribute:
+                    deprecation_message = f"Accessing config attribute `{name}` directly via '{self.__class__.__name__}' object attribute is deprecated. Please access '{name}' over '{self.__class__.__name__}'s config object instead, e.g. 'unet.config.{name}' or 'scheduler.config.{name}'."
+                    deprecate("direct config name access", "1.0.0", deprecation_message, standard_warn=False)
                     return self._internal_dict[name]
             except AttributeError as e:
                 raise AttributeError(str(e).replace("super", self.__class__.__name__))

From fd2df1bc561880a321b7bf62352ee14a6a65abef Mon Sep 17 00:00:00 2001
From: Patrick von Platen <patrick.v.platen@gmail.com>
Date: Mon, 17 Apr 2023 11:15:03 +0000
Subject: [PATCH 03/16] Better doc string

---
 src/diffusers/configuration_utils.py | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/src/diffusers/configuration_utils.py b/src/diffusers/configuration_utils.py
index 3ede931944e2..fbe9298e2c4f 100644
--- a/src/diffusers/configuration_utils.py
+++ b/src/diffusers/configuration_utils.py
@@ -119,6 +119,8 @@ def register_to_config(self, **kwargs):
         self._internal_dict = FrozenDict(internal_dict)
 
     def __getattr__(self, name):
+        """The only reason we overwrite `getattr` here is to gracefully deprecate accessing
+        config attributes directly. See https://github.com/huggingface/diffusers/pull/3129"""
         try:
             getattr(super(), name)
         except AttributeError as e:
@@ -136,6 +138,8 @@ def __getattr__(self, name):
             raise AttributeError(str(e).replace("super", self.__class__.__name__))
 
     def _safe_hasattr(self, name):
+        """This method should NOT be used and is only implemented for `def __getattr__`
+        for deprecation purposes"""
         try:
             self.__getattribute__(name)
         except AttributeError:

From b007c65a5a58861dc561c1f5b0723152d6e3cf38 Mon Sep 17 00:00:00 2001
From: Patrick von Platen <patrick.v.platen@gmail.com>
Date: Mon, 17 Apr 2023 11:33:27 +0000
Subject: [PATCH 04/16] Fixes

---
 src/diffusers/configuration_utils.py      |  3 +--
 src/diffusers/models/modeling_utils.py    | 19 +++++++++++++++++++
 src/diffusers/models/unet_2d.py           | 12 +-----------
 src/diffusers/pipelines/pipeline_utils.py |  2 +-
 4 files changed, 22 insertions(+), 14 deletions(-)

diff --git a/src/diffusers/configuration_utils.py b/src/diffusers/configuration_utils.py
index fbe9298e2c4f..dfb8478cdadc 100644
--- a/src/diffusers/configuration_utils.py
+++ b/src/diffusers/configuration_utils.py
@@ -122,12 +122,11 @@ def __getattr__(self, name):
         """The only reason we overwrite `getattr` here is to gracefully deprecate accessing
         config attributes directly. See https://github.com/huggingface/diffusers/pull/3129"""
         try:
-            getattr(super(), name)
+            return getattr(super(), name)
         except AttributeError as e:
             try:
                 is_in_config = self._safe_hasattr("_internal_dict") and hasattr(self._internal_dict, name)
                 is_attribute = self._safe_hasattr(name)
-
                 if is_in_config and not is_attribute:
                     deprecation_message = f"Accessing config attribute `{name}` directly via '{self.__class__.__name__}' object attribute is deprecated. Please access '{name}' over '{self.__class__.__name__}'s config object instead, e.g. 'unet.config.{name}' or 'scheduler.config.{name}'."
                     deprecate("direct config name access", "1.0.0", deprecation_message, standard_warn=False)
diff --git a/src/diffusers/models/modeling_utils.py b/src/diffusers/models/modeling_utils.py
index 6a849f6f0e45..faa74a76678d 100644
--- a/src/diffusers/models/modeling_utils.py
+++ b/src/diffusers/models/modeling_utils.py
@@ -32,6 +32,7 @@
     WEIGHTS_NAME,
     _add_variant,
     _get_model_file,
+    deprecate,
     is_accelerate_available,
     is_safetensors_available,
     is_torch_version,
@@ -156,6 +157,24 @@ class ModelMixin(torch.nn.Module):
     def __init__(self):
         super().__init__()
 
+    def __getattr__(self, name):
+        """The only reason we overwrite `getattr` here is to gracefully deprecate accessing
+        config attributes directly. See https://github.com/huggingface/diffusers/pull/3129"""
+        try:
+            return super().__getattr__(name)
+        except AttributeError as e:
+            try:
+                is_in_config = self._safe_hasattr("_internal_dict") and hasattr(self._internal_dict, name)
+                is_attribute = self._safe_hasattr(name)
+                if is_in_config and not is_attribute:
+                    deprecation_message = f"Accessing config attribute `{name}` directly via '{self.__class__.__name__}' object attribute is deprecated. Please access '{name}' over '{self.__class__.__name__}'s config object instead, e.g. 'unet.config.{name}' or 'scheduler.config.{name}'."
+                    deprecate("direct config name access", "1.0.0", deprecation_message, standard_warn=False)
+                    return self._internal_dict[name]
+            except AttributeError as e:
+                raise AttributeError(str(e).replace("super", self.__class__.__name__))
+
+            raise AttributeError(str(e).replace("super", self.__class__.__name__))
+
     @property
     def is_gradient_checkpointing(self) -> bool:
         """
diff --git a/src/diffusers/models/unet_2d.py b/src/diffusers/models/unet_2d.py
index a83e4917c143..2a6a1b9de5f2 100644
--- a/src/diffusers/models/unet_2d.py
+++ b/src/diffusers/models/unet_2d.py
@@ -18,7 +18,7 @@
 import torch.nn as nn
 
 from ..configuration_utils import ConfigMixin, register_to_config
-from ..utils import BaseOutput, deprecate
+from ..utils import BaseOutput
 from .embeddings import GaussianFourierProjection, TimestepEmbedding, Timesteps
 from .modeling_utils import ModelMixin
 from .unet_2d_blocks import UNetMidBlock2D, get_down_block, get_up_block
@@ -216,16 +216,6 @@ def __init__(
         self.conv_act = nn.SiLU()
         self.conv_out = nn.Conv2d(block_out_channels[0], out_channels, kernel_size=3, padding=1)
 
-    @property
-    def in_channels(self):
-        deprecate(
-            "in_channels",
-            "1.0.0",
-            "Accessing `in_channels` directly via unet.in_channels is deprecated. Please use `unet.config.in_channels` instead",
-            standard_warn=False,
-        )
-        return self.config.in_channels
-
     def forward(
         self,
         sample: torch.FloatTensor,
diff --git a/src/diffusers/pipelines/pipeline_utils.py b/src/diffusers/pipelines/pipeline_utils.py
index c095da1665de..38f13fa11e66 100644
--- a/src/diffusers/pipelines/pipeline_utils.py
+++ b/src/diffusers/pipelines/pipeline_utils.py
@@ -508,7 +508,7 @@ def register_modules(self, **kwargs):
             setattr(self, name, module)
 
     def __setattr__(self, name: str, value: Any):
-        if hasattr(self, name) and hasattr(self.config, name):
+        if self._safe_hasattr(name) and hasattr(self.config, name):
             # We need to overwrite the config if name exists in config
             if isinstance(getattr(self.config, name), (tuple, list)):
                 if value is not None and self.config[name][0] is not None:

From c6cc8244fa97531263ea8525842e188457508b95 Mon Sep 17 00:00:00 2001
From: Patrick von Platen <patrick.v.platen@gmail.com>
Date: Mon, 17 Apr 2023 11:42:50 +0000
Subject: [PATCH 05/16] fix more

---
 src/diffusers/configuration_utils.py   | 3 +--
 src/diffusers/models/modeling_utils.py | 3 +--
 2 files changed, 2 insertions(+), 4 deletions(-)

diff --git a/src/diffusers/configuration_utils.py b/src/diffusers/configuration_utils.py
index dfb8478cdadc..f7b48ce471a3 100644
--- a/src/diffusers/configuration_utils.py
+++ b/src/diffusers/configuration_utils.py
@@ -126,8 +126,7 @@ def __getattr__(self, name):
         except AttributeError as e:
             try:
                 is_in_config = self._safe_hasattr("_internal_dict") and hasattr(self._internal_dict, name)
-                is_attribute = self._safe_hasattr(name)
-                if is_in_config and not is_attribute:
+                if is_in_config:
                     deprecation_message = f"Accessing config attribute `{name}` directly via '{self.__class__.__name__}' object attribute is deprecated. Please access '{name}' over '{self.__class__.__name__}'s config object instead, e.g. 'unet.config.{name}' or 'scheduler.config.{name}'."
                     deprecate("direct config name access", "1.0.0", deprecation_message, standard_warn=False)
                     return self._internal_dict[name]
diff --git a/src/diffusers/models/modeling_utils.py b/src/diffusers/models/modeling_utils.py
index faa74a76678d..14b8d6879c5e 100644
--- a/src/diffusers/models/modeling_utils.py
+++ b/src/diffusers/models/modeling_utils.py
@@ -165,8 +165,7 @@ def __getattr__(self, name):
         except AttributeError as e:
             try:
                 is_in_config = self._safe_hasattr("_internal_dict") and hasattr(self._internal_dict, name)
-                is_attribute = self._safe_hasattr(name)
-                if is_in_config and not is_attribute:
+                if is_in_config:
                     deprecation_message = f"Accessing config attribute `{name}` directly via '{self.__class__.__name__}' object attribute is deprecated. Please access '{name}' over '{self.__class__.__name__}'s config object instead, e.g. 'unet.config.{name}' or 'scheduler.config.{name}'."
                     deprecate("direct config name access", "1.0.0", deprecation_message, standard_warn=False)
                     return self._internal_dict[name]

From 9a65cbe40e5e057d4d3a179a4432819d9eaaab87 Mon Sep 17 00:00:00 2001
From: Patrick von Platen <patrick.v.platen@gmail.com>
Date: Mon, 17 Apr 2023 12:00:26 +0000
Subject: [PATCH 06/16] fix more

---
 src/diffusers/configuration_utils.py | 8 +++++---
 1 file changed, 5 insertions(+), 3 deletions(-)

diff --git a/src/diffusers/configuration_utils.py b/src/diffusers/configuration_utils.py
index f7b48ce471a3..2e713220e598 100644
--- a/src/diffusers/configuration_utils.py
+++ b/src/diffusers/configuration_utils.py
@@ -122,7 +122,7 @@ def __getattr__(self, name):
         """The only reason we overwrite `getattr` here is to gracefully deprecate accessing
         config attributes directly. See https://github.com/huggingface/diffusers/pull/3129"""
         try:
-            return getattr(super(), name)
+            return super().__getattr__(name)
         except AttributeError as e:
             try:
                 is_in_config = self._safe_hasattr("_internal_dict") and hasattr(self._internal_dict, name)
@@ -131,9 +131,11 @@ def __getattr__(self, name):
                     deprecate("direct config name access", "1.0.0", deprecation_message, standard_warn=False)
                     return self._internal_dict[name]
             except AttributeError as e:
-                raise AttributeError(str(e).replace("super", self.__class__.__name__))
+                error = str(e).replace("super", self.__class__.__name__).replace("__getattr__", name)
+                raise AttributeError(error)
 
-            raise AttributeError(str(e).replace("super", self.__class__.__name__))
+            error = str(e).replace("super", self.__class__.__name__).replace("__getattr__", name)
+            raise AttributeError(error)
 
     def _safe_hasattr(self, name):
         """This method should NOT be used and is only implemented for `def __getattr__`

From e56d51a5e9968d37f528b8fe81fb523461b90480 Mon Sep 17 00:00:00 2001
From: Patrick von Platen <patrick.v.platen@gmail.com>
Date: Mon, 17 Apr 2023 12:14:47 +0000
Subject: [PATCH 07/16] Improve __getattr__

---
 src/diffusers/configuration_utils.py   | 41 ++++++++++----------------
 src/diffusers/models/modeling_utils.py | 33 +++++++++++----------
 2 files changed, 32 insertions(+), 42 deletions(-)

diff --git a/src/diffusers/configuration_utils.py b/src/diffusers/configuration_utils.py
index 2e713220e598..d231ae0e8d9a 100644
--- a/src/diffusers/configuration_utils.py
+++ b/src/diffusers/configuration_utils.py
@@ -118,34 +118,23 @@ def register_to_config(self, **kwargs):
 
         self._internal_dict = FrozenDict(internal_dict)
 
-    def __getattr__(self, name):
+    def __getattr__(self, name: str) -> Any:
         """The only reason we overwrite `getattr` here is to gracefully deprecate accessing
-        config attributes directly. See https://github.com/huggingface/diffusers/pull/3129"""
-        try:
-            return super().__getattr__(name)
-        except AttributeError as e:
-            try:
-                is_in_config = self._safe_hasattr("_internal_dict") and hasattr(self._internal_dict, name)
-                if is_in_config:
-                    deprecation_message = f"Accessing config attribute `{name}` directly via '{self.__class__.__name__}' object attribute is deprecated. Please access '{name}' over '{self.__class__.__name__}'s config object instead, e.g. 'unet.config.{name}' or 'scheduler.config.{name}'."
-                    deprecate("direct config name access", "1.0.0", deprecation_message, standard_warn=False)
-                    return self._internal_dict[name]
-            except AttributeError as e:
-                error = str(e).replace("super", self.__class__.__name__).replace("__getattr__", name)
-                raise AttributeError(error)
-
-            error = str(e).replace("super", self.__class__.__name__).replace("__getattr__", name)
-            raise AttributeError(error)
-
-    def _safe_hasattr(self, name):
-        """This method should NOT be used and is only implemented for `def __getattr__`
-        for deprecation purposes"""
-        try:
-            self.__getattribute__(name)
-        except AttributeError:
-            return False
+        config attributes directly. See https://github.com/huggingface/diffusers/pull/3129
+
+        Tihs funtion is mostly copied from PyTorch's __getattr__ overwrite:
+        https://pytorch.org/docs/stable/_modules/torch/nn/modules/module.html#Module
+        """
+
+        is_in_config = "_internal_dict" in self.__dict__ and hasattr(self.__dict__["_internal_dict"], name)
+        is_attribute = name in self.__dict__
+
+        if is_in_config and not is_attribute:
+            deprecation_message = f"Accessing config attribute `{name}` directly via '{self.__class__.__name__}' object attribute is deprecated. Please access '{name}' over '{self.__class__.__name__}'s config object instead, e.g. 'unet.config.{name}' or 'scheduler.config.{name}'."
+            deprecate("direct config name access", "1.0.0", deprecation_message, standard_warn=False)
+            return self._internal_dict[name]
 
-        return True
+        raise AttributeError(f"'{type(self).__name__}' object has no attribute '{name}'")
 
     def save_config(self, save_directory: Union[str, os.PathLike], push_to_hub: bool = False, **kwargs):
         """
diff --git a/src/diffusers/models/modeling_utils.py b/src/diffusers/models/modeling_utils.py
index 14b8d6879c5e..533f1a3caacc 100644
--- a/src/diffusers/models/modeling_utils.py
+++ b/src/diffusers/models/modeling_utils.py
@@ -17,7 +17,7 @@
 import inspect
 import os
 from functools import partial
-from typing import Callable, List, Optional, Tuple, Union
+from typing import Any, Callable, List, Optional, Tuple, Union
 
 import torch
 from torch import Tensor, device
@@ -157,22 +157,23 @@ class ModelMixin(torch.nn.Module):
     def __init__(self):
         super().__init__()
 
-    def __getattr__(self, name):
+    def __getattr__(self, name: str) -> Any:
         """The only reason we overwrite `getattr` here is to gracefully deprecate accessing
-        config attributes directly. See https://github.com/huggingface/diffusers/pull/3129"""
-        try:
-            return super().__getattr__(name)
-        except AttributeError as e:
-            try:
-                is_in_config = self._safe_hasattr("_internal_dict") and hasattr(self._internal_dict, name)
-                if is_in_config:
-                    deprecation_message = f"Accessing config attribute `{name}` directly via '{self.__class__.__name__}' object attribute is deprecated. Please access '{name}' over '{self.__class__.__name__}'s config object instead, e.g. 'unet.config.{name}' or 'scheduler.config.{name}'."
-                    deprecate("direct config name access", "1.0.0", deprecation_message, standard_warn=False)
-                    return self._internal_dict[name]
-            except AttributeError as e:
-                raise AttributeError(str(e).replace("super", self.__class__.__name__))
-
-            raise AttributeError(str(e).replace("super", self.__class__.__name__))
+        config attributes directly. See https://github.com/huggingface/diffusers/pull/3129 We need to overwrite
+        __getattr__ here in addition so that we don't trigger `torch.nn.Module`'s __getattr__':
+        https://pytorch.org/docs/stable/_modules/torch/nn/modules/module.html#Module
+        """
+
+        is_in_config = "_internal_dict" in self.__dict__ and hasattr(self.__dict__["_internal_dict"], name)
+        is_attribute = name in self.__dict__
+
+        if is_in_config and not is_attribute:
+            deprecation_message = f"Accessing config attribute `{name}` directly via '{self.__class__.__name__}' object attribute is deprecated. Please access '{name}' over '{self.__class__.__name__}'s config object instead, e.g. 'unet.config.{name}' or 'scheduler.config.{name}'."
+            deprecate("direct config name access", "1.0.0", deprecation_message, standard_warn=False)
+            return self._internal_dict[name]
+
+        # call PyTorch's https://pytorch.org/docs/stable/_modules/torch/nn/modules/module.html#Module
+        return super().__getattr__(name)
 
     @property
     def is_gradient_checkpointing(self) -> bool:

From 2d45454b0a24778f9978def9c1beb4128cb0b0b4 Mon Sep 17 00:00:00 2001
From: Patrick von Platen <patrick.v.platen@gmail.com>
Date: Mon, 17 Apr 2023 12:18:28 +0000
Subject: [PATCH 08/16] correct more

---
 src/diffusers/pipelines/pipeline_utils.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/diffusers/pipelines/pipeline_utils.py b/src/diffusers/pipelines/pipeline_utils.py
index 38f13fa11e66..c095da1665de 100644
--- a/src/diffusers/pipelines/pipeline_utils.py
+++ b/src/diffusers/pipelines/pipeline_utils.py
@@ -508,7 +508,7 @@ def register_modules(self, **kwargs):
             setattr(self, name, module)
 
     def __setattr__(self, name: str, value: Any):
-        if self._safe_hasattr(name) and hasattr(self.config, name):
+        if hasattr(self, name) and hasattr(self.config, name):
             # We need to overwrite the config if name exists in config
             if isinstance(getattr(self.config, name), (tuple, list)):
                 if value is not None and self.config[name][0] is not None:

From 351bf978d70a3ed0020df07ed7893b9efedb1aa3 Mon Sep 17 00:00:00 2001
From: Patrick von Platen <patrick.v.platen@gmail.com>
Date: Mon, 17 Apr 2023 12:21:46 +0000
Subject: [PATCH 09/16] fix more

---
 src/diffusers/configuration_utils.py      | 1 +
 src/diffusers/pipelines/pipeline_utils.py | 2 +-
 2 files changed, 2 insertions(+), 1 deletion(-)

diff --git a/src/diffusers/configuration_utils.py b/src/diffusers/configuration_utils.py
index d231ae0e8d9a..7a564ca19f0a 100644
--- a/src/diffusers/configuration_utils.py
+++ b/src/diffusers/configuration_utils.py
@@ -131,6 +131,7 @@ def __getattr__(self, name: str) -> Any:
 
         if is_in_config and not is_attribute:
             deprecation_message = f"Accessing config attribute `{name}` directly via '{self.__class__.__name__}' object attribute is deprecated. Please access '{name}' over '{self.__class__.__name__}'s config object instead, e.g. 'unet.config.{name}' or 'scheduler.config.{name}'."
+            assert False
             deprecate("direct config name access", "1.0.0", deprecation_message, standard_warn=False)
             return self._internal_dict[name]
 
diff --git a/src/diffusers/pipelines/pipeline_utils.py b/src/diffusers/pipelines/pipeline_utils.py
index c095da1665de..94725185e69d 100644
--- a/src/diffusers/pipelines/pipeline_utils.py
+++ b/src/diffusers/pipelines/pipeline_utils.py
@@ -508,7 +508,7 @@ def register_modules(self, **kwargs):
             setattr(self, name, module)
 
     def __setattr__(self, name: str, value: Any):
-        if hasattr(self, name) and hasattr(self.config, name):
+        if name in self.__dict__ and hasattr(self.config, name):
             # We need to overwrite the config if name exists in config
             if isinstance(getattr(self.config, name), (tuple, list)):
                 if value is not None and self.config[name][0] is not None:

From 3fe30de42e3104d2e09ab67dc2a265726fed3c0c Mon Sep 17 00:00:00 2001
From: Patrick von Platen <patrick.v.platen@gmail.com>
Date: Mon, 17 Apr 2023 12:31:39 +0000
Subject: [PATCH 10/16] fix

---
 src/diffusers/configuration_utils.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/src/diffusers/configuration_utils.py b/src/diffusers/configuration_utils.py
index 7a564ca19f0a..d231ae0e8d9a 100644
--- a/src/diffusers/configuration_utils.py
+++ b/src/diffusers/configuration_utils.py
@@ -131,7 +131,6 @@ def __getattr__(self, name: str) -> Any:
 
         if is_in_config and not is_attribute:
             deprecation_message = f"Accessing config attribute `{name}` directly via '{self.__class__.__name__}' object attribute is deprecated. Please access '{name}' over '{self.__class__.__name__}'s config object instead, e.g. 'unet.config.{name}' or 'scheduler.config.{name}'."
-            assert False
             deprecate("direct config name access", "1.0.0", deprecation_message, standard_warn=False)
             return self._internal_dict[name]
 

From d9149fcc2a5cdb66f095277e7702e535d48c89fc Mon Sep 17 00:00:00 2001
From: Patrick von Platen <patrick.v.platen@gmail.com>
Date: Mon, 17 Apr 2023 12:53:45 +0000
Subject: [PATCH 11/16] Improve more

---
 src/diffusers/configuration_utils.py      |  2 +-
 src/diffusers/models/modeling_utils.py    |  4 +-
 src/diffusers/pipelines/pipeline_utils.py | 49 +++++++++++------------
 src/diffusers/utils/deprecation_utils.py  |  4 +-
 4 files changed, 29 insertions(+), 30 deletions(-)

diff --git a/src/diffusers/configuration_utils.py b/src/diffusers/configuration_utils.py
index d231ae0e8d9a..fe9047137b4e 100644
--- a/src/diffusers/configuration_utils.py
+++ b/src/diffusers/configuration_utils.py
@@ -130,7 +130,7 @@ def __getattr__(self, name: str) -> Any:
         is_attribute = name in self.__dict__
 
         if is_in_config and not is_attribute:
-            deprecation_message = f"Accessing config attribute `{name}` directly via '{self.__class__.__name__}' object attribute is deprecated. Please access '{name}' over '{self.__class__.__name__}'s config object instead, e.g. 'unet.config.{name}' or 'scheduler.config.{name}'."
+            deprecation_message = f"Accessing config attribute `{name}` directly via '{self.__class__.__name__}' object attribute is deprecated. Please access '{name}' over '{self.__class__.__name__}'s config object instead, e.g. 'scheduler.config.{name}'."
             deprecate("direct config name access", "1.0.0", deprecation_message, standard_warn=False)
             return self._internal_dict[name]
 
diff --git a/src/diffusers/models/modeling_utils.py b/src/diffusers/models/modeling_utils.py
index 533f1a3caacc..16941336eb2e 100644
--- a/src/diffusers/models/modeling_utils.py
+++ b/src/diffusers/models/modeling_utils.py
@@ -168,8 +168,8 @@ def __getattr__(self, name: str) -> Any:
         is_attribute = name in self.__dict__
 
         if is_in_config and not is_attribute:
-            deprecation_message = f"Accessing config attribute `{name}` directly via '{self.__class__.__name__}' object attribute is deprecated. Please access '{name}' over '{self.__class__.__name__}'s config object instead, e.g. 'unet.config.{name}' or 'scheduler.config.{name}'."
-            deprecate("direct config name access", "1.0.0", deprecation_message, standard_warn=False)
+            deprecation_message = f"Accessing config attribute `{name}` directly via '{self.__class__.__name__}' object attribute is deprecated. Please access '{name}' over '{self.__class__.__name__}'s config object instead, e.g. 'unet.config.{name}'."
+            deprecate("direct config name access", "1.0.0", deprecation_message, standard_warn=False, stacklevel=3)
             return self._internal_dict[name]
 
         # call PyTorch's https://pytorch.org/docs/stable/_modules/torch/nn/modules/module.html#Module
diff --git a/src/diffusers/pipelines/pipeline_utils.py b/src/diffusers/pipelines/pipeline_utils.py
index 94725185e69d..0af7ba36dc0d 100644
--- a/src/diffusers/pipelines/pipeline_utils.py
+++ b/src/diffusers/pipelines/pipeline_utils.py
@@ -648,26 +648,25 @@ def module_is_offloaded(module):
             )
 
         module_names, _ = self._get_signature_keys(self)
-        module_names = [m for m in module_names if hasattr(self, m)]
+        module_names = [m for m in module_names if isinstance(m, torch.nn.Module)]
 
         is_offloaded = pipeline_is_offloaded or pipeline_is_sequentially_offloaded
         for name in module_names:
             module = getattr(self, name)
-            if isinstance(module, torch.nn.Module):
-                module.to(torch_device, torch_dtype)
-                if (
-                    module.dtype == torch.float16
-                    and str(torch_device) in ["cpu"]
-                    and not silence_dtype_warnings
-                    and not is_offloaded
-                ):
-                    logger.warning(
-                        "Pipelines loaded with `torch_dtype=torch.float16` cannot run with `cpu` device. It"
-                        " is not recommended to move them to `cpu` as running them will fail. Please make"
-                        " sure to use an accelerator to run the pipeline in inference, due to the lack of"
-                        " support for`float16` operations on this device in PyTorch. Please, remove the"
-                        " `torch_dtype=torch.float16` argument, or use another device for inference."
-                    )
+            module.to(torch_device, torch_dtype)
+            if (
+                module.dtype == torch.float16
+                and str(torch_device) in ["cpu"]
+                and not silence_dtype_warnings
+                and not is_offloaded
+            ):
+                logger.warning(
+                    "Pipelines loaded with `torch_dtype=torch.float16` cannot run with `cpu` device. It"
+                    " is not recommended to move them to `cpu` as running them will fail. Please make"
+                    " sure to use an accelerator to run the pipeline in inference, due to the lack of"
+                    " support for`float16` operations on this device in PyTorch. Please, remove the"
+                    " `torch_dtype=torch.float16` argument, or use another device for inference."
+                )
         return self
 
     @property
@@ -677,12 +676,12 @@ def device(self) -> torch.device:
             `torch.device`: The torch device on which the pipeline is located.
         """
         module_names, _ = self._get_signature_keys(self)
-        module_names = [m for m in module_names if hasattr(self, m)]
+        module_names = [m for m in module_names if isinstance(m, torch.nn.Module)]
 
         for name in module_names:
             module = getattr(self, name)
-            if isinstance(module, torch.nn.Module):
-                return module.device
+            return module.device
+
         return torch.device("cpu")
 
     @classmethod
@@ -1452,12 +1451,11 @@ def fn_recursive_set_mem_eff(module: torch.nn.Module):
                 fn_recursive_set_mem_eff(child)
 
         module_names, _, _ = self.extract_init_dict(dict(self.config))
-        module_names = [m for m in module_names if hasattr(self, m)]
+        module_names = [m for m in module_names if isinstance(m, torch.nn.Module)]
 
         for module_name in module_names:
             module = getattr(self, module_name)
-            if isinstance(module, torch.nn.Module):
-                fn_recursive_set_mem_eff(module)
+            fn_recursive_set_mem_eff(module)
 
     def enable_attention_slicing(self, slice_size: Optional[Union[str, int]] = "auto"):
         r"""
@@ -1485,9 +1483,10 @@ def disable_attention_slicing(self):
 
     def set_attention_slice(self, slice_size: Optional[int]):
         module_names, _, _ = self.extract_init_dict(dict(self.config))
-        module_names = [m for m in module_names if hasattr(self, m)]
+        module_names = [
+            m for m in module_names if isinstance(m, torch.nn.Module) and hasattr(m, "set_attention_slice")
+        ]
 
         for module_name in module_names:
             module = getattr(self, module_name)
-            if isinstance(module, torch.nn.Module) and hasattr(module, "set_attention_slice"):
-                module.set_attention_slice(slice_size)
+            module.set_attention_slice(slice_size)
diff --git a/src/diffusers/utils/deprecation_utils.py b/src/diffusers/utils/deprecation_utils.py
index 6bdda664e102..f482deddd2f4 100644
--- a/src/diffusers/utils/deprecation_utils.py
+++ b/src/diffusers/utils/deprecation_utils.py
@@ -5,7 +5,7 @@
 from packaging import version
 
 
-def deprecate(*args, take_from: Optional[Union[Dict, Any]] = None, standard_warn=True):
+def deprecate(*args, take_from: Optional[Union[Dict, Any]] = None, standard_warn=True, stacklevel=2):
     from .. import __version__
 
     deprecated_kwargs = take_from
@@ -32,7 +32,7 @@ def deprecate(*args, take_from: Optional[Union[Dict, Any]] = None, standard_warn
 
         if warning is not None:
             warning = warning + " " if standard_warn else ""
-            warnings.warn(warning + message, FutureWarning, stacklevel=2)
+            warnings.warn(warning + message, FutureWarning, stacklevel=stacklevel)
 
     if isinstance(deprecated_kwargs, dict) and len(deprecated_kwargs) > 0:
         call_frame = inspect.getouterframes(inspect.currentframe())[1]

From 041fd125de54cebc608696061a390a4e8718ff35 Mon Sep 17 00:00:00 2001
From: Patrick von Platen <patrick.v.platen@gmail.com>
Date: Mon, 17 Apr 2023 13:15:05 +0000
Subject: [PATCH 12/16] more improvements

---
 src/diffusers/pipelines/pipeline_utils.py | 30 +++++++++++------------
 1 file changed, 14 insertions(+), 16 deletions(-)

diff --git a/src/diffusers/pipelines/pipeline_utils.py b/src/diffusers/pipelines/pipeline_utils.py
index 0af7ba36dc0d..ad8980944eac 100644
--- a/src/diffusers/pipelines/pipeline_utils.py
+++ b/src/diffusers/pipelines/pipeline_utils.py
@@ -648,11 +648,11 @@ def module_is_offloaded(module):
             )
 
         module_names, _ = self._get_signature_keys(self)
-        module_names = [m for m in module_names if isinstance(m, torch.nn.Module)]
+        modules = [getattr(self, n, None) for n in module_names]
+        modules = [m for m in modules if isinstance(m, torch.nn.Module)]
 
         is_offloaded = pipeline_is_offloaded or pipeline_is_sequentially_offloaded
-        for name in module_names:
-            module = getattr(self, name)
+        for module in modules:
             module.to(torch_device, torch_dtype)
             if (
                 module.dtype == torch.float16
@@ -676,10 +676,10 @@ def device(self) -> torch.device:
             `torch.device`: The torch device on which the pipeline is located.
         """
         module_names, _ = self._get_signature_keys(self)
-        module_names = [m for m in module_names if isinstance(m, torch.nn.Module)]
+        modules = [getattr(self, n, None) for n in module_names]
+        modules = [m for m in modules if isinstance(m, torch.nn.Module)]
 
-        for name in module_names:
-            module = getattr(self, name)
+        for module in modules:
             return module.device
 
         return torch.device("cpu")
@@ -1450,11 +1450,11 @@ def fn_recursive_set_mem_eff(module: torch.nn.Module):
             for child in module.children():
                 fn_recursive_set_mem_eff(child)
 
-        module_names, _, _ = self.extract_init_dict(dict(self.config))
-        module_names = [m for m in module_names if isinstance(m, torch.nn.Module)]
+        module_names, _ = self._get_signature_keys(self)
+        modules = [getattr(self, n, None) for n in module_names]
+        modules = [m for m in modules if isinstance(m, torch.nn.Module)]
 
-        for module_name in module_names:
-            module = getattr(self, module_name)
+        for module in modules:
             fn_recursive_set_mem_eff(module)
 
     def enable_attention_slicing(self, slice_size: Optional[Union[str, int]] = "auto"):
@@ -1482,11 +1482,9 @@ def disable_attention_slicing(self):
         self.enable_attention_slicing(None)
 
     def set_attention_slice(self, slice_size: Optional[int]):
-        module_names, _, _ = self.extract_init_dict(dict(self.config))
-        module_names = [
-            m for m in module_names if isinstance(m, torch.nn.Module) and hasattr(m, "set_attention_slice")
-        ]
+        module_names, _ = self._get_signature_keys(self)
+        modules = [getattr(self, n, None) for n in module_names]
+        modules = [m for m in modules if isinstance(m, torch.nn.Module) and hasattr(m, "set_attention_slice")]
 
-        for module_name in module_names:
-            module = getattr(self, module_name)
+        for module in modules:
             module.set_attention_slice(slice_size)

From b07e42c74ca5f69e9b068a50c44a14182a8fa56e Mon Sep 17 00:00:00 2001
From: Patrick von Platen <patrick.v.platen@gmail.com>
Date: Mon, 17 Apr 2023 13:20:24 +0000
Subject: [PATCH 13/16] fix more

---
 src/diffusers/models/unet_2d_condition.py | 12 +-----------
 1 file changed, 1 insertion(+), 11 deletions(-)

diff --git a/src/diffusers/models/unet_2d_condition.py b/src/diffusers/models/unet_2d_condition.py
index 1b982aedc5de..b2814356939b 100644
--- a/src/diffusers/models/unet_2d_condition.py
+++ b/src/diffusers/models/unet_2d_condition.py
@@ -21,7 +21,7 @@
 
 from ..configuration_utils import ConfigMixin, register_to_config
 from ..loaders import UNet2DConditionLoadersMixin
-from ..utils import BaseOutput, deprecate, logging
+from ..utils import BaseOutput, logging
 from .attention_processor import AttentionProcessor, AttnProcessor
 from .embeddings import GaussianFourierProjection, TimestepEmbedding, Timesteps
 from .modeling_utils import ModelMixin
@@ -447,16 +447,6 @@ def __init__(
             block_out_channels[0], out_channels, kernel_size=conv_out_kernel, padding=conv_out_padding
         )
 
-    @property
-    def in_channels(self):
-        deprecate(
-            "in_channels",
-            "1.0.0",
-            "Accessing `in_channels` directly via unet.in_channels is deprecated. Please use `unet.config.in_channels` instead",
-            standard_warn=False,
-        )
-        return self.config.in_channels
-
     @property
     def attn_processors(self) -> Dict[str, AttentionProcessor]:
         r"""

From 72d9bd56052eb5ab709a9709f49d5a6d43bc9e8b Mon Sep 17 00:00:00 2001
From: Patrick von Platen <patrick.v.platen@gmail.com>
Date: Mon, 17 Apr 2023 14:22:46 +0100
Subject: [PATCH 14/16] Apply suggestions from code review

Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
---
 src/diffusers/configuration_utils.py   | 2 +-
 src/diffusers/models/modeling_utils.py | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/diffusers/configuration_utils.py b/src/diffusers/configuration_utils.py
index fe9047137b4e..772e119fbe97 100644
--- a/src/diffusers/configuration_utils.py
+++ b/src/diffusers/configuration_utils.py
@@ -130,7 +130,7 @@ def __getattr__(self, name: str) -> Any:
         is_attribute = name in self.__dict__
 
         if is_in_config and not is_attribute:
-            deprecation_message = f"Accessing config attribute `{name}` directly via '{self.__class__.__name__}' object attribute is deprecated. Please access '{name}' over '{self.__class__.__name__}'s config object instead, e.g. 'scheduler.config.{name}'."
+            deprecation_message = f"Accessing config attribute `{name}` directly via '{type(self).__name__}' object attribute is deprecated. Please access '{name}' over '{type(self).__name__}'s config object instead, e.g. 'scheduler.config.{name}'."
             deprecate("direct config name access", "1.0.0", deprecation_message, standard_warn=False)
             return self._internal_dict[name]
 
diff --git a/src/diffusers/models/modeling_utils.py b/src/diffusers/models/modeling_utils.py
index 16941336eb2e..5363e6330623 100644
--- a/src/diffusers/models/modeling_utils.py
+++ b/src/diffusers/models/modeling_utils.py
@@ -168,7 +168,7 @@ def __getattr__(self, name: str) -> Any:
         is_attribute = name in self.__dict__
 
         if is_in_config and not is_attribute:
-            deprecation_message = f"Accessing config attribute `{name}` directly via '{self.__class__.__name__}' object attribute is deprecated. Please access '{name}' over '{self.__class__.__name__}'s config object instead, e.g. 'unet.config.{name}'."
+            deprecation_message = f"Accessing config attribute `{name}` directly via '{type(self).__name__}' object attribute is deprecated. Please access '{name}' over '{type(self).__name__}'s config object instead, e.g. 'unet.config.{name}'."
             deprecate("direct config name access", "1.0.0", deprecation_message, standard_warn=False, stacklevel=3)
             return self._internal_dict[name]
 

From f19468647d6d3c13a9b2601eabaefb34b110cfd8 Mon Sep 17 00:00:00 2001
From: Patrick von Platen <patrick.v.platen@gmail.com>
Date: Mon, 17 Apr 2023 13:23:18 +0000
Subject: [PATCH 15/16] make style

---
 .../versatile_diffusion/modeling_text_unet.py     | 15 +--------------
 1 file changed, 1 insertion(+), 14 deletions(-)

diff --git a/src/diffusers/pipelines/versatile_diffusion/modeling_text_unet.py b/src/diffusers/pipelines/versatile_diffusion/modeling_text_unet.py
index 35ddfcadc3cb..4377be1181a8 100644
--- a/src/diffusers/pipelines/versatile_diffusion/modeling_text_unet.py
+++ b/src/diffusers/pipelines/versatile_diffusion/modeling_text_unet.py
@@ -18,7 +18,7 @@
 from ...models.embeddings import GaussianFourierProjection, TimestepEmbedding, Timesteps
 from ...models.transformer_2d import Transformer2DModel
 from ...models.unet_2d_condition import UNet2DConditionOutput
-from ...utils import deprecate, logging
+from ...utils import logging
 
 
 logger = logging.get_logger(__name__)  # pylint: disable=invalid-name
@@ -544,19 +544,6 @@ def __init__(
             block_out_channels[0], out_channels, kernel_size=conv_out_kernel, padding=conv_out_padding
         )
 
-    @property
-    def in_channels(self):
-        deprecate(
-            "in_channels",
-            "1.0.0",
-            (
-                "Accessing `in_channels` directly via unet.in_channels is deprecated. Please use"
-                " `unet.config.in_channels` instead"
-            ),
-            standard_warn=False,
-        )
-        return self.config.in_channels
-
     @property
     def attn_processors(self) -> Dict[str, AttentionProcessor]:
         r"""

From b5de4e8b0194ca2e868a096d54a91dd923ac4a14 Mon Sep 17 00:00:00 2001
From: Patrick von Platen <patrick.v.platen@gmail.com>
Date: Mon, 17 Apr 2023 15:54:22 +0000
Subject: [PATCH 16/16] Fix all rest & add tests & remove old deprecation fns

---
 .../community/unclip_image_interpolation.py   | 12 ++---
 .../community/unclip_text_interpolation.py    | 12 ++---
 src/diffusers/models/autoencoder_kl.py        | 12 +----
 src/diffusers/models/unet_1d.py               | 12 +----
 .../pipeline_text_to_video_zero.py            |  2 +-
 .../pipelines/unclip/pipeline_unclip.py       | 12 ++---
 .../unclip/pipeline_unclip_image_variation.py | 12 ++---
 ...ipeline_versatile_diffusion_dual_guided.py |  2 +-
 ...ine_versatile_diffusion_image_variation.py |  2 +-
 ...eline_versatile_diffusion_text_to_image.py |  2 +-
 src/diffusers/schedulers/scheduling_ddpm.py   | 12 +----
 tests/models/test_modeling_common.py          | 47 ++++++++++++++++++-
 tests/pipelines/unclip/test_unclip.py         |  8 ++--
 .../unclip/test_unclip_image_variation.py     | 13 +++--
 tests/schedulers/test_schedulers.py           | 44 +++++++++++++++++
 15 files changed, 133 insertions(+), 71 deletions(-)

diff --git a/examples/community/unclip_image_interpolation.py b/examples/community/unclip_image_interpolation.py
index d0b54125b688..453ac07af7c6 100644
--- a/examples/community/unclip_image_interpolation.py
+++ b/examples/community/unclip_image_interpolation.py
@@ -372,9 +372,9 @@ def __call__(
         self.decoder_scheduler.set_timesteps(decoder_num_inference_steps, device=device)
         decoder_timesteps_tensor = self.decoder_scheduler.timesteps
 
-        num_channels_latents = self.decoder.in_channels
-        height = self.decoder.sample_size
-        width = self.decoder.sample_size
+        num_channels_latents = self.decoder.config.in_channels
+        height = self.decoder.config.sample_size
+        width = self.decoder.config.sample_size
 
         decoder_latents = self.prepare_latents(
             (batch_size, num_channels_latents, height, width),
@@ -425,9 +425,9 @@ def __call__(
         self.super_res_scheduler.set_timesteps(super_res_num_inference_steps, device=device)
         super_res_timesteps_tensor = self.super_res_scheduler.timesteps
 
-        channels = self.super_res_first.in_channels // 2
-        height = self.super_res_first.sample_size
-        width = self.super_res_first.sample_size
+        channels = self.super_res_first.config.in_channels // 2
+        height = self.super_res_first.config.sample_size
+        width = self.super_res_first.config.sample_size
 
         super_res_latents = self.prepare_latents(
             (batch_size, channels, height, width),
diff --git a/examples/community/unclip_text_interpolation.py b/examples/community/unclip_text_interpolation.py
index ac6b73d974b6..290f45317004 100644
--- a/examples/community/unclip_text_interpolation.py
+++ b/examples/community/unclip_text_interpolation.py
@@ -452,9 +452,9 @@ def __call__(
         self.decoder_scheduler.set_timesteps(decoder_num_inference_steps, device=device)
         decoder_timesteps_tensor = self.decoder_scheduler.timesteps
 
-        num_channels_latents = self.decoder.in_channels
-        height = self.decoder.sample_size
-        width = self.decoder.sample_size
+        num_channels_latents = self.decoder.config.in_channels
+        height = self.decoder.config.sample_size
+        width = self.decoder.config.sample_size
 
         decoder_latents = self.prepare_latents(
             (batch_size, num_channels_latents, height, width),
@@ -505,9 +505,9 @@ def __call__(
         self.super_res_scheduler.set_timesteps(super_res_num_inference_steps, device=device)
         super_res_timesteps_tensor = self.super_res_scheduler.timesteps
 
-        channels = self.super_res_first.in_channels // 2
-        height = self.super_res_first.sample_size
-        width = self.super_res_first.sample_size
+        channels = self.super_res_first.config.in_channels // 2
+        height = self.super_res_first.config.sample_size
+        width = self.super_res_first.config.sample_size
 
         super_res_latents = self.prepare_latents(
             (batch_size, channels, height, width),
diff --git a/src/diffusers/models/autoencoder_kl.py b/src/diffusers/models/autoencoder_kl.py
index 5d1c54a9af25..1a8a204d80ce 100644
--- a/src/diffusers/models/autoencoder_kl.py
+++ b/src/diffusers/models/autoencoder_kl.py
@@ -18,7 +18,7 @@
 import torch.nn as nn
 
 from ..configuration_utils import ConfigMixin, register_to_config
-from ..utils import BaseOutput, apply_forward_hook, deprecate
+from ..utils import BaseOutput, apply_forward_hook
 from .modeling_utils import ModelMixin
 from .vae import Decoder, DecoderOutput, DiagonalGaussianDistribution, Encoder
 
@@ -123,16 +123,6 @@ def __init__(
         self.tile_latent_min_size = int(sample_size / (2 ** (len(self.config.block_out_channels) - 1)))
         self.tile_overlap_factor = 0.25
 
-    @property
-    def block_out_channels(self):
-        deprecate(
-            "block_out_channels",
-            "1.0.0",
-            "Accessing `block_out_channels` directly via vae.block_out_channels is deprecated. Please use `vae.config.block_out_channels instead`",
-            standard_warn=False,
-        )
-        return self.config.block_out_channels
-
     def _set_gradient_checkpointing(self, module, value=False):
         if isinstance(module, (Encoder, Decoder)):
             module.gradient_checkpointing = value
diff --git a/src/diffusers/models/unet_1d.py b/src/diffusers/models/unet_1d.py
index c7755bb3ed45..34a1d2b5160e 100644
--- a/src/diffusers/models/unet_1d.py
+++ b/src/diffusers/models/unet_1d.py
@@ -19,7 +19,7 @@
 import torch.nn as nn
 
 from ..configuration_utils import ConfigMixin, register_to_config
-from ..utils import BaseOutput, deprecate
+from ..utils import BaseOutput
 from .embeddings import GaussianFourierProjection, TimestepEmbedding, Timesteps
 from .modeling_utils import ModelMixin
 from .unet_1d_blocks import get_down_block, get_mid_block, get_out_block, get_up_block
@@ -190,16 +190,6 @@ def __init__(
             fc_dim=block_out_channels[-1] // 4,
         )
 
-    @property
-    def in_channels(self):
-        deprecate(
-            "in_channels",
-            "1.0.0",
-            "Accessing `in_channels` directly via unet.in_channels is deprecated. Please use `unet.config.in_channels` instead",
-            standard_warn=False,
-        )
-        return self.config.in_channels
-
     def forward(
         self,
         sample: torch.FloatTensor,
diff --git a/src/diffusers/pipelines/text_to_video_synthesis/pipeline_text_to_video_zero.py b/src/diffusers/pipelines/text_to_video_synthesis/pipeline_text_to_video_zero.py
index cf5e6e399a77..5b163bbbc8f5 100644
--- a/src/diffusers/pipelines/text_to_video_synthesis/pipeline_text_to_video_zero.py
+++ b/src/diffusers/pipelines/text_to_video_synthesis/pipeline_text_to_video_zero.py
@@ -441,7 +441,7 @@ def __call__(
         timesteps = self.scheduler.timesteps
 
         # Prepare latent variables
-        num_channels_latents = self.unet.in_channels
+        num_channels_latents = self.unet.config.in_channels
         latents = self.prepare_latents(
             batch_size * num_videos_per_prompt,
             num_channels_latents,
diff --git a/src/diffusers/pipelines/unclip/pipeline_unclip.py b/src/diffusers/pipelines/unclip/pipeline_unclip.py
index 3aac39b3a3b0..abbb48ce8f46 100644
--- a/src/diffusers/pipelines/unclip/pipeline_unclip.py
+++ b/src/diffusers/pipelines/unclip/pipeline_unclip.py
@@ -413,9 +413,9 @@ def __call__(
         self.decoder_scheduler.set_timesteps(decoder_num_inference_steps, device=device)
         decoder_timesteps_tensor = self.decoder_scheduler.timesteps
 
-        num_channels_latents = self.decoder.in_channels
-        height = self.decoder.sample_size
-        width = self.decoder.sample_size
+        num_channels_latents = self.decoder.config.in_channels
+        height = self.decoder.config.sample_size
+        width = self.decoder.config.sample_size
 
         decoder_latents = self.prepare_latents(
             (batch_size, num_channels_latents, height, width),
@@ -466,9 +466,9 @@ def __call__(
         self.super_res_scheduler.set_timesteps(super_res_num_inference_steps, device=device)
         super_res_timesteps_tensor = self.super_res_scheduler.timesteps
 
-        channels = self.super_res_first.in_channels // 2
-        height = self.super_res_first.sample_size
-        width = self.super_res_first.sample_size
+        channels = self.super_res_first.config.in_channels // 2
+        height = self.super_res_first.config.sample_size
+        width = self.super_res_first.config.sample_size
 
         super_res_latents = self.prepare_latents(
             (batch_size, channels, height, width),
diff --git a/src/diffusers/pipelines/unclip/pipeline_unclip_image_variation.py b/src/diffusers/pipelines/unclip/pipeline_unclip_image_variation.py
index 56d522354d9a..30d74cd36bb0 100644
--- a/src/diffusers/pipelines/unclip/pipeline_unclip_image_variation.py
+++ b/src/diffusers/pipelines/unclip/pipeline_unclip_image_variation.py
@@ -339,9 +339,9 @@ def __call__(
         self.decoder_scheduler.set_timesteps(decoder_num_inference_steps, device=device)
         decoder_timesteps_tensor = self.decoder_scheduler.timesteps
 
-        num_channels_latents = self.decoder.in_channels
-        height = self.decoder.sample_size
-        width = self.decoder.sample_size
+        num_channels_latents = self.decoder.config.in_channels
+        height = self.decoder.config.sample_size
+        width = self.decoder.config.sample_size
 
         if decoder_latents is None:
             decoder_latents = self.prepare_latents(
@@ -393,9 +393,9 @@ def __call__(
         self.super_res_scheduler.set_timesteps(super_res_num_inference_steps, device=device)
         super_res_timesteps_tensor = self.super_res_scheduler.timesteps
 
-        channels = self.super_res_first.in_channels // 2
-        height = self.super_res_first.sample_size
-        width = self.super_res_first.sample_size
+        channels = self.super_res_first.config.in_channels // 2
+        height = self.super_res_first.config.sample_size
+        width = self.super_res_first.config.sample_size
 
         if super_res_latents is None:
             super_res_latents = self.prepare_latents(
diff --git a/src/diffusers/pipelines/versatile_diffusion/pipeline_versatile_diffusion_dual_guided.py b/src/diffusers/pipelines/versatile_diffusion/pipeline_versatile_diffusion_dual_guided.py
index 0f385ed6612c..661a1bd3cf73 100644
--- a/src/diffusers/pipelines/versatile_diffusion/pipeline_versatile_diffusion_dual_guided.py
+++ b/src/diffusers/pipelines/versatile_diffusion/pipeline_versatile_diffusion_dual_guided.py
@@ -533,7 +533,7 @@ def __call__(
         timesteps = self.scheduler.timesteps
 
         # 5. Prepare latent variables
-        num_channels_latents = self.image_unet.in_channels
+        num_channels_latents = self.image_unet.config.in_channels
         latents = self.prepare_latents(
             batch_size * num_images_per_prompt,
             num_channels_latents,
diff --git a/src/diffusers/pipelines/versatile_diffusion/pipeline_versatile_diffusion_image_variation.py b/src/diffusers/pipelines/versatile_diffusion/pipeline_versatile_diffusion_image_variation.py
index 2b47184d7773..e3a2ee370362 100644
--- a/src/diffusers/pipelines/versatile_diffusion/pipeline_versatile_diffusion_image_variation.py
+++ b/src/diffusers/pipelines/versatile_diffusion/pipeline_versatile_diffusion_image_variation.py
@@ -378,7 +378,7 @@ def __call__(
         timesteps = self.scheduler.timesteps
 
         # 5. Prepare latent variables
-        num_channels_latents = self.image_unet.in_channels
+        num_channels_latents = self.image_unet.config.in_channels
         latents = self.prepare_latents(
             batch_size * num_images_per_prompt,
             num_channels_latents,
diff --git a/src/diffusers/pipelines/versatile_diffusion/pipeline_versatile_diffusion_text_to_image.py b/src/diffusers/pipelines/versatile_diffusion/pipeline_versatile_diffusion_text_to_image.py
index fdca625fd99d..26b9be2bfa76 100644
--- a/src/diffusers/pipelines/versatile_diffusion/pipeline_versatile_diffusion_text_to_image.py
+++ b/src/diffusers/pipelines/versatile_diffusion/pipeline_versatile_diffusion_text_to_image.py
@@ -452,7 +452,7 @@ def __call__(
         timesteps = self.scheduler.timesteps
 
         # 5. Prepare latent variables
-        num_channels_latents = self.image_unet.in_channels
+        num_channels_latents = self.image_unet.config.in_channels
         latents = self.prepare_latents(
             batch_size * num_images_per_prompt,
             num_channels_latents,
diff --git a/src/diffusers/schedulers/scheduling_ddpm.py b/src/diffusers/schedulers/scheduling_ddpm.py
index 2bc34bb8b444..a8a71fe420aa 100644
--- a/src/diffusers/schedulers/scheduling_ddpm.py
+++ b/src/diffusers/schedulers/scheduling_ddpm.py
@@ -22,7 +22,7 @@
 import torch
 
 from ..configuration_utils import ConfigMixin, register_to_config
-from ..utils import BaseOutput, deprecate, randn_tensor
+from ..utils import BaseOutput, randn_tensor
 from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin
 
 
@@ -168,16 +168,6 @@ def __init__(
 
         self.variance_type = variance_type
 
-    @property
-    def num_train_timesteps(self):
-        deprecate(
-            "num_train_timesteps",
-            "1.0.0",
-            "Accessing `num_train_timesteps` directly via scheduler.num_train_timesteps is deprecated. Please use `scheduler.config.num_train_timesteps instead`",
-            standard_warn=False,
-        )
-        return self.config.num_train_timesteps
-
     def scale_model_input(self, sample: torch.FloatTensor, timestep: Optional[int] = None) -> torch.FloatTensor:
         """
         Ensures interchangeability with schedulers that need to scale the denoising model input depending on the
diff --git a/tests/models/test_modeling_common.py b/tests/models/test_modeling_common.py
index 40aba3b24967..4a94a77fcabb 100644
--- a/tests/models/test_modeling_common.py
+++ b/tests/models/test_modeling_common.py
@@ -26,8 +26,8 @@
 
 from diffusers.models import UNet2DConditionModel
 from diffusers.training_utils import EMAModel
-from diffusers.utils import torch_device
-from diffusers.utils.testing_utils import require_torch_gpu
+from diffusers.utils import logging, torch_device
+from diffusers.utils.testing_utils import CaptureLogger, require_torch_gpu
 
 
 class ModelUtilsTest(unittest.TestCase):
@@ -155,6 +155,49 @@ def test_from_save_pretrained(self):
         max_diff = (image - new_image).abs().sum().item()
         self.assertLessEqual(max_diff, 5e-5, "Models give different forward passes")
 
+    def test_getattr_is_correct(self):
+        init_dict, inputs_dict = self.prepare_init_args_and_inputs_for_common()
+        model = self.model_class(**init_dict)
+
+        # save some things to test
+        model.dummy_attribute = 5
+        model.register_to_config(test_attribute=5)
+
+        logger = logging.get_logger("diffusers.models.modeling_utils")
+        # 30 for warning
+        logger.setLevel(30)
+        with CaptureLogger(logger) as cap_logger:
+            assert hasattr(model, "dummy_attribute")
+            assert getattr(model, "dummy_attribute") == 5
+            assert model.dummy_attribute == 5
+
+        # no warning should be thrown
+        assert cap_logger.out == ""
+
+        logger = logging.get_logger("diffusers.models.modeling_utils")
+        # 30 for warning
+        logger.setLevel(30)
+        with CaptureLogger(logger) as cap_logger:
+            assert hasattr(model, "save_pretrained")
+            fn = model.save_pretrained
+            fn_1 = getattr(model, "save_pretrained")
+
+            assert fn == fn_1
+        # no warning should be thrown
+        assert cap_logger.out == ""
+
+        # warning should be thrown
+        with self.assertWarns(FutureWarning):
+            assert model.test_attribute == 5
+
+        with self.assertWarns(FutureWarning):
+            assert getattr(model, "test_attribute") == 5
+
+        with self.assertRaises(AttributeError) as error:
+            model.does_not_exist
+
+        assert str(error.exception) == f"'{type(model).__name__}' object has no attribute 'does_not_exist'"
+
     def test_from_save_pretrained_variant(self):
         init_dict, inputs_dict = self.prepare_init_args_and_inputs_for_common()
 
diff --git a/tests/pipelines/unclip/test_unclip.py b/tests/pipelines/unclip/test_unclip.py
index 4df3e4d3828b..d2c699ea501d 100644
--- a/tests/pipelines/unclip/test_unclip.py
+++ b/tests/pipelines/unclip/test_unclip.py
@@ -293,16 +293,16 @@ class DummyScheduler:
         prior_latents = pipe.prepare_latents(
             shape, dtype=dtype, device=device, generator=generator, latents=None, scheduler=DummyScheduler()
         )
-        shape = (batch_size, decoder.in_channels, decoder.sample_size, decoder.sample_size)
+        shape = (batch_size, decoder.config.in_channels, decoder.config.sample_size, decoder.config.sample_size)
         decoder_latents = pipe.prepare_latents(
             shape, dtype=dtype, device=device, generator=generator, latents=None, scheduler=DummyScheduler()
         )
 
         shape = (
             batch_size,
-            super_res_first.in_channels // 2,
-            super_res_first.sample_size,
-            super_res_first.sample_size,
+            super_res_first.config.in_channels // 2,
+            super_res_first.config.sample_size,
+            super_res_first.config.sample_size,
         )
         super_res_latents = pipe.prepare_latents(
             shape, dtype=dtype, device=device, generator=generator, latents=None, scheduler=DummyScheduler()
diff --git a/tests/pipelines/unclip/test_unclip_image_variation.py b/tests/pipelines/unclip/test_unclip_image_variation.py
index 57d15559cc75..c1b8be9cd49e 100644
--- a/tests/pipelines/unclip/test_unclip_image_variation.py
+++ b/tests/pipelines/unclip/test_unclip_image_variation.py
@@ -379,16 +379,21 @@ class DummyScheduler:
         dtype = pipe.decoder.dtype
         batch_size = 1
 
-        shape = (batch_size, pipe.decoder.in_channels, pipe.decoder.sample_size, pipe.decoder.sample_size)
+        shape = (
+            batch_size,
+            pipe.decoder.config.in_channels,
+            pipe.decoder.config.sample_size,
+            pipe.decoder.config.sample_size,
+        )
         decoder_latents = pipe.prepare_latents(
             shape, dtype=dtype, device=device, generator=generator, latents=None, scheduler=DummyScheduler()
         )
 
         shape = (
             batch_size,
-            pipe.super_res_first.in_channels // 2,
-            pipe.super_res_first.sample_size,
-            pipe.super_res_first.sample_size,
+            pipe.super_res_first.config.in_channels // 2,
+            pipe.super_res_first.config.sample_size,
+            pipe.super_res_first.config.sample_size,
         )
         super_res_latents = pipe.prepare_latents(
             shape, dtype=dtype, device=device, generator=generator, latents=None, scheduler=DummyScheduler()
diff --git a/tests/schedulers/test_schedulers.py b/tests/schedulers/test_schedulers.py
index bfbf5cbc798f..69cddb36dde2 100755
--- a/tests/schedulers/test_schedulers.py
+++ b/tests/schedulers/test_schedulers.py
@@ -596,3 +596,47 @@ def test_trained_betas(self):
                 new_scheduler = scheduler_class.from_pretrained(tmpdirname)
 
             assert scheduler.betas.tolist() == new_scheduler.betas.tolist()
+
+    def test_getattr_is_correct(self):
+        for scheduler_class in self.scheduler_classes:
+            scheduler_config = self.get_scheduler_config()
+            scheduler = scheduler_class(**scheduler_config)
+
+            # save some things to test
+            scheduler.dummy_attribute = 5
+            scheduler.register_to_config(test_attribute=5)
+
+            logger = logging.get_logger("diffusers.configuration_utils")
+            # 30 for warning
+            logger.setLevel(30)
+            with CaptureLogger(logger) as cap_logger:
+                assert hasattr(scheduler, "dummy_attribute")
+                assert getattr(scheduler, "dummy_attribute") == 5
+                assert scheduler.dummy_attribute == 5
+
+            # no warning should be thrown
+            assert cap_logger.out == ""
+
+            logger = logging.get_logger("diffusers.schedulers.schedulering_utils")
+            # 30 for warning
+            logger.setLevel(30)
+            with CaptureLogger(logger) as cap_logger:
+                assert hasattr(scheduler, "save_pretrained")
+                fn = scheduler.save_pretrained
+                fn_1 = getattr(scheduler, "save_pretrained")
+
+                assert fn == fn_1
+            # no warning should be thrown
+            assert cap_logger.out == ""
+
+            # warning should be thrown
+            with self.assertWarns(FutureWarning):
+                assert scheduler.test_attribute == 5
+
+            with self.assertWarns(FutureWarning):
+                assert getattr(scheduler, "test_attribute") == 5
+
+            with self.assertRaises(AttributeError) as error:
+                scheduler.does_not_exist
+
+            assert str(error.exception) == f"'{type(scheduler).__name__}' object has no attribute 'does_not_exist'"