diff --git a/src/diffusers/pipelines/ddim/pipeline_ddim.py b/src/diffusers/pipelines/ddim/pipeline_ddim.py
index 95b49e045f67..17b8ec83a9a4 100644
--- a/src/diffusers/pipelines/ddim/pipeline_ddim.py
+++ b/src/diffusers/pipelines/ddim/pipeline_ddim.py
@@ -14,7 +14,6 @@
 # limitations under the License.
 
 
-import warnings
 from typing import Optional, Tuple, Union
 
 import torch
@@ -74,20 +73,6 @@ def __call__(
             generated images.
         """
 
-        if "torch_device" in kwargs:
-            device = kwargs.pop("torch_device")
-            warnings.warn(
-                "`torch_device` is deprecated as an input argument to `__call__` and will be removed in v0.3.0."
-                " Consider using `pipe.to(torch_device)` instead."
-            )
-
-            # Set device as before (to be removed in 0.3.0)
-            if device is None:
-                device = "cuda" if torch.cuda.is_available() else "cpu"
-            self.to(device)
-
-        # eta corresponds to η in paper and should be between [0, 1]
-
         # Sample gaussian noise to begin loop
         image = torch.randn(
             (batch_size, self.unet.in_channels, self.unet.sample_size, self.unet.sample_size),
@@ -103,6 +88,7 @@ def __call__(
             model_output = self.unet(image, t).sample
 
             # 2. predict previous mean of image x_t-1 and add variance depending on eta
+            # eta corresponds to η in paper and should be between [0, 1]
             # do x_t -> x_t-1
             image = self.scheduler.step(model_output, t, image, eta).prev_sample
 
diff --git a/src/diffusers/pipelines/ddpm/pipeline_ddpm.py b/src/diffusers/pipelines/ddpm/pipeline_ddpm.py
index b7f7093e379b..9f62a6a1258a 100644
--- a/src/diffusers/pipelines/ddpm/pipeline_ddpm.py
+++ b/src/diffusers/pipelines/ddpm/pipeline_ddpm.py
@@ -14,7 +14,6 @@
 # limitations under the License.
 
 
-import warnings
 from typing import Optional, Tuple, Union
 
 import torch
@@ -66,17 +65,6 @@ def __call__(
             `return_dict` is True, otherwise a `tuple. When returning a tuple, the first element is a list with the
             generated images.
         """
-        if "torch_device" in kwargs:
-            device = kwargs.pop("torch_device")
-            warnings.warn(
-                "`torch_device` is deprecated as an input argument to `__call__` and will be removed in v0.3.0."
-                " Consider using `pipe.to(torch_device)` instead."
-            )
-
-            # Set device as before (to be removed in 0.3.0)
-            if device is None:
-                device = "cuda" if torch.cuda.is_available() else "cpu"
-            self.to(device)
 
         # Sample gaussian noise to begin loop
         image = torch.randn(
diff --git a/src/diffusers/pipelines/latent_diffusion/pipeline_latent_diffusion.py b/src/diffusers/pipelines/latent_diffusion/pipeline_latent_diffusion.py
index 43b734c97c39..dbf2e792f29b 100644
--- a/src/diffusers/pipelines/latent_diffusion/pipeline_latent_diffusion.py
+++ b/src/diffusers/pipelines/latent_diffusion/pipeline_latent_diffusion.py
@@ -1,5 +1,4 @@
 import inspect
-import warnings
 from typing import List, Optional, Tuple, Union
 
 import torch
@@ -94,17 +93,6 @@ def __call__(
             `return_dict` is True, otherwise a `tuple. When returning a tuple, the first element is a list with the
             generated images.
         """
-        if "torch_device" in kwargs:
-            device = kwargs.pop("torch_device")
-            warnings.warn(
-                "`torch_device` is deprecated as an input argument to `__call__` and will be removed in v0.3.0."
-                " Consider using `pipe.to(torch_device)` instead."
-            )
-
-            # Set device as before (to be removed in 0.3.0)
-            if device is None:
-                device = "cuda" if torch.cuda.is_available() else "cpu"
-            self.to(device)
 
         if isinstance(prompt, str):
             batch_size = 1
diff --git a/src/diffusers/pipelines/latent_diffusion_uncond/pipeline_latent_diffusion_uncond.py b/src/diffusers/pipelines/latent_diffusion_uncond/pipeline_latent_diffusion_uncond.py
index 5574b65df9f8..b7104bd709c6 100644
--- a/src/diffusers/pipelines/latent_diffusion_uncond/pipeline_latent_diffusion_uncond.py
+++ b/src/diffusers/pipelines/latent_diffusion_uncond/pipeline_latent_diffusion_uncond.py
@@ -1,5 +1,4 @@
 import inspect
-import warnings
 from typing import Optional, Tuple, Union
 
 import torch
@@ -60,18 +59,6 @@ def __call__(
             generated images.
         """
 
-        if "torch_device" in kwargs:
-            device = kwargs.pop("torch_device")
-            warnings.warn(
-                "`torch_device` is deprecated as an input argument to `__call__` and will be removed in v0.3.0."
-                " Consider using `pipe.to(torch_device)` instead."
-            )
-
-            # Set device as before (to be removed in 0.3.0)
-            if device is None:
-                device = "cuda" if torch.cuda.is_available() else "cpu"
-            self.to(device)
-
         latents = torch.randn(
             (batch_size, self.unet.in_channels, self.unet.sample_size, self.unet.sample_size),
             generator=generator,
diff --git a/src/diffusers/pipelines/pndm/pipeline_pndm.py b/src/diffusers/pipelines/pndm/pipeline_pndm.py
index ae6c10e9e967..483f86da16db 100644
--- a/src/diffusers/pipelines/pndm/pipeline_pndm.py
+++ b/src/diffusers/pipelines/pndm/pipeline_pndm.py
@@ -14,7 +14,6 @@
 # limitations under the License.
 
 
-import warnings
 from typing import Optional, Tuple, Union
 
 import torch
@@ -75,18 +74,6 @@ def __call__(
         # For more information on the sampling method you can take a look at Algorithm 2 of
         # the official paper: https://arxiv.org/pdf/2202.09778.pdf
 
-        if "torch_device" in kwargs:
-            device = kwargs.pop("torch_device")
-            warnings.warn(
-                "`torch_device` is deprecated as an input argument to `__call__` and will be removed in v0.3.0."
-                " Consider using `pipe.to(torch_device)` instead."
-            )
-
-            # Set device as before (to be removed in 0.3.0)
-            if device is None:
-                device = "cuda" if torch.cuda.is_available() else "cpu"
-            self.to(device)
-
         # Sample gaussian noise to begin loop
         image = torch.randn(
             (batch_size, self.unet.in_channels, self.unet.sample_size, self.unet.sample_size),
diff --git a/src/diffusers/pipelines/score_sde_ve/pipeline_score_sde_ve.py b/src/diffusers/pipelines/score_sde_ve/pipeline_score_sde_ve.py
index b29795e7f661..1907fc7d50d8 100644
--- a/src/diffusers/pipelines/score_sde_ve/pipeline_score_sde_ve.py
+++ b/src/diffusers/pipelines/score_sde_ve/pipeline_score_sde_ve.py
@@ -1,5 +1,4 @@
 #!/usr/bin/env python3
-import warnings
 from typing import Optional, Tuple, Union
 
 import torch
@@ -53,18 +52,6 @@ def __call__(
             generated images.
         """
 
-        if "torch_device" in kwargs:
-            device = kwargs.pop("torch_device")
-            warnings.warn(
-                "`torch_device` is deprecated as an input argument to `__call__` and will be removed in v0.3.0."
-                " Consider using `pipe.to(torch_device)` instead."
-            )
-
-            # Set device as before (to be removed in 0.3.0)
-            if device is None:
-                device = "cuda" if torch.cuda.is_available() else "cpu"
-            self.to(device)
-
         img_size = self.unet.config.sample_size
         shape = (batch_size, 3, img_size, img_size)
 
diff --git a/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py b/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py
index 216a76a55997..d4e41d699b3c 100644
--- a/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py
+++ b/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py
@@ -165,18 +165,6 @@ def __call__(
             (nsfw) content, according to the `safety_checker`.
         """
 
-        if "torch_device" in kwargs:
-            device = kwargs.pop("torch_device")
-            warnings.warn(
-                "`torch_device` is deprecated as an input argument to `__call__` and will be removed in v0.3.0."
-                " Consider using `pipe.to(torch_device)` instead."
-            )
-
-            # Set device as before (to be removed in 0.3.0)
-            if device is None:
-                device = "cuda" if torch.cuda.is_available() else "cpu"
-            self.to(device)
-
         if isinstance(prompt, str):
             batch_size = 1
         elif isinstance(prompt, list):
diff --git a/src/diffusers/pipelines/stochastic_karras_ve/pipeline_stochastic_karras_ve.py b/src/diffusers/pipelines/stochastic_karras_ve/pipeline_stochastic_karras_ve.py
index 1984a25ac0c6..1e7e7a26a216 100644
--- a/src/diffusers/pipelines/stochastic_karras_ve/pipeline_stochastic_karras_ve.py
+++ b/src/diffusers/pipelines/stochastic_karras_ve/pipeline_stochastic_karras_ve.py
@@ -1,5 +1,4 @@
 #!/usr/bin/env python3
-import warnings
 from typing import Optional, Tuple, Union
 
 import torch
@@ -64,17 +63,6 @@ def __call__(
             `return_dict` is True, otherwise a `tuple. When returning a tuple, the first element is a list with the
             generated images.
         """
-        if "torch_device" in kwargs:
-            device = kwargs.pop("torch_device")
-            warnings.warn(
-                "`torch_device` is deprecated as an input argument to `__call__` and will be removed in v0.3.0."
-                " Consider using `pipe.to(torch_device)` instead."
-            )
-
-            # Set device as before (to be removed in 0.3.0)
-            if device is None:
-                device = "cuda" if torch.cuda.is_available() else "cpu"
-            self.to(device)
 
         img_size = self.unet.config.sample_size
         shape = (batch_size, 3, img_size, img_size)