[Pytorch] add dep. warning for pytorch schedulers

src/diffusers/schedulers/scheduling_ddim.py

@@ -120,7 +120,15 @@ def __init__(
         clip_sample: bool = True,
         set_alpha_to_one: bool = True,
         steps_offset: int = 0,
+        **kwargs,
     ):
+        if "tensor_format" in kwargs:
+            warnings.warn(
+                "`tensor_format` is deprecated as an argument and will be removed in version `0.5.0`."
+                "If you're running your code in PyTorch, you can safely remove this argument.",
+                DeprecationWarning,
+            )
+
         if trained_betas is not None:
             self.betas = torch.from_numpy(trained_betas)
         if beta_schedule == "linear":

src/diffusers/schedulers/scheduling_ddpm.py

@@ -15,6 +15,7 @@
 # DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
 
 import math
+import warnings
 from dataclasses import dataclass
 from typing import Optional, Tuple, Union
 
@@ -112,7 +113,15 @@ def __init__(
         trained_betas: Optional[np.ndarray] = None,
         variance_type: str = "fixed_small",
         clip_sample: bool = True,
+        **kwargs,
     ):
+        if "tensor_format" in kwargs:
+            warnings.warn(
+                "`tensor_format` is deprecated as an argument and will be removed in version `0.5.0`."
+                "If you're running your code in PyTorch, you can safely remove this argument.",
+                DeprecationWarning,
+            )
+
         if trained_betas is not None:
             self.betas = torch.from_numpy(trained_betas)
         elif beta_schedule == "linear":

src/diffusers/schedulers/scheduling_karras_ve.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 
+import warnings
 from dataclasses import dataclass
 from typing import Optional, Tuple, Union
 
@@ -86,7 +87,15 @@ def __init__(
         s_churn: float = 80,
         s_min: float = 0.05,
         s_max: float = 50,
+        **kwargs,
     ):
+        if "tensor_format" in kwargs:
+            warnings.warn(
+                "`tensor_format` is deprecated as an argument and will be removed in version `0.5.0`."
+                "If you're running your code in PyTorch, you can safely remove this argument.",
+                DeprecationWarning,
+            )
+
         # setable values
         self.num_inference_steps: int = None
         self.timesteps: np.ndarray = None

src/diffusers/schedulers/scheduling_lms_discrete.py

@@ -12,6 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import warnings
 from dataclasses import dataclass
 from typing import Optional, Tuple, Union
 
@@ -74,7 +75,15 @@ def __init__(
         beta_end: float = 0.02,
         beta_schedule: str = "linear",
         trained_betas: Optional[np.ndarray] = None,
+        **kwargs,
     ):
+        if "tensor_format" in kwargs:
+            warnings.warn(
+                "`tensor_format` is deprecated as an argument and will be removed in version `0.5.0`."
+                "If you're running your code in PyTorch, you can safely remove this argument.",
+                DeprecationWarning,
+            )
+
         if trained_betas is not None:
             self.betas = torch.from_numpy(trained_betas)
         if beta_schedule == "linear":

src/diffusers/schedulers/scheduling_pndm.py

@@ -100,7 +100,15 @@ def __init__(
         skip_prk_steps: bool = False,
         set_alpha_to_one: bool = False,
         steps_offset: int = 0,
+        **kwargs,
     ):
+        if "tensor_format" in kwargs:
+            warnings.warn(
+                "`tensor_format` is deprecated as an argument and will be removed in version `0.5.0`."
+                "If you're running your code in PyTorch, you can safely remove this argument.",
+                DeprecationWarning,
+            )
+
         if trained_betas is not None:
             self.betas = torch.from_numpy(trained_betas)
         if beta_schedule == "linear":

src/diffusers/schedulers/scheduling_sde_ve.py

@@ -76,7 +76,15 @@ def __init__(
         sigma_max: float = 1348.0,
         sampling_eps: float = 1e-5,
         correct_steps: int = 1,
+        **kwargs,
     ):
+        if "tensor_format" in kwargs:
+            warnings.warn(
+                "`tensor_format` is deprecated as an argument and will be removed in version `0.5.0`."
+                "If you're running your code in PyTorch, you can safely remove this argument.",
+                DeprecationWarning,
+            )
+
         # setable values
         self.timesteps = None
 

src/diffusers/schedulers/scheduling_sde_vp.py

@@ -17,6 +17,7 @@
 # TODO(Patrick, Anton, Suraj) - make scheduler framework independent and clean-up a bit
 
 import math
+import warnings
 
 import torch
 
@@ -40,7 +41,13 @@ class ScoreSdeVpScheduler(SchedulerMixin, ConfigMixin):
     """
 
     @register_to_config
-    def __init__(self, num_train_timesteps=2000, beta_min=0.1, beta_max=20, sampling_eps=1e-3):
+    def __init__(self, num_train_timesteps=2000, beta_min=0.1, beta_max=20, sampling_eps=1e-3, **kwargs):
+        if "tensor_format" in kwargs:
+            warnings.warn(
+                "`tensor_format` is deprecated as an argument and will be removed in version `0.5.0`."
+                "If you're running your code in PyTorch, you can safely remove this argument.",
+                DeprecationWarning,
+            )
         self.sigmas = None
         self.discrete_sigmas = None
         self.timesteps = None

src/diffusers/schedulers/scheduling_utils.py

@@ -11,6 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
+import warnings
 from dataclasses import dataclass
 
 import torch
@@ -41,3 +42,12 @@ class SchedulerMixin:
     """
 
     config_name = SCHEDULER_CONFIG_NAME
+
+    def set_format(self, tensor_format="pt"):
+        warnings.warn(
+            "The method `set_format` is deprecated and will be removed in version `0.5.0`."
+            "If you're running your code in PyTorch, you can safely remove this function as the schedulers"
+            "are always in Pytorch",
+            DeprecationWarning,
+        )
+        return self