fix(ddim): validate eta is in [0, 1] in DDIMPipeline (#13367)

* fix(ddim): validate eta is in [0, 1] in DDIMPipeline.__call__

The DDIM paper defines η (eta) as a value that must lie in [0, 1]:
η=0 corresponds to deterministic DDIM, η=1 corresponds to DDPM.
The docstring already documented this constraint, but no runtime
validation was in place, so users could silently pass out-of-range
values (e.g. negative or >1) without any error.

Add an explicit ValueError check before the denoising loop so that
invalid eta values are caught early with a clear message.

Fixes #13362

Signed-off-by: NIK-TIGER-BILL <nik.tiger.bill@github.com>

* fix(ddim): downgrade eta out-of-range from error to warning

Per maintainer feedback from @yiyixuxu — the documentation is
sufficient; a hard ValueError is too strict. Replace with a
UserWarning so callers are informed without breaking existing code
that passes eta outside [0, 1].

Signed-off-by: NIK-TIGER-BILL <nik.tiger.bill@github.com>

* fix(ddim): use logger.warning instead of warnings.warn for eta validation

Address review request from @yiyixuxu: switch from warnings.warn() to
logger.warning() to be consistent with all other diffusers pipelines.

The eta validation check itself (0.0 <= eta <= 1.0) is unchanged.

Signed-off-by: NIK-TIGER-BILL <nik.tiger.bill@github.com>

---------

Signed-off-by: NIK-TIGER-BILL <nik.tiger.bill@github.com>
Co-authored-by: NIK-TIGER-BILL <nik.tiger.bill@github.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>

Author: 3 people

src/diffusers/pipelines/ddim/pipeline_ddim.py

@@ -12,6 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import logging
+
 import torch
 
 from ...models import UNet2DModel
@@ -21,6 +23,9 @@
 from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
 
 
+logger = logging.getLogger(__name__)
+
+
 if is_torch_xla_available():
     import torch_xla.core.xla_model as xm
 
@@ -129,6 +134,13 @@ def __call__(
         else:
             image_shape = (batch_size, self.unet.config.in_channels, *self.unet.config.sample_size)
 
+        if not 0.0 <= eta <= 1.0:
+            logger.warning(
+                f"`eta` should be between 0 and 1 (inclusive), but received {eta}. "
+                "A value of 0 corresponds to DDIM and 1 corresponds to DDPM. "
+                "Unexpected results may occur for values outside this range."
+            )
+
         if isinstance(generator, list) and len(generator) != batch_size:
             raise ValueError(
                 f"You have passed a list of generators of length {len(generator)}, but requested an effective batch"