remove unused code

Author: rebel-kblee

src/optimum/rbln/transformers/models/gemma3/modeling_gemma3.py

@@ -403,26 +403,6 @@ def _create_embedding_layer(self):
             )
         return embed_tokens
 
-    @classmethod
-    def _update_sliding_window_config(cls, model_config: PretrainedConfig, rbln_config: RBLNGemma3ForCausalLMConfig):
-        sliding_window = getattr(model_config, "sliding_window", None)
-        sliding_window_pattern = getattr(model_config, "sliding_window_pattern", None)
-        if sliding_window_pattern is None:
-            if hasattr(model_config, "layer_types"):
-                first_full_attention_index = model_config.layer_types.index("full_attention")
-                sliding_window_pattern = first_full_attention_index + 1
-            else:
-                raise ValueError("Cannot determine sliding_window_pattern from model_config")
-
-        if sliding_window_pattern <= model_config.num_hidden_layers:
-            rbln_config.cache_impl = "hybrid"
-            rbln_config.sliding_window = sliding_window
-            rbln_config.sliding_window_layers = [
-                i for i in range(model_config.num_hidden_layers) if (i + 1) % sliding_window_pattern > 0
-            ]
-
-        return rbln_config
-
     @classmethod
     def _update_submodule_config(
         cls,

src/optimum/rbln/transformers/models/mistral/modeling_mistral.py

@@ -12,13 +12,11 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from transformers import PretrainedConfig
 
 from ....utils import logging
 from ...models.decoderonly import (
     RBLNDecoderOnlyModel,
     RBLNDecoderOnlyModelForCausalLM,
-    RBLNDecoderOnlyModelForCausalLMConfig,
 )
 from .mistral_architecture import MistralWrapper
 
@@ -85,16 +83,6 @@ class RBLNMistralForCausalLM(RBLNDecoderOnlyModelForCausalLM):
 
     _decoder_wrapper_cls = MistralWrapper
 
-    @classmethod
-    def _update_sliding_window_config(
-        cls, model_config: PretrainedConfig, rbln_config: RBLNDecoderOnlyModelForCausalLMConfig
-    ):
-        rbln_config.cache_impl = "sliding_window"
-        rbln_config.sliding_window = model_config.sliding_window
-        rbln_config.sliding_window_layers = list(range(model_config.num_hidden_layers))
-
-        return rbln_config
-
 
 class RBLNMistralModel(RBLNDecoderOnlyModel):
     """
@@ -103,13 +91,3 @@ class RBLNMistralModel(RBLNDecoderOnlyModel):
     """
 
     _decoder_wrapper_cls = MistralWrapper
-
-    @classmethod
-    def _update_sliding_window_config(
-        cls, model_config: PretrainedConfig, rbln_config: RBLNDecoderOnlyModelForCausalLMConfig
-    ):
-        rbln_config.cache_impl = "sliding_window"
-        rbln_config.sliding_window = model_config.sliding_window
-        rbln_config.sliding_window_layers = list(range(model_config.num_hidden_layers))
-
-        return rbln_config

src/optimum/rbln/transformers/models/qwen2/modeling_qwen2.py

@@ -12,13 +12,11 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from transformers import PretrainedConfig
 
 from ....utils import logging
 from ...models.decoderonly import (
     RBLNDecoderOnlyModel,
     RBLNDecoderOnlyModelForCausalLM,
-    RBLNDecoderOnlyModelForCausalLMConfig,
 )
 from .qwen2_architecture import QWEN2Wrapper
 
@@ -87,19 +85,6 @@ class RBLNQwen2ForCausalLM(RBLNDecoderOnlyModelForCausalLM):
 
     _decoder_wrapper_cls = QWEN2Wrapper
 
-    @classmethod
-    def _update_sliding_window_config(
-        cls, model_config: PretrainedConfig, rbln_config: RBLNDecoderOnlyModelForCausalLMConfig
-    ):
-        # https://github.com/huggingface/transformers/issues/35896
-        # There seems to be a bug in transformers(v4.52.4). Therefore, similar to when attn_implementation is eager,
-        # we set all layers to use sliding window in this version. This should be updated once the bug is fixed.
-
-        rbln_config.cache_impl = "sliding_window"
-        rbln_config.sliding_window = model_config.sliding_window
-        rbln_config.sliding_window_layers = list(range(model_config.num_hidden_layers))
-        return rbln_config
-
 
 class RBLNQwen2Model(RBLNDecoderOnlyModel):
     """
@@ -108,16 +93,3 @@ class RBLNQwen2Model(RBLNDecoderOnlyModel):
     """
 
     _decoder_wrapper_cls = QWEN2Wrapper
-
-    @classmethod
-    def _update_sliding_window_config(
-        cls, model_config: PretrainedConfig, rbln_config: RBLNDecoderOnlyModelForCausalLMConfig
-    ):
-        # https://github.com/huggingface/transformers/issues/35896
-        # There seems to be a bug in transformers(v4.52.4). Therefore, similar to when attn_implementation is eager,
-        # we set all layers to use sliding window in this version. This should be updated once the bug is fixed.
-
-        rbln_config.cache_impl = "sliding_window"
-        rbln_config.sliding_window = model_config.sliding_window
-        rbln_config.sliding_window_layers = list(range(model_config.num_hidden_layers))
-        return rbln_config

src/optimum/rbln/transformers/models/qwen3/modeling_qwen3.py

@@ -14,21 +14,18 @@
 
 from typing import TYPE_CHECKING
 
-from transformers import PretrainedConfig
-
 from ....utils import logging
 from ...models.decoderonly import (
     RBLNDecoderOnlyModel,
     RBLNDecoderOnlyModelForCausalLM,
-    RBLNDecoderOnlyModelForCausalLMConfig,
 )
 from .qwen3_architecture import Qwen3Wrapper
 
 
 logger = logging.get_logger(__name__)
 
 if TYPE_CHECKING:
-    from transformers import PretrainedConfig
+    pass
 
 
 class RBLNQwen3ForCausalLM(RBLNDecoderOnlyModelForCausalLM):
@@ -84,19 +81,6 @@ class RBLNQwen3ForCausalLM(RBLNDecoderOnlyModelForCausalLM):
 
     _decoder_wrapper_cls = Qwen3Wrapper
 
-    @classmethod
-    def _update_sliding_window_config(
-        cls, model_config: PretrainedConfig, rbln_config: RBLNDecoderOnlyModelForCausalLMConfig
-    ):
-        # https://github.com/huggingface/transformers/issues/35896
-        # There seems to be a bug in transformers(v4.52.4). Therefore, similar to when attn_implementation is eager,
-        # we set all layers to use sliding window in this version. This should be updated once the bug is fixed.
-
-        rbln_config.cache_impl = "sliding_window"
-        rbln_config.sliding_window = model_config.sliding_window
-        rbln_config.sliding_window_layers = list(range(model_config.num_hidden_layers))
-        return rbln_config
-
     def forward(self, *args, **kwargs):
         kwargs["return_dict"] = True
         return super().forward(*args, **kwargs)