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[Docs] Update the name of Transformers backend -> Transformers modeling backend (#28725)

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Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
This commit is contained in:
Harry Mellor
2025-11-14 16:34:14 +00:00
committed by GitHub
parent c934caee88
commit 5f3cd7f7f2
16 changed files with 46 additions and 43 deletions
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4
vllm/model_executor/models/transformers/__init__.py
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@@ -120,8 +120,8 @@ def __getattr__(name: str):
"""Handle imports of non-existent classes with a helpful error message."""
if name not in globals():
raise AttributeError(
"The Transformers backend does not currently have a class to handle "
f"the requested model type: {name}. Please open an issue at "
"The Transformers modeling backend does not currently have a class to "
f"handle the requested model type: {name}. Please open an issue at "
"https://github.com/vllm-project/vllm/issues/new"
)
return globals()[name]

9
vllm/model_executor/models/transformers/base.py
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@@ -14,7 +14,7 @@
# 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.
"""Transformers backend base class."""
"""Transformers modeling backend base class."""
from collections.abc import Iterable
from typing import TYPE_CHECKING
@@ -118,7 +118,7 @@ class Base(nn.Module, VllmModel, SupportsQuant, SupportsLoRA, SupportsPP):
def __init__(self, *, vllm_config: "VllmConfig", prefix: str = ""):
super().__init__()
logger.info("Using Transformers backend.")
logger.info("Using Transformers modeling backend.")
self.config = vllm_config.model_config.hf_config
self.text_config = self.config.get_text_config()
@@ -147,7 +147,8 @@ class Base(nn.Module, VllmModel, SupportsQuant, SupportsLoRA, SupportsPP):
# Check for unsupported quantization methods.
if quant_method_name == "mxfp4":
raise NotImplementedError(
"Transformers backend does not support MXFP4 quantization yet."
"Transformers modeling backend does "
"not support MXFP4 quantization yet."
)
# Skip loading extra bias for GPTQ models.
if "gptq" in quant_method_name:
@@ -458,6 +459,6 @@ class Base(nn.Module, VllmModel, SupportsQuant, SupportsLoRA, SupportsPP):
required = Version(min_version)
if installed < required:
raise ImportError(
f"Transformers backend requires transformers>={required} "
f"Transformers modeling backend requires transformers>={required} "
f"for {feature}, but got {installed}"
)

2
vllm/model_executor/models/transformers/causal.py
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@@ -14,7 +14,7 @@
# 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.
"""Transformers backend mixin for causal language models."""
"""Transformers modeling backend mixin for causal language models."""
from typing import TYPE_CHECKING

2
vllm/model_executor/models/transformers/legacy.py
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@@ -14,7 +14,7 @@
# 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.
"""Transformers backend mixin for legacy models."""
"""Transformers modeling backend mixin for legacy models."""
from typing import TYPE_CHECKING

4
vllm/model_executor/models/transformers/moe.py
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@@ -14,7 +14,7 @@
# 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.
"""Transformers backend mixin for Mixture of Experts (MoE) models."""
"""Transformers modeling backend mixin for Mixture of Experts (MoE) models."""
from typing import TYPE_CHECKING, Any
@@ -39,7 +39,7 @@ if TYPE_CHECKING:
@CustomOp.register("transformers_fused_moe")
class TransformersFusedMoE(FusedMoE):
"""Custom FusedMoE for the Transformers backend."""
"""Custom FusedMoE for the Transformers modeling backend."""
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)

12
vllm/model_executor/models/transformers/multimodal.py
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@@ -14,7 +14,7 @@
# 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.
"""Transformers backend mixin for multi-modal models."""
"""Transformers modeling backend mixin for multi-modal models."""
from collections.abc import Mapping
from typing import TYPE_CHECKING
@@ -310,9 +310,9 @@ class MultiModalMixin(SupportsMultiModal, SupportsMRoPE):
return model_output
def get_language_model(self) -> torch.nn.Module:
"""Transformers backend multimodal classes do not contain a separate vLLM
language model class. Therefore, in order to return a language model vLLM class,
we use a wrapper to give `self` the same interface as a text model."""
"""Transformers modeling backend multimodal classes do not contain a separate
vLLM language model class. Therefore, in order to return a language model vLLM
class, we use a wrapper to give `self` the same interface as a text model."""
# Exclude self and object
bases = self.__class__.mro()[1:-1]
@@ -385,7 +385,9 @@ class MultiModalMixin(SupportsMultiModal, SupportsMRoPE):
for k, v in kwargs.items()
if k not in {"image_grid_thw", "video_grid_thw"}
):
raise NotImplementedError("Transformers backend only supports images.")
raise NotImplementedError(
"Transformers modeling backend only supports images."
)
image_grid_thw = kwargs.get("image_grid_thw", [])
video_grid_thw = kwargs.get("video_grid_thw", [])

2
vllm/model_executor/models/transformers/pooling.py
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@@ -14,7 +14,7 @@
# 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.
"""Transformers backend mixins for pooling models."""
"""Transformers modeling backend mixins for pooling models."""
from typing import TYPE_CHECKING

2
vllm/model_executor/models/transformers/utils.py
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@@ -14,7 +14,7 @@
# 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.
"""Transformers backend utilities."""
"""Transformers modeling backend utilities."""
from contextlib import contextmanager
from pathlib import Path