Rename

Signed-off-by: DarkLight1337 <[email protected]>
vllm-project · Jan 7, 2025 · 62942e3 · 62942e3
1 parent 5f940fc
commit 62942e3
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Showing 18 changed files with 71 additions and 68 deletions.
diff --git a/tests/multimodal/test_processing.py b/tests/multimodal/test_processing.py
@@ -690,7 +690,7 @@ def _test_processing_cache_correctness(
 
     baseline_processor = factories.build_processor(ctx, cache=None)
     cached_processor = factories.build_processor(ctx, cache=cache)
-    dummy_data_builder = baseline_processor.dummy_data_builder
+    dummy_inputs = baseline_processor.dummy_inputs
 
     rng = np.random.RandomState(0)
 
@@ -722,7 +722,7 @@ def _test_processing_cache_correctness(
         }
 
         mm_counts = {k: len(vs) for k, vs in mm_data.items()}
-        prompt = dummy_data_builder.get_dummy_processor_inputs(
+        prompt = dummy_inputs.get_dummy_processor_inputs(
             model_config.max_model_len,
             mm_counts,
         ).prompt_text

diff --git a/tests/plugins/vllm_add_dummy_model/vllm_add_dummy_model/my_llava.py b/tests/plugins/vllm_add_dummy_model/vllm_add_dummy_model/my_llava.py
@@ -2,7 +2,7 @@
 
 import torch
 
-from vllm.model_executor.models.llava import (LlavaDummyDataBuilder,
+from vllm.model_executor.models.llava import (LlavaDummyInputsBuilder,
                                               LlavaForConditionalGeneration,
                                               LlavaMultiModalProcessor,
                                               LlavaProcessingInfo)
@@ -12,7 +12,7 @@
 
 @MULTIMODAL_REGISTRY.register_processor(LlavaMultiModalProcessor,
                                         info=LlavaProcessingInfo,
-                                        dummy_data=LlavaDummyDataBuilder)
+                                        dummy=LlavaDummyInputsBuilder)
 class MyLlava(LlavaForConditionalGeneration):
 
     def compute_logits(

diff --git a/vllm/model_executor/models/aria.py b/vllm/model_executor/models/aria.py
@@ -26,7 +26,7 @@
 from vllm.multimodal.parse import MultiModalDataItems
 from vllm.multimodal.processing import BaseProcessingInfo, PromptReplacement
 from vllm.multimodal.processor import BaseMultiModalProcessor
-from vllm.multimodal.profiling import BaseDummyDataBuilder, ProcessorInputs
+from vllm.multimodal.profiling import BaseDummyInputsBuilder, ProcessorInputs
 from vllm.sequence import IntermediateTensors
 from vllm.transformers_utils.configs.aria import (AriaMoELMConfig,
                                                   AriaVisionConfig)
@@ -464,7 +464,7 @@ def get_num_image_tokens(self) -> int:
         return max(hf_config.projector_patch_to_query_dict.values())
 
 
-class AriaDummyDataBuilder(BaseDummyDataBuilder[AriaProcessingInfo]):
+class AriaDummyInputsBuilder(BaseDummyInputsBuilder[AriaProcessingInfo]):
 
     def get_dummy_processor_inputs(
         self,
@@ -526,7 +526,7 @@ def _get_prompt_replacements(
 
 @MULTIMODAL_REGISTRY.register_processor(AriaMultiModalProcessor,
                                         info=AriaProcessingInfo,
-                                        dummy_data=AriaDummyDataBuilder)
+                                        dummy=AriaDummyInputsBuilder)
 class AriaForConditionalGeneration(nn.Module, SupportsMultiModal):
     """
     Aria model for conditional generation tasks.

diff --git a/vllm/model_executor/models/blip2.py b/vllm/model_executor/models/blip2.py
@@ -20,7 +20,7 @@
 from vllm.multimodal.parse import MultiModalDataItems
 from vllm.multimodal.processing import BaseProcessingInfo, PromptReplacement
 from vllm.multimodal.processor import BaseMultiModalProcessor
-from vllm.multimodal.profiling import BaseDummyDataBuilder, ProcessorInputs
+from vllm.multimodal.profiling import BaseDummyInputsBuilder, ProcessorInputs
 from vllm.sequence import IntermediateTensors
 
 from .blip import BlipVisionModel
@@ -413,7 +413,7 @@ def get_num_image_tokens(self) -> int:
         return hf_config.num_query_tokens
 
 
-class Blip2DummyDataBuilder(BaseDummyDataBuilder[Blip2ProcessingInfo]):
+class Blip2DummyInputsBuilder(BaseDummyInputsBuilder[Blip2ProcessingInfo]):
 
     def get_dummy_processor_inputs(
         self,
@@ -490,7 +490,7 @@ def apply(
 
 @MULTIMODAL_REGISTRY.register_processor(Blip2MultiModalProcessor,
                                         info=Blip2ProcessingInfo,
-                                        dummy_data=Blip2DummyDataBuilder)
+                                        dummy=Blip2DummyInputsBuilder)
 class Blip2ForConditionalGeneration(nn.Module, SupportsMultiModal, SupportsPP):
 
     def __init__(self, *, vllm_config: VllmConfig, prefix: str = ""):

diff --git a/vllm/model_executor/models/chameleon.py b/vllm/model_executor/models/chameleon.py
@@ -33,7 +33,7 @@
 from vllm.multimodal.parse import MultiModalDataItems
 from vllm.multimodal.processing import BaseProcessingInfo, PromptReplacement
 from vllm.multimodal.processor import BaseMultiModalProcessor
-from vllm.multimodal.profiling import BaseDummyDataBuilder, ProcessorInputs
+from vllm.multimodal.profiling import BaseDummyInputsBuilder, ProcessorInputs
 from vllm.sequence import IntermediateTensors
 from vllm.utils import print_warning_once
 
@@ -68,7 +68,8 @@ def get_num_image_tokens(self) -> int:
         return processor.image_seq_length
 
 
-class ChameleonDummyDataBuilder(BaseDummyDataBuilder[ChameleonProcessingInfo]):
+class ChameleonDummyInputsBuilder(
+        BaseDummyInputsBuilder[ChameleonProcessingInfo]):
 
     def get_dummy_processor_inputs(
         self,
@@ -915,7 +916,7 @@ def forward(
 
 @MULTIMODAL_REGISTRY.register_processor(ChameleonMultiModalProcessor,
                                         info=ChameleonProcessingInfo,
-                                        dummy_data=ChameleonDummyDataBuilder)
+                                        dummy=ChameleonDummyInputsBuilder)
 class ChameleonForConditionalGeneration(nn.Module, SupportsMultiModal,
                                         SupportsPP):
 

diff --git a/vllm/model_executor/models/fuyu.py b/vllm/model_executor/models/fuyu.py
@@ -37,7 +37,7 @@
                                    MultiModalDataItems)
 from vllm.multimodal.processing import BaseProcessingInfo, PromptReplacement
 from vllm.multimodal.processor import BaseMultiModalProcessor
-from vllm.multimodal.profiling import BaseDummyDataBuilder, ProcessorInputs
+from vllm.multimodal.profiling import BaseDummyInputsBuilder, ProcessorInputs
 from vllm.sequence import IntermediateTensors
 
 from .interfaces import SupportsMultiModal, SupportsPP
@@ -117,7 +117,7 @@ def get_image_size_with_most_features(self) -> ImageSize:
                          height=image_processor.size["height"])
 
 
-class FuyuDummyDataBuilder(BaseDummyDataBuilder[FuyuProcessingInfo]):
+class FuyuDummyInputsBuilder(BaseDummyInputsBuilder[FuyuProcessingInfo]):
 
     def get_dummy_processor_inputs(
         self,
@@ -244,7 +244,7 @@ def apply(
 
 @MULTIMODAL_REGISTRY.register_processor(FuyuMultiModalProcessor,
                                         info=FuyuProcessingInfo,
-                                        dummy_data=FuyuDummyDataBuilder)
+                                        dummy=FuyuDummyInputsBuilder)
 class FuyuForCausalLM(nn.Module, SupportsMultiModal, SupportsPP):
 
     def __init__(self, *, vllm_config: VllmConfig, prefix: str = ""):

diff --git a/vllm/model_executor/models/llava.py b/vllm/model_executor/models/llava.py
@@ -29,7 +29,7 @@
 from vllm.multimodal.processing import (BaseProcessingInfo, ProcessingCache,
                                         PromptReplacement)
 from vllm.multimodal.processor import BaseMultiModalProcessor
-from vllm.multimodal.profiling import BaseDummyDataBuilder, ProcessorInputs
+from vllm.multimodal.profiling import BaseDummyInputsBuilder, ProcessorInputs
 from vllm.sequence import IntermediateTensors
 
 from .clip import CLIPVisionModel
@@ -170,7 +170,7 @@ def get_max_image_tokens(self) -> int:
 _I = TypeVar("_I", bound=BaseLlavaProcessingInfo)
 
 
-class LlavaDummyDataBuilder(BaseDummyDataBuilder[_I]):
+class LlavaDummyInputsBuilder(BaseDummyInputsBuilder[_I]):
 
     def get_dummy_processor_inputs(
         self,
@@ -360,23 +360,23 @@ def _build_llava_or_pixtral_hf_info(
 
 def _build_llava_or_pixtral_hf_processor(
     info: _I,
-    dummy_data_builder: BaseDummyDataBuilder[_I],
+    dummy_inputs: BaseDummyInputsBuilder[_I],
     *,
     cache: Optional[ProcessingCache] = None,
     enable_sanity_checks: bool = True,
 ) -> BaseMultiModalProcessor:
     if isinstance(info, PixtralHFProcessingInfo):
         return PixtralHFMultiModalProcessor(
             info,
-            dummy_data_builder,  # type: ignore
+            dummy_inputs,  # type: ignore
             cache=cache,
             enable_sanity_checks=enable_sanity_checks,
         )
 
     if isinstance(info, LlavaProcessingInfo):
         return LlavaMultiModalProcessor(
             info,
-            dummy_data_builder,  # type: ignore
+            dummy_inputs,  # type: ignore
             cache=cache,
             enable_sanity_checks=enable_sanity_checks,
         )
@@ -461,7 +461,7 @@ def init_vision_tower_for_llava(
 
 @MULTIMODAL_REGISTRY.register_processor(_build_llava_or_pixtral_hf_processor,
                                         info=_build_llava_or_pixtral_hf_info,
-                                        dummy_data=LlavaDummyDataBuilder)
+                                        dummy=LlavaDummyInputsBuilder)
 class LlavaForConditionalGeneration(nn.Module, SupportsMultiModal, SupportsPP):
     # BitandBytes specific attributes
     bitsandbytes_stacked_params_mapping = {
@@ -793,6 +793,6 @@ def get_replacement_mantis(item_idx: int):
 # `--hf_overrides '{"architectures": ["MantisForConditionalGeneration"]}'`
 @MULTIMODAL_REGISTRY.register_processor(MantisMultiModalProcessor,
                                         info=LlavaProcessingInfo,
-                                        dummy_data=LlavaDummyDataBuilder)
+                                        dummy=LlavaDummyInputsBuilder)
 class MantisForConditionalGeneration(LlavaForConditionalGeneration):
     pass
diff --git a/vllm/model_executor/models/llava_next.py b/vllm/model_executor/models/llava_next.py
@@ -21,7 +21,7 @@
 from .clip import CLIPVisionModel
 from .interfaces import SupportsMultiModal, SupportsPP
 from .llava import (BaseLlavaMultiModalProcessor, BaseLlavaProcessingInfo,
-                    LlavaDummyDataBuilder, LlavaLikeConfig,
+                    LlavaDummyInputsBuilder, LlavaLikeConfig,
                     LlavaMultiModalProjector, init_vision_tower_for_llava)
 from .siglip import SiglipVisionModel
 from .utils import (AutoWeightsLoader, embed_multimodal, flatten_bn,
@@ -181,7 +181,7 @@ class LlavaNextMultiModalProcessor(
 
 @MULTIMODAL_REGISTRY.register_processor(LlavaNextMultiModalProcessor,
                                         info=LlavaNextProcessingInfo,
-                                        dummy_data=LlavaDummyDataBuilder)
+                                        dummy=LlavaDummyInputsBuilder)
 class LlavaNextForConditionalGeneration(nn.Module, SupportsMultiModal,
                                         SupportsPP):
 

diff --git a/vllm/model_executor/models/llava_next_video.py b/vllm/model_executor/models/llava_next_video.py
@@ -21,7 +21,7 @@
                                    VideoEmbeddingItems, VideoProcessorItems)
 from vllm.multimodal.processing import BaseProcessingInfo, PromptReplacement
 from vllm.multimodal.processor import BaseMultiModalProcessor
-from vllm.multimodal.profiling import BaseDummyDataBuilder, ProcessorInputs
+from vllm.multimodal.profiling import BaseDummyInputsBuilder, ProcessorInputs
 from vllm.sequence import IntermediateTensors
 from vllm.utils import is_list_of
 
@@ -134,8 +134,8 @@ def get_max_num_frames(self, seq_len: int) -> int:
         return max(max_total_frames // max(max_videos, 1), 1)
 
 
-class LlavaNextVideoDummyDataBuilder(
-        BaseDummyDataBuilder[LlavaNextVideoProcessingInfo]):
+class LlavaNextVideoDummyInputsBuilder(
+        BaseDummyInputsBuilder[LlavaNextVideoProcessingInfo]):
 
     def get_dummy_processor_inputs(
         self,
@@ -269,7 +269,7 @@ def forward(self, image_features: torch.Tensor) -> torch.Tensor:
 @MULTIMODAL_REGISTRY.register_processor(
     LlavaNextVideoMultiModalProcessor,
     info=LlavaNextVideoProcessingInfo,
-    dummy_data=LlavaNextVideoDummyDataBuilder,
+    dummy=LlavaNextVideoDummyInputsBuilder,
 )
 class LlavaNextVideoForConditionalGeneration(nn.Module, SupportsMultiModal,
                                              SupportsPP):

diff --git a/vllm/model_executor/models/llava_onevision.py b/vllm/model_executor/models/llava_onevision.py
@@ -28,7 +28,7 @@
 
 from .clip import CLIPVisionModel
 from .interfaces import SupportsMultiModal, SupportsPP
-from .llava import LlavaDummyDataBuilder, init_vision_tower_for_llava
+from .llava import LlavaDummyInputsBuilder, init_vision_tower_for_llava
 from .llava_next import (BaseLlavaNextMultiModalProcessor, LlavaNextLikeConfig,
                          LlavaNextProcessingInfo)
 from .siglip import SiglipVisionModel
@@ -233,8 +233,8 @@ def get_max_video_tokens(self, seq_len: int) -> int:
         )
 
 
-class LlavaOnevisionDummyDataBuilder(
-        LlavaDummyDataBuilder[LlavaOnevisionProcessingInfo]):
+class LlavaOnevisionDummyInputsBuilder(
+        LlavaDummyInputsBuilder[LlavaOnevisionProcessingInfo]):
 
     def get_dummy_processor_inputs(
         self,
@@ -392,10 +392,9 @@ def forward(self, image_features: torch.Tensor) -> torch.Tensor:
         return hidden_states
 
 
-@MULTIMODAL_REGISTRY.register_processor(
-    LlavaOnevisionMultiModalProcessor,
-    info=LlavaOnevisionProcessingInfo,
-    dummy_data=LlavaOnevisionDummyDataBuilder)
+@MULTIMODAL_REGISTRY.register_processor(LlavaOnevisionMultiModalProcessor,
+                                        info=LlavaOnevisionProcessingInfo,
+                                        dummy=LlavaOnevisionDummyInputsBuilder)
 class LlavaOnevisionForConditionalGeneration(nn.Module, SupportsMultiModal,
                                              SupportsPP):
 

diff --git a/vllm/model_executor/models/phi3v.py b/vllm/model_executor/models/phi3v.py
@@ -39,7 +39,7 @@
                                         BoundPromptReplacement,
                                         PlaceholderInfo, PromptReplacement)
 from vllm.multimodal.processor import BaseMultiModalProcessor
-from vllm.multimodal.profiling import BaseDummyDataBuilder, ProcessorInputs
+from vllm.multimodal.profiling import BaseDummyInputsBuilder, ProcessorInputs
 from vllm.sequence import IntermediateTensors
 from vllm.utils import is_list_of
 
@@ -344,7 +344,7 @@ def get_image_size_with_most_features(self) -> ImageSize:
         return ImageSize(height=8000, width=50)
 
 
-class Phi3VDummyDataBuilder(BaseDummyDataBuilder[Phi3VProcessingInfo]):
+class Phi3VDummyInputsBuilder(BaseDummyInputsBuilder[Phi3VProcessingInfo]):
 
     def get_dummy_processor_inputs(
         self,
@@ -498,7 +498,7 @@ def apply(
 
 @MULTIMODAL_REGISTRY.register_processor(Phi3VMultiModalProcessor,
                                         info=Phi3VProcessingInfo,
-                                        dummy_data=Phi3VDummyDataBuilder)
+                                        dummy=Phi3VDummyInputsBuilder)
 class Phi3VForCausalLM(nn.Module, SupportsMultiModal, SupportsPP):
     hf_to_vllm_mapper = WeightsMapper(
         orig_to_new_prefix={

diff --git a/vllm/model_executor/models/qwen2_audio.py b/vllm/model_executor/models/qwen2_audio.py
@@ -42,7 +42,7 @@
                                    MultiModalDataParser)
 from vllm.multimodal.processing import BaseProcessingInfo, PromptReplacement
 from vllm.multimodal.processor import BaseMultiModalProcessor
-from vllm.multimodal.profiling import BaseDummyDataBuilder, ProcessorInputs
+from vllm.multimodal.profiling import BaseDummyInputsBuilder, ProcessorInputs
 from vllm.sequence import IntermediateTensors
 
 from .interfaces import SupportsMultiModal, SupportsPP
@@ -115,8 +115,8 @@ def get_mm_max_tokens_per_item(self, seq_len: int) -> Mapping[str, int]:
         return {"audio": max_output_lengths}
 
 
-class Qwen2AudioDummyDataBuilder(BaseDummyDataBuilder[Qwen2AudioProcessingInfo]
-                                 ):
+class Qwen2AudioDummyInputsBuilder(
+        BaseDummyInputsBuilder[Qwen2AudioProcessingInfo]):
 
     def get_dummy_processor_inputs(
         self,
@@ -237,7 +237,7 @@ def _always_apply_prompt_replacements(self) -> bool:
 
 @MULTIMODAL_REGISTRY.register_processor(Qwen2AudioMultiModalProcessor,
                                         info=Qwen2AudioProcessingInfo,
-                                        dummy_data=Qwen2AudioDummyDataBuilder)
+                                        dummy=Qwen2AudioDummyInputsBuilder)
 class Qwen2AudioForConditionalGeneration(nn.Module, SupportsMultiModal,
                                          SupportsPP):
 

diff --git a/vllm/model_executor/models/qwen2_vl.py b/vllm/model_executor/models/qwen2_vl.py
@@ -60,7 +60,7 @@
                                    MultiModalDataItems, MultiModalDataParser)
 from vllm.multimodal.processing import BaseProcessingInfo, PromptReplacement
 from vllm.multimodal.processor import BaseMultiModalProcessor
-from vllm.multimodal.profiling import BaseDummyDataBuilder, ProcessorInputs
+from vllm.multimodal.profiling import BaseDummyInputsBuilder, ProcessorInputs
 from vllm.platforms import _Backend
 from vllm.sequence import IntermediateTensors
 from vllm.transformers_utils.config import uses_mrope
@@ -883,7 +883,7 @@ def get_max_video_tokens(self, seq_len: int) -> int:
         )
 
 
-class Qwen2VLDummyDataBuilder(BaseDummyDataBuilder[Qwen2VLProcessingInfo]):
+class Qwen2VLDummyInputsBuilder(BaseDummyInputsBuilder[Qwen2VLProcessingInfo]):
 
     def get_dummy_processor_inputs(
         self,
@@ -991,7 +991,7 @@ def _get_mm_fields_config(
 
 @MULTIMODAL_REGISTRY.register_processor(Qwen2VLMultiModalProcessor,
                                         info=Qwen2VLProcessingInfo,
-                                        dummy_data=Qwen2VLDummyDataBuilder)
+                                        dummy=Qwen2VLDummyInputsBuilder)
 class Qwen2VLForConditionalGeneration(nn.Module, SupportsMultiModal,
                                       SupportsLoRA, SupportsPP):
     packed_modules_mapping = {

diff --git a/vllm/model_executor/models/ultravox.py b/vllm/model_executor/models/ultravox.py
@@ -27,7 +27,7 @@
 from vllm.multimodal.parse import MultiModalDataItems, MultiModalDataParser
 from vllm.multimodal.processing import BaseProcessingInfo, PromptReplacement
 from vllm.multimodal.processor import BaseMultiModalProcessor
-from vllm.multimodal.profiling import BaseDummyDataBuilder, ProcessorInputs
+from vllm.multimodal.profiling import BaseDummyInputsBuilder, ProcessorInputs
 from vllm.sequence import IntermediateTensors
 from vllm.transformers_utils.configs.ultravox import UltravoxConfig
 
@@ -98,7 +98,8 @@ def get_mm_max_tokens_per_item(self, seq_len: int) -> Mapping[str, int]:
         return {"audio": max_audio_tokens}
 
 
-class UltravoxDummyDataBuilder(BaseDummyDataBuilder[UltravoxProcessingInfo]):
+class UltravoxDummyInputsBuilder(BaseDummyInputsBuilder[UltravoxProcessingInfo]
+                                 ):
 
     def get_dummy_processor_inputs(
         self,
@@ -340,7 +341,7 @@ def forward(
 
 @MULTIMODAL_REGISTRY.register_processor(UltravoxMultiModalProcessor,
                                         info=UltravoxProcessingInfo,
-                                        dummy_data=UltravoxDummyDataBuilder)
+                                        dummy=UltravoxDummyInputsBuilder)
 class UltravoxModel(nn.Module, SupportsMultiModal, SupportsPP):
 
     hf_to_vllm_mapper = WeightsMapper(