Better support for transformers t5

comfy/language/transformers_model_management.py

@@ -159,12 +159,13 @@ class TransformersManagedModel(ModelManageable):
                 filename, chat_template = candidate_chat_templates[0]
                 logging.debug(f"Selected chat template filename={filename} for {self.model.name_or_path}")
         try:
-            # todo: this should come from node inputs
-            prompt = tokenizer.apply_chat_template([
-                {"role": "user", "content": prompt},
-            ], chat_template=chat_template, add_generation_prompt=True, tokenize=False)
+            if hasattr(tokenizer, "apply_chat_template"):
+                # todo: this should come from node inputs
+                prompt = tokenizer.apply_chat_template([
+                    {"role": "user", "content": prompt},
+                ], chat_template=chat_template, add_generation_prompt=True, tokenize=False)
         except Exception as exc:
-            logging.error("Could not apply chat template", exc_info=exc)
+            logging.debug("Could not apply chat template", exc_info=exc)
 
         if self.processor is None:
             batch_encoding = tokenizer(prompt, return_tensors="pt").to(device=self.load_device)

comfy/model_downloader.py

@@ -167,6 +167,13 @@ KNOWN_CHECKPOINTS = [
     CivitFile(133005, 357609, filename="juggernautXL_v9Rundiffusionphoto2.safetensors"),
     CivitFile(112902, 351306, filename="dreamshaperXL_v21TurboDPMSDE.safetensors"),
     CivitFile(139562, 344487, filename="realvisxlV40_v40Bakedvae.safetensors"),
+    HuggingFile("SG161222/Realistic_Vision_V6.0_B1_noVAE","Realistic_Vision_V6.0_NV_B1_fp16.safetensors"),
+    HuggingFile("SG161222/Realistic_Vision_V5.1_noVAE","Realistic_Vision_V5.1_fp16-no-ema.safetensors"),
+    CivitFile(4384, 128713, filename="dreamshaper_8.safetensors"),
+    CivitFile(7371, 425083, filename="revAnimated_v2Rebirth.safetensors"),
+    CivitFile(4468, 57618, filename="counterfeitV30_v30.safetensors"),
+    CivitFile(241415, 272376, filename="picxReal_10.safetensors"),
+    CivitFile(23900, 95489, filename="anyloraCheckpoint_bakedvaeBlessedFp16.safetensors"),
 ]
 
 KNOWN_UNCLIP_CHECKPOINTS = [
@@ -195,8 +202,9 @@ KNOWN_CLIP_VISION_MODELS = [
 KNOWN_LORAS = [
     CivitFile(model_id=211577, model_version_id=238349, filename="openxl_handsfix.safetensors"),
     CivitFile(model_id=324815, model_version_id=364137, filename="blur_control_xl_v1.safetensors"),
+    CivitFile(model_id=47085, model_version_id=55199, filename="GoodHands-beta2.safetensors"),
     HuggingFile("ByteDance/Hyper-SD", "Hyper-SDXL-12steps-CFG-lora.safetensors"),
-    HuggingFile("ByteDance/Hyper-SD", "Hyper-SD15-12steps-CFG-lora.safetensors")
+    HuggingFile("ByteDance/Hyper-SD", "Hyper-SD15-12steps-CFG-lora.safetensors"),
 ]
 
 KNOWN_CONTROLNETS = [

comfy/nodes/package.py

@@ -44,9 +44,19 @@ def _import_and_enumerate_nodes_in_module(module: types.ModuleType,
     exported_nodes = ExportedNodes()
     timings = []
     exceptions = []
-    if _import_nodes_in_module(exported_nodes, module):
-        pass
-    else:
+    with tracer.start_as_current_span("Load Node") as span:
+        time_before = time.perf_counter()
+        try:
+            module_decl = _import_nodes_in_module(exported_nodes, module)
+            full_name = module.__name__
+            span.set_attribute("full_name", full_name)
+            timings.append((time.perf_counter() - time_before, full_name, True, exported_nodes))
+        except Exception as exc:
+            logging.error(f"{full_name} import failed", exc_info=exc)
+            span.set_status(Status(StatusCode.ERROR))
+            span.record_exception(exc)
+            exceptions.append(exc)
+    if module_decl is None or not module_decl:
         # Iterate through all the submodules
         for _, name, is_pkg in pkgutil.iter_modules(module.__path__):
             span: Span
@@ -55,6 +65,7 @@ def _import_and_enumerate_nodes_in_module(module: types.ModuleType,
                 time_before = time.perf_counter()
                 success = True
                 span.set_attribute("full_name", full_name)
+                new_nodes = ExportedNodes()
                 if full_name.endswith(".disabled"):
                     continue
                 try:
@@ -75,11 +86,11 @@ def _import_and_enumerate_nodes_in_module(module: types.ModuleType,
                     exceptions.append(x)
                     span.set_status(Status(StatusCode.ERROR))
                     span.record_exception(x)
-                timings.append((time.perf_counter() - time_before, full_name, success))
+                timings.append((time.perf_counter() - time_before, full_name, success, new_nodes))
 
-    if print_import_times and len(timings) > 0 or any(not success for (_, _, success) in timings):
-        for (duration, module_name, success) in sorted(timings):
-            print(f"{duration:6.1f} seconds{'' if success else ' (IMPORT FAILED)'}, {module_name}")
+    if print_import_times and len(timings) > 0 or any(not success for (_, _, success, _) in timings):
+        for (duration, module_name, success, new_nodes) in sorted(timings):
+            logging.info(f"{duration:6.1f} seconds{'' if success else ' (IMPORT FAILED)'}, {module_name} ({len(new_nodes)} nodes loaded)")
     if raise_on_failure and len(exceptions) > 0:
         try:
             raise ExceptionGroup("Node import failed", exceptions)

comfy_extras/nodes/nodes_language.py

@@ -11,7 +11,7 @@ from typing import Any, Dict, Optional, List, Callable, Union
 import torch
 from transformers import AutoModelForCausalLM, AutoTokenizer, PreTrainedModel, LogitsProcessor, TextStreamer, \
     PreTrainedTokenizerBase, LogitsProcessorList, PretrainedConfig, AutoProcessor, BatchFeature, ProcessorMixin, \
-    LlavaNextForConditionalGeneration, LlavaNextProcessor
+    LlavaNextForConditionalGeneration, LlavaNextProcessor, T5EncoderModel, AutoModel
 from typing_extensions import TypedDict
 
 from comfy.language.chat_templates import KNOWN_CHAT_TEMPLATES
@@ -245,8 +245,9 @@ class TransformersLoader(CustomNode):
             }
 
             try:
-                model = AutoModelForCausalLM.from_pretrained(**from_pretrained_kwargs)
+                model = AutoModel.from_pretrained(**from_pretrained_kwargs)
             except:
+                # not yet supported by automodel
                 model = LlavaNextForConditionalGeneration.from_pretrained(**from_pretrained_kwargs)
 
             config_dict, _ = PretrainedConfig.get_config_dict(ckpt_name, trust_remote_code=True, **hub_kwargs)

setup.py

@@ -185,7 +185,12 @@ def dependencies(force_nightly: bool = False) -> List[str]:
     return _dependencies
 
 
-package_data = ['sd1_tokenizer/*', '**/*.json', '**/*.yaml']
+package_data = [
+    'sd1_tokenizer/*',
+    't5_tokenizer/*',
+    '**/*.json',
+    '**/*.yaml',
+]
 if not is_editable:
     package_data.append('comfy/web/**/*')
 dev_dependencies = open(os.path.join(os.path.dirname(__file__), "requirements-dev.txt")).readlines()