Update sd_model.py

sd_model.py

@@ -55,18 +55,18 @@ class LoraConfig:
 
 @dataclass
 class SDModelConfig(BaseModelConfig):
-    _target_: str = "trainer.models.sd_model.SDModel"
+    _target_: str = "sd_model.SDModel"
     pretrained_model_name_or_path: str = "runwayml/stable-diffusion-v1-5"
     conditioning_dropout_prob: float = 0.05
     use_ema: bool = True
-    concat_all_steps: bool = II("dataset.concat_all_steps")
+    concat_all_steps: bool = False
     positional_encoding_type: Optional[str] = "sinusoidal"
     positional_encoding_length: Optional[int] = None
     image_positional_encoding_type: Optional[str] = None #"sinusoidal"
     image_positional_encoding_length: Optional[int] = None
     broadcast_positional_encoding: bool = True
-    sequence_length: Optional[int] = II("dataset.sequence_length") # TODO consider changing interp on next line to this +1? 
-    text_sequence_length: Optional[int] = II("dataset.text_sequence_length")
+    sequence_length: Optional[int] = 6
+    text_sequence_length: Optional[int] = 7
     use_lora: bool = False
     # lora_cfg: Any = LoraConfig()
     zero_snr: bool = True
@@ -76,8 +76,10 @@ class SDModelConfig(BaseModelConfig):
     
     
 class SDModel(ModelMixin, ConfigMixin, PushToHubMixin):
-    def __init__(self, cfg: SDModelConfig) -> None:
+    def __init__(self, cfg: SDModelConfig = None) -> None:
         super().__init__()
+        if cfg is not None: # workaround for default
+            cfg = SDM
         self.cfg = cfg
         self.noise_scheduler = DDPMScheduler.from_pretrained(
             self.cfg.pretrained_model_name_or_path,