Merge pull request #101 from saddam213/LCM_LORA

Support LCM_LoRA models

Author: saddam213

OnnxStack.Core/Model/OnnxInferenceParameters.cs

@@ -170,6 +170,18 @@ public void AddOutputBuffer()
         public IReadOnlyDictionary<string, OrtValue> OutputNameValues => _outputs.NameValues;
 
 
+        /// <summary>
+        /// Gets the expected input parameter count.
+        /// </summary>
+        public int InputCount => _metadata.Inputs.Count;
+
+
+        /// <summary>
+        /// Gets the expected output parameter count.
+        /// </summary>
+        public int OutputCount => _metadata.Outputs.Count;
+
+
         /// <summary>
         /// Performs application-defined tasks associated with freeing, releasing, or resetting unmanaged resources.
         /// </summary>

OnnxStack.StableDiffusion/Diffusers/LatentConsistency/InpaintLegacyDiffuser.cs

@@ -114,7 +114,8 @@ protected override async Task<DenseTensor<float>> SchedulerStepAsync(ModelOption
                         inferenceParameters.AddInputTensor(inputTensor);
                         inferenceParameters.AddInputTensor(timestepTensor);
                         inferenceParameters.AddInputTensor(promptEmbeddings.PromptEmbeds);
-                        inferenceParameters.AddInputTensor(guidanceEmbeddings);
+                        if (inferenceParameters.InputCount == 4)
+                            inferenceParameters.AddInputTensor(guidanceEmbeddings);
                         inferenceParameters.AddOutputBuffer(outputDimension);
 
                         var results = await _onnxModelService.RunInferenceAsync(modelOptions.BaseModel, OnnxModelType.Unet, inferenceParameters);

OnnxStack.StableDiffusion/Diffusers/LatentConsistency/LatentConsistencyDiffuser.cs

@@ -127,7 +127,8 @@ protected override async Task<DenseTensor<float>> SchedulerStepAsync(ModelOption
                         inferenceParameters.AddInputTensor(inputTensor);
                         inferenceParameters.AddInputTensor(timestepTensor);
                         inferenceParameters.AddInputTensor(promptEmbeddings.PromptEmbeds);
-                        inferenceParameters.AddInputTensor(guidanceEmbeddings);
+                        if (inferenceParameters.InputCount == 4)
+                            inferenceParameters.AddInputTensor(guidanceEmbeddings);
                         inferenceParameters.AddOutputBuffer(outputDimension);
 
                         var results = await _onnxModelService.RunInferenceAsync(modelOptions.BaseModel, OnnxModelType.Unet, inferenceParameters);