Merge branch 'master' into CUDA

# Conflicts:
#	OnnxStack.UI/OnnxStack.UI.csproj

Author: saddam213

OnnxStack.Console/appsettings.json

@@ -13,7 +13,6 @@
 				"IsEnabled": true,
 				"PadTokenId": 49407,
 				"BlankTokenId": 49407,
-				"InputTokenLimit": 2048,
 				"TokenizerLimit": 77,
 				"EmbeddingsLength": 768,
 				"ScaleFactor": 0.18215,

OnnxStack.Core/Config/OnnxModelType.cs

@@ -7,6 +7,5 @@ public enum OnnxModelType
         TextEncoder = 20,
         VaeEncoder = 30,
         VaeDecoder = 40,
-        SafetyChecker = 100,
     }
 }

OnnxStack.StableDiffusion/Common/IModelOptions.cs

@@ -12,7 +12,6 @@ public interface IModelOptions : IOnnxModel
         int BlankTokenId { get; set; }
         float ScaleFactor { get; set; }
         int TokenizerLimit { get; set; }
-        int InputTokenLimit { get; set; }
         int EmbeddingsLength { get; set; }
         DiffuserPipelineType PipelineType { get; set; }
         List<DiffuserType> Diffusers { get; set; }

OnnxStack.StableDiffusion/Config/ModelOptions.cs

@@ -15,7 +15,6 @@ public class ModelOptions : IModelOptions, IOnnxModelSetConfig
         public bool IsEnabled { get; set; }
         public int PadTokenId { get; set; }
         public int BlankTokenId { get; set; }
-        public int InputTokenLimit { get; set; } = 2048;
         public int TokenizerLimit { get; set; }
         public int EmbeddingsLength { get; set; }
         public float ScaleFactor { get; set; }
@@ -34,7 +33,7 @@ public class ModelOptions : IModelOptions, IOnnxModelSetConfig
 
         public void InitBlankTokenArray()
         {
-            BlankTokenValueArray = Enumerable.Repeat(BlankTokenId, InputTokenLimit).ToImmutableArray();
+            BlankTokenValueArray = Enumerable.Repeat(BlankTokenId, 20480).ToImmutableArray();
         }
     }
 }

OnnxStack.StableDiffusion/Diffusers/LatentConsistency/LatentConsistencyDiffuser.cs

@@ -193,9 +193,18 @@ protected virtual async Task<DenseTensor<float>> DecodeLatents(IModelOptions mod
         protected virtual IReadOnlyList<NamedOnnxValue> CreateUnetInputParams(IModelOptions model, DenseTensor<float> inputTensor, DenseTensor<float> promptEmbeddings, DenseTensor<float> guidanceEmbeddings, int timestep)
         {
             var inputNames = _onnxModelService.GetInputNames(model, OnnxModelType.Unet);
+            var inputMetaData = _onnxModelService.GetInputMetadata(model, OnnxModelType.Unet);
+
+            // Some models support Long or Float, could be more but fornow just support these 2
+            var timesepMetaKey = inputNames[1];
+            var timestepMetaData = inputMetaData[timesepMetaKey];
+            var timestepNamedOnnxValue = timestepMetaData.ElementDataType == TensorElementType.Int64
+                ? NamedOnnxValue.CreateFromTensor(timesepMetaKey, new DenseTensor<long>(new long[] { timestep }, new int[] { 1 }))
+                : NamedOnnxValue.CreateFromTensor(timesepMetaKey, new DenseTensor<float>(new float[] { timestep }, new int[] { 1 }));
+
             return CreateInputParameters(
                  NamedOnnxValue.CreateFromTensor(inputNames[0], inputTensor),
-                 NamedOnnxValue.CreateFromTensor(inputNames[1], new DenseTensor<long>(new long[] { timestep }, new int[] { 1 })),
+                 timestepNamedOnnxValue,
                  NamedOnnxValue.CreateFromTensor(inputNames[2], promptEmbeddings),
                  NamedOnnxValue.CreateFromTensor(inputNames[3], guidanceEmbeddings));
         }

OnnxStack.StableDiffusion/Diffusers/StableDiffusion/StableDiffusionDiffuser.cs

@@ -213,9 +213,18 @@ protected virtual DenseTensor<float> PerformGuidance(DenseTensor<float> noisePre
         protected virtual IReadOnlyList<NamedOnnxValue> CreateUnetInputParams(IModelOptions model, DenseTensor<float> inputTensor, DenseTensor<float> promptEmbeddings, int timestep)
         {
             var inputNames = _onnxModelService.GetInputNames(model, OnnxModelType.Unet);
+            var inputMetaData = _onnxModelService.GetInputMetadata(model, OnnxModelType.Unet);
+
+            // Some models support Long or Float, could be more but fornow just support these 2
+            var timesepMetaKey = inputNames[1];
+            var timestepMetaData = inputMetaData[timesepMetaKey];
+            var timestepNamedOnnxValue = timestepMetaData.ElementDataType == TensorElementType.Int64
+                ? NamedOnnxValue.CreateFromTensor(timesepMetaKey, new DenseTensor<long>(new long[] { timestep }, new int[] { 1 }))
+                : NamedOnnxValue.CreateFromTensor(timesepMetaKey, new DenseTensor<float>(new float[] { timestep }, new int[] { 1 }));
+
             return CreateInputParameters(
                  NamedOnnxValue.CreateFromTensor(inputNames[0], inputTensor),
-                 NamedOnnxValue.CreateFromTensor(inputNames[1], new DenseTensor<long>(new long[] { timestep }, new int[] { 1 })),
+                 timestepNamedOnnxValue,
                  NamedOnnxValue.CreateFromTensor(inputNames[2], promptEmbeddings));
         }
 

OnnxStack.StableDiffusion/README.md

@@ -153,7 +153,6 @@ Each model can be assigned to its own device, which is handy if you have only a
       "Name": "StableDiffusion 1.5",
       "PadTokenId": 49407,
       "BlankTokenId": 49407,
-      "InputTokenLimit": 512,
       "TokenizerLimit": 77,
       "EmbeddingsLength": 768,
       "ScaleFactor": 0.18215,