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Merge branch 'master' into LCM_Inpaint
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‎.dockerignore‎

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**/.dockerignore
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**/.env
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**/.git
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**/.gitignore
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**/.project
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**/.settings
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**/.toolstarget
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**/.vs
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**/.vscode
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**/.idea
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**/*.*proj.user
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**/*.dbmdl
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**/*.jfm
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**/azds.yaml
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**/bin
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**/charts
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**/docker-compose*
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**/Dockerfile*
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**/node_modules
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**/npm-debug.log
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**/obj
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**/secrets.dev.yaml
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**/values.dev.yaml
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docker-test-output/
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LICENSE
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README.md

‎.gitignore‎

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@@ -344,3 +344,4 @@ test/TensorFlowNET.Examples/mnist
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site/
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/OnnxStack.WebUI/wwwroot/images/Results/*
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docker-test-output/*

‎Dockerfile‎

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FROM mcr.microsoft.com/dotnet/sdk:7.0 AS build
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WORKDIR /app
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# Install Git and Git LFS
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RUN apt-get update && apt-get install -y curl
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RUN curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.deb.sh | bash && apt-get install -y git-lfs
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# Clone the Stable Diffusion 1.5 base model
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RUN git clone https://huggingface.co/runwayml/stable-diffusion-v1-5 -b onnx
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# Clone the LCM Dreamshaper V7 model
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RUN git clone https://huggingface.co/TheyCallMeHex/LCM-Dreamshaper-V7-ONNX
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COPY . .
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RUN dotnet build OnnxStackCore.sln
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ENTRYPOINT ["dotnet", "test", "OnnxStackCore.sln"]

‎OnnxStack.Console/Examples/StableDebug.cs‎

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@@ -52,7 +52,7 @@ public async Task RunAsync()
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foreach (var model in _stableDiffusionService.Models)
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{
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OutputHelpers.WriteConsole($"Loading Model `{model.Name}`...", ConsoleColor.Green);
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await _stableDiffusionService.LoadModel(model);
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await _stableDiffusionService.LoadModelAsync(model);
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foreach (var schedulerType in model.PipelineType.GetSchedulerTypes())
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{
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}
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OutputHelpers.WriteConsole($"Unloading Model `{model.Name}`...", ConsoleColor.Green);
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await _stableDiffusionService.UnloadModel(model);
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await _stableDiffusionService.UnloadModelAsync(model);
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}
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break;
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}

‎OnnxStack.Console/Examples/StableDiffusionBatch.cs‎

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@@ -54,7 +54,7 @@ public async Task RunAsync()
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foreach (var model in _stableDiffusionService.Models)
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{
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OutputHelpers.WriteConsole($"Loading Model `{model.Name}`...", ConsoleColor.Green);
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await _stableDiffusionService.LoadModel(model);
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await _stableDiffusionService.LoadModelAsync(model);
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var batchIndex = 0;
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var callback = (int batch, int batchCount, int step, int steps) =>
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}
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OutputHelpers.WriteConsole($"Unloading Model `{model.Name}`...", ConsoleColor.Green);
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await _stableDiffusionService.UnloadModel(model);
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await _stableDiffusionService.UnloadModelAsync(model);
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}
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}
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}

‎OnnxStack.Console/Examples/StableDiffusionExample.cs‎

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foreach (var model in _stableDiffusionService.Models)
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{
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OutputHelpers.WriteConsole($"Loading Model `{model.Name}`...", ConsoleColor.Green);
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await _stableDiffusionService.LoadModel(model);
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await _stableDiffusionService.LoadModelAsync(model);
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foreach (var schedulerType in model.PipelineType.GetSchedulerTypes())
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{
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}
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OutputHelpers.WriteConsole($"Unloading Model `{model.Name}`...", ConsoleColor.Green);
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await _stableDiffusionService.UnloadModel(model);
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await _stableDiffusionService.UnloadModelAsync(model);
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}
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}
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}

‎OnnxStack.Console/Examples/StableDiffusionGenerator.cs‎

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foreach (var model in _stableDiffusionService.Models)
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{
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OutputHelpers.WriteConsole($"Loading Model `{model.Name}`...", ConsoleColor.Green);
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await _stableDiffusionService.LoadModel(model);
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await _stableDiffusionService.LoadModelAsync(model);
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foreach (var generationPrompt in _generationPrompts)
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{
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}
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OutputHelpers.WriteConsole($"Unloading Model `{model.Name}`...", ConsoleColor.Green);
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await _stableDiffusionService.UnloadModel(model);
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await _stableDiffusionService.UnloadModelAsync(model);
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}
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OutputHelpers.WriteConsole("Complete :)", ConsoleColor.DarkMagenta);
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OutputHelpers.ReadConsole(ConsoleColor.Gray);

‎OnnxStack.Console/OnnxStack.Console.csproj‎

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</PropertyGroup>
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<ItemGroup>
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<PackageReference Include="Microsoft.Extensions.Hosting" Version="7.0.1" />
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<PackageReference Include="Microsoft.Extensions.Logging" Version="7.0.0" />
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<PackageReference Include="Microsoft.ML.OnnxRuntime.DirectML" Version="1.16.1" />
12+
<PackageReference Include="Microsoft.Extensions.Hosting" Version="8.0.0" />
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<PackageReference Include="Microsoft.Extensions.Logging" Version="8.0.0" />
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<PackageReference Include="Microsoft.ML.OnnxRuntime.DirectML" Version="1.16.2" />
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</ItemGroup>
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<ItemGroup>

‎OnnxStack.Console/appsettings.json‎

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"InterOpNumThreads": 0,
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"IntraOpNumThreads": 0,
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"ExecutionMode": "ORT_SEQUENTIAL",
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"ExecutionProvider": "Cuda",
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"ExecutionProvider": "DirectML",
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"ModelConfigurations": [
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{
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"Type": "Tokenizer",

‎OnnxStack.Core/Extensions.cs‎

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using Microsoft.ML.OnnxRuntime.Tensors;
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using OnnxStack.Core.Config;
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using System;
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using System.Buffers;
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using System.Collections.Concurrent;
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using System.Collections.Generic;
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using System.Linq;
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using System.Numerics;
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using System.Runtime.InteropServices;
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namespace OnnxStack.Core
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{
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}
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207209

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/// <summary>
211+
/// Converts to long.
212+
/// </summary>
213+
/// <param name="array">The array.</param>
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/// <returns></returns>
208215
public static long[] ToLong(this ReadOnlySpan<int> array)
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{
210217
return Array.ConvertAll(array.ToArray(), Convert.ToInt64);
211218
}
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/// <summary>
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/// Converts the string representation of a number to an integer.
223+
/// </summary>
224+
/// <param name="array">The array.</param>
225+
/// <returns></returns>
213226
public static int[] ToInt(this long[] array)
214227
{
215228
return Array.ConvertAll(array, Convert.ToInt32);
216229
}
217230

231+
232+
/// <summary>
233+
/// Converts to long.
234+
/// </summary>
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/// <param name="array">The array.</param>
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/// <returns></returns>
218237
public static long[] ToLong(this int[] array)
219238
{
220239
return Array.ConvertAll(array, Convert.ToInt64);
221240
}
222241

223242

224-
public static OrtValue ToOrtValue<T>(this DenseTensor<T> tensor) where T : unmanaged
243+
/// <summary>
244+
/// Creates and OrtValue form the DenseTensor and NodeMetaData provided
245+
/// </summary>
246+
/// <param name="tensor">The tensor.</param>
247+
/// <param name="nodeMetadata">The node metadata.</param>
248+
/// <returns></returns>
249+
public static OrtValue ToOrtValue(this DenseTensor<float> tensor, NodeMetadata nodeMetadata)
225250
{
226-
return OrtValue.CreateTensorValueFromMemory(OrtMemoryInfo.DefaultInstance, tensor.Buffer, tensor.Dimensions.ToLong());
251+
var dimensions = tensor.Dimensions.ToLong();
252+
return nodeMetadata.ElementDataType switch
253+
{
254+
TensorElementType.Float16 => OrtValue.CreateTensorValueFromMemory(OrtMemoryInfo.DefaultInstance, tensor.Buffer.ToFloat16(), dimensions),
255+
TensorElementType.BFloat16 => OrtValue.CreateTensorValueFromMemory(OrtMemoryInfo.DefaultInstance, tensor.Buffer.ToBFloat16(), dimensions),
256+
_ => OrtValue.CreateTensorValueFromMemory(OrtMemoryInfo.DefaultInstance, tensor.Buffer, dimensions)
257+
};
227258
}
228259

260+
261+
/// <summary>
262+
/// Creates and allocates output tensors buffer.
263+
/// </summary>
264+
/// <param name="nodeMetadata">The node metadata.</param>
265+
/// <param name="dimensions">The dimensions.</param>
266+
/// <returns></returns>
267+
public static OrtValue CreateOutputBuffer(this NodeMetadata nodeMetadata, ReadOnlySpan<int> dimensions)
268+
{
269+
return OrtValue.CreateAllocatedTensorValue(OrtAllocator.DefaultInstance, nodeMetadata.ElementDataType, dimensions.ToLong());
270+
}
271+
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273+
/// <summary>
274+
/// Converts to DenseTensor<float>.
275+
/// </summary>
276+
/// <param name="ortValue">The ort value.</param>
277+
/// <returns></returns>
278+
public static DenseTensor<float> ToDenseTensor(this OrtValue ortValue)
279+
{
280+
var typeInfo = ortValue.GetTensorTypeAndShape();
281+
var dimensions = typeInfo.Shape.ToInt();
282+
return typeInfo.ElementDataType switch
283+
{
284+
TensorElementType.Float16 => new DenseTensor<float>(ortValue.GetTensorDataAsSpan<Float16>().ToFloat(), dimensions),
285+
TensorElementType.BFloat16 => new DenseTensor<float>(ortValue.GetTensorDataAsSpan<BFloat16>().ToFloat(), dimensions),
286+
_ => new DenseTensor<float>(ortValue.GetTensorDataAsSpan<float>().ToArray(), dimensions)
287+
};
288+
}
289+
290+
291+
/// <summary>
292+
/// Converts to array.
293+
/// </summary>
294+
/// <param name="ortValue">The ort value.</param>
295+
/// <returns></returns>
296+
public static float[] ToArray(this OrtValue ortValue)
297+
{
298+
var typeInfo = ortValue.GetTensorTypeAndShape();
299+
var dimensions = typeInfo.Shape.ToInt();
300+
return typeInfo.ElementDataType switch
301+
{
302+
TensorElementType.Float16 => ortValue.GetTensorDataAsSpan<Float16>().ToFloat().ToArray(),
303+
TensorElementType.BFloat16 => ortValue.GetTensorDataAsSpan<BFloat16>().ToFloat().ToArray(),
304+
_ => ortValue.GetTensorDataAsSpan<float>().ToArray()
305+
};
306+
}
307+
308+
309+
/// <summary>
310+
/// Converts to float16.
311+
/// </summary>
312+
/// <param name="inputMemory">The input memory.</param>
313+
/// <returns></returns>
314+
internal static Memory<Float16> ToFloat16(this Memory<float> inputMemory)
315+
{
316+
var elementCount = inputMemory.Length;
317+
var floatArray = new Float16[inputMemory.Length];
318+
for (int i = 0; i < elementCount; i++)
319+
floatArray[i] = (Float16)inputMemory.Span[i];
320+
321+
return floatArray.AsMemory();
322+
}
323+
324+
325+
/// <summary>
326+
/// Converts to BFloat16.
327+
/// </summary>
328+
/// <param name="inputMemory">The input memory.</param>
329+
/// <returns></returns>
330+
internal static Memory<BFloat16> ToBFloat16(this Memory<float> inputMemory)
331+
{
332+
var elementCount = inputMemory.Length;
333+
var floatArray = new BFloat16[inputMemory.Length];
334+
for (int i = 0; i < elementCount; i++)
335+
floatArray[i] = (BFloat16)inputMemory.Span[i];
336+
337+
return floatArray.AsMemory();
338+
}
339+
340+
341+
/// <summary>
342+
/// Converts to float.
343+
/// </summary>
344+
/// <param name="inputMemory">The input memory.</param>
345+
/// <returns></returns>
346+
internal static Memory<float> ToFloat(this ReadOnlySpan<Float16> inputMemory)
347+
{
348+
var elementCount = inputMemory.Length;
349+
var floatArray = new float[elementCount];
350+
for (int i = 0; i < elementCount; i++)
351+
floatArray[i] = (float)inputMemory[i];
352+
353+
return floatArray.AsMemory();
354+
}
355+
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357+
/// <summary>
358+
/// Converts to float.
359+
/// </summary>
360+
/// <param name="inputMemory">The input memory.</param>
361+
/// <returns></returns>
362+
internal static Memory<float> ToFloat(this ReadOnlySpan<BFloat16> inputMemory)
363+
{
364+
var elementCount = inputMemory.Length;
365+
var floatArray = new float[elementCount];
366+
for (int i = 0; i < elementCount; i++)
367+
floatArray[i] = (float)inputMemory[i];
368+
369+
return floatArray.AsMemory();
370+
}
229371
}
230372
}

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