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Batched TimeIds #82

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Dec 26, 2023
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Batched TimeIds #82

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5 changes: 3 additions & 2 deletions OnnxStack.StableDiffusion/Diffusers/LatentConsistencyXL/InpaintLegacyDiffuser.cs
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Original file line number Diff line number Diff line change
Expand Up @@ -72,7 +72,7 @@ protected override async Task<DenseTensor<float>> SchedulerStepAsync(StableDiffu
var metadata = _onnxModelService.GetModelMetadata(modelOptions, OnnxModelType.Unet);

// Get Time ids
var addTimeIds = GetAddTimeIds(modelOptions, schedulerOptions, performGuidance);
var addTimeIds = GetAddTimeIds(modelOptions, schedulerOptions);

// Loop though the timesteps
var step = 0;
Expand All @@ -86,6 +86,7 @@ protected override async Task<DenseTensor<float>> SchedulerStepAsync(StableDiffu
var inputLatent = performGuidance ? latents.Repeat(2) : latents;
var inputTensor = scheduler.ScaleInput(inputLatent, timestep);
var timestepTensor = CreateTimestepTensor(timestep);
var timeids = performGuidance ? addTimeIds.Repeat(2) : addTimeIds;

var outputChannels = performGuidance ? 2 : 1;
var outputDimension = schedulerOptions.GetScaledDimension(outputChannels);
Expand All @@ -95,7 +96,7 @@ protected override async Task<DenseTensor<float>> SchedulerStepAsync(StableDiffu
inferenceParameters.AddInputTensor(timestepTensor);
inferenceParameters.AddInputTensor(promptEmbeddings.PromptEmbeds);
inferenceParameters.AddInputTensor(promptEmbeddings.PooledPromptEmbeds);
inferenceParameters.AddInputTensor(addTimeIds);
inferenceParameters.AddInputTensor(timeids);
inferenceParameters.AddOutputBuffer(outputDimension);

var results = await _onnxModelService.RunInferenceAsync(modelOptions, OnnxModelType.Unet, inferenceParameters);
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5 changes: 3 additions & 2 deletions OnnxStack.StableDiffusion/Diffusers/StableDiffusionXL/InpaintLegacyDiffuser.cs
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Original file line number Diff line number Diff line change
Expand Up @@ -72,7 +72,7 @@ protected override async Task<DenseTensor<float>> SchedulerStepAsync(StableDiffu
var metadata = _onnxModelService.GetModelMetadata(modelOptions, OnnxModelType.Unet);

// Get Time ids
var addTimeIds = GetAddTimeIds(modelOptions, schedulerOptions, performGuidance);
var addTimeIds = GetAddTimeIds(modelOptions, schedulerOptions);

// Loop though the timesteps
var step = 0;
Expand All @@ -86,6 +86,7 @@ protected override async Task<DenseTensor<float>> SchedulerStepAsync(StableDiffu
var inputLatent = performGuidance ? latents.Repeat(2) : latents;
var inputTensor = scheduler.ScaleInput(inputLatent, timestep);
var timestepTensor = CreateTimestepTensor(timestep);
var timeids = performGuidance ? addTimeIds.Repeat(2) : addTimeIds;

var outputChannels = performGuidance ? 2 : 1;
var outputDimension = schedulerOptions.GetScaledDimension(outputChannels);
Expand All @@ -95,7 +96,7 @@ protected override async Task<DenseTensor<float>> SchedulerStepAsync(StableDiffu
inferenceParameters.AddInputTensor(timestepTensor);
inferenceParameters.AddInputTensor(promptEmbeddings.PromptEmbeds);
inferenceParameters.AddInputTensor(promptEmbeddings.PooledPromptEmbeds);
inferenceParameters.AddInputTensor(addTimeIds);
inferenceParameters.AddInputTensor(timeids);
inferenceParameters.AddOutputBuffer(outputDimension);

var results = await _onnxModelService.RunInferenceAsync(modelOptions, OnnxModelType.Unet, inferenceParameters);
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28 changes: 7 additions & 21 deletions OnnxStack.StableDiffusion/Diffusers/StableDiffusionXL/StableDiffusionXLDiffuser.cs
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Original file line number Diff line number Diff line change
Expand Up @@ -60,7 +60,7 @@ protected override async Task<DenseTensor<float>> SchedulerStepAsync(StableDiffu
var metadata = _onnxModelService.GetModelMetadata(modelOptions, OnnxModelType.Unet);

// Get Time ids
var addTimeIds = GetAddTimeIds(modelOptions, schedulerOptions, performGuidance);
var addTimeIds = GetAddTimeIds(modelOptions, schedulerOptions);

// Loop though the timesteps
var step = 0;
Expand All @@ -74,6 +74,7 @@ protected override async Task<DenseTensor<float>> SchedulerStepAsync(StableDiffu
var inputLatent = performGuidance ? latents.Repeat(2) : latents;
var inputTensor = scheduler.ScaleInput(inputLatent, timestep);
var timestepTensor = CreateTimestepTensor(timestep);
var timeids = performGuidance ? addTimeIds.Repeat(2) : addTimeIds;

var outputChannels = performGuidance ? 2 : 1;
var outputDimension = schedulerOptions.GetScaledDimension(outputChannels);
Expand All @@ -83,7 +84,7 @@ protected override async Task<DenseTensor<float>> SchedulerStepAsync(StableDiffu
inferenceParameters.AddInputTensor(timestepTensor);
inferenceParameters.AddInputTensor(promptEmbeddings.PromptEmbeds);
inferenceParameters.AddInputTensor(promptEmbeddings.PooledPromptEmbeds);
inferenceParameters.AddInputTensor(addTimeIds);
inferenceParameters.AddInputTensor(timeids);
inferenceParameters.AddOutputBuffer(outputDimension);

var results = await _onnxModelService.RunInferenceAsync(modelOptions, OnnxModelType.Unet, inferenceParameters);
Expand Down Expand Up @@ -115,26 +116,11 @@ protected override async Task<DenseTensor<float>> SchedulerStepAsync(StableDiffu
/// </summary>
/// <param name="schedulerOptions">The scheduler options.</param>
/// <returns></returns>
protected DenseTensor<float> GetAddTimeIds(StableDiffusionModelSet model, SchedulerOptions schedulerOptions, bool performGuidance)
protected DenseTensor<float> GetAddTimeIds(StableDiffusionModelSet model, SchedulerOptions schedulerOptions)
{
float[] result;
if (model.ModelType == ModelType.Refiner)
{
//original_size + crops_coords_top_left + aesthetic_score
//original_size + crops_coords_top_left + negative_aesthetic_score
result = !performGuidance
? new float[] { schedulerOptions.Height, schedulerOptions.Width, 0, 0, schedulerOptions.AestheticScore }
: new float[] { schedulerOptions.Height, schedulerOptions.Width, 0, 0, schedulerOptions.AestheticNegativeScore, schedulerOptions.Height, schedulerOptions.Width, 0, 0, schedulerOptions.AestheticScore };
}
else
{
//original_size + crops_coords_top_left + target_size
//original_size + crops_coords_top_left + negative_target_size
result = !performGuidance
? new float[] { schedulerOptions.Height, schedulerOptions.Width, 0, 0, schedulerOptions.Height, schedulerOptions.Width }
: new float[] { schedulerOptions.Height, schedulerOptions.Width, 0, 0, schedulerOptions.Height, schedulerOptions.Width, schedulerOptions.Height, schedulerOptions.Width, 0, 0, schedulerOptions.Height, schedulerOptions.Width };
}

float[] result = model.ModelType == ModelType.Refiner
? new float[] { schedulerOptions.Height, schedulerOptions.Width, 0, 0, schedulerOptions.AestheticScore }
: new float[] { schedulerOptions.Height, schedulerOptions.Width, 0, 0, schedulerOptions.Height, schedulerOptions.Width };
return TensorHelper.CreateTensor(result, new[] { 1, result.Length });
}

Expand Down