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https://github.com/PaddlePaddle/FastDeploy.git
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d74e1209ae
* Update Inpaint pipeline * Update concat * Add GaussianRandomKernel * Update GaussianRandom * Add vae endoder * Add unet infer * Add vae decoder predict * add PrepareMaskAndMaskedImage * Add imwrite * Add time counter * Fix pipeline * use FDTensor move * Fix scaled_linear dpm solver * Add RGB2BGR
35 lines
1.3 KiB
C++
35 lines
1.3 KiB
C++
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#pragma once
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#include "fastdeploy/core/fd_tensor.h"
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namespace fastdeploy {
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class Scheduler {
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public:
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virtual void SetTimesteps(int num_inference_steps) = 0;
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virtual FDTensor GetTimesteps() = 0;
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virtual void Step(const FDTensor& model_output, int timestep,
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const FDTensor& sample, FDTensor* prev_sample) = 0;
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virtual void ScaleModelInput(const FDTensor& sample, FDTensor* out,
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const std::vector<FDTensor>& timesteps = {}) = 0;
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virtual void AddNoise(const FDTensor& original_samples, const FDTensor& noise,
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const FDTensor& timesteps, FDTensor* out) = 0;
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virtual float InitNoiseSigma() = 0;
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};
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} // namespace fastdeploy
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