Ensures interchangeability with schedulers that need to scale the denoising model input depending on the current timestep. A

Forward process in flow-matching Args: sample (`torch.FloatTensor`): The input sample. times

Sets the begin index for the scheduler. This function should be run from pipeline before the inference. Args: begin_inde

Sets the begin index for the scheduler. This function should be run from pipeline before the inference. Args: begin_inde

Sets the discrete timesteps used for the diffusion chain (to be run before inference). Args: num_inference_steps (`int`)

Predict the sample from the previous timestep by reversing the SDE. This function propagates the diffusion process from the learned m

The index counter for current timestep. It will increase 1 after each scheduler step.

The index counter for current timestep. It will increase 1 after each scheduler step.