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Specifications and Common Mistakes

- Specifications and Common Mistakes:

- Misspellings or punctuation mistakes,incorrect formulas, abnormal display.

- Incorrect links, empty cells, or wrong formats.

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- Minor inconsistencies between the UI and descriptions.

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mindflow.cell

API Name	Description	Supported Platforms
mindflow.cell.AttentionBlock	AttentionBlock comprises an MultiHeadAttention and an MLP layer.	Ascend CPU
mindflow.cell.ConditionDiffusionTransformer	Conditioned Diffusion Transformer implementation.	Ascend
mindflow.cell.DiffusionTrainer	Diffusion Trainer base class.	Ascend
mindflow.cell.DiffusionTransformer	Diffusion model with Transformer backbone implementation.	Ascend
mindflow.cell.DDIMPipeline	Pipeline for DDIM generation.	Ascend
mindflow.cell.DDIMScheduler	DDIMScheduler extends the denoising procedure introduced in denoising diffusion probabilistic models.	Ascend
mindflow.cell.DDPMPipeline	Pipeline for DDPM generation.	Ascend
mindflow.cell.DDPMScheduler	DDPMScheduler is an implementation of the denoising procedure introduced in denoising diffusion probabilistic models (DDPMs).	Ascend
mindflow.cell.FCSequential	A sequential container of the dense layers, dense layers are added to the container sequentially.	Ascend GPU
mindflow.cell.FNO1D	The 1D Fourier Neural Operator, which usually contains a Lifting Layer, a Fourier Block Layer and a Projection Layer.	Ascend GPU
mindflow.cell.FNO2D	The 2D Fourier Neural Operator, which usually contains a Lifting Layer, a Fourier Block Layer and a Projection Layer.	Ascend GPU
mindflow.cell.FNO3D	The 3D Fourier Neural Operator, which usually contains a Lifting Layer, a Fourier Block Layer and a Projection Layer.	Ascend GPU
mindflow.cell.InputScale	Scale the input value to specified region based on $(x_i-input\mathrm{\_}center)\ast input\mathrm{\_}scale$	Ascend GPU
mindflow.cell.LinearBlock	The LinearBlock.	Ascend GPU
mindflow.cell.MultiHeadAttention	Multi Head Attention proposed in Attention Is All You Need.	Ascend CPU
mindflow.cell.MultiScaleFCSequential	The multi-scale fully conneted network.	Ascend GPU
mindflow.cell.PDENet	The PDE-Net model.	Ascend GPU
mindflow.cell.PeRCNN	Physics-embedded Recurrent Convolutional Neural Network (PeRCNN) Cell.	Ascend GPU
mindflow.cell.ResBlock	The ResBlock of dense layer.	Ascend GPU
mindflow.cell.SNO	The Spectral Neural Operator (SNO) base class, which contains a lifting layer (encoder), multiple spectral transform layers (linear transforms in spectral space) and a projection layer (decoder).	Ascend GPU
mindflow.cell.SNO1D	The 1D SNO, which contains a lifting layer (encoder), multiple spectral transform layers and a projection layer (decoder).	Ascend GPU CPU
mindflow.cell.SNO2D	The 2D SNO, which contains a lifting layer (encoder), multiple spectral transform layers and a projection layer (decoder).	Ascend GPU CPU
mindflow.cell.SNO3D	The 3D SNO, which contains a lifting layer (encoder), multiple spectral transform layers and a projection layer (decoder).	Ascend GPU CPU
mindflow.cell.UNet2D	The 2-dimensional U-Net model.	Ascend GPU
mindflow.cell.ViT	This module based on ViT backbone which including encoder, decoding_embedding, decoder and dense layer.	Ascend GPU
mindflow.cell.get_activation	Gets the activation function.	Ascend GPU