Implement ConvLSTM/ConvGRU cell with Pytorch. This idea has been proposed in this paper:Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting Experiments with ConvLSTM on MovingMN
Encoder-decoder structure. Takes in a sequence of 10 movingMNIST fames and attempts to output the remaining frames. Instructions RequiresPytorch v1.1or later (and GPUs) Clone repository git clone https://github.com/jhhuang96/ConvLSTM-PyTorch.git ...
使用PyTorch 创建的多步时间序列预测的 Encoder-Decoder 模型 数据网络pytorchself模型 Encoder-decoder 模型在序列到序列的自然语言处理任务(如语言翻译等)中提供了最先进的结果。多步时间序列预测也可以被视为一个 seq2seq 任务,可以使用 encoder-decoder 模型来处理。本文提供了一个用于解决 Kaggle 时间序列预测任务的...
Encoder-decoder structure. Takes in a sequence of 10 movingMNIST fames and attempts to output the remaining frames. Instructions RequiresPytorch v1.1or later (and GPUs) Clone repository git clone https://github.com/jhhuang96/ConvLSTM-PyTorch.git ...
1#-*- encoding: utf-8 -*-2"""3@File : main.py4@Time : 2020/11/145@Author : Ding6@Description: main function7"""89importos10fromConvLSTM.encoderimportEncoder11fromConvLSTM.decoderimportDecoder12fromConvLSTM.modelimportED13fromConvLSTM.net_paramsimportconvgru_encoder_params, convgru_decoder_par...
ConvLSTM2D:卷积长短记忆循环网络层。结构上类似LSTM,但对输入的转换操作和对状态的转换操作都是卷积运算。 Bidirectional:双向循环网络包装器。可以将LSTM,GRU等层包装成双向循环网络。从而增强特征提取能力。 RNN:RNN基本层。接受一个循环网络单元或一个循环单元列表,通过调用tf.keras.backend.rnn函数在序列上进行迭代从...
'TransformerDecoder', 'TransformerDecoderLayer', 'TransformerEncoder', 'TransformerEncoderLayer', 'TripletMarginLoss', 'TripletMarginWithDistanceLoss', 'Unflatten', 'Unfold', 'UninitializedBuffer', 'UninitializedParameter', 'Upsample', 'UpsamplingBilinear2d', 'UpsamplingNearest2d', 'ZeroPad1d', 'ZeroPa...
袁宝玺/ConvLSTM-PyTorch forked fromlhx/ConvLSTM-PyTorch 确定同步? 同步操作将从lhx/ConvLSTM-PyTorch强制同步,此操作会覆盖自 Fork 仓库以来所做的任何修改,且无法恢复!!! 确定后同步将在后台操作,完成时将刷新页面,请耐心等待。 删除在远程仓库中不存在的分支和标签 ...
convlstm_forecaster_params[1]).cuda() iftorch.cuda.device_count()>1: encoder=nn.DataParallel(encoder) decoder=nn.DataParallel(decoder) trainFolder=MovingMNIST(is_train=True, root='data/', n_frames_input=10, n_frames_output=10, num_objects=[3]) ...
ConvLSTM/ConvGRU (Encoder-Decoder) with PyTorch on Moving-MNIST - ConvLSTM-PyTorch/encoder.py at master · joynny/ConvLSTM-PyTorch