update docs and configs

README.md

@@ -77,9 +77,11 @@ python setup.py develop
 * tqdm
 </details>
 
+Please refer to [install.md](docs/en/install.md) for more detailed instructions.
+
 ## Getting Started
 
-An example of single GPU training SimVP+gSTA on Moving MNIST dataset.
+Please see [get_started.md](docs/en/get_started.md) for the basic usage. Here is an example of single GPU training SimVP+gSTA on Moving MNIST dataset.
 ```shell
 bash tools/prepare_data/download_mmnist.sh
 python tools/non_dist_train.py -d mmnist -m SimVP --model_type gsta --lr 1e-3 --ex_name mmnist_simvp_gsta

configs/mmnist/ConvLSTM-L.py

@@ -14,4 +14,6 @@
 filter_size = 5
 stride = 1
 patch_size = 4
-layer_norm = 0
+layer_norm = 0
+# training
+sched = 'onecycle'

configs/mmnist/ConvLSTM.py

@@ -14,4 +14,6 @@
 filter_size = 5
 stride = 1
 patch_size = 4
-layer_norm = 0
+layer_norm = 0
+# training
+sched = 'onecycle'

configs/mmnist/CrevNet.py

@@ -1,4 +1,6 @@
 method = 'CrevNet'
 n_eval = 18
 rnn_size = 32
-predictor_rnn_layers = 8
+predictor_rnn_layers = 8
+# training
+sched = 'onecycle'

configs/mmnist/E3DLSTM.py

@@ -14,4 +14,6 @@
 filter_size = 5
 stride = 1
 patch_size = 4
-layer_norm = 0
+layer_norm = 0
+# training
+sched = 'onecycle'

configs/mmnist/MAU.py

@@ -13,4 +13,6 @@
 sr_size = 4
 tau = 5
 cell_mode = 'normal'
-model_mode = 'normal'
+model_mode = 'normal'
+# training
+sched = 'onecycle'

configs/mmnist/MIM.py

@@ -17,4 +17,5 @@
 layer_norm = 0
 # training
 batch_size = 16
-val_batch_size = 16
+val_batch_size = 16
+sched = 'onecycle'

configs/mmnist/PhyDNet.py

@@ -1 +1,3 @@
-method = 'PhyDNet'
+method = 'PhyDNet'
+# training
+sched = 'onecycle'

configs/mmnist/PredRNN.py

@@ -14,4 +14,6 @@
 filter_size = 5
 stride = 1
 patch_size = 4
-layer_norm = 0
+layer_norm = 0
+# training
+sched = 'onecycle'

configs/mmnist/PredRNNpp.py

@@ -14,4 +14,6 @@
 filter_size = 5
 stride = 1
 patch_size = 4
-layer_norm = 0
+layer_norm = 0
+# training
+sched = 'onecycle'

configs/mmnist/PredRNNv2.py

@@ -15,4 +15,6 @@
 stride = 1
 patch_size = 4
 layer_norm = 0
-decouple_beta = 0.1
+decouple_beta = 0.1
+# training
+sched = 'onecycle'

configs/mmnist/SimVP.py

@@ -1,8 +1,11 @@
 method = 'SimVP'
+# model
 spatio_kernel_enc = 3
 spatio_kernel_dec = 3
 # model_type = None  # define `model_type` in args
 hid_S = 64
 hid_T = 512
 N_T = 8
-N_S = 4
+N_S = 4
+# training
+sched = 'onecycle'

configs/mmnist/simvp/SimVP-L.py

@@ -1,8 +1,14 @@
 method = 'SimVP'
+# model
 spatio_kernel_enc = 3
 spatio_kernel_dec = 3
 # model_type = None  # define `model_type` in args
 hid_S = 128
 hid_T = 1024
 N_T = 24
-N_S = 4
+N_S = 4
+# training
+lr = 1e-3
+batch_size = 16
+drop_path = 0
+sched = 'onecycle'

configs/mmnist/simvp/SimVP_ConvMixer.py

@@ -1,11 +1,14 @@
 method = 'SimVP'
+# model
 spatio_kernel_enc = 3
 spatio_kernel_dec = 3
 model_type = 'convmixer'
 hid_S = 64
 hid_T = 512
 N_T = 8
 N_S = 4
+# training
 lr = 1e-2
 batch_size = 16
-drop_path = 0
+drop_path = 0
+sched = 'onecycle'

configs/mmnist/simvp/SimVP_ConvNeXt.py

@@ -1,11 +1,14 @@
 method = 'SimVP'
+# model
 spatio_kernel_enc = 3
 spatio_kernel_dec = 3
 model_type = 'convnext'
 hid_S = 64
 hid_T = 512
 N_T = 8
 N_S = 4
+# training
 lr = 1e-2
 batch_size = 16
-drop_path = 0
+drop_path = 0
+sched = 'onecycle'

configs/mmnist/simvp/SimVP_HorNet.py

@@ -1,11 +1,14 @@
 method = 'SimVP'
+# model
 spatio_kernel_enc = 3
 spatio_kernel_dec = 3
 model_type = 'hornet'
 hid_S = 64
 hid_T = 512
 N_T = 8
 N_S = 4
+# training
 lr = 1e-3
 batch_size = 16
-drop_path = 0
+drop_path = 0
+sched = 'onecycle'

configs/mmnist/simvp/SimVP_IncepU.py

@@ -1,10 +1,13 @@
 method = 'SimVP'
+# model
 spatio_kernel_enc = 3
 spatio_kernel_dec = 3
 model_type = 'IncepU'  # SimVP.V1
 hid_S = 64
 hid_T = 512
 N_T = 8
 N_S = 4
+# training
 lr = 1e-3
-batch_size = 16
+batch_size = 16
+sched = 'onecycle'

configs/mmnist/simvp/SimVP_MLPMixer.py

@@ -1,11 +1,14 @@
 method = 'SimVP'
+# model
 spatio_kernel_enc = 3
 spatio_kernel_dec = 3
 model_type = 'mlp'
 hid_S = 64
 hid_T = 512
 N_T = 8
 N_S = 4
+# training
 lr = 1e-3
 batch_size = 16
-drop_path = 0
+drop_path = 0
+sched = 'onecycle'

configs/mmnist/simvp/SimVP_MogaNet.py

@@ -1,11 +1,14 @@
 method = 'SimVP'
+# model
 spatio_kernel_enc = 3
 spatio_kernel_dec = 3
 model_type = 'moga'
 hid_S = 64
 hid_T = 512
 N_T = 8
 N_S = 4
+# training
 lr = 1e-3
 batch_size = 16
-drop_path = 0
+drop_path = 0
+sched = 'onecycle'

configs/mmnist/simvp/SimVP_Poolformer.py

@@ -1,11 +1,14 @@
 method = 'SimVP'
+# model
 spatio_kernel_enc = 3
 spatio_kernel_dec = 3
 model_type = 'poolformer'
 hid_S = 64
 hid_T = 512
 N_T = 8
 N_S = 4
+# training
 lr = 1e-3
 batch_size = 16
-drop_path = 0
+drop_path = 0
+sched = 'onecycle'

configs/mmnist/simvp/SimVP_Swin.py

@@ -1,11 +1,14 @@
 method = 'SimVP'
+# model
 spatio_kernel_enc = 3
 spatio_kernel_dec = 3
 model_type = 'swin'
 hid_S = 64
 hid_T = 512
 N_T = 8
 N_S = 4
+# training
 lr = 1e-3
 batch_size = 16
-drop_path = 0
+drop_path = 0
+sched = 'onecycle'

configs/mmnist/simvp/SimVP_Uniformer.py

@@ -1,11 +1,14 @@
 method = 'SimVP'
+# model
 spatio_kernel_enc = 3
 spatio_kernel_dec = 3
 model_type = 'uniformer'
 hid_S = 64
 hid_T = 512
 N_T = 8
 N_S = 4
+# training
 lr = 5e-4
 batch_size = 16
-drop_path = 0
+drop_path = 0
+sched = 'onecycle'

configs/mmnist/simvp/SimVP_VAN.py

@@ -1,11 +1,14 @@
 method = 'SimVP'
+# model
 spatio_kernel_enc = 3
 spatio_kernel_dec = 3
 model_type = 'convmixer'
 hid_S = 64
 hid_T = 512
 N_T = 8
 N_S = 4
+# training
 lr = 1e-3
 batch_size = 16
-drop_path = 0
+drop_path = 0
+sched = 'onecycle'

configs/mmnist/simvp/SimVP_ViT.py

@@ -1,11 +1,14 @@
 method = 'SimVP'
+# model
 spatio_kernel_enc = 3
 spatio_kernel_dec = 3
 model_type = 'vit'
 hid_S = 64
 hid_T = 512
 N_T = 8
 N_S = 4
+# training
 lr = 1e-3
 batch_size = 16
-drop_path = 0
+drop_path = 0
+sched = 'onecycle'

configs/mmnist/simvp/SimVP_gSTA-L.py

@@ -1,11 +1,14 @@
 method = 'SimVP'
+# model
 spatio_kernel_enc = 3
 spatio_kernel_dec = 3
 model_type = 'gSTA'
 hid_S = 128
 hid_T = 1024
 N_T = 24
 N_S = 4
+# training
 lr = 1e-3
 batch_size = 16
-drop_path = 0
+drop_path = 0
+sched = 'onecycle'

configs/mmnist/simvp/SimVP_gSTA.py

@@ -1,11 +1,14 @@
 method = 'SimVP'
+# model
 spatio_kernel_enc = 3
 spatio_kernel_dec = 3
 model_type = 'gSTA'
 hid_S = 64
 hid_T = 512
 N_T = 8
 N_S = 4
+# training
 lr = 1e-3
 batch_size = 16
-drop_path = 0
+drop_path = 0
+sched = 'onecycle'

configs/taxibj/SimVP.py

@@ -1,8 +1,9 @@
 method = 'SimVP'
+# model
 spatio_kernel_enc = 3
 spatio_kernel_dec = 3
 # model_type = None
-hid_S = 64
+hid_S = 32
 hid_T = 256
 N_T = 8
 N_S = 2

configs/taxibj/simvp/SimVP_ConvMixer.py

@@ -0,0 +1,9 @@
+method = 'SimVP'
+# model
+spatio_kernel_enc = 3
+spatio_kernel_dec = 3
+model_type = 'convmixer'
+hid_S = 32
+hid_T = 256
+N_T = 8
+N_S = 2