Uploaded main instructions for basic runs. Need to test and also deta…

…il hyperparameter search and interpretability.

README.md

@@ -19,6 +19,35 @@ Anthony Bourached, Ryan-Rhys Griffiths, Robert Gray, Ashwani Jha, Parashkev Nach
 
 [CMU mocap](http://mocap.cs.cmu.edu/) was obtained from the [repo](https://github.com/chaneyddtt/Convolutional-Sequence-to-Sequence-Model-for-Human-Dynamics) of ConvSeq2Seq paper.
 
+### Training commands
+All the running args are defined in [opt.py](utils/opt.py). We use following commands to train on different datasets and representations.
+To train on angle space, in-distribution, H3.6M:
+```bash
+python main.py --data_dir "[Path To Your H36M data]/h3.6m/dataset/" --variational True --lambda 0.003 --n_z 8 --dropout 0.3 --lr_gamma 1.0 --input_n 10 --output_n 10 --dct_n 20
+```
+in-distribution (CMU):
+```bash
+python main.py --dataset 'cmu_mocap' --data_dir "[Path To Your CMU data]/cmu_mocap/" --variational True --lambda 0.003 --n_z 8 --dropout 0.3 --lr_gamma 1.0 --input_n 10 --output_n 25 --dct_n 35
+```
+to train on 3D space for CMU, simply change the ```--dataset 'cmu_mocap'``` to ```--dataset 'cmu_mocap_3d```. This flag is 'h3.6m' by default.
+
+To train on 'walking' and test out-of-distribution (for h3.6M), include the extra flag:
+```bash
+--out_of_distribution 'walking' 
+```
+identically to train on 'basketball' and test out-of-distribution (for CMU), include the extra flag:
+```bash
+--out_of_distribution 'basketball' 
+```
+The same models may be trained (or used for inference independent of how they were trained) without the VGAE branch by changing the 
+```
+--variational True
+``` 
+flag to 
+```
+--variational False
+```
+(True by default).
 
 ### Citing
 

utils/opt.py

@@ -52,7 +52,7 @@ def _initial(self):
         self.parser.add_argument('--is_norm', dest='is_norm', action='store_true', help='whether to normalize the angles/3d coordinates')
 
         self.parser.add_argument('--out_of_distribution', nargs='+', type=str, default=None, help='input the out of distribution action')
-        self.parser.add_argument('--variational', type=bool, default=False, help='true if want to include a latent variable')
+        self.parser.add_argument('--variational', type=bool, default=True, help='true if want to include a latent variable')
         self.parser.add_argument('--lambda_', type=float, default=0.003, help='weighting loss for VGAE')
         self.parser.add_argument('--n_z', type=int, default=8, help='number of latent dimensions per joint')
         self.parser.add_argument('--num_decoder_stage', type=int, default=6, help='number of graph convolutional blocks in decoder')