jthsieh / ddpae-video-prediction Goto Github PK

[2019-02-20,14:11:07] Arguments: 
 - batch_size: 100
 - ckpt_dir: /l/yildizc1/Dropbox/Academic_Stuff/gp/odegp/others/DDPAE-video-prediction_original/ckpt
 - ckpt_name: 200k
 - ckpt_path: /l/yildizc1/Dropbox/Academic_Stuff/gp/odegp/others/DDPAE-video-prediction_original/ckpt/bouncing_balls/crop_NC4_lr1.0e-03_bt100_200k
 - content_latent_size: 128
 - dset_dir: /l/yildizc1/Dropbox/Academic_Stuff/gp/odegp/others/DDPAE-video-prediction_original/datasets
 - dset_name: bouncing_balls
 - dset_path: /l/yildizc1/Dropbox/Academic_Stuff/gp/odegp/others/DDPAE-video-prediction_original/datasets/bouncing_balls
 - evaluate_every: 10
 - gpus: 0
 - hidden_size: 128
 - image_latent_size: 256
 - image_size: (128, 128)
 - independent_components: 0
 - is_train: True
 - load_ckpt_dir: 
 - load_ckpt_epoch: 0
 - log_every: 400
 - lr_decay: 1
 - lr_init: 0.001
 - model: crop
 - n_channels: 1
 - n_components: 4
 - n_epochs: 50
 - n_frames_input: 10
 - n_frames_output: 10
 - n_iters: 200000
 - n_workers: 4
 - ngf: 8
 - num_objects: [2]
 - pose_latent_size: 3
 - save_every: 50
 - split: train
 - start_epoch: 0
 - stn_scale_prior: 4.0
 - when_to_predict_only: 0
Val dataset: 500
Image size: 128
[2019-02-20,14:11:09] Total epochs: 40000
Train epoch 0
Traceback (most recent call last):
  File "/u/65/yildizc1/unix/.local/lib/python3.6/site-packages/pyro/poutine/trace_messenger.py", line 147, in __call__
    ret = self.fn(*args, **kwargs)
  File "/l/yildizc1/Dropbox/Academic_Stuff/gp/odegp/others/DDPAE-video-prediction_original/models/DDPAE.py", line 380, in guide
    self.encode(input, sample=True)
  File "/l/yildizc1/Dropbox/Academic_Stuff/gp/odegp/others/DDPAE-video-prediction_original/models/DDPAE.py", line 315, in encode
    initial_pose_mu, initial_pose_sigma = self.pose_model(input)
  File "/u/65/yildizc1/unix/.local/lib/python3.6/site-packages/torch/nn/modules/module.py", line 489, in __call__
    result = self.forward(*input, **kwargs)
  File "/u/65/yildizc1/unix/.local/lib/python3.6/site-packages/torch/nn/parallel/data_parallel.py", line 141, in forward
    return self.module(*inputs[0], **kwargs[0])
  File "/u/65/yildizc1/unix/.local/lib/python3.6/site-packages/torch/nn/modules/module.py", line 489, in __call__
    result = self.forward(*input, **kwargs)
  File "/l/yildizc1/Dropbox/Academic_Stuff/gp/odegp/others/DDPAE-video-prediction_original/models/networks/pose_rnn.py", line 152, in forward
    encoder_outputs, hidden_states = self.encode(input)
  File "/l/yildizc1/Dropbox/Academic_Stuff/gp/odegp/others/DDPAE-video-prediction_original/models/networks/pose_rnn.py", line 80, in encode
    h = torch.cat([hidden[0][0:1], hidden[0][1:]], dim=2)
RuntimeError: invalid argument 0: Sizes of tensors must match except in dimension 2. Got 0 and 1 in dimension 0 at /pytorch/aten/src/THC/generic/THCTensorMath.cu:83

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "train.py", line 38, in <module>
    _, loss_dict = model.train(*data)
  File "/l/yildizc1/Dropbox/Academic_Stuff/gp/odegp/others/DDPAE-video-prediction_original/models/DDPAE.py", line 399, in train
    loss = svi.loss_and_grads(svi.model, svi.guide, input, output)
  File "/u/65/yildizc1/unix/.local/lib/python3.6/site-packages/pyro/infer/trace_elbo.py", line 125, in loss_and_grads
    for model_trace, guide_trace in self._get_traces(model, guide, *args, **kwargs):
  File "/u/65/yildizc1/unix/.local/lib/python3.6/site-packages/pyro/infer/elbo.py", line 164, in _get_traces
    yield self._get_trace(model, guide, *args, **kwargs)
  File "/u/65/yildizc1/unix/.local/lib/python3.6/site-packages/pyro/infer/trace_elbo.py", line 52, in _get_trace
    "flat", self.max_plate_nesting, model, guide, *args, **kwargs)
  File "/u/65/yildizc1/unix/.local/lib/python3.6/site-packages/pyro/infer/enum.py", line 42, in get_importance_trace
    guide_trace = poutine.trace(guide, graph_type=graph_type).get_trace(*args, **kwargs)
  File "/u/65/yildizc1/unix/.local/lib/python3.6/site-packages/pyro/poutine/trace_messenger.py", line 169, in get_trace
    self(*args, **kwargs)
  File "/u/65/yildizc1/unix/.local/lib/python3.6/site-packages/pyro/poutine/trace_messenger.py", line 153, in __call__
    traceback)
  File "/m/work/modules/Ubuntu/14.04/amd64/common/anaconda3/latest/lib/python3.6/site-packages/six.py", line 692, in reraise
    raise value.with_traceback(tb)
  File "/u/65/yildizc1/unix/.local/lib/python3.6/site-packages/pyro/poutine/trace_messenger.py", line 147, in __call__
    ret = self.fn(*args, **kwargs)
  File "/l/yildizc1/Dropbox/Academic_Stuff/gp/odegp/others/DDPAE-video-prediction_original/models/DDPAE.py", line 380, in guide
    self.encode(input, sample=True)
  File "/l/yildizc1/Dropbox/Academic_Stuff/gp/odegp/others/DDPAE-video-prediction_original/models/DDPAE.py", line 315, in encode
    initial_pose_mu, initial_pose_sigma = self.pose_model(input)
  File "/u/65/yildizc1/unix/.local/lib/python3.6/site-packages/torch/nn/modules/module.py", line 489, in __call__
    result = self.forward(*input, **kwargs)
  File "/u/65/yildizc1/unix/.local/lib/python3.6/site-packages/torch/nn/parallel/data_parallel.py", line 141, in forward
    return self.module(*inputs[0], **kwargs[0])
  File "/u/65/yildizc1/unix/.local/lib/python3.6/site-packages/torch/nn/modules/module.py", line 489, in __call__
    result = self.forward(*input, **kwargs)
  File "/l/yildizc1/Dropbox/Academic_Stuff/gp/odegp/others/DDPAE-video-prediction_original/models/networks/pose_rnn.py", line 152, in forward
    encoder_outputs, hidden_states = self.encode(input)
  File "/l/yildizc1/Dropbox/Academic_Stuff/gp/odegp/others/DDPAE-video-prediction_original/models/networks/pose_rnn.py", line 80, in encode
    h = torch.cat([hidden[0][0:1], hidden[0][1:]], dim=2)
RuntimeError: invalid argument 0: Sizes of tensors must match except in dimension 2. Got 0 and 1 in dimension 0 at /pytorch/aten/src/THC/generic/THCTensorMath.cu:83
                                    Trace Shapes:                
                                     Param Sites:                
  pose_model$$$module.image_encoder.main.0.weight   8   1   4   4
  pose_model$$$module.image_encoder.main.2.weight  16   8   4   4
  pose_model$$$module.image_encoder.main.3.weight              16
    pose_model$$$module.image_encoder.main.3.bias              16
  pose_model$$$module.image_encoder.main.5.weight  32  16   4   4
  pose_model$$$module.image_encoder.main.6.weight              32
    pose_model$$$module.image_encoder.main.6.bias              32
  pose_model$$$module.image_encoder.main.8.weight  64  32   4   4
  pose_model$$$module.image_encoder.main.9.weight              64
    pose_model$$$module.image_encoder.main.9.bias              64
 pose_model$$$module.image_encoder.main.11.weight 128  64   4   4
 pose_model$$$module.image_encoder.main.12.weight             128
   pose_model$$$module.image_encoder.main.12.bias             128
 pose_model$$$module.image_encoder.main.14.weight 256 128   4   4
      pose_model$$$module.encode_rnn.weight_ih_l0         512 384
      pose_model$$$module.encode_rnn.weight_hh_l0         512 128
        pose_model$$$module.encode_rnn.bias_ih_l0             512
        pose_model$$$module.encode_rnn.bias_hh_l0             512
     pose_model$$$module.predict_rnn.weight_ih_l0         512 256
     pose_model$$$module.predict_rnn.weight_hh_l0         512 128
       pose_model$$$module.predict_rnn.bias_ih_l0             512
       pose_model$$$module.predict_rnn.bias_hh_l0             512
         pose_model$$$module.beta_mu_layer.weight           3 128
           pose_model$$$module.beta_mu_layer.bias               3
      pose_model$$$module.beta_sigma_layer.weight           3 128
        pose_model$$$module.beta_sigma_layer.bias               3
pose_model$$$module.initial_pose_rnn.weight_ih_l0         512 128
pose_model$$$module.initial_pose_rnn.weight_hh_l0         512 128
  pose_model$$$module.initial_pose_rnn.bias_ih_l0             512
  pose_model$$$module.initial_pose_rnn.bias_hh_l0             512
       pose_model$$$module.initial_pose_mu.weight           3 128
         pose_model$$$module.initial_pose_mu.bias               3
    pose_model$$$module.initial_pose_sigma.weight           3 128
      pose_model$$$module.initial_pose_sigma.bias               3
                   encoder$$$module.main.0.weight   8   1   4   4
                   encoder$$$module.main.2.weight  16   8   4   4
                   encoder$$$module.main.3.weight              16
                     encoder$$$module.main.3.bias              16
                   encoder$$$module.main.5.weight  32  16   4   4
                   encoder$$$module.main.6.weight              32
                     encoder$$$module.main.6.bias              32
                   encoder$$$module.main.8.weight  64  32   4   4
                   encoder$$$module.main.9.weight              64
                     encoder$$$module.main.9.bias              64
                  encoder$$$module.main.11.weight 128  64   4   4
                                    Sample Sites:                

#h = torch.cat([hidden[0][0:1], hidden[0][1:]], dim=2)
#c = torch.cat([hidden[1][0:1], hidden[1][1:]], dim=2)
# these 2 lines throw a dim error, is it supposed to be:  
h = hidden[0] 
c = hidden[1]