I am using your code and I manage to train on linemod dataset. However in the template config file the batch size is set to 1.
When I try a batch size > 1, I get this error after the neighbors calibration :
/opt/miniconda3/envs/py37/lib/python3.7/site-packages/torch/nn/modules/container.py:435: UserWarning: Setting attributes on ParameterList is not supported.
warnings.warn("Setting attributes on ParameterList is not supported.")
correspondences_2d3d
all input arrays must have the same shape
Traceback (most recent call last):
File "/home/RNNPose//tools/train.py", line 775, in <module>
fire.Fire()
File "/opt/miniconda3/envs/py37/lib/python3.7/site-packages/fire/core.py", line 141, in Fire
component_trace = _Fire(component, args, parsed_flag_args, context, name)
File "/opt/miniconda3/envs/py37/lib/python3.7/site-packages/fire/core.py", line 471, in _Fire
target=component.__name__)
File "/opt/miniconda3/envs/py37/lib/python3.7/site-packages/fire/core.py", line 681, in _CallAndUpdateTrace
component = fn(*varargs, **kwargs)
File "/home/RNNPose//tools/train.py", line 240, in multi_proc_train
args=( params,) )
File "/opt/miniconda3/envs/py37/lib/python3.7/site-packages/torch/multiprocessing/spawn.py", line 199, in spawn
return start_processes(fn, args, nprocs, join, daemon, start_method='spawn')
File "/opt/miniconda3/envs/py37/lib/python3.7/site-packages/torch/multiprocessing/spawn.py", line 157, in start_processes
while not context.join():
File "/opt/miniconda3/envs/py37/lib/python3.7/site-packages/torch/multiprocessing/spawn.py", line 118, in join
raise Exception(msg)
Exception:
-- Process 0 terminated with the following error:
Traceback (most recent call last):
File "/opt/miniconda3/envs/py37/lib/python3.7/site-packages/torch/multiprocessing/spawn.py", line 19, in _wrap
fn(i, *args)
File "/home/RNNPose/tools/train.py", line 275, in train_worker
gpu_id=params.start_gpu_id+rank,
File "/home/RNNPose/tools/train.py", line 670, in train
raise e
File "/home/RNNPose/tools/train.py", line 551, in train
for example in dataloader:
File "/opt/miniconda3/envs/py37/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 435, in __next__
data = self._next_data()
File "/opt/miniconda3/envs/py37/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 475, in _next_data
data = self._dataset_fetcher.fetch(index) # may raise StopIteration
File "/opt/miniconda3/envs/py37/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 47, in fetch
return self.collate_fn(data)
File "/home/RNNPose/data/preprocess.py", line 736, in collate_fn_descriptor_deepim
ret = merge_batch(list_data)
File "/home/RNNPose/data/preprocess.py", line 70, in merge_batch
ret[key] = np.stack(elems, axis=0)
File "<__array_function__ internals>", line 6, in stack
File "/opt/miniconda3/envs/py37/lib/python3.7/site-packages/numpy/core/shape_base.py", line 427, in stack
raise ValueError('all input arrays must have the same shape')
ValueError: all input arrays must have the same shape
It happens when stacking correspondences_2d3d :
Because correspondences_2d3d is of different length for each image.
Is it something you have faced as well and do you recommend using a batch size > 1 ?
Hi, thank you for your work !
I am using your code and I manage to train on linemod dataset. However in the template config file the batch size is set to 1.
When I try a batch size > 1, I get this error after the neighbors calibration :
It happens when stacking correspondences_2d3d : Because correspondences_2d3d is of different length for each image.
Is it something you have faced as well and do you recommend using a batch size > 1 ?