Is that backbone style modle support variation dropout layers to get feature importance
I am current using backbone to build my model , everything seems well.
However, when I going to export the feature importance of variation layers , I got :
Traceback (most recent call last):
File "/home/data/miniconda/envs/py3/lib/python3.8/runpy.py", line 194, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/home/data/miniconda/envs/py3/lib/python3.8/runpy.py", line 87, in _run_code
exec(code, run_globals)
File "/ofs/llm-for-dptd/huxinlei/general-prediction-server/easy_rec/python/tools/feature_selection.py", line 307, in
fs.process()
File "/ofs/llm-for-dptd/huxinlei/general-prediction-server/easy_rec/python/tools/feature_selection.py", line 59, in process
feature_dim_dropout_p_map, embedding_wise_variational_dropout = self._feature_dim_dropout_ratio(
File "/ofs/llm-for-dptd/huxinlei/general-prediction-server/easy_rec/python/tools/feature_selection.py", line 110, in _feature_dim_dropout_ratio
logit_p = reader.get_tensor(logit_p_name)
File "/home/luban/.local/lib/python3.8/site-packages/tensorflow/python/training/py_checkpoint_reader.py", line 71, in get_tensor
error_translator(e)
File "/home/luban/.local/lib/python3.8/site-packages/tensorflow/python/training/py_checkpoint_reader.py", line 31, in error_translator
raise errors_impl.NotFoundError(None, None, error_message)
tensorflow.python.framework.errors_impl.NotFoundError: Key logit_p_wide not found in checkpoint
Is that backbone style modle support variation dropout layers to get feature importance I am current using backbone to build my model , everything seems well. However, when I going to export the feature importance of variation layers , I got : Traceback (most recent call last): File "/home/data/miniconda/envs/py3/lib/python3.8/runpy.py", line 194, in _run_module_as_main return _run_code(code, main_globals, None, File "/home/data/miniconda/envs/py3/lib/python3.8/runpy.py", line 87, in _run_code exec(code, run_globals) File "/ofs/llm-for-dptd/huxinlei/general-prediction-server/easy_rec/python/tools/feature_selection.py", line 307, in
fs.process()
File "/ofs/llm-for-dptd/huxinlei/general-prediction-server/easy_rec/python/tools/feature_selection.py", line 59, in process
feature_dim_dropout_p_map, embedding_wise_variational_dropout = self._feature_dim_dropout_ratio(
File "/ofs/llm-for-dptd/huxinlei/general-prediction-server/easy_rec/python/tools/feature_selection.py", line 110, in _feature_dim_dropout_ratio
logit_p = reader.get_tensor(logit_p_name)
File "/home/luban/.local/lib/python3.8/site-packages/tensorflow/python/training/py_checkpoint_reader.py", line 71, in get_tensor
error_translator(e)
File "/home/luban/.local/lib/python3.8/site-packages/tensorflow/python/training/py_checkpoint_reader.py", line 31, in error_translator
raise errors_impl.NotFoundError(None, None, error_message)
tensorflow.python.framework.errors_impl.NotFoundError: Key logit_p_wide not found in checkpoint