You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
The full traceback is below:
runner = Runner.from_cfg(cfg)
File "/opt/conda/lib/python3.9/site-packages/mmengine/runner/runner.py", line 462, in from_cfg
runner = cls(
File "/opt/conda/lib/python3.9/site-packages/mmengine/runner/runner.py", line 429, in init
self.model = self.build_model(model)
File "/opt/conda/lib/python3.9/site-packages/mmengine/runner/runner.py", line 836, in build_model
model = MODELS.build(model)
File "/opt/conda/lib/python3.9/site-packages/mmengine/registry/registry.py", line 570, in build
return self.build_func(cfg, *args, **kwargs, registry=self)
File "/opt/conda/lib/python3.9/site-packages/mmengine/registry/build_functions.py", line 232, in build_model_from_cfg
return build_from_cfg(cfg, registry, default_args)
File "/opt/conda/lib/python3.9/site-packages/mmengine/registry/build_functions.py", line 121, in build_from_cfg
obj = obj_cls(**args) # type: ignore
File "/mmrazor/mmrazor/implementations/pruning/group_fisher/algorithm.py", line 57, in init
self.mutator.prepare_from_supernet(self.architecture)
File "/mmrazor/mmrazor/models/mutators/channel_mutator/channel_mutator.py", line 113, in prepare_from_supernet
units = self._prepare_from_tracer(supernet, self.parse_cfg)
File "/mmrazor/mmrazor/models/mutators/channel_mutator/channel_mutator.py", line 311, in _prepare_from_tracer
unit_configs = tracer.analyze(model)
File "/mmrazor/mmrazor/models/task_modules/tracer/channel_analyzer.py", line 107, in analyze
fx_graph = self._fx_trace(model)
File "/mmrazor/mmrazor/models/task_modules/tracer/channel_analyzer.py", line 132, in _fx_trace
args = self.demo_input.get_data(model)
File "/mmrazor/mmrazor/models/task_modules/demo_inputs/demo_inputs.py", line 34, in get_data
data = self._get_data(model, input_shape, training)
File "/mmrazor/mmrazor/models/task_modules/demo_inputs/default_demo_inputs.py", line 108, in _get_data
return defaul_demo_inputs(model, input_shape, training, self.scope)
File "/mmrazor/mmrazor/models/task_modules/demo_inputs/default_demo_inputs.py", line 79, in defaul_demo_inputs
return demo_input().get_data(model, input_shape, training)
File "/mmrazor/mmrazor/models/task_modules/demo_inputs/demo_inputs.py", line 34, in get_data
data = self._get_data(model, input_shape, training)
File "/mmrazor/mmrazor/models/task_modules/demo_inputs/demo_inputs.py", line 57, in _get_data
data = self._get_mm_data(model, input_shape, training)
File "/mmrazor/mmrazor/models/task_modules/demo_inputs/demo_inputs.py", line 63, in _get_mm_data
data = model.data_preprocessor(data, training)
File "/opt/conda/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1190, in _call_impl
return forward_call(*input, **kwargs)
File "/opt/conda/lib/python3.9/site-packages/mmpose/models/data_preprocessors/data_preprocessor.py", line 94, in forward
for data_sample, pad_shape in zip(data_samples, batch_pad_shape):
To Reproduce
Just run the train.py having rtmo_s with coco dataset format on body_2d_keypoint by using the pruning method.
Post related information
i have done all the relevant changes in config data and metafile to run this successfully but failure persists.
Additional context
Add any other context about the problem here.
[here]
The text was updated successfully, but these errors were encountered:
Describe the bug
The full traceback is below:
runner = Runner.from_cfg(cfg)
File "/opt/conda/lib/python3.9/site-packages/mmengine/runner/runner.py", line 462, in from_cfg
runner = cls(
File "/opt/conda/lib/python3.9/site-packages/mmengine/runner/runner.py", line 429, in init
self.model = self.build_model(model)
File "/opt/conda/lib/python3.9/site-packages/mmengine/runner/runner.py", line 836, in build_model
model = MODELS.build(model)
File "/opt/conda/lib/python3.9/site-packages/mmengine/registry/registry.py", line 570, in build
return self.build_func(cfg, *args, **kwargs, registry=self)
File "/opt/conda/lib/python3.9/site-packages/mmengine/registry/build_functions.py", line 232, in build_model_from_cfg
return build_from_cfg(cfg, registry, default_args)
File "/opt/conda/lib/python3.9/site-packages/mmengine/registry/build_functions.py", line 121, in build_from_cfg
obj = obj_cls(**args) # type: ignore
File "/mmrazor/mmrazor/implementations/pruning/group_fisher/algorithm.py", line 57, in init
self.mutator.prepare_from_supernet(self.architecture)
File "/mmrazor/mmrazor/models/mutators/channel_mutator/channel_mutator.py", line 113, in prepare_from_supernet
units = self._prepare_from_tracer(supernet, self.parse_cfg)
File "/mmrazor/mmrazor/models/mutators/channel_mutator/channel_mutator.py", line 311, in _prepare_from_tracer
unit_configs = tracer.analyze(model)
File "/mmrazor/mmrazor/models/task_modules/tracer/channel_analyzer.py", line 107, in analyze
fx_graph = self._fx_trace(model)
File "/mmrazor/mmrazor/models/task_modules/tracer/channel_analyzer.py", line 132, in _fx_trace
args = self.demo_input.get_data(model)
File "/mmrazor/mmrazor/models/task_modules/demo_inputs/demo_inputs.py", line 34, in get_data
data = self._get_data(model, input_shape, training)
File "/mmrazor/mmrazor/models/task_modules/demo_inputs/default_demo_inputs.py", line 108, in _get_data
return defaul_demo_inputs(model, input_shape, training, self.scope)
File "/mmrazor/mmrazor/models/task_modules/demo_inputs/default_demo_inputs.py", line 79, in defaul_demo_inputs
return demo_input().get_data(model, input_shape, training)
File "/mmrazor/mmrazor/models/task_modules/demo_inputs/demo_inputs.py", line 34, in get_data
data = self._get_data(model, input_shape, training)
File "/mmrazor/mmrazor/models/task_modules/demo_inputs/demo_inputs.py", line 57, in _get_data
data = self._get_mm_data(model, input_shape, training)
File "/mmrazor/mmrazor/models/task_modules/demo_inputs/demo_inputs.py", line 63, in _get_mm_data
data = model.data_preprocessor(data, training)
File "/opt/conda/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1190, in _call_impl
return forward_call(*input, **kwargs)
File "/opt/conda/lib/python3.9/site-packages/mmpose/models/data_preprocessors/data_preprocessor.py", line 94, in forward
for data_sample, pad_shape in zip(data_samples, batch_pad_shape):
To Reproduce
Just run the train.py having rtmo_s with coco dataset format on body_2d_keypoint by using the pruning method.
Post related information
i have done all the relevant changes in config data and metafile to run this successfully but failure persists.
Additional context
Add any other context about the problem here.
[here]
The text was updated successfully, but these errors were encountered: