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AttributeError: 'NoneType' object has no attribute 'save' #15

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SonTung2308 opened this issue Apr 10, 2024 · 0 comments
Open

AttributeError: 'NoneType' object has no attribute 'save' #15

SonTung2308 opened this issue Apr 10, 2024 · 0 comments

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@SonTung2308
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AttributeError: 'NoneType' object has no attribute 'save' , i donot know why ?

this is all of my issue
(sadtalker) iec@iec-Default-string:~/sontung/xtalker$ python inference.py --driven_audio examples/driven_audio/bus_chinese.wav --source_image examples/source_image/art_0.png --result_dir ./result
using safetensor as default
start to generate video... 1712734309.613055
device========= cpu
---------device----------- cpu
0000: Audio2Coeff
0.08464241027832031
No CUDA runtime is found, using CUDA_HOME='/usr'
0001: AnimateFromCoeff
1.8580634593963623
3DMM Extraction for source image
landmark Det:: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:01<00:00, 1.36s/it]
3DMM Extraction In Video:: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 24.55it/s]
0002: preprocess_model generate
4.304378986358643
eyeblick? pose?
None
None
mel:: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 84/84 [00:00<00:00, 41439.84it/s]
audio2exp:: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 9/9 [00:00<00:00, 57.17it/s]
0003: audio_to_coeff generate...
0.6201522350311279
./result/2024_04_10_14.31.49/art_0##bus_chinese.mat
rank, p_num: 0, 1
84
2024-04-10 14:31:58 [INFO] Start auto tuning.
2024-04-10 14:31:58 [INFO] Quantize model without tuning!
2024-04-10 14:31:58 [INFO] Quantize the model with default configuration without evaluating the model. To perform the tuning process, please either provide an eval_func or provide an eval_dataloader an eval_metric.
2024-04-10 14:31:58 [INFO] Adaptor has 5 recipes.
2024-04-10 14:31:58 [INFO] 0 recipes specified by user.
2024-04-10 14:31:58 [INFO] 3 recipes require future tuning.
2024-04-10 14:31:58 [INFO] *** Initialize auto tuning
2024-04-10 14:31:58 [INFO] {
2024-04-10 14:31:58 [INFO] 'PostTrainingQuantConfig': {
2024-04-10 14:31:58 [INFO] 'AccuracyCriterion': {
2024-04-10 14:31:58 [INFO] 'criterion': 'relative',
2024-04-10 14:31:58 [INFO] 'higher_is_better': True,
2024-04-10 14:31:58 [INFO] 'tolerable_loss': 0.01,
2024-04-10 14:31:58 [INFO] 'absolute': None,
2024-04-10 14:31:58 [INFO] 'keys': <bound method AccuracyCriterion.keys of <neural_compressor.config.AccuracyCriterion object at 0x703e32671ca0>>,
2024-04-10 14:31:58 [INFO] 'relative': 0.01
2024-04-10 14:31:58 [INFO] },
2024-04-10 14:31:58 [INFO] 'approach': 'post_training_static_quant',
2024-04-10 14:31:58 [INFO] 'backend': 'default',
2024-04-10 14:31:58 [INFO] 'calibration_sampling_size': [
2024-04-10 14:31:58 [INFO] 100
2024-04-10 14:31:58 [INFO] ],
2024-04-10 14:31:58 [INFO] 'device': 'cpu',
2024-04-10 14:31:58 [INFO] 'diagnosis': False,
2024-04-10 14:31:58 [INFO] 'domain': 'auto',
2024-04-10 14:31:58 [INFO] 'example_inputs': 'Not printed here due to large size tensors...',
2024-04-10 14:31:58 [INFO] 'excluded_precisions': [
2024-04-10 14:31:58 [INFO] ],
2024-04-10 14:31:58 [INFO] 'framework': 'pytorch_fx',
2024-04-10 14:31:58 [INFO] 'inputs': [
2024-04-10 14:31:58 [INFO] ],
2024-04-10 14:31:58 [INFO] 'model_name': '',
2024-04-10 14:31:58 [INFO] 'ni_workload_name': 'quantization',
2024-04-10 14:31:58 [INFO] 'op_name_dict': None,
2024-04-10 14:31:58 [INFO] 'op_type_dict': None,
2024-04-10 14:31:58 [INFO] 'outputs': [
2024-04-10 14:31:58 [INFO] ],
2024-04-10 14:31:58 [INFO] 'quant_format': 'default',
2024-04-10 14:31:58 [INFO] 'quant_level': 'auto',
2024-04-10 14:31:58 [INFO] 'recipes': {
2024-04-10 14:31:58 [INFO] 'smooth_quant': False,
2024-04-10 14:31:58 [INFO] 'smooth_quant_args': {
2024-04-10 14:31:58 [INFO] },
2024-04-10 14:31:58 [INFO] 'layer_wise_quant': False,
2024-04-10 14:31:58 [INFO] 'layer_wise_quant_args': {
2024-04-10 14:31:58 [INFO] },
2024-04-10 14:31:58 [INFO] 'fast_bias_correction': False,
2024-04-10 14:31:58 [INFO] 'weight_correction': False,
2024-04-10 14:31:58 [INFO] 'gemm_to_matmul': True,
2024-04-10 14:31:58 [INFO] 'graph_optimization_level': None,
2024-04-10 14:31:58 [INFO] 'first_conv_or_matmul_quantization': True,
2024-04-10 14:31:58 [INFO] 'last_conv_or_matmul_quantization': True,
2024-04-10 14:31:58 [INFO] 'pre_post_process_quantization': True,
2024-04-10 14:31:58 [INFO] 'add_qdq_pair_to_weight': False,
2024-04-10 14:31:58 [INFO] 'optypes_to_exclude_output_quant': [
2024-04-10 14:31:58 [INFO] ],
2024-04-10 14:31:58 [INFO] 'dedicated_qdq_pair': False,
2024-04-10 14:31:58 [INFO] 'rtn_args': {
2024-04-10 14:31:58 [INFO] },
2024-04-10 14:31:58 [INFO] 'awq_args': {
2024-04-10 14:31:58 [INFO] },
2024-04-10 14:31:58 [INFO] 'gptq_args': {
2024-04-10 14:31:58 [INFO] },
2024-04-10 14:31:58 [INFO] 'teq_args': {
2024-04-10 14:31:58 [INFO] },
2024-04-10 14:31:58 [INFO] 'autoround_args': {
2024-04-10 14:31:58 [INFO] }
2024-04-10 14:31:58 [INFO] },
2024-04-10 14:31:58 [INFO] 'reduce_range': None,
2024-04-10 14:31:58 [INFO] 'TuningCriterion': {
2024-04-10 14:31:58 [INFO] 'max_trials': 100,
2024-04-10 14:31:58 [INFO] 'objective': [
2024-04-10 14:31:58 [INFO] 'performance'
2024-04-10 14:31:58 [INFO] ],
2024-04-10 14:31:58 [INFO] 'strategy': 'basic',
2024-04-10 14:31:58 [INFO] 'strategy_kwargs': None,
2024-04-10 14:31:58 [INFO] 'timeout': 0
2024-04-10 14:31:58 [INFO] },
2024-04-10 14:31:58 [INFO] 'use_bf16': True
2024-04-10 14:31:58 [INFO] }
2024-04-10 14:31:58 [INFO] }
2024-04-10 14:31:58 [WARNING] [Strategy] Please install mpi4py correctly if using distributed tuning; otherwise, ignore this warning.
2024-04-10 14:31:58 [INFO] Attention Blocks: 0
2024-04-10 14:31:58 [INFO] FFN Blocks: 0
2024-04-10 14:31:58 [INFO] Pass query framework capability elapsed time: 182.33 ms
2024-04-10 14:31:58 [INFO] Do not evaluate the baseline and quantize the model with default configuration.
2024-04-10 14:31:58 [INFO] Quantize the model with default config.
2024-04-10 14:31:59 [INFO] Fx trace of the entire model failed, We will conduct auto quantization
Face Renderer:: 0%| | 0/8 [00:01<?, ?it/s]
2024-04-10 14:32:00 [ERROR] Unexpected exception RuntimeError('cannot call get_autograd_meta() on undefined tensor') happened during tuning.
Traceback (most recent call last):
File "/home/iec/anaconda3/envs/sadtalker/lib/python3.8/site-packages/neural_compressor/quantization.py", line 234, in fit
strategy.traverse()
File "/home/iec/anaconda3/envs/sadtalker/lib/python3.8/site-packages/neural_compressor/strategy/auto.py", line 140, in traverse
super().traverse()
File "/home/iec/anaconda3/envs/sadtalker/lib/python3.8/site-packages/neural_compressor/strategy/strategy.py", line 508, in traverse
q_model = self.adaptor.quantize(copy.deepcopy(tune_cfg), self.model, self.calib_dataloader, self.q_func)
File "/home/iec/anaconda3/envs/sadtalker/lib/python3.8/site-packages/neural_compressor/utils/utility.py", line 306, in fi
res = func(*args, **kwargs)
File "/home/iec/anaconda3/envs/sadtalker/lib/python3.8/site-packages/neural_compressor/adaptor/pytorch.py", line 3643, in quantize
q_func(q_model._model)
File "/home/iec/sontung/xtalker/src/facerender/modules/make_animation.py", line 129, in calib_func
out = generator(source_image, kp_source=kp_source, kp_driving=kp_norm)
File "/home/iec/anaconda3/envs/sadtalker/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "/home/iec/sontung/xtalker/src/facerender/modules/generator.py", line 251, in forward
out = self.decoder(out)
File "/home/iec/anaconda3/envs/sadtalker/lib/python3.8/site-packages/torch/fx/graph_module.py", line 662, in call_wrapped
return self._wrapped_call(self, *args, **kwargs)
File "/home/iec/anaconda3/envs/sadtalker/lib/python3.8/site-packages/torch/fx/graph_module.py", line 281, in call
raise e
File "/home/iec/anaconda3/envs/sadtalker/lib/python3.8/site-packages/torch/fx/graph_module.py", line 271, in call
return super(self.cls, obj).call(*args, **kwargs) # type: ignore[misc]
File "/home/iec/anaconda3/envs/sadtalker/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "<eval_with_key>.74", line 8, in forward
g_middle_0_norm_0_param_free_norm = self.G_middle_0.norm_0.param_free_norm(activation_post_process_1)
File "/home/iec/anaconda3/envs/sadtalker/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "/home/iec/anaconda3/envs/sadtalker/lib/python3.8/site-packages/torch/nn/modules/instancenorm.py", line 74, in forward
return self._apply_instance_norm(input)
File "/home/iec/anaconda3/envs/sadtalker/lib/python3.8/site-packages/torch/nn/modules/instancenorm.py", line 34, in _apply_instance_norm
return F.instance_norm(
File "/home/iec/anaconda3/envs/sadtalker/lib/python3.8/site-packages/torch/nn/functional.py", line 2495, in instance_norm
return torch.instance_norm(
RuntimeError: cannot call get_autograd_meta() on undefined tensor
2024-04-10 14:32:00 [ERROR] Specified timeout or max trials is reached! Not found any quantized model which meet accuracy goal. Exit.
Traceback (most recent call last):
File "inference.py", line 217, in
main(args)
File "inference.py", line 152, in main
result = animate_from_coeff.generate(data, save_dir, pic_path, crop_info,
File "/home/iec/sontung/xtalker/src/facerender/animate.py", line 182, in generate
predictions_video = make_animation(source_image, source_semantics, target_semantics,
File "/home/iec/sontung/xtalker/src/facerender/modules/make_animation.py", line 135, in make_animation
generator.save(f"generator_int8")
AttributeError: 'NoneType' object has no attribute 'save'
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