how to ignore gru layer for Adaround.apply_adaround?

[bestboybsh]

Hi, I'm tring to use adaround for the model including several cnn layers and gru layers.

but, the assertion occured with the below message.

AttributeError: 'str' object has no attribute 'enabled'.

When I exclude gru layer in the model, then, it works well. I think the gru layer should be excluded for applying adaround.

Is there any method for doing that?

[quic-mangal]

Hi @bestboybsh, could you tell us which framework you are referring to?

[bestboybsh]

Hi, @quic-mangal , I am using the torch model to quantize.

[quic-mangal]

The GRU layer is already excluded from adaround, we only adaround- AdaroundSupportedModules = (torch.nn.Conv2d, torch.nn.ConvTranspose2d, torch.nn.Linear)

That being said, could you post the full error for better analysis?

[bestboybsh]

I runned the below code

bn_folded_model = copy.deepcopy(model).eval() ada_model = Adaround.apply_adaround(bn_folded_model, dummy_input_total.cuda(), params, path='./', filename_prefix='adaround', default_param_bw=8, default_quant_scheme=QuantScheme.post_training_tf_enhanced)

And, the error message is as follows

2023-10-06 01:24:30,223 - Quant - INFO - No config file provided, defaulting to config file at /root/miniconda3/lib/python3.8/site-packages/aimet_common/quantsim_config/default_config.json
2023-10-06 01:24:30,247 - Quant - INFO - Unsupported op type Squeeze
2023-10-06 01:24:30,248 - Quant - INFO - Unsupported op type Pad
2023-10-06 01:24:30,249 - Quant - INFO - Unsupported op type Mean
2023-10-06 01:24:30,253 - Utils - INFO - ...... subset to store [Conv_86, Relu_88]
2023-10-06 01:24:30,254 - Utils - INFO - ...... subset to store [Conv_90, Relu_92]
2023-10-06 01:24:30,255 - Utils - INFO - ...... subset to store [Conv_70, Relu_72]
2023-10-06 01:24:30,256 - Utils - INFO - ...... subset to store [Conv_74, Relu_76]
2023-10-06 01:24:30,257 - Utils - INFO - ...... subset to store [Conv_78, Relu_80]
2023-10-06 01:24:30,258 - Utils - INFO - ...... subset to store [Conv_82, Relu_84]
2023-10-06 01:24:30,259 - Quant - INFO - Selecting DefaultOpInstanceConfigGenerator to compute the specialized config. hw_version:default
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
Cell In[41], line 2
      1 bn_folded_model = copy.deepcopy(model).eval()
----> 2 ada_model = Adaround.apply_adaround(bn_folded_model, dummy_input_total.cuda(), params,
      3                                     path='./', filename_prefix='adaround', default_param_bw=8,
      4                                     default_quant_scheme=QuantScheme.post_training_tf_enhanced)

File ~/miniconda3/lib/python3.8/site-packages/aimet_torch/adaround/adaround_weight.py:155, in Adaround.apply_adaround(cls, model, dummy_input, params, path, filename_prefix, default_param_bw, param_bw_override_list, ignore_quant_ops_list, default_quant_scheme, default_config_file)
    152 # Compute only param encodings
    153 cls._compute_param_encodings(quant_sim)
--> 155 return cls._apply_adaround(quant_sim, model, dummy_input, params, path, filename_prefix)

File ~/miniconda3/lib/python3.8/site-packages/aimet_torch/adaround/adaround_weight.py:180, in Adaround._apply_adaround(cls, quant_sim, model, dummy_input, params, path, filename_prefix)
    178 _, input_quantizers, output_quantizers = utils.get_all_quantizers(quant_sim.model)
    179 for quantizer in itertools.chain(input_quantizers, output_quantizers):
--> 180     assert not quantizer.enabled
    182 # Get the module - activation function pair using ConnectedGraph
    183 module_act_func_pair = connectedgraph_utils.get_module_act_func_pair(model, dummy_input)

AttributeError: 'str' object has no attribute 'enabled'

[quic-hitameht]

@bestboybsh Thanks for reporting this. This bug has been fixed already but isn't part of AIMET 1.28 release.

You can still try updating get_all_quantizers utility from aimet_torch/utils.py file from tip of develop branch.

Let us know if you see any other issues.

[quic-hitameht]

Closing this as resolved. If there is another question please re-open or create a new issue.