I have managed to train fcnet on mnist and extract the .ckpt, .meta , .data files and the 'checkpoint' file that contains the name of the .ckpt.
I am executing ./scripts/infer_fcnet.sh with the argument --intr_qmap=path-to-.json file. The .json file contains the quantization map :
{
"FCNet" : "nearest,8,4"
}
So I chose to quantize the fcn operation in the specific fixed point representation. The .json file is loaded correctly from :
intr_q_map=utils.quantizer_map('qMap_filename')
but I get an error on runtime :
INFO:tensorflow:Scale of 0 disables regularizer.
INFO:tensorflow:Quantizing (intr) layer FCNet/logits
Traceback (most recent call last):
File "eval_image_classifier.py", line 277, in <module>
tf.app.run()
File "/home/xxxxx/virtual-tensorflow/local/lib/python2.7/site-packages/tensorflow/python/platform/app.py", line 48, in run
_sys.exit(main(_sys.argv[:1] + flags_passthrough))
File "eval_image_classifier.py", line 186, in main
logits, endpoints = network_fn(images)
File "/home/xxxxx/tensorflow/TensorQuant/slim/nets/nets_factory.py", line 144, in network_fn
fully_connected=fully_connected)
File "/home/xxxxx/tensorflow/TensorQuant/slim/nets/fcnet.py", line 36, in fcnet
scope='logits')
File "/home/xxxxx/tensorflow/TensorQuant/Quantize/Factories.py", line 49, in func
net=q_layer_function(*args,**kwargs)
File "/home/xxxxx/virtual-tensorflow/local/lib/python2.7/site-packages/tensorflow/contrib/framework/python/ops/arg_scope.py", line 181, in func_with_args
return func(*args, **current_args)
File "/home/xxxxx/tensorflow/TensorQuant/Quantize/QFullyConnect.py", line 86, in fully_connected
outputs = layer.apply(inputs)
File "/home/xxxxx/virtual-tensorflow/local/lib/python2.7/site-packages/tensorflow/python/layers/base.py", line 503, in apply
return self.__call__(inputs, *args, **kwargs)
File "/home/xxxxx/virtual-tensorflow/local/lib/python2.7/site-packages/tensorflow/python/layers/base.py", line 450, in __call__
outputs = self.call(inputs, *args, **kwargs)
File "/home/xxxxx/tensorflow/TensorQuant/Quantize/QFullyConnect.py", line 153, in call
used_kernel = self.quantizer.quantize(used_kernel)
AttributeError: 'unicode' object has no attribute 'quantize'
Hello,
I have managed to train fcnet on mnist and extract the .ckpt, .meta , .data files and the 'checkpoint' file that contains the name of the .ckpt.
I am executing
./scripts/infer_fcnet.sh
with the argument--intr_qmap=path-to-.json
file. The.json
file contains the quantization map :So I chose to quantize the fcn operation in the specific fixed point representation. The .json file is loaded correctly from :
but I get an error on runtime :
Any idea what the cause is?