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Tensorflow 1.3 with Python 3.6.2 under Windows 10 64 Bit OS has issue when run tensorflow/tensorflow/examples/image_retraining/label_image.py #12736
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I am having this issue as well. I am using WinPython rather than Anaconda. My Tensorflow version is also 1.3 and Python 3.6.2.
UPDATE: My implementation is now working after changing the lines 78-79 in label_image.py from:
I am not sure why they were set to those other values to begin with - as far as I can tell, they are not valid operations.
Currently the only difference is the default
Some of the confusion here is probably caused by slippage between the main version of the tutorial (1.4) and people using the master branch of the git clone. This is fixed in the master version of the tutorial. A fix is inflight to add a versioned link to the tutorial to help people use the matching version.
Thanks for the input_layer="Mul" hint, saved me.
I tried to display the node names to find precisely that. I only got some nodes for the picture feeding and similar, nothing for the inception model. Anyone knows how to find them so I am not reliant on random websearches?
hey, guys, after I retrained Inception-V3 using my own data. when i use label_image.py to test, it comes that my input layer and output layer is not right. I changed them.
NodeDef: import/conv/Conv2D = Conv2D[T=DT_FLOAT, data_format="NHWC", dilations=[1, 1, 1, 1], padding="VALID", strides=[1, 2, 2, 1], use_cudnn_on_gpu=true, _device="/job:localhost/replica:0/task:0/device:GPU:0"](_arg_import/Mul_0_0/_1, import/conv/conv2d_params).
[[Node: import/conv/Conv2D = Conv2D[T=DT_FLOAT, data_format="NHWC", dilations=[1, 1, 1, 1], padding="VALID", strides=[1, 2, 2, 1], use_cudnn_on_gpu=true, _device="/job:localhost/replica:0/task:0/device:GPU:0"](_arg_import/Mul_0_0/_1, import/conv/conv2d_params)]]
Thanks for helping!!!
This did not work for me is there any other solution for this ?
Please suggest me a solution