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Posted to commits@mxnet.apache.org by GitBox <gi...@apache.org> on 2017/11/06 21:15:07 UTC

[GitHub] chsin opened a new issue #8563: feature extraction results in different output for same input

chsin opened a new issue #8563: feature extraction results in different output for same input
URL: https://github.com/apache/incubator-mxnet/issues/8563
 
 
   ## Description
   I get different outputs from the caffenet fc7 layer for the same input. I don't remember where I downloaded the model, but it was either through http://data.dmlc.ml/mxnet/models/ or the older mxnet model repo.
   
   ## Environment info (Required)
   maxOS Sierra, v10.12.6
   Python 2.7.10
   
   ## Minimum reproducible example
   put this into test_fe_sym.py  where [model_dir] is where caffenet-0000.params and caffenet-symbol.json is.
   ``` python
   import mxnet as mx
   import numpy as np
   
   print 'mxnet version', mx.__version__
   print 'numpy version', np.__version__
   
   mod_name = "[mod_dir]/caffenet" 
   sym, arg_params, aux_params = mx.model.load_checkpoint(mod_name, 0)
   all_layers = sym.get_internals()
   fe_sym = all_layers['fc7_output']
   
   print fe_sym.get_internals()
   
   concat_args = {key:arg_params[key] for key in arg_params.keys()}
   mod = mx.mod.Module(symbol=fe_sym, data_names=['data'], label_names=[])
   mod.bind(data_shapes=[('data',(1, 3, 224, 224))])
   mod.init_params(arg_params = concat_args)
   
   mx_img = mx.nd.array(np.zeros((1,3,224,224)))
   batch = mx.io.DataBatch([mx_img], [])
   
   for _ in range(10):
     mod.forward(batch)
     print mod.get_outputs()[0]
   ```
   
   This is what I get when I run it in terminal:
   ```
   >> python test_fe_sym.py 
   mxnet version 0.11.0
   numpy version 1.13.3
   [16:14:24] src/nnvm/legacy_json_util.cc:190: Loading symbol saved by previous version v0.8.0. Attempting to upgrade...
   [16:14:24] src/nnvm/legacy_json_util.cc:198: Symbol successfully upgraded!
   <Symbol group [data, conv1_weight, conv1_bias, conv1, relu1, pool1, norm1, conv2_weight, conv2_bias, conv2, relu2, pool2, norm2, conv3_weight, conv3_bias, conv3, relu3, conv4_weight, conv4_bias, conv4, relu4, conv5_weight, conv5_bias, conv5, relu5, pool5, flatten_0, fc6_weight, fc6_bias, fc6, relu6, drop6, fc7_weight, fc7_bias, fc7]>
   
   [[-1.93128979 -2.29720759 -2.70292187 ..., -2.25644875 -3.05303383
     -1.76401949]]
   <NDArray 1x4096 @cpu(0)>
   
   [[-1.80183637 -2.68599343 -2.66020608 ..., -1.50269926 -2.29078102
     -2.43784142]]
   <NDArray 1x4096 @cpu(0)>
   
   [[-1.28073776 -2.04497075 -3.16189289 ..., -1.27064598 -3.24989033
     -2.34601569]]
   <NDArray 1x4096 @cpu(0)>
   
   [[-1.86191022 -2.48778987 -2.61905193 ..., -2.04039574 -2.48587728
     -2.52999163]]
   <NDArray 1x4096 @cpu(0)>
   
   [[-2.63889694 -2.77093887 -3.30290985 ..., -2.15549564 -2.78999281
     -2.12462115]]
   <NDArray 1x4096 @cpu(0)>
   
   [[-1.32172596 -2.2919054  -2.7314136  ..., -1.93443453 -2.81845975
     -2.4142251 ]]
   <NDArray 1x4096 @cpu(0)>
   
   [[-1.30976808 -2.26464558 -3.43015289 ..., -1.98673713 -2.11255097
     -2.5531776 ]]
   <NDArray 1x4096 @cpu(0)>
   
   [[-2.22697783 -2.39356375 -2.24538589 ..., -2.7480278  -2.95472836
     -2.87552905]]
   <NDArray 1x4096 @cpu(0)>
   
   [[-2.72385931 -2.22037935 -3.52920914 ..., -2.34241581 -2.66669798
     -2.02456665]]
   <NDArray 1x4096 @cpu(0)>
   
   [[-2.73990583 -1.87716341 -3.2182374  ..., -2.65652514 -2.66080451
     -2.56173849]]
   <NDArray 1x4096 @cpu(0)>
   ```

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