[GitHub] eric-haibin-lin opened a new issue #7317: check_numeric_grad with FullyConnected fails

[git]

eric-haibin-lin opened a new issue #7317: check_numeric_grad with 
FullyConnected fails
URL: https://github.com/apache/incubator-mxnet/issues/7317
 
 
   For bugs or installation issues, please provide the following information.
   The more information you provide, the more likely people will be able to 
help you.
   
   ## Environment info
   Operating System: DL AMI
   
   Compiler:
   
   Package used (Python/R/Scala/Julia):
   
   MXNet version:
   
   Or if installed from source: 
   
   MXNet commit hash (`git rev-parse HEAD`): 
861e929cec8fa8fbab06884d9605debb74cd7217
   
   If you are using python package, please provide
   
   Python version and distribution:
   
   If you are using R package, please provide
   
   R `sessionInfo()`:
   
   ## Error Message:
   Please paste the full error message, including stack trace.
   ```
   /home/ubuntu/upstream-cpu/python/mxnet/test_utils.py:412: UserWarning: 
Calling forward the second time after forward(is_train=True) without calling 
backward first. Is this intended$
     executor.forward(is_train=use_forward_train)
   /home/ubuntu/upstream-cpu/python/mxnet/test_utils.py:404: UserWarning: 
Calling forward the second time after forward(is_train=True) without calling 
backward first. Is this intended?
     executor.forward(is_train=use_forward_train)
   Traceback (most recent call last):
     File "./test.py", line 13, in <module>
       check_fully_connected((32, 100), 10)
     File "./test.py", line 11, in check_fully_connected
       check_numeric_gradient(test, location)
     File "/home/ubuntu/upstream-cpu/python/mxnet/test_utils.py", line 524, in 
check_numeric_gradient
       ("NUMERICAL_%s"%name, "BACKWARD_%s"%name))
     File "/home/ubuntu/upstream-cpu/python/mxnet/test_utils.py", line 154, in 
assert_almost_equal
       raise AssertionError(msg)
   AssertionError:
   Items are not equal:
   Error 294.098633 exceeds tolerance rtol=0.010000, atol=0.000000.  Location 
of maximum error:(19, 54), a=0.001162, b=0.000295
    NUMERICAL_x: array([[ 3.73460722,  0.2527386 , -1.75657499, ..., 
-1.24495852,
            0.74711072, -5.7607851 ],
          [ 2.94259191, -0.7109642 , -1.08036399, ..., -0.87466836,...
    BACKWARD_x: array([[ 3.7337687 ,  0.25231028, -1.75907421, ..., -1.24670959,
            0.74810255, -5.76152706],
          [ 2.94111443, -0.7087307 , -1.0836978 , ..., -0.87180936,...
   ```
   ## Minimum reproducible example
   if you are using your own code, please provide a short script that 
reproduces the error.
   
   ```
   import mxnet as mx
   from mxnet.test_utils import *
   def check_fully_connected(shape, num_hidden):
       x = mx.symbol.Variable('x')
       w = mx.symbol.Variable('w')
       test = mx.sym.FullyConnected(data=x, weight=w, num_hidden=num_hidden, 
no_bias=True)
       x_nd = mx.nd.array(random_arrays(shape))
       w_nd = mx.nd.array(random_arrays((num_hidden, shape[1])))
       location = {'x': x_nd, 'w': w_nd}
       out_dns = mx.nd.dot(x_nd, w_nd.T).asnumpy()
       check_numeric_gradient(test, location)
   
   check_fully_connected((32, 100), 10)
   ```
   
   ## Steps to reproduce
   or if you are running standard examples, please provide the commands you 
have run that lead to the error.
   
   1. run the above code
   2.
   3.
   
   ## What have you tried to solve it?
   
   1. 
   2.
   3.
   
 
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