#5960 - results analysis

test_analyze.py

import numpy as np

def load_results():
  path = '' #if you run from a different folder
  a = np.load(path+'test_forward_start_end_ipblob.npy')
  b = np.load(path+'test_forward_start_end_manual.npy')
  c = np.load(path+'test_backward_start_end_convblob.npy')
  d = np.load(path+'test_backward_start_end_manual.npy')
  return a, b, c, d

def find_diffs(x,y,rtol):
  def getFalseIndices(data):
    indices = []
    if len(data.shape)==1:
      for i, datum in enumerate(data):
        if data[i] == False:
          indices.append([i])
    else:
      for i, datum in enumerate(data):
        if datum.all() == False:
          indices = [[i] + r for r in getFalseIndices(datum)]
    return indices
  if x.shape!=y.shape:
    print "bad shape"
    return None
  s = x.shape
  m = np.core.numeric.isclose(x,y,rtol=rtol)
  return getFalseIndices(m)
  
if __name__ == "__main__":
  forward_caffe, forward_manual, backward_caffe, backward_manual = load_results()
  #obtain indices of results that failed the test (uses the same comparison as test_net.py)
  diffs = find_diffs(backward_caffe, backward_manual, 1e-3)
  for diff in diffs:
    print backward_caffe[tuple(diff)], backward_manual[tuple(diff)]
  #also print minimum absvals of each blob to prove that they are the culprit
  print np.abs(backward_caffe).min(), np.abs(backward_manual).min()