address cr comments

contrib/Python/cntk/ops/tests/reshaping_test.py

@@ -49,7 +49,7 @@ def test_op_reshape(input_shape, output_shape, expected_output_shape, device_id,
     # Backward pass test
     # ==================
     # Reshaping is just moving the input values to different indexes of the result tensor.
-    # If we would compute the gradients on the unmodified tensor, reshape would get 1 for all inputs.
+    # If we compute the gradients on the unmodified tensor, reshape would get 1 for all inputs.
     # For testing the gradients we want to have different gradients for each input index otherwise we can't
     # test if they get wrongly permuted during test. To this end we multiply the reshaping result with itself.     
     # The expected gradient is identical to the input tensor.
@@ -224,7 +224,7 @@ def test_op_transpose_dimensions(input_shape, axis1, axis2, expected_output_shap
     # Backward pass test
     # ==================
     # Reshaping is just moving the input values to different indexes of the result tensor.
-    # If we would compute the gradients on the unmodified tensor, reshape would get 1 for all inputs.
+    # If we compute the gradients on the unmodified tensor, reshape would get 1 for all inputs.
     # For testing the gradients we want to have different gradients for each input index otherwise we can't
     # test if they get wrongly permuted during test. To this end we multiply the reshaping result with itself.     
     # The expected gradient is identical to the input tensor.

contrib/Python/cntk/utils/tests/eval_test.py

@@ -38,19 +38,19 @@ def test_eval_plus_two_inputs():
     result = cntk.eval(cntk.plus(cntk.input_numpy([_LEFT]), cntk.input_numpy([_RIGHT])))
     TOLERANCE_ABSOLUTE = 1E-06    
     assert np.allclose(result, _EXPECTED, atol=TOLERANCE_ABSOLUTE)
-	
+
 def test_eval_plus_one_constant():
     result = cntk.eval(cntk.plus(cntk.constant(_LEFT), _RIGHT))
     TOLERANCE_ABSOLUTE = 1E-06    
-    assert np.allclose(result, _EXPECTED, atol=TOLERANCE_ABSOLUTE)	
-	
+    assert np.allclose(result, _EXPECTED, atol=TOLERANCE_ABSOLUTE)
+
 def test_eval_plus_one_constant_last():
     result = cntk.eval(cntk.plus(_LEFT, cntk.constant(_RIGHT)))
     TOLERANCE_ABSOLUTE = 1E-06    
-    assert np.allclose(result, _EXPECTED, atol=TOLERANCE_ABSOLUTE)		
+    assert np.allclose(result, _EXPECTED, atol=TOLERANCE_ABSOLUTE)
 
-# this is dis-activated for now because we cannot have a netowrk without inputs	
+# this is dis-activated for now because we cannot have a netowrk without inputs
 def _test_eval_plus_two_constants():
     result = cntk.eval(cntk.plus(cntk.constant(_LEFT), cntk.constant(_RIGHT)))
     TOLERANCE_ABSOLUTE = 1E-06    
-    assert np.allclose(result, _EXPECTED, atol=TOLERANCE_ABSOLUTE)			
+    assert np.allclose(result, _EXPECTED, atol=TOLERANCE_ABSOLUTE)