fix helper name

contrib/Python/cntk/context.py

@@ -56,22 +56,19 @@ class AbstractContext(object, metaclass=ABCMeta):
     '''
 
     def __init__(self, name,
-                 graph=None,
-                 device_id=-1,
                  root_nodes=None,
-                 clean_up=True,
-                 node_unit_test=False):
+                 device_id=-1,                 
+                 precision="float",
+                 clean_up=True):      
         '''
         AbstractContext Constructer
 
         :param name: context name
-        :param graph: the computational graph to be used for training, testing and prediction        
         :param device_id: whether to use CPU or a specific GPU. -1 for CPU larger values
         :param root_nodes: list of top nodes of the graph or single node itself
-        :param clean_up: whether the temporary directory should be removed when the context is left
-        are the GPUs indices.        
-        :param node_unit_test: set to True if you want to output the gradient of a node (backward pass)
-
+        :param clean_up: whether the temporary directory should be removed when the context is left        
+        are the GPUs indices.                
+        :param precision: either float or double
         '''
         if isinstance(name, str):
             tmpdir = name
@@ -88,6 +85,7 @@ class AbstractContext(object, metaclass=ABCMeta):
 
         self.name = name
         self.device_id = device_id
+        self.precision = precision
         self.clean_up = clean_up
         self.input_nodes = set()
         if root_nodes is None:
@@ -169,6 +167,7 @@ class AbstractContext(object, metaclass=ABCMeta):
 
         tmpl_dict = {
             'DevideId': self.device_id,
+            'Precision': self.precision,
             'ModelDescription': description,
             'ModelPath': model_filename,
             'Reader': '\n'.join(r.generate_config() for r in readers),
@@ -192,6 +191,7 @@ class AbstractContext(object, metaclass=ABCMeta):
 
         tmpl_dict = {
             'DevideId': self.device_id,
+            'Precision': self.precision,
             'ModelPath': model_filename,
             'Reader': reader_config,
         }
@@ -216,6 +216,7 @@ class AbstractContext(object, metaclass=ABCMeta):
 
         tmpl_dict = {
             'DevideId': self.device_id,
+            'Precision': self.precision,
             'ModelPath': model_filename,
             'PredictOutputFile': output_filename_base,
             'Reader': reader_config,
@@ -249,7 +250,8 @@ class AbstractContext(object, metaclass=ABCMeta):
         output_filename = os.path.join(self.directory, CNTK_OUTPUT_FILENAME)
         tmpl_dict = {
             'DevideId': self.device_id,
-            'NodeUnitTest': self.node_unit_test,
+            'Precision': self.precision,
+            'NodeUnitTest': node_unit_test,
             'OutputFile': output_filename,
             'ModelDescription': description,
             'Reader': '\n'.join(r.generate_config() for r in readers),

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

@@ -11,7 +11,7 @@ the forward and the backward pass
 
 import numpy as np
 import pytest
-from .ops_test_utils import test_helper, C, AA, I, cpu_gpu
+from .ops_test_utils import unittest_helper, C, AA, I, cpu_gpu
 from ...graph import *
 from ...reader import *
 import numpy as np
@@ -26,13 +26,13 @@ import numpy as np
     #Adding two 3x2 inputs of sequence length 1
     #([[30,40], [1,2], [0.1, 0.2]], [[10,20], [3,4], [-0.5, -0.4]]),     
     ])
-def test_op_add(left_operand, right_operand, cpu_gpu):    
+def test_op_plus(left_operand, right_operand, cpu_gpu):    
 
     #Forward pass test
-    
+    #==================
     #we compute the expected output for the forward pass
     # we need two surrounding brackets
-    # the first for sequence of 1 element, since we have has_sequence_dimension=False
+    # the first for sequences (length=1, since we have has_sequence_dimension=False)
     # the second for batch of one sample
     expected = [[AA(left_operand) + AA(right_operand)]]
 
@@ -40,14 +40,16 @@ def test_op_add(left_operand, right_operand, cpu_gpu):
     b = I([right_operand], has_sequence_dimension=False)    
     
     left_as_input = a + right_operand    
-    test_helper(left_as_input, expected, cpu_gpu, False)
+    unittest_helper(left_as_input, expected, cpu_gpu, False)
     
     right_as_input = left_operand + b
-    test_helper(right_as_input, expected, cpu_gpu, False)
+    unittest_helper(right_as_input, expected, cpu_gpu, False)
     
     #Backward pass test
-    
+    #==================
     #the expected results for the backward pass is all ones
     expected = [[[np.ones_like(x) for x in left_operand]]]
-    test_helper(left_as_input, expected, cpu_gpu, clean_up=True, backward_pass = True, input_node = a)    
-    test_helper(right_as_input, expected, cpu_gpu, clean_up=True, backward_pass = True, input_node = b)
+    unittest_helper(left_as_input, expected, cpu_gpu, clean_up=True, backward_pass = True, input_node = a)    
+    unittest_helper(right_as_input, expected, cpu_gpu, clean_up=True, backward_pass = True, input_node = b)
+    
+    

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

@@ -23,7 +23,7 @@ AA = np.asarray
 def cpu_gpu(request):
     return request.param
 
-def test_helper(root_node, expected, device_id = -1, clean_up=True, backward_pass = False, input_node = None):
+def unittest_helper(root_node, expected, device_id = -1, clean_up=True, backward_pass = False, input_node = None):
     with get_new_context() as ctx:
         ctx.clean_up = clean_up
         ctx.device_id = device_id