renamed default_type argument to rand_type for clarity

updated function docstring with argument description

removed rand_type setting for non-max pooling tests

python/mxnet/test_utils.py

@@ -1204,7 +1204,7 @@ def check_speed(sym, location=None, ctx=None, N=20, grad_req=None, typ="whole",
 def check_consistency(sym, ctx_list, scale=1.0, grad_req='write',
                       arg_params=None, aux_params=None, tol=None,
                       raise_on_err=True, ground_truth=None, equal_nan=False,
-                      use_uniform=False, default_type=np.float64):
+                      use_uniform=False, rand_type=np.float64):
     """Check symbol gives the same output for different running context
 
     Parameters
@@ -1221,6 +1221,10 @@ def check_consistency(sym, ctx_list, scale=1.0, grad_req='write',
         Optional, When flag set to true,
         random input data generated follows uniform distribution,
         not normal distribution
+    rand_type: np.dtype
+        Optional, when input data is passed via arg_params,
+        defaults to np.float64 (python float default)
+
     Examples
     --------
     >>> # create the symbol
@@ -1282,10 +1286,10 @@ def check_consistency(sym, ctx_list, scale=1.0, grad_req='write',
         if n not in arg_params:
             if use_uniform:
                 arg_params[n] = np.random.uniform(low=-0.92, high=0.92,
-                                                  size=arr.shape).astype(default_type)
+                                                  size=arr.shape).astype(rand_type)
             else:
                 arg_params[n] = np.random.normal(size=arr.shape,
-                                                 scale=scale).astype(default_type)
+                                                 scale=scale).astype(rand_type)
     for n, arr in exe_list[0].aux_dict.items():
         if n not in aux_params:
             aux_params[n] = 0

tests/python/gpu/test_operator_gpu.py

@@ -614,13 +614,13 @@ def test_pooling_with_type():
                 {'ctx': mx.cpu(0), 'pool_data': (2, 2, 10, 10), 'type_dict': {'pool_data': np.float64}},
                 {'ctx': mx.cpu(0), 'pool_data': (2, 2, 10, 10), 'type_dict': {'pool_data': np.float32}}]
     sym = mx.sym.Pooling(kernel=(3,3), pool_type='max', pooling_convention='valid', name='pool')
-    check_consistency(sym, ctx_list, default_type=np.float16)
+    check_consistency(sym, ctx_list, rand_type=np.float16)
 
     sym = mx.sym.Pooling(kernel=(3,3), pool_type='max', pooling_convention='full', name='pool')
-    check_consistency(sym, ctx_list, default_type=np.float16)
+    check_consistency(sym, ctx_list, rand_type=np.float16)
 
     sym = mx.sym.Pooling(kernel=(300,300), pool_type='max', global_pool=True, name='pool')
-    check_consistency(sym, ctx_list, default_type=np.float16)
+    check_consistency(sym, ctx_list, rand_type=np.float16)
 
 
 @with_seed()
@@ -774,16 +774,16 @@ def test_pooling_with_type2():
                 {'ctx': mx.cpu(0), 'pool_data': (10, 2, 10, 10), 'type_dict': {'pool_data': np.float32}}]
 
     sym = mx.sym.Pooling(name='pool', kernel=(3,3), stride=(2,2), pool_type='max')
-    check_consistency(sym, ctx_list, default_type=np.float16)
+    check_consistency(sym, ctx_list, rand_type=np.float16)
 
     sym = mx.sym.Pooling(name='pool', kernel=(3,3), pad=(1,1), pool_type='avg')
-    check_consistency(sym, ctx_list, default_type=np.float16)
+    check_consistency(sym, ctx_list)
 
     sym = mx.sym.Pooling(name='pool', kernel=(5,5), pad=(2,2), pool_type='max')
-    check_consistency(sym, ctx_list, default_type=np.float16)
+    check_consistency(sym, ctx_list, rand_type=np.float16)
 
     sym = mx.sym.Pooling(name='pool', kernel=(3,3), pad=(1,1), pool_type='sum')
-    check_consistency(sym, ctx_list, default_type=np.float16)
+    check_consistency(sym, ctx_list)
 
 @unittest.skip("Flaky test https://github.com/apache/incubator-mxnet/issues/11517")
 @with_seed()