Fix typos and simplify tests.

theano/gpuarray/tests/test_dnn.py

@@ -1067,15 +1067,19 @@ def get_conv3d_test_cases():
     return itt
 
 
-def run_conv_small_batched_vs_multicall(inputs_shape, filters_shape, batch_sub, subsample):
+def run_conv_small_batched_vs_multicall(inputs_shape, filters_shape, batch_sub):
     # Function to check issue #5985 (see tests below): https://github.com/Theano/Theano/issues/5985
 
+    # Error occurs with algorithm `small` (CUDNN_CONVOLUTION_FWD_ALGO_IMPLICIT_PRECOMP_GEMM)
     algo = 'small'
+
     batch_size = inputs_shape[0]
 
     utt.seed_rng()
     inputs_val = np.random.random(inputs_shape).astype('float32')
     filters_val = np.random.random(filters_shape).astype('float32')
+    # Scale down the input values to prevent very large absolute errors
+    # due to float rounding
     inputs_val /= 10
     filters_val /= 10
     inputs = theano.shared(inputs_val)
@@ -1085,19 +1089,18 @@ def run_conv_small_batched_vs_multicall(inputs_shape, filters_shape, batch_sub,
         dnn_func = dnn.dnn_conv3d
     else:
         dnn_func = dnn.dnn_conv
-    conv = dnn_func(img=inputs, kerns=filters, algo=algo, subsample=subsample)
-    # Just compute firt and last outputs to reduce execution time.
-    sub_conv_top = dnn_func(img=inputs[:batch_sub],
-                            kerns=filters, algo=algo, subsample=subsample)
-    sub_conv_bottom = dnn_func(img=inputs[(batch_size - batch_sub):],
-                               kerns=filters, algo=algo, subsample=subsample)
+    conv = dnn_func(img=inputs, kerns=filters, algo=algo)
+    # Just compute first and last outputs, to reduce execution time.
+    sub_conv_top = dnn_func(img=inputs[:batch_sub], kerns=filters, algo=algo)
+    sub_conv_bottom = dnn_func(img=inputs[(batch_size - batch_sub):], kerns=filters, algo=algo)
     f = theano.function([], [conv, sub_conv_top, sub_conv_bottom], mode=mode_with_gpu)
     res_all, res_batch_top, res_batch_bottom = f()
-    for i in range(0, batch_sub):
+    for i in range(batch_sub):
+        # Check first ouputs.
         utt.assert_allclose(res_batch_top[i], res_all[i])
+        # Then check last outputs.
         p = batch_size - batch_sub + i
-        # It seems there is a liimit batch size of 65536 for a good computation
-        # with algorithm `small`.
+        # It seems there is a limit batch size of 65536  with algorithm `small`.
         checked_limit = 2**16
         if p >= checked_limit:
             # It seems results are repeated in the entire conv.
@@ -1108,17 +1111,17 @@ def run_conv_small_batched_vs_multicall(inputs_shape, filters_shape, batch_sub,
 
 
 def test_batched_conv_small():
-    yield (run_conv_small_batched_vs_multicall, (65534, 2, 2, 2), (1, 2, 2, 2), 5, (1, 1))  # OK
-    yield (run_conv_small_batched_vs_multicall, (65535, 2, 2, 2), (1, 2, 2, 2), 5, (1, 1))  # OK
-    yield (run_conv_small_batched_vs_multicall, (65536, 2, 2, 2), (1, 2, 2, 2), 5, (1, 1))  # OK
-    yield (run_conv_small_batched_vs_multicall, (65537, 2, 2, 2), (1, 2, 2, 2), 5, (1, 1))  # ERROR
+    yield (run_conv_small_batched_vs_multicall, (65534, 2, 2, 2), (1, 2, 2, 2), 5)  # OK
+    yield (run_conv_small_batched_vs_multicall, (65535, 2, 2, 2), (1, 2, 2, 2), 5)  # OK
+    yield (run_conv_small_batched_vs_multicall, (65536, 2, 2, 2), (1, 2, 2, 2), 5)  # OK
+    yield (run_conv_small_batched_vs_multicall, (65537, 2, 2, 2), (1, 2, 2, 2), 5)  # ERROR
 
 
 def test_batched_conv3d_small():
-    yield (run_conv_small_batched_vs_multicall, (65534, 2, 2, 2, 2), (1, 2, 2, 2, 2), 5, (1, 1, 1))  # OK
-    yield (run_conv_small_batched_vs_multicall, (65535, 2, 2, 2, 2), (1, 2, 2, 2, 2), 5, (1, 1, 1))  # OK
-    yield (run_conv_small_batched_vs_multicall, (65536, 2, 2, 2, 2), (1, 2, 2, 2, 2), 5, (1, 1, 1))  # OK
-    yield (run_conv_small_batched_vs_multicall, (65537, 2, 2, 2, 2), (1, 2, 2, 2, 2), 5, (1, 1, 1))  # ERROR ALSO.
+    yield (run_conv_small_batched_vs_multicall, (65534, 2, 2, 2, 2), (1, 2, 2, 2, 2), 5)  # OK
+    yield (run_conv_small_batched_vs_multicall, (65535, 2, 2, 2, 2), (1, 2, 2, 2, 2), 5)  # OK
+    yield (run_conv_small_batched_vs_multicall, (65536, 2, 2, 2, 2), (1, 2, 2, 2, 2), 5)  # OK
+    yield (run_conv_small_batched_vs_multicall, (65537, 2, 2, 2, 2), (1, 2, 2, 2, 2), 5)  # ERROR ALSO.
 
 
 def test_conv3d_fwd():