re-enabled tests in test_nn and fixed flake8 issues

Author: lcskrishna

test/common_nn.py

@@ -622,7 +622,6 @@ def ctcloss_reference(log_probs, targets, input_lengths, target_lengths, blank=0
         reference_fn=lambda i, t, m:
             hingeembeddingloss_reference(i, t, reduction=get_reduction(m)),
         check_sum_reduction=True,
-        test_cuda=(not TEST_WITH_ROCM)
     ),
     dict(
         module_name='HingeEmbeddingLoss',
@@ -633,7 +632,6 @@ def ctcloss_reference(log_probs, targets, input_lengths, target_lengths, blank=0
             hingeembeddingloss_reference(i, t, margin=0.5, reduction=get_reduction(m)),
         desc='margin',
         check_sum_reduction=True,
-        test_cuda=(not TEST_WITH_ROCM)
     ),
     dict(
         module_name='MultiLabelMarginLoss',
@@ -739,7 +737,6 @@ def ctcloss_reference(log_probs, targets, input_lengths, target_lengths, blank=0
         reference_fn=lambda i, t, m:
             cosineembeddingloss_reference(i[0], i[1], t, reduction=get_reduction(m)),
         check_sum_reduction=True,
-        test_cuda=(not TEST_WITH_ROCM)
     ),
     dict(
         module_name='CosineEmbeddingLoss',
@@ -750,7 +747,6 @@ def ctcloss_reference(log_probs, targets, input_lengths, target_lengths, blank=0
             cosineembeddingloss_reference(i[0], i[1], t, margin=0.7, reduction=get_reduction(m)),
         desc='margin',
         check_sum_reduction=True,
-        test_cuda=(not TEST_WITH_ROCM)
     ),
     dict(
         module_name='MarginRankingLoss',

test/test_nn.py

@@ -2609,7 +2609,6 @@ def test_batchnorm_simple_average(self):
         self._test_batchnorm_simple_average()
 
     @unittest.skipIf(not TEST_CUDA, "CUDA unavailable")
-    @skipIfRocm
     def test_batchnorm_simple_average_cuda(self):
         self._test_batchnorm_simple_average(torch.cuda.FloatTensor)
 
@@ -3961,7 +3960,6 @@ def test_variable_sequence(self):
 
     @unittest.skipIf(not TEST_CUDA, 'CUDA not available')
     @repeat_test_for_types(ALL_TENSORTYPES)
-    @skipIfRocm
     def test_variable_sequence_cuda(self, dtype=torch.float):
         self._test_variable_sequence("cuda", dtype)
 
@@ -4274,7 +4272,6 @@ def test_rnn_retain_variables(self):
 
     @unittest.skipIf(not TEST_CUDA, 'CUDA not available')
     @repeat_test_for_types(ALL_TENSORTYPES)
-    @skipIfRocm
     def test_rnn_retain_variables_cuda(self, dtype=torch.float):
         with torch.backends.cudnn.flags(enabled=False):
             self._test_rnn_retain_variables("cuda", dtype)
@@ -4833,7 +4830,6 @@ def test_batchnorm_update_stats(self):
         self._test_batchnorm_update_stats()
 
     @unittest.skipIf(not TEST_CUDA, "CUDA unavailable")
-    @skipIfRocm
     def test_batchnorm_update_stats_cuda(self):
         self._test_batchnorm_update_stats("cuda", torch.float)
 
@@ -6686,7 +6682,7 @@ def forward(self, *args):
             loss_reference_fns['NLLLossNd'](i, t, reduction=get_reduction(m)),
         check_sum_reduction=True,
         desc='2d',
-        test_cuda=(not TEST_WITH_ROCM),
+        test_cuda=(not TEST_WITH_ROCM)
     ),
     dict(
         module_name='NLLLoss',
@@ -6950,6 +6946,7 @@ def bce_with_logistic_no_reduce_test():
         check_gradgrad=False,
         pickle=False,
         decorator=skipIfRocm)
+        pickle=False,)
 
 
 def bce_with_logistic_no_reduce_scalar_test():