Remove lambda functions that are not anymore needed

theano/tensor/nnet/tests/test_conv3d2d.py

@@ -76,10 +76,9 @@ def pyconv3d(signals, filters):
 
 
 def check_diagonal_subtensor_view_traces(fn):
-    def check_node_type(node):
-        return isinstance(node.op, (DiagonalSubtensor, IncDiagonalSubtensor))
-    assert check_stack_trace(fn, ops_to_check=check_node_type,
-                             bug_print='ignore')
+    assert check_stack_trace(
+        fn, ops_to_check=(DiagonalSubtensor, IncDiagonalSubtensor),
+        bug_print='ignore')
 
 
 def test_conv3d(mode=mode_without_gpu, shared=theano.tensor._shared):

theano/tensor/nnet/tests/test_nnet.py

@@ -1354,8 +1354,7 @@ def test_argmax_pushdown_bias():
     for i, type in enumerate(types_to_check):
         assert isinstance(fgraph.toposort()[i].op, type)
     assert str(fgraph.toposort()[3].op) == 'OutputGuard'
-    assert check_stack_trace(
-        fgraph, ops_to_check=lambda node: isinstance(node.op, types_to_check))
+    assert check_stack_trace(fgraph, ops_to_check=types_to_check)
 
     x = tensor.matrix()
     b = tensor.vector()
@@ -1381,9 +1380,8 @@ def test_argmax_pushdown_bias():
     assert isinstance(fgraph.toposort()[1].op.scalar_op, theano.scalar.Maximum)
     assert str(fgraph.toposort()[2].op) == 'OutputGuard'
     assert check_stack_trace(
-        fgraph, ops_to_check=lambda node: (
-            isinstance(node, (SoftmaxWithBias, tensor.CAReduce)) or
-            isinstance(node.op.scalar_op, theano.scalar.Maximum)))
+        fgraph, ops_to_check=(SoftmaxWithBias, tensor.CAReduce))
+
 
 def test_asymptotic_32():
     """

theano/tensor/nnet/tests/test_sigm.py

@@ -368,9 +368,7 @@ class T_softplus_opts(unittest.TestCase):
                           theano.tensor.nnet.sigm.ScalarSoftplus,
                           theano.scalar.Neg)
 
-        assert check_stack_trace(
-            f, ops_to_check=
-            lambda x: isinstance(x.op.scalar_op, types_to_check))
+        assert check_stack_trace(f, ops_to_check=types_to_check)
         topo = f.maker.fgraph.toposort()
         assert len(topo) == 3
         for i, op in enumerate(types_to_check):