Remove now useless exception_verbosity extra info that is now added by default.

theano/tensor/basic.py

@@ -7843,24 +7843,11 @@ class Dot(Op):
     def perform(self, node, inp, out):
         x, y = inp
         z, = out
-        try:
-            # the asarray is here because dot between two vectors
-            # gives a numpy float object but we need to return a 0d
-            # ndarray
-            z[0] = numpy.asarray(numpy.dot(x, y))
-        except ValueError, e:
-            # The error raised by numpy has no shape information, we mean to
-            # add that
-            if config.exception_verbosity == 'high':
-                raise ValueError('dot product failed.\n'
-                                 'First arg dims: ' + str(x.shape) + '\n'
-                                 'Second arg dims: ' + str(y.shape) + '\n'
-                                 'First arg: \n' +
-                                 min_informative_str(node.inputs[0]) +
-                                 '\nSecond arg: \n' +
-                                 min_informative_str(node.inputs[1]))
-            e.args = e.args + (x.shape, y.shape)
-            raise
+
+        # the asarray is here because dot between two vectors
+        # gives a numpy float object but we need to return a 0d
+        # ndarray
+        z[0] = numpy.asarray(numpy.dot(x, y))
 
     def grad(self, inp, grads):
 

theano/tensor/elemwise.py

@@ -807,14 +807,7 @@ class Elemwise(Op):
 
                 base_exc_str = 'Dimension mismatch; shapes are %s' % (
                                ', '.join(msg))
-                if config.exception_verbosity == 'high':
-                    msg_chunks = [base_exc_str]
-                    for i, ipt in enumerate(node.inputs):
-                        msg_chunks.append('input %d: %s' %
-                                          (i, min_informative_str(ipt)))
-                    raise ValueError('\n'.join(msg_chunks))
-                else:
-                    raise ValueError(base_exc_str)
+                raise ValueError(base_exc_str)
 
         # Determine the shape of outputs
         out_shape = []
@@ -875,29 +868,7 @@ class Elemwise(Op):
                                       self.scalar_op.nout))
             nout = ufunc.nout
 
-        try:
-            variables = ufunc(*ufunc_args)
-        except Exception, e:
-            errormsg = ('While computing ' + str(node.outputs) +
-                        ': Failed calling ufunc for op ' +
-                        str(self.scalar_op) +
-                        ' for params of shape ' +
-                        str([arg.shape for arg in ufunc_args]))
-
-            if config.exception_verbosity == 'high':
-                errormsg += 'inputs are: \n'
-                for i, ipt in enumerate(node.inputs):
-                    errormsg += '(' + str(i) + ') ' + \
-                            min_informative_str(ipt) + '\n'
-                errormsg += 'outputs are: \n'
-                for i, output in enumerate(node.outputs):
-                    errormsg += '(' + str(i) + ') ' + \
-                            min_informative_str(output) + '\n'
-                errormsg += 'original exception was: ' + '\n'.join(
-                        traceback.format_exception_only(*sys.exc_info()[0:2]))
-
-            e.args = e.args + (errormsg, )
-            raise
+        variables = ufunc(*ufunc_args)
 
         if nout == 1:
             variables = [variables]

theano/tensor/tests/test_basic.py

@@ -4907,9 +4907,6 @@ class t_dot(unittest.TestCase):
                     # Reported by Theano perform
                     e0.split()[0:4]
                          == ['Incompatible', 'shapes', 'for', 'gemv'] or
-                    # Reported by Theano when 'exception_verbosity' is set
-                    # to 'high'.
-                    e0.split()[0:3] == ['dot', 'product', 'failed.'],
                     e)
         finally:
             _logger.setLevel(oldlevel)