Update and refactor logger warnings

tests/unittest_tools.py

@@ -255,7 +255,7 @@ class InferShapeTester:
                 else:
                     shp = inp.shape
                 if len(set(shp)) != len(shp):
-                    _logger.warn(
+                    _logger.warning(
                         "While testing shape inference for %r, we received an"
                         " input with a shape that has some repeated values: %r"
                         ", like a square matrix. This makes it impossible to"

theano/compile/debugmode.py

@@ -1437,7 +1437,7 @@ def _check_preallocated_output(
             fn_attr_name = ops_with_inner_function[type(node.op)]
             fn = getattr(node.op, fn_attr_name, None)
             if not fn or not hasattr(fn, "maker") or not hasattr(fn.maker, "mode"):
-                _logger.warn(
+                _logger.warning(
                     "Expected theano function not found in %s.%s", node.op, fn_attr_name
                 )
             else:
@@ -1482,7 +1482,7 @@ def _check_preallocated_output(
 
             if not out_map:
                 # Map is empty, there is no need to execute thunk() again
-                _logger.warn("%s: out_map is empty", name)
+                _logger.warning("%s: out_map is empty", name)
                 continue
 
             # Copy the inputs over, if they were marked as destroyed or viewed
@@ -1904,7 +1904,7 @@ class _Linker(gof.link.LocalLinker):
                 thunks_py.append(None)
 
             if not self.maker.mode.check_c_code and thunks_py[-1] is None:
-                _logger.warn(
+                _logger.warning(
                     "Op %s doesn't have a perform, "
                     "forcing check of the C code" % node.op
                 )
@@ -1921,7 +1921,7 @@ class _Linker(gof.link.LocalLinker):
                 elif thunks_c[-1] is None:
                     thunks_c[-1] = thunk_other
                 else:
-                    _logger.warn(
+                    _logger.warning(
                         "We won't check the perform function "
                         "of node '%s' but we will check its "
                         "make_thunk function" % node

theano/gof/cmodule.py

@@ -2055,7 +2055,7 @@ class GCC_compiler(Compiler):
             and "clang-omp++" not in theano.config.cxx
             and "icpc" not in theano.config.cxx
         ):
-            _logger.warn(
+            _logger.warning(
                 "OPTIMIZATION WARNING: your Theano flag `cxx` seems not to be"
                 " the g++ compiler. So we disable the compiler optimization"
                 " specific to g++ that tell to compile for a specific CPU."
@@ -2124,7 +2124,7 @@ class GCC_compiler(Compiler):
                     )
                 else:
                     reported_lines = native_lines
-                _logger.warn(
+                _logger.warning(
                     "OPTIMIZATION WARNING: Theano was not able to find the"
                     " g++ parameters that tune the compilation to your "
                     " specific CPU. This can slow down the execution of Theano"
@@ -2137,7 +2137,7 @@ class GCC_compiler(Compiler):
                 default_lines = get_lines("%s -E -v -" % theano.config.cxx)
                 _logger.info("g++ default lines: %s", default_lines)
                 if len(default_lines) < 1:
-                    _logger.warn(
+                    _logger.warning(
                         "OPTIMIZATION WARNING: Theano was not able to find the"
                         " default g++ parameters. This is needed to tune"
                         " the compilation to your specific"

theano/gof/compilelock.py

@@ -349,7 +349,7 @@ def refresh_lock(lock_file):
         # This way, only 1 test would fail.
         while get_lock.n_lock > 0:
             release_lock()
-        _logger.warn(
+        _logger.warning(
             "Refreshing lock failed, we release the"
             " lock before raising again the exception"
         )

theano/gof/vm.py

@@ -924,7 +924,7 @@ class VM_Linker(link.LocalLinker):
             if self.use_cloop and (
                 self.callback is not None or self.callback_input is not None
             ):
-                logger.warn("CVM does not support callback, using Stack VM.")
+                logger.warning("CVM does not support callback, using Stack VM.")
             if self.use_cloop and config.profile_memory:
                 warnings.warn("CVM does not support memory profile, using Stack VM.")
             if not self.use_cloop and self.allow_partial_eval:

theano/printing.py

@@ -862,7 +862,7 @@ def pydotprint(
             ):
                 cond = node
         if cond is None:
-            _logger.warn(
+            _logger.warning(
                 "pydotprint: cond_highlight is set but there is no"
                 " IfElse node in the graph"
             )

theano/tensor/nnet/conv.py

@@ -559,7 +559,7 @@ class ConvOp(OpenMPOp):
                     " bsize(%i). We revert it to %i. This"
                     " won't change the result, but may make it slower."
                 )
-                _logger.warn(warnstr, self.unroll_batch, self.bsize, new)
+                _logger.warning(warnstr, self.unroll_batch, self.bsize, new)
 
                 self.unroll_batch = new
 
@@ -585,7 +585,7 @@ class ConvOp(OpenMPOp):
                     " nkern(%i). We revert it to %i. This"
                     " won't change the result, but may make it slower."
                 )
-                _logger.warn(warnstr, self.unroll_kern, self.nkern, new)
+                _logger.warning(warnstr, self.unroll_kern, self.nkern, new)
                 self.unroll_kern = new
 
         self.outshp = get_conv_output_shape(

theano/tensor/opt.py

@@ -3251,7 +3251,7 @@ def merge_two_slices(slice1, len1, slice2, len2):
             # sl.stop backwards
             n_val = sl1.stop - 1 - sl2 * sl1.step
             if config.warn.subtensor_merge_bug:
-                warnings.warn(
+                warnings.warning(
                     (
                         "Your current code is fine, but Theano versions "
                         "prior to 0.5rc2 might have given an incorrect result. "
@@ -3843,7 +3843,7 @@ def local_adv_sub1_adv_inc_sub1(node):
 
     if not inp.owner.op.set_instead_of_inc:
         if config.warn.inc_subtensor1_opt:
-            warnings.warn(
+            warnings.warning(
                 "Your current code is fine, but Theano versions "
                 "between 0.7rc1 and 0.10 (or development versions "
                 "between Nov. 2014 and May 2017) "
@@ -5851,7 +5851,7 @@ def local_sum_prod_div_dimshuffle(node):
                         break
 
                 if compatible_dims:
-                    _logger.warn(
+                    _logger.warning(
                         "WARNING: Your current code is fine, but"
                         " Theano versions between "
                         "rev. 3bd9b789f5e8 (2010-06-16) and"
@@ -5906,7 +5906,7 @@ def local_sum_prod_div_dimshuffle(node):
                         if config.warn.sum_div_dimshuffle_bug and isinstance(
                             node.op, T.Sum
                         ):
-                            _logger.warn(
+                            _logger.warning(
                                 "WARNING: Your current code is fine,"
                                 " but Theano versions between "
                                 "rev. 3bd9b789f5e8 (2010-06-16) and"
@@ -6016,7 +6016,7 @@ def local_op_of_op(node):
                     and newaxis != newaxis_old
                     and len(newaxis) == len(newaxis_old)
                 ):
-                    _logger.warn(
+                    _logger.warning(
                         "WARNING (YOUR CURRENT CODE IS FINE): Theano "
                         "versions between version 9923a40c7b7a and August "
                         "2nd, 2010 generated bugged code in this case. "
@@ -6102,7 +6102,7 @@ def local_reduce_join(node):
         # I put this warning late to don't add extra warning.
         if len(reduce_axis) != 1 or 0 not in reduce_axis:
             if theano.config.warn.reduce_join:
-                warnings.warn(
+                warnings.warning(
                     (
                         "Your current code is fine, but Theano versions "
                         "prior to 0.7 (or this development version Sept 2014) "
@@ -7691,7 +7691,6 @@ def local_elemwise_fusion_op(OP, max_input_fct=lambda node: 32, maker=None):
 
         for i in node.inputs:
             do_fusion = False
-            catch = False
             # Will store inputs of the fused node that are not currently inputs
             # of the node we want to create (to avoid duplicating inputs).
             tmp_input = []
@@ -7712,7 +7711,6 @@ def local_elemwise_fusion_op(OP, max_input_fct=lambda node: 32, maker=None):
                 # computation due to broadcast.
                 i.owner.outputs[0].broadcastable == node.outputs[0].broadcastable
             ):
-                do_fusion = True
                 try:
                     tmp_s_input = []
                     # we should not put duplicate input into s_inputs and inputs
@@ -7746,12 +7744,11 @@ def local_elemwise_fusion_op(OP, max_input_fct=lambda node: 32, maker=None):
                         ["z" for z in i.owner.outputs],
                         {"fail": "%(fail)s"},
                     )
-                except MethodNotDefined:
-                    catch = True
-                except NotImplementedError:
-                    catch = True
-                if catch:
-                    _logger.info(
+
+                    do_fusion = True
+
+                except (NotImplementedError, MethodNotDefined):
+                    _logger.warning(
                         (
                             "%s does not implement the c_code function."
                             " As well as being potentially slow, this"
@@ -7819,8 +7816,8 @@ your code will run correctly, but may be slower."""
                 ["z" for x in s_new_out],
                 {"fail": "%(fail)s"},
             )
-        except MethodNotDefined:
-            _logger.info(
+        except (NotImplementedError, MethodNotDefined):
+            _logger.warning(
                 (
                     "%s does not implement the c_code function."
                     " As well as being potentially slow, this disables "
@@ -7828,17 +7825,6 @@ your code will run correctly, but may be slower."""
                 )
                 % str(s_new_out[0].owner.op)
             )
-            return False
-        except NotImplementedError:
-            _logger.info(
-                (
-                    "%s does not implement the c_code function. As well"
-                    " as being potentially slow, this disables loop"
-                    " fusion of this op."
-                )
-                % str(s_new_out[0].owner.op)
-            )
-            return False
 
         # create the composite op.
         C = scalar.Composite(s_inputs, s_new_out)
@@ -7850,7 +7836,7 @@ your code will run correctly, but may be slower."""
         assert node.outputs[0].dtype == n.outputs[0].dtype
 
         if len(n.inputs) > max_nb_input:
-            _logger.info(
+            _logger.warning(
                 "loop fusion failed because Op would exceed" " kernel argument limit."
             )
             return False