Rename Scan optimization tags

aesara/scan/op.py

@@ -1823,11 +1823,10 @@ class Scan(Op, ScanMethodsMixin, HasInnerGraph):
                                 # case we write about.
                                 raise
                             ne = ValueError(
-                                "An output of the scan has changed shape. "
-                                "This may be caused by a pushout optimization."
-                                " Try adding "
-                                "'optimizer_excluding=scanOp_pushout_output' "
-                                "to your Aesara flags."
+                                "An output of the Scan has changed shape. "
+                                "This may be caused by a push-out optimization."
+                                " Try adding 'optimizer_excluding=scan_pushout'"
+                                " to your Aesara flags."
                             )
                             raise ne from e
 

aesara/scan/opt.py

@@ -786,7 +786,7 @@ def add_nitsot_outputs(
     fgraph.replace_all_validate_remove(
         list(zip(old_scan_node.outputs, new_node_old_outputs)),
         remove=[old_scan_node],
-        reason="scan_pushout_output",
+        reason="scan_pushout_add",
     )
     return new_scan_node, {}
 
@@ -1003,7 +1003,7 @@ class ScanInplaceOptimizer(GlobalOptimizer):
             fgraph.replace_all_validate_remove(
                 list(zip(node.outputs, new_outs)),
                 remove=[node],
-                reason="scanOp_make_inplace",
+                reason="scan_make_inplace",
             )
             return new_outs[0].owner
         except InconsistencyError:
@@ -1892,7 +1892,7 @@ class ScanMerge(GlobalOptimizer):
             if len(subset) > 1:
                 proposal = self.merge(subset)
                 fgraph.replace_all_validate_remove(
-                    proposal, remove=subset, reason="scanOp_merge"
+                    proposal, remove=subset, reason="scan_merge"
                 )
 
 
@@ -2341,14 +2341,14 @@ optdb.register("scan_eqopt1", scan_eqopt1, 0.05, "fast_run", "scan")
 optdb.register("scan_eqopt2", scan_eqopt2, 1.6, "fast_run", "scan")
 # ScanSaveMem should execute only once per node.
 optdb.register(
-    "scanOp_save_mem",
+    "scan_save_mem",
     in2out(save_mem_new_scan, ignore_newtrees=True),
     1.61,
     "fast_run",
     "scan",
 )
 optdb.register(
-    "scanOp_make_inplace",
+    "scan_make_inplace",
     ScanInplaceOptimizer(typeInfer=None),
     75,
     "fast_run",
@@ -2360,7 +2360,7 @@ scan_eqopt1.register("all_pushout_opt", scan_seqopt1, 1, "fast_run", "scan")
 
 
 scan_seqopt1.register(
-    "scanOp_remove_constants_and_unused_inputs0",
+    "scan_remove_constants_and_unused_inputs0",
     in2out(remove_constants_and_unused_inputs_scan, ignore_newtrees=True),
     1,
     "remove_constants_and_unused_inputs_scan",
@@ -2370,20 +2370,22 @@ scan_seqopt1.register(
 
 
 scan_seqopt1.register(
-    "scanOp_pushout_nonseqs_ops",
+    "scan_pushout_nonseqs_ops",
     in2out(push_out_non_seq_scan, ignore_newtrees=True),
     2,
     "fast_run",
     "scan",
+    "scan_pushout",
 )
 
 
 scan_seqopt1.register(
-    "scanOp_pushout_seqs_ops",
+    "scan_pushout_seqs_ops",
     in2out(push_out_seq_scan, ignore_newtrees=True),
     3,
     "fast_run",
     "scan",
+    "scan_pushout",
 )
 
 
@@ -2394,17 +2396,19 @@ scan_seqopt1.register(
     "fast_run",
     "more_mem",
     "scan",
+    "scan_pushout",
 )
 
 
 scan_seqopt1.register(
-    "scanOp_pushout_output",
+    "scan_pushout_add",
     # TODO: Perhaps this should be an `EquilibriumOptimizer`?
     in2out(push_out_add_scan, ignore_newtrees=False),
     5,
     "fast_run",
     "more_mem",
     "scan",
+    "scan_pushout",
 )
 
 
@@ -2418,7 +2422,7 @@ scan_eqopt2.register(
 
 
 scan_eqopt2.register(
-    "scanOp_remove_constants_and_unused_inputs1",
+    "scan_remove_constants_and_unused_inputs1",
     in2out(remove_constants_and_unused_inputs_scan, ignore_newtrees=True),
     2,
     "remove_constants_and_unused_inputs_scan",
@@ -2430,11 +2434,11 @@ scan_eqopt2.register(
 # after const merge but before stabilize so that we can have identity
 # for equivalent nodes but we still have the chance to hoist stuff out
 # of the scan later.
-scan_eqopt2.register("scanOp_merge", ScanMerge(), 4, "fast_run", "scan")
+scan_eqopt2.register("scan_merge", ScanMerge(), 4, "fast_run", "scan")
 
 # After Merge optimization
 scan_eqopt2.register(
-    "scanop_remove_constants_and_unused_inputs2",
+    "scan_remove_constants_and_unused_inputs2",
     in2out(remove_constants_and_unused_inputs_scan, ignore_newtrees=True),
     5,
     "remove_constants_and_unused_inputs_scan",
@@ -2443,17 +2447,16 @@ scan_eqopt2.register(
 )
 
 scan_eqopt2.register(
-    "scanOp_merge_inouts",
+    "scan_merge_inouts",
     in2out(scan_merge_inouts, ignore_newtrees=True),
     6,
-    "scan_merge_inouts",
     "fast_run",
     "scan",
 )
 
 # After everything else
 scan_eqopt2.register(
-    "scanOp_remove_constants_and_unused_inputs3",
+    "scan_remove_constants_and_unused_inputs3",
     in2out(remove_constants_and_unused_inputs_scan, ignore_newtrees=True),
     8,
     "remove_constants_and_unused_inputs_scan",

aesara/scan/scan_perform.pyx

@@ -58,7 +58,7 @@ from aesara.link.utils import raise_with_op
 
 
 def get_version():
-    return 0.300
+    return 0.301
 
 @cython.boundscheck(False)
 def perform(
@@ -545,11 +545,10 @@ def perform(
                         if i == 0:
                             raise
                         raise ValueError(
-                            "An output of the scan has changed shape. "
-                            "This may be caused by a pushout optimization."
-                            " Try adding "
-                            "'optimizer_excluding=scanOp_pushout_output' "
-                            "to your Aesara flags.")
+                            "An output of the Scan has changed shape. "
+                            "This may be caused by a push-out optimization."
+                            " Try adding 'optimizer_excluding=scan_pushout'"
+                            " to your Aesara flags.")
 
         # 5.6 Copy over the values for outputs corresponding to shared
         # variables

aesara/scan/scan_perform_ext.py

@@ -21,7 +21,7 @@ if not config.cxx:
 
 _logger = logging.getLogger("aesara.scan.scan_perform")
 
-version = 0.300  # must match constant returned in function get_version()
+version = 0.301  # must match constant returned in function get_version()
 
 need_reload = False
 

doc/troubleshooting.rst

@@ -159,9 +159,9 @@ Could lower the memory usage, but raise computation time:
   <aesara.tensor.nnet.batchnorm.batch_normalization>`. It use less memory
   then building a corresponding Aesara graph.
 - Disable one or scan more optimizations:
-    - ``optimizer_excluding=scanOp_pushout_seqs_ops``
+    - ``optimizer_excluding=scan_pushout_seqs_ops``
     - ``optimizer_excluding=scan_pushout_dot1``
-    - ``optimizer_excluding=scanOp_pushout_output``
+    - ``optimizer_excluding=scan_pushout_add``
 - Disable all optimization tagged as raising memory usage:
   ``optimizer_excluding=more_mem`` (currently only the 3 scan optimizations above)
 - `float16 <https://github.com/Theano/Theano/issues/2908>`_.

tests/scan/test_basic.py

@@ -2523,7 +2523,7 @@ class TestScan:
         sy, upy = scan(sum, sequences=[y])
 
         f = function(
-            [x, y], [sx, sy], mode=mode_with_opt.excluding("scanOp_pushout_seqs_ops")
+            [x, y], [sx, sy], mode=mode_with_opt.excluding("scan_pushout_seqs_ops")
         )
         topo = f.maker.fgraph.toposort()
         scans = [n for n in topo if isinstance(n.op, Scan)]
@@ -2533,7 +2533,7 @@ class TestScan:
         sy, upy = scan(sum, sequences=[y], n_steps=3)
 
         f = function(
-            [x, y], [sx, sy], mode=mode_with_opt.excluding("scanOp_pushout_seqs_ops")
+            [x, y], [sx, sy], mode=mode_with_opt.excluding("scan_pushout_seqs_ops")
         )
         topo = f.maker.fgraph.toposort()
         scans = [n for n in topo if isinstance(n.op, Scan)]
@@ -2543,7 +2543,7 @@ class TestScan:
         sy, upy = scan(sum, sequences=[y], n_steps=4)
 
         f = function(
-            [x, y], [sx, sy], mode=mode_with_opt.excluding("scanOp_pushout_seqs_ops")
+            [x, y], [sx, sy], mode=mode_with_opt.excluding("scan_pushout_seqs_ops")
         )
         topo = f.maker.fgraph.toposort()
         scans = [n for n in topo if isinstance(n.op, Scan)]
@@ -2553,7 +2553,7 @@ class TestScan:
         sy, upy = scan(sum, sequences=[x])
 
         f = function(
-            [x], [sx, sy], mode=mode_with_opt.excluding("scanOp_pushout_seqs_ops")
+            [x], [sx, sy], mode=mode_with_opt.excluding("scan_pushout_seqs_ops")
         )
         topo = f.maker.fgraph.toposort()
         scans = [n for n in topo if isinstance(n.op, Scan)]
@@ -2563,7 +2563,7 @@ class TestScan:
         sy, upy = scan(sum, sequences=[x], mode="FAST_COMPILE")
 
         f = function(
-            [x], [sx, sy], mode=mode_with_opt.excluding("scanOp_pushout_seqs_ops")
+            [x], [sx, sy], mode=mode_with_opt.excluding("scan_pushout_seqs_ops")
         )
         topo = f.maker.fgraph.toposort()
         scans = [n for n in topo if isinstance(n.op, Scan)]
@@ -2573,7 +2573,7 @@ class TestScan:
         sy, upy = scan(sum, sequences=[x], truncate_gradient=1)
 
         f = function(
-            [x], [sx, sy], mode=mode_with_opt.excluding("scanOp_pushout_seqs_ops")
+            [x], [sx, sy], mode=mode_with_opt.excluding("scan_pushout_seqs_ops")
         )
         topo = f.maker.fgraph.toposort()
         scans = [n for n in topo if isinstance(n.op, Scan)]
@@ -2596,7 +2596,7 @@ class TestScan:
         sz, upz = scan(sum, sequences=[sx], n_steps=4, name="Z")
 
         f = function(
-            [x, y], [sy, sz], mode=mode_with_opt.excluding("scanOp_pushout_seqs_ops")
+            [x, y], [sy, sz], mode=mode_with_opt.excluding("scan_pushout_seqs_ops")
         )
         topo = f.maker.fgraph.toposort()
         scans = [n for n in topo if isinstance(n.op, Scan)]

tests/scan/test_opt.py

@@ -156,7 +156,7 @@ class TestPushOutScanOutputDot:
         opt_mode = mode.including("scan")
         f_opt = aesara.function([v, m], jacobian(output, v), mode=opt_mode)
 
-        no_opt_mode = mode.excluding("scanOp_pushout_output")
+        no_opt_mode = mode.excluding("scan_pushout_add")
         f_no_opt = aesara.function([v, m], jacobian(output, v), mode=no_opt_mode)
 
         # Ensure that the optimization was performed correctly in f_opt
@@ -198,7 +198,7 @@ class TestPushOutScanOutputDot:
         opt_mode = mode.including("scan")
         f_opt = aesara.function([a, b], outputs, mode=opt_mode)
 
-        no_opt_mode = mode.excluding("scanOp_pushout_output")
+        no_opt_mode = mode.excluding("scan_pushout_add")
         f_no_opt = aesara.function([a, b], outputs, mode=no_opt_mode)
 
         # Ensure that the optimization was performed correctly in f_opt
@@ -244,7 +244,7 @@ class TestPushOutScanOutputDot:
         opt_mode = mode.including("scan")
         f_opt = aesara.function([a, b], outputs, mode=opt_mode)
 
-        no_opt_mode = mode.excluding("scanOp_pushout_output")
+        no_opt_mode = mode.excluding("scan_pushout_add")
         f_no_opt = aesara.function([a, b], outputs, mode=no_opt_mode)
 
         # Ensure that the optimization was performed correctly in f_opt
@@ -346,7 +346,7 @@ class TestPushOutSumOfDot:
         grad1 = grad(cost, [U, V, W])
         f_opt = aesara.function(inputs=[x, ri, zi], outputs=grad1, mode=opt_mode)
 
-        no_opt_mode = mode.excluding("scanOp_pushout_output")
+        no_opt_mode = mode.excluding("scan_pushout_add")
         h, _ = aesara.scan(
             rnn_step1,
             sequences=[x, ri, zi],
@@ -405,7 +405,7 @@ class TestPushOutSumOfDot:
         output = h[-1]
         f_opt = aesara.function([input1, input2, input3], output, mode=opt_mode)
 
-        no_opt_mode = mode.excluding("scanOp_pushout_output")
+        no_opt_mode = mode.excluding("scan_pushout_add")
         h, _ = aesara.scan(
             inner_fct,
             sequences=[input1, input2, input3],