[Relay] Flexible shape dispatch transformation

python/tvm/auto_scheduler/dispatcher.py

@@ -130,11 +130,13 @@ class ApplyHistoryBest(DispatchContext):
 
     Parameters
     ----------
-    records : str or iterator of (auto_scheduler.measure.MeasureInput,\
-                                  auto_scheduler.measure.MeasureResult)
+    records : str, list of str, or iterator of (auto_scheduler.measure.MeasureInput,\
+                                                auto_scheduler.measure.MeasureResult)
         Collection of tuning records.
         If is str, then it should be the filename of a records log file.
-        Each row of this file is an encoded record pair. Otherwise, it is an iterator.
+        Each row of this file is an encoded record pair. If it is an iterator,
+        it can either be a set of str filenames which will be applied jointly,
+        or a set of (input, result) tuples.
     n_lines: Optional[int]
         if it is not None, only load the first `n_lines` lines of log.
     include_compatible: bool
@@ -196,20 +198,29 @@ def load(self, records, n_lines=None):
         n_lines: Optional[int]
             if it is not None, only load the first `n_lines` lines of log
         """
-        if isinstance(records, pathlib.Path):
-            records = str(records)
+        joint_records = []
+        if not isinstance(records, (list, tuple)):
+            records = [records]
 
-        if isinstance(records, str):
-            records = load_records(records)
+        for rec in records:
+            if isinstance(rec, pathlib.Path):
+                rec = str(rec)
+
+            if isinstance(rec, str):
+                rec = load_records(rec)
+                joint_records += rec
+            else:
+                if rec is not None:
+                    joint_records.append(rec)
 
-        if not records:
+        if not joint_records:
             return
 
         best_by_targetkey = self.best_by_targetkey
         best_by_model = self.best_by_model
 
         counter = 0
-        for inp, res in records:
+        for inp, res in joint_records:
             if n_lines is not None and counter >= n_lines:
                 break
             counter += 1

python/tvm/autotvm/task/dispatcher.py

@@ -184,10 +184,12 @@ class ApplyHistoryBest(DispatchContext):
 
     Parameters
     ----------
-    records : str or iterator of (autotvm.measure.MeasureInput, autotvm.measure.MeasureResult)
+    records : str, list of str, or iterator of (autotvm.measure.MeasureInput,\
+                                                autotvm.measure.MeasureResult)
         Collection of tuning records.
         If is str, then it should be the filename of a records log file.
-        Each row of this file is an encoded record pair. Otherwise, it is an iterator.
+        Each row of this file is an encoded record pair. If it is a list, it can either be
+        a list of paths to log files that will be loaded jointly or an iterator or records.
     """
 
     def __init__(self, records):
@@ -205,28 +207,41 @@ def load(self, records):
 
         Parameters
         ----------
-        records : str or iterator of (autotvm.measure.MeasureInput, autotvm.measure.MeasureResult)
+        records : str, list of str, or iterator of (autotvm.measure.MeasureInput,\
+                                                    autotvm.measure.MeasureResult)
             Collection of tuning records.
             If is str, then it should be the filename of a records log file.
-            Each row of this file is an encoded record pair. Otherwise, it is an iterator.
+            Each row of this file is an encoded record pair. If it is a list
+            it can either be a list of paths to logs that will loaded jointly or
+            an iterator of measurement results.
         """
         # pylint: disable=import-outside-toplevel
         from pathlib import Path
         from ..record import load_from_file
 
-        if isinstance(records, Path):
-            records = str(records)
+        joint_records = []
+        if not isinstance(records, (list, tuple)):
+            records = [records]
 
-        if isinstance(records, str):
-            records = load_from_file(records)
-        if not records:
+        for rec in records:
+            if isinstance(rec, Path):
+                rec = str(rec)
+
+            if isinstance(rec, str):
+                rec = load_from_file(rec)
+                joint_records += rec
+            else:
+                if rec is not None:
+                    joint_records.append(rec)
+
+        if not joint_records:
             return
 
         best_by_targetkey = self.best_by_targetkey
         best_by_model = self.best_by_model
 
         counter = 0
-        for inp, res in records:
+        for inp, res in joint_records:
             counter += 1
             if res.error_no != 0:
                 continue

python/tvm/relay/transform/__init__.py

@@ -20,3 +20,4 @@
 from .transform import *
 from .recast import recast
 from . import fake_quantization_to_integer, mixed_precision
+from .flexible_shape import FlexibleShapeDispatch