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new a1a1a7ca03 [AUTOTVM][FIX] Typo fixes and add a warning in the Droplet
Search (#16289)
a1a1a7ca03 is described below
commit a1a1a7ca033f83315d02411d4b2c475ddacc795e
Author: Michael Canesche <[email protected]>
AuthorDate: Mon Jan 8 14:11:51 2024 -0300
[AUTOTVM][FIX] Typo fixes and add a warning in the Droplet Search (#16289)
Typo fixes and add warning
---
python/tvm/autotvm/tuner/__init__.py | 2 +-
.../tuner/{droplet_turner.py => droplet_tuner.py} | 17 ++++++++++++++---
2 files changed, 15 insertions(+), 4 deletions(-)
diff --git a/python/tvm/autotvm/tuner/__init__.py
b/python/tvm/autotvm/tuner/__init__.py
index dd53862d7d..437a97041d 100644
--- a/python/tvm/autotvm/tuner/__init__.py
+++ b/python/tvm/autotvm/tuner/__init__.py
@@ -28,4 +28,4 @@ from .tuner import Tuner
from .index_based_tuner import GridSearchTuner, RandomTuner
from .ga_tuner import GATuner
from .xgboost_tuner import XGBTuner
-from .droplet_turner import DropletTuner
+from .droplet_tuner import DropletTuner
diff --git a/python/tvm/autotvm/tuner/droplet_turner.py
b/python/tvm/autotvm/tuner/droplet_tuner.py
similarity index 88%
rename from python/tvm/autotvm/tuner/droplet_turner.py
rename to python/tvm/autotvm/tuner/droplet_tuner.py
index 35bc7d857f..d58bfa4989 100644
--- a/python/tvm/autotvm/tuner/droplet_turner.py
+++ b/python/tvm/autotvm/tuner/droplet_tuner.py
@@ -17,6 +17,7 @@
"""Tuner with droplet algorithm"""
import logging
+import os
import numpy as np
from scipy import stats
from .tuner import Tuner
@@ -44,13 +45,15 @@ class DropletTuner(Tuner):
for _, v in self.space.space_map.items():
self.dims.append(len(v))
+ if len(self.dims) == 0:
+ self.dims.append(1)
# start position
start_position = [0] * len(self.dims) if start_position is None else
start_position
self.best_choice = (-1, [0] * len(self.dims), [99999])
self.visited = set([self.space.knob2point(start_position)])
- self.execution, self.total_execution, self.batch = 1, max(self.dims),
16
- self.pvalue, self.step = pvalue, 1
+ self.execution, self.total_execution, self.pvalue = 1, max(self.dims),
pvalue
+ self.step, self.iter, self.batch = 1, 0, max(16, os.cpu_count())
self.next = [(self.space.knob2point(start_position), start_position)]
def num_to_bin(self, value, factor=1):
@@ -100,7 +103,7 @@ class DropletTuner(Tuner):
self.next += self.next_pos(self.search_space(self.execution))
def update(self, inputs, results):
- found_best_pos = False
+ found_best_pos, count_valids = False, 0
for i, (_, res) in enumerate(zip(inputs, results)):
try:
if np.mean(self.best_choice[2]) > np.mean(res.costs) and
self.p_value(
@@ -108,6 +111,7 @@ class DropletTuner(Tuner):
):
self.best_choice = (self.next[i][0], self.next[i][1],
res.costs)
found_best_pos = True
+ count_valids += 1
except TypeError:
LOGGER.debug("Solution is not valid")
continue
@@ -119,6 +123,13 @@ class DropletTuner(Tuner):
self.next += self.next_pos(self.search_space())
self.execution = 1
self.speculation()
+ # stop, because all neighborhoods are invalid.
+ if count_valids == 0 and self.iter > 3:
+ self.next = []
+ LOGGER.warning(
+ f"Warning: early termination due to an all-invalid
neighborhood \
+ after {self.iter} iterations"
+ )
def has_next(self):
return len(self.next) > 0
