fix tests

gallery/how_to/tune_with_autotvm/tune_relay_arm.py

@@ -302,7 +302,7 @@ def tune_tasks(
                 tuner_obj.load_history(autotvm.record.load_from_file(tmp_log_file))
 
         # process tuning
-        tsk_trial = min(n_trial, len(tsk.config_space))
+        tsk_trial = min(n_trial, tsk.config_space.filtered_length)
         tuner_obj.tune(
             n_trial=tsk_trial,
             early_stopping=early_stopping,

gallery/how_to/tune_with_autotvm/tune_relay_cuda.py

@@ -204,7 +204,7 @@ def tune_tasks(
                 tuner_obj.load_history(autotvm.record.load_from_file(tmp_log_file))
 
         # do tuning
-        tsk_trial = min(n_trial, len(tsk.config_space))
+        tsk_trial = min(n_trial, tsk.config_space.filtered_length)
         tuner_obj.tune(
             n_trial=tsk_trial,
             early_stopping=early_stopping,

gallery/how_to/tune_with_autotvm/tune_relay_mobile_gpu.py

@@ -293,7 +293,7 @@ def tune_tasks(
                 tuner_obj.load_history(autotvm.record.load_from_file(tmp_log_file))
 
         # do tuning
-        tsk_trial = min(n_trial, len(tsk.config_space))
+        tsk_trial = min(n_trial, tsk.config_space.filtered_length)
         tuner_obj.tune(
             n_trial=tsk_trial,
             early_stopping=early_stopping,

gallery/how_to/tune_with_autotvm/tune_relay_x86.py

@@ -171,7 +171,7 @@ def tune_kernels(
             raise ValueError("Invalid tuner: " + tuner)
 
         # do tuning
-        n_trial = len(task.config_space)
+        n_trial = task.config_space.filtered_length
         tuner_obj.tune(
             n_trial=n_trial,
             early_stopping=early_stopping,

gallery/tutorial/autotvm_relay_x86.py

@@ -362,7 +362,7 @@
     prefix = "[Task %2d/%2d] " % (i + 1, len(tasks))
     tuner_obj = XGBTuner(task, loss_type="rank")
     tuner_obj.tune(
-        n_trial=min(tuning_option["trials"], len(task.config_space)),
+        n_trial=min(tuning_option["trials"], task.config_space.filtered_length),
         early_stopping=tuning_option["early_stopping"],
         measure_option=tuning_option["measure_option"],
         callbacks=[

python/tvm/autotvm/tuner/index_based_tuner.py

@@ -96,6 +96,7 @@ def __init__(self, task, range_idx=None):
         # we can generate non-repetitive random indices.
         self.rand_state = {}
         self.rand_max = self.range_length
+        self.visited = []
 
     def next_batch(self, batch_size):
         ret = []
@@ -110,6 +111,7 @@ def next_batch(self, batch_size):
             if cfg:
                 ret.append(cfg)
                 self.counter += 1
+                self.visited.append(index)
 
             # Update the direct index map.
             self.rand_state[index_] = self.rand_state.get(self.rand_max, self.rand_max)

python/tvm/contrib/torch/pytorch_tvm.py

@@ -65,7 +65,7 @@ def tune_tasks(
                 tuner_obj.load_history(autotvm.record.load_from_file(tmp_log_file))
 
         # do tuning
-        tsk_trial = min(n_trial, len(tsk.config_space))
+        tsk_trial = min(n_trial, tsk.config_space.filtered_length)
         tuner_obj.tune(
             n_trial=tsk_trial,
             early_stopping=early_stopping,

python/tvm/driver/tvmc/autotuner.py

@@ -692,7 +692,7 @@ def tune_tasks(
             logging.info("loaded history in %.2f sec(s)", time.time() - start_time)
 
         tuner_obj.tune(
-            n_trial=min(trials, len(tsk.config_space)),
+            n_trial=min(trials, tsk.config_space.filtered_length),
             early_stopping=early_stopping,
             measure_option=measure_option,
             callbacks=[

python/tvm/testing/autotvm.py

@@ -107,6 +107,8 @@ def get_sample_records(n):
 
     inps, ress = [], []
     for i in range(n):
-        inps.append(MeasureInput(target, tsk, tsk.config_space.get(i % len(tsk.config_space))))
+        inps.append(
+            MeasureInput(target, tsk, tsk.config_space.get(i % tsk.config_space.filtered_length))
+        )
         ress.append(MeasureResult((i + 1,), 0, i, time.time()))
     return list(zip(inps, ress))

tests/python/contrib/test_hexagon/test_autotvm.py

@@ -105,7 +105,7 @@ def tune_tasks(
             if os.path.isfile(tmp_log_file):
                 tuner_obj.load_history(autotvm.record.load_from_file(tmp_log_file))
 
-        tsk_trial = min(n_trial, len(tsk.config_space))
+        tsk_trial = min(n_trial, tsk.config_space.filtered_length)
         tuner_obj.tune(
             n_trial=tsk_trial,
             early_stopping=early_stopping,

tests/python/relay/collage/demo_collage_partitioner.py

@@ -185,7 +185,7 @@ def tune_autotvm_tasks(tasks, log_filename):
             tuner_obj.load_history(tvm.autotvm.record.load_from_file(tmp_log_filename))
 
         # do tuning
-        n_trial = min(AUTOTVM_NUM_TRIALS, len(task.config_space))
+        n_trial = min(AUTOTVM_NUM_TRIALS, task.config_space.filtered_length)
         tuner_obj.tune(
             n_trial=n_trial,
             early_stopping=AUTOTVM_EARLY_STOPPING,

tests/python/unittest/test_autotvm_index_tuner.py

@@ -30,7 +30,7 @@ def test_gridsearch_tuner():
 
     # When no range index, range_length should be the length of config space
     tuner = autotvm.tuner.GridSearchTuner(task)
-    assert tuner.range_length == len(task.config_space)
+    assert tuner.range_length == task.config_space.total_length
     assert tuner.index_offset == 0
 
     # With range index, range_length should be the length of the specified range
@@ -70,9 +70,7 @@ def test_random_tuner():
     tuner.tune(n_trial=8, measure_option=measure_option)
     assert tuner.counter == 8
     assert not tuner.has_next()
-    visited = set()
     for idx in tuner.visited:
-        assert idx not in visited
         assert 8 <= idx <= 15
 
 

tests/python/unittest/test_autotvm_space.py

@@ -42,7 +42,7 @@ def test_split():
     cfg = ConfigSpace()
 
     gemm_func(cfg, 128)
-    assert len(cfg) == 64
+    assert cfg.total_length == 64
     assert len(cfg.space_map["tile_y"]) == 8
 
     # test policy

vta/scripts/tune_conv2d.py

@@ -166,11 +166,11 @@ def conv2d(N, CI, H, W, CO, KH, KW, strides, padding, dilation):
         # Run Tuner
         tuner = autotvm.tuner.RandomTuner(task)
         tuner.tune(
-            n_trial=len(task.config_space),
+            n_trial=task.config_space.filtered_length,
             early_stopping=None,
             measure_option=measure_option,
             callbacks=[
-                autotvm.callback.progress_bar(len(task.config_space), prefix=prefix),
+                autotvm.callback.progress_bar(task.config_space.filtered_length, prefix=prefix),
                 autotvm.callback.log_to_file(tmp_log_file),
             ],
         )

vta/scripts/tune_conv2d_transpose.py

@@ -157,11 +157,11 @@ def conv2d_transpose(N, CI, H, W, CO, KH, KW, strides, padding, opadding):
         # Run Tuner
         tuner = autotvm.tuner.RandomTuner(task)
         tuner.tune(
-            n_trial=len(task.config_space),
+            n_trial=task.config_space.filtered_length,
             early_stopping=None,
             measure_option=measure_option,
             callbacks=[
-                autotvm.callback.progress_bar(len(task.config_space), prefix=prefix),
+                autotvm.callback.progress_bar(task.config_space.filtered_length, prefix=prefix),
                 autotvm.callback.log_to_file(tmp_log_file),
             ],
         )

vta/scripts/tune_dense.py

@@ -123,11 +123,11 @@ def dense(N, CI, CO):
         # Run Tuner
         tuner = autotvm.tuner.RandomTuner(task)
         tuner.tune(
-            n_trial=len(task.config_space),
+            n_trial=task.config_space.filtered_length,
             early_stopping=None,
             measure_option=measure_option,
             callbacks=[
-                autotvm.callback.progress_bar(len(task.config_space), prefix=prefix),
+                autotvm.callback.progress_bar(task.config_space.filtered_length, prefix=prefix),
                 autotvm.callback.log_to_file(tmp_log_file),
             ],
         )

vta/scripts/tune_group_conv2d.py

@@ -161,11 +161,11 @@ def group_conv2d(N, CI, H, W, CO, KH, KW, strides, padding, dilation, group):
         # Run Tuner
         tuner = autotvm.tuner.RandomTuner(task)
         tuner.tune(
-            n_trial=len(task.config_space),
+            n_trial=task.config_space.filtered_length,
             early_stopping=None,
             measure_option=measure_option,
             callbacks=[
-                autotvm.callback.progress_bar(len(task.config_space), prefix=prefix),
+                autotvm.callback.progress_bar(task.config_space.filtered_length, prefix=prefix),
                 autotvm.callback.log_to_file(tmp_log_file),
             ],
         )

vta/scripts/tune_resnet.py

@@ -199,7 +199,7 @@ def tune_tasks(
                 tuner_obj.load_history(autotvm.record.load_from_file(tmp_log_file))
 
         # do tuning
-        n_trial_ = min(n_trial, len(tsk.config_space))
+        n_trial_ = min(n_trial, tsk.config_space.filtered_length)
         tuner_obj.tune(
             n_trial_,
             early_stopping=early_stopping,

vta/tutorials/autotvm/tune_alu_vta.py

@@ -197,7 +197,7 @@ def tune_tasks(
                 tuner_obj.load_history(autotvm.record.load_from_file(tmp_log_file))
 
         # do tuning
-        tsk_trial = min(n_trial, len(tsk.config_space))
+        tsk_trial = min(n_trial, tsk.config_space.filtered_length)
         tuner_obj.tune(
             n_trial=tsk_trial,
             early_stopping=early_stopping,

vta/tutorials/autotvm/tune_relay_vta.py

@@ -282,7 +282,7 @@ def tune_tasks(
                 tuner_obj.load_history(autotvm.record.load_from_file(tmp_log_file))
 
         # do tuning
-        tsk_trial = min(n_trial, len(tsk.config_space))
+        tsk_trial = min(n_trial, tsk.config_space.filtered_length)
         tuner_obj.tune(
             n_trial=tsk_trial,
             early_stopping=early_stopping,