From 0d518aba992e36f7317b6180ec6bb20181a5041d Mon Sep 17 00:00:00 2001
From: Yifan Zhao <yifanz16@illinois.edu>
Date: Thu, 28 Jan 2021 20:36:38 -0600
Subject: [PATCH] Added progress bar support
---
predtuner/torchapp.py | 15 ++++++++++++---
test/test_model_zoo_acc.py | 2 +-
2 files changed, 13 insertions(+), 4 deletions(-)
diff --git a/predtuner/torchapp.py b/predtuner/torchapp.py
index 0e6fc28..4c9618a 100644
--- a/predtuner/torchapp.py
+++ b/predtuner/torchapp.py
@@ -9,8 +9,14 @@ from torch.utils.data.dataloader import DataLoader
from ._logging import PathLike
from .approxapp import ApproxKnob, BaselineKnob, KnobsT
-from .modeledapp import (IPerfModel, IQoSModel, LinearPerfModel, ModeledApp,
- QoSModelP1, QoSModelP2)
+from .modeledapp import (
+ IPerfModel,
+ IQoSModel,
+ LinearPerfModel,
+ ModeledApp,
+ QoSModelP1,
+ QoSModelP2,
+)
from .torchutil import ModuleIndexer, get_summary, move_to_device_recursively
@@ -161,14 +167,17 @@ class TorchApp(ModeledApp, abc.ABC):
@torch.no_grad()
def empirical_measure_qos_perf(
- self, with_approxes: KnobsT, is_test: bool
+ self, with_approxes: KnobsT, is_test: bool, progress: bool = False
) -> Tuple[float, float]:
"""Measure the QoS and performance of Module with given approximation
empirically (i.e., by running the Module on the dataset)."""
from time import time_ns
+ from tqdm import tqdm
dataloader = self.test_loader if is_test else self.tune_loader
+ if progress:
+ dataloader = tqdm(dataloader)
approxed = self._apply_knobs(with_approxes)
qoses = []
diff --git a/test/test_model_zoo_acc.py b/test/test_model_zoo_acc.py
index 55f770d..e402881 100644
--- a/test/test_model_zoo_acc.py
+++ b/test/test_model_zoo_acc.py
@@ -34,5 +34,5 @@ class TestModelZooAcc(unittest.TestCase):
)
tune = DataLoader(dataset, batchsize)
app = TorchApp("", network, tune, tune, get_knobs_from_file(), accuracy)
- qos, _ = app.measure_qos_perf({}, False)
+ qos, _ = app.empirical_measure_qos_perf({}, False, True)
self.assertAlmostEqual(qos, target_acc)
--
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