From a95a29828d0ecfeaef4d045de35351b4a9aa9bb6 Mon Sep 17 00:00:00 2001
From: Yifan Zhao <yifanz16@illinois.edu>
Date: Sat, 23 Jan 2021 06:36:53 -0600
Subject: [PATCH] Default model-less performance is given by measuring time
---
predtuner/torchapp.py | 11 +++++++++--
1 file changed, 9 insertions(+), 2 deletions(-)
diff --git a/predtuner/torchapp.py b/predtuner/torchapp.py
index fbd52b4..cb4a0a7 100644
--- a/predtuner/torchapp.py
+++ b/predtuner/torchapp.py
@@ -123,16 +123,21 @@ class TorchApp(ModeledApp, abc.ABC):
def empirical_measure_qos_perf(
self, with_approxes: KnobsT, is_testset: bool
) -> Tuple[float, float]:
+ from time import time_ns
+
dataloader = self.test_loader if is_testset else self.val_loader
approxed = self._apply_knobs(with_approxes)
qoses = []
+
+ time_begin = time_ns() / (10 ** 9)
for inputs, targets in dataloader:
inputs = move_to_device_recursively(inputs, self.device)
targets = move_to_device_recursively(targets, self.device)
outputs = approxed(inputs)
qoses.append(self.tensor_to_qos(outputs, targets))
+ time_end = time_ns() / (10 ** 9)
qos = self.combine_qos(np.array(qoses))
- return float(qos), 0.0 # float64->float
+ return float(qos), time_end - time_begin # float64->float
def __repr__(self) -> str:
class_name = self.__class__.__name__
@@ -161,7 +166,9 @@ class TorchApp(ModeledApp, abc.ABC):
if last_baseline_knob is None:
last_baseline_knob = k
else:
- raise ValueError(f"Found more than 1 baseline knobs: {last_baseline_knob} and {k}")
+ raise ValueError(
+ f"Found more than 1 baseline knobs: {last_baseline_knob} and {k}"
+ )
if last_baseline_knob is None:
knobs.add(BaselineKnob())
return knobs
--
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