From bd407ac4dc4d1f4b4bb79370fe26da30ca54d29a Mon Sep 17 00:00:00 2001
From: D-X-Y <280835372@qq.com>
Date: Wed, 19 May 2021 07:23:50 +0000
Subject: [PATCH] Refine lib -> xautodl
---
docs/CVPR-2019-GDAS.md | 2 +-
docs/ICCV-2019-SETN.md | 2 +-
xautodl/utils/flop_benchmark.py | 4 ++--
3 files changed, 4 insertions(+), 4 deletions(-)
diff --git a/docs/CVPR-2019-GDAS.md b/docs/CVPR-2019-GDAS.md
index 5d43889..0464434 100644
--- a/docs/CVPR-2019-GDAS.md
+++ b/docs/CVPR-2019-GDAS.md
@@ -1,6 +1,6 @@
# [Searching for A Robust Neural Architecture in Four GPU Hours](https://arxiv.org/abs/1910.04465)
-
+
Searching for A Robust Neural Architecture in Four GPU Hours is accepted at CVPR 2019.
In this paper, we proposed a Gradient-based searching algorithm using Differentiable Architecture Sampling (GDAS).
diff --git a/docs/ICCV-2019-SETN.md b/docs/ICCV-2019-SETN.md
index c818fd5..13c5fa1 100644
--- a/docs/ICCV-2019-SETN.md
+++ b/docs/ICCV-2019-SETN.md
@@ -1,6 +1,6 @@
# [One-Shot Neural Architecture Search via Self-Evaluated Template Network](https://arxiv.org/abs/1910.05733)
-
+
Highlight: we equip one-shot NAS with an architecture sampler and train network weights using uniformly sampling.
diff --git a/xautodl/utils/flop_benchmark.py b/xautodl/utils/flop_benchmark.py
index 32dce0a..e9141f7 100644
--- a/xautodl/utils/flop_benchmark.py
+++ b/xautodl/utils/flop_benchmark.py
@@ -10,9 +10,9 @@ def count_parameters_in_MB(model):
def count_parameters(model_or_parameters, unit="mb"):
if isinstance(model_or_parameters, nn.Module):
counts = sum(np.prod(v.size()) for v in model_or_parameters.parameters())
- elif isinstance(models_or_parameters, nn.Parameter):
+ elif isinstance(model_or_parameters, nn.Parameter):
counts = models_or_parameters.numel()
- elif isinstance(models_or_parameters, (list, tuple)):
+ elif isinstance(model_or_parameters, (list, tuple)):
counts = sum(count_parameters(x, None) for x in models_or_parameters)
else:
counts = sum(np.prod(v.size()) for v in model_or_parameters)