From 7193c526fe923fe959e646d6043d98e1fb0a43e6 Mon Sep 17 00:00:00 2001
From: Neta Zmora <31280975+nzmora@users.noreply.github.com>
Date: Sun, 30 Sep 2018 01:23:45 +0300
Subject: [PATCH] test_summarygraph.py: remove dead code
Somehow 4 copies of the same test were pasted into this file: removed 3 instances.
---
tests/test_summarygraph.py | 36 ------------------------------------
1 file changed, 36 deletions(-)
diff --git a/tests/test_summarygraph.py b/tests/test_summarygraph.py
index b5bf6a8..6fcda7e 100755
--- a/tests/test_summarygraph.py
+++ b/tests/test_summarygraph.py
@@ -143,42 +143,6 @@ def test_simplenet():
assert len(preds) == 1
-def test_simplenet():
- g = create_graph('cifar10', 'simplenet_cifar')
- assert g is not None
- preds = g.predecessors_f(normalize_module_name('module.conv1'), 'Conv')
- logging.debug("[simplenet_cifar]: preds of module.conv1 = {}".format(preds))
- assert len(preds) == 0
-
- preds = g.predecessors_f(normalize_module_name('module.conv2'), 'Conv')
- logging.debug("[simplenet_cifar]: preds of module.conv2 = {}".format(preds))
- assert len(preds) == 1
-
-
-def test_simplenet():
- g = create_graph('cifar10', 'simplenet_cifar')
- assert g is not None
- preds = g.predecessors_f(normalize_module_name('module.conv1'), 'Conv')
- logging.debug("[simplenet_cifar]: preds of module.conv1 = {}".format(preds))
- assert len(preds) == 0
-
- preds = g.predecessors_f(normalize_module_name('module.conv2'), 'Conv')
- logging.debug("[simplenet_cifar]: preds of module.conv2 = {}".format(preds))
- assert len(preds) == 1
-
-
-def test_simplenet():
- g = create_graph('cifar10', 'simplenet_cifar')
- assert g is not None
- preds = g.predecessors_f(normalize_module_name('module.conv1'), 'Conv')
- logging.debug("[simplenet_cifar]: preds of module.conv1 = {}".format(preds))
- assert len(preds) == 0
-
- preds = g.predecessors_f(normalize_module_name('module.conv2'), 'Conv')
- logging.debug("[simplenet_cifar]: preds of module.conv2 = {}".format(preds))
- assert len(preds) == 1
-
-
def name_test(dataset, arch):
model = create_model(False, dataset, arch, parallel=False)
modelp = create_model(False, dataset, arch, parallel=True)
--
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