From c5e2cfc441093c2999b6ae6527ec4042891e74db Mon Sep 17 00:00:00 2001
From: Yaman Umuroglu <maltanar@gmail.com>
Date: Mon, 11 May 2020 22:47:43 +0100
Subject: [PATCH] [Analysis] rename to nodes_topologically_sorted
---
src/finn/analysis/topology.py | 9 +++--
tests/analysis/test_topology_checks.py | 52 +++++++++++++-------------
2 files changed, 31 insertions(+), 30 deletions(-)
diff --git a/src/finn/analysis/topology.py b/src/finn/analysis/topology.py
index 3973c8d26..acdb8ed7f 100644
--- a/src/finn/analysis/topology.py
+++ b/src/finn/analysis/topology.py
@@ -81,10 +81,11 @@ def node_inputs_in_expected_order(model):
return {"node_inputs_in_expected_order": all_OK}
-def nodes_in_expected_order(model):
- """Verifies that the graph is topologically sorted.
+def nodes_topologically_sorted(model):
+ """Verifies that graph.node is topologically sorted. This is required by the
+ ONNX specification.
- Returns {"nodes_in_expected_order": Bool}."""
+ Returns {"nodes_topologically_sorted": Bool}."""
# get successors of every node and check that
# successor index > current node index
@@ -100,4 +101,4 @@ def nodes_in_expected_order(model):
if index_n > index_suc:
all_OK = False
- return {"nodes_in_expected_order": all_OK}
+ return {"nodes_topologically_sorted": all_OK}
diff --git a/tests/analysis/test_topology_checks.py b/tests/analysis/test_topology_checks.py
index 7c9a131f6..7f7f800da 100644
--- a/tests/analysis/test_topology_checks.py
+++ b/tests/analysis/test_topology_checks.py
@@ -92,45 +92,45 @@ def test_node_inputs_in_expected_order():
assert ret["node_inputs_in_expected_order"] is False
-def test_nodes_in_expected_order():
- # test analysis pass (nodes_in_expected_order) with different models
+def test_nodes_topologically_sorted():
+ # test analysis pass (nodes_topologically_sorted) with different models
# test with data/onnx/finn-hls-model/tfc_w1_a1_after_conv_to_hls.onnx
raw_m = get_data(
"finn", "data/onnx/finn-hls-model/tfc_w1_a1_after_conv_to_hls.onnx"
)
model = ModelWrapper(raw_m)
- ret = model.analysis(ta.nodes_in_expected_order)
- assert ret["nodes_in_expected_order"] is True
+ ret = model.analysis(ta.nodes_topologically_sorted)
+ assert ret["nodes_topologically_sorted"] is True
# remove first node and add it at the end
graph = model.graph
first_node = graph.node[0]
graph.node.remove(first_node)
graph.node.append(first_node)
- ret = model.analysis(ta.nodes_in_expected_order)
- assert ret["nodes_in_expected_order"] is False
+ ret = model.analysis(ta.nodes_topologically_sorted)
+ assert ret["nodes_topologically_sorted"] is False
# test with data/onnx/mnist-conv/model.onnx
raw_m = get_data("finn", "data/onnx/mnist-conv/model.onnx")
model = ModelWrapper(raw_m)
- ret = model.analysis(ta.nodes_in_expected_order)
- assert ret["nodes_in_expected_order"] is True
+ ret = model.analysis(ta.nodes_topologically_sorted)
+ assert ret["nodes_topologically_sorted"] is True
# remove first node and add it at the end
graph = model.graph
first_node = graph.node[0]
graph.node.remove(first_node)
graph.node.append(first_node)
- ret = model.analysis(ta.nodes_in_expected_order)
- assert ret["nodes_in_expected_order"] is False
+ ret = model.analysis(ta.nodes_topologically_sorted)
+ assert ret["nodes_topologically_sorted"] is False
# test with manually created small network
- Neg_node = oh.make_node("Neg", inputs=["in1"], outputs=["neg1"],)
- Round_node = oh.make_node("Round", inputs=["neg1"], outputs=["round1"],)
+ Neg_node = oh.make_node("Neg", inputs=["in1"], outputs=["neg1"])
+ Round_node = oh.make_node("Round", inputs=["neg1"], outputs=["round1"])
- Ceil_node = oh.make_node("Ceil", inputs=["neg1"], outputs=["ceil1"],)
- Add_node = oh.make_node("Add", inputs=["round1", "ceil1"], outputs=["out1"],)
+ Ceil_node = oh.make_node("Ceil", inputs=["neg1"], outputs=["ceil1"])
+ Add_node = oh.make_node("Add", inputs=["round1", "ceil1"], outputs=["out1"])
in1 = oh.make_tensor_value_info("in1", TensorProto.FLOAT, [4, 4])
out1 = oh.make_tensor_value_info("out1", TensorProto.FLOAT, [4, 4])
@@ -150,8 +150,8 @@ def test_nodes_in_expected_order():
onnx_model = oh.make_model(graph, producer_name="simple-model")
model = ModelWrapper(onnx_model)
- ret = model.analysis(ta.nodes_in_expected_order)
- assert ret["nodes_in_expected_order"] is True
+ ret = model.analysis(ta.nodes_topologically_sorted)
+ assert ret["nodes_topologically_sorted"] is True
# create same graph but with "wrong" node order
graph = oh.make_graph(
@@ -169,22 +169,22 @@ def test_nodes_in_expected_order():
onnx_model = oh.make_model(graph, producer_name="simple-model")
model = ModelWrapper(onnx_model)
- ret = model.analysis(ta.nodes_in_expected_order)
- assert ret["nodes_in_expected_order"] is False
+ ret = model.analysis(ta.nodes_topologically_sorted)
+ assert ret["nodes_topologically_sorted"] is False
# test with data/onnx/finn-hls-model/finn-hls-onnx-model.onnx
raw_m = get_data("finn", "data/onnx/finn-hls-model/finn-hls-onnx-model.onnx")
model = ModelWrapper(raw_m)
- ret = model.analysis(ta.nodes_in_expected_order)
- assert ret["nodes_in_expected_order"] is True
+ ret = model.analysis(ta.nodes_topologically_sorted)
+ assert ret["nodes_topologically_sorted"] is True
# remove first node and add it at the end
graph = model.graph
first_node = graph.node[0]
graph.node.remove(first_node)
graph.node.append(first_node)
- ret = model.analysis(ta.nodes_in_expected_order)
- assert ret["nodes_in_expected_order"] is False
+ ret = model.analysis(ta.nodes_topologically_sorted)
+ assert ret["nodes_topologically_sorted"] is False
# test with cnv_w1a1
build_dir = "/tmp/" + os.environ["FINN_INST_NAME"]
@@ -193,13 +193,13 @@ def test_nodes_in_expected_order():
cnv, (1, 3, 32, 32), build_dir + "/end2end_cnv_w1a1_export.onnx"
)
model = ModelWrapper(build_dir + "/end2end_cnv_w1a1_export.onnx")
- ret = model.analysis(ta.nodes_in_expected_order)
- assert ret["nodes_in_expected_order"] is True
+ ret = model.analysis(ta.nodes_topologically_sorted)
+ assert ret["nodes_topologically_sorted"] is True
# remove first node and add it at the end
graph = model.graph
first_node = graph.node[0]
graph.node.remove(first_node)
graph.node.append(first_node)
- ret = model.analysis(ta.nodes_in_expected_order)
- assert ret["nodes_in_expected_order"] is False
+ ret = model.analysis(ta.nodes_topologically_sorted)
+ assert ret["nodes_topologically_sorted"] is False
--
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