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Add assert statement to check model structure on model_visualization_test #20208

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Sep 5, 2024
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Add assert statement to check model structure on model_visualization_test #20208

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c651c9e
Add assert statement to check model structure
shashaka Sep 4, 2024
08bce13
Apply pytest on model_visualization_test
shashaka Sep 5, 2024
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141 changes: 109 additions & 32 deletions integration_tests/model_visualization_test.py
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Original file line number Diff line number Diff line change
@@ -1,21 +1,61 @@
import re
from pathlib import Path

import keras
from keras.src.utils import model_to_dot
from keras.src.utils import plot_model


def assert_file_exists(path):
assert Path(path).is_file(), "File does not exist"


def parse_text_from_html(html):
pattern = r"<font[^>]*>(.*?)</font>"
matches = re.findall(pattern, html)

for match in matches:
clean_text = re.sub(r"<[^>]*>", "", match)
return clean_text
return ""


def get_node_text(node):
attributes = node.get_attributes()

if "label" in attributes:
html = node.get_attributes()["label"]
return parse_text_from_html(html)
else:
return None


def get_edge_dict(dot):
node_dict = dict()
for node in dot.get_nodes():
node_dict[node.get_name()] = get_node_text(node)

edge_dict = dict()
for edge in dot.get_edges():
edge_dict[node_dict[edge.get_source()]] = node_dict[
edge.get_destination()
]

return edge_dict


def test_plot_sequential_model():
model = keras.Sequential(
[
keras.Input((3,)),
keras.layers.Dense(4, activation="relu"),
keras.layers.Dense(1, activation="sigmoid"),
keras.Input((3,), name="input"),
keras.layers.Dense(4, activation="relu", name="dense"),
keras.layers.Dense(1, activation="sigmoid", name="dense_1"),
]
)

edge_dict = get_edge_dict(model_to_dot(model))
assert edge_dict["dense (Dense)"] == "dense_1 (Dense)"

file_name = "sequential.png"
plot_model(model, file_name)
assert_file_exists(file_name)
Expand Down Expand Up @@ -90,23 +130,39 @@ def test_plot_sequential_model():


def test_plot_functional_model():
inputs = keras.Input((3,))
x = keras.layers.Dense(4, activation="relu", trainable=False)(inputs)
inputs = keras.Input((3,), name="input")
x = keras.layers.Dense(4, activation="relu", trainable=False, name="dense")(
inputs
)
residual = x
x = keras.layers.Dense(4, activation="relu")(x)
x = keras.layers.Dense(4, activation="relu")(x)
x = keras.layers.Dense(4, activation="relu")(x)
x = keras.layers.Dense(4, activation="relu", name="dense_1")(x)
x = keras.layers.Dense(4, activation="relu", name="dense_2")(x)
x = keras.layers.Dense(4, activation="relu", name="dense_3")(x)
x += residual
residual = x
x = keras.layers.Dense(4, activation="relu")(x)
x = keras.layers.Dense(4, activation="relu")(x)
x = keras.layers.Dense(4, activation="relu")(x)
x = keras.layers.Dense(4, activation="relu", name="dense_4")(x)
x = keras.layers.Dense(4, activation="relu", name="dense_5")(x)
x = keras.layers.Dense(4, activation="relu", name="dense_6")(x)
x += residual
x = keras.layers.Dropout(0.5)(x)
outputs = keras.layers.Dense(1, activation="sigmoid")(x)
x = keras.layers.Dropout(0.5, name="dropout")(x)
outputs = keras.layers.Dense(1, activation="sigmoid", name="dense_7")(x)

model = keras.Model(inputs, outputs)

edge_dict = get_edge_dict(model_to_dot(model))

assert edge_dict["input (InputLayer)"] == "dense (Dense)"
assert edge_dict["dense (Dense)"] == "add (Add)"
assert edge_dict["dense_1 (Dense)"] == "dense_2 (Dense)"
assert edge_dict["dense_2 (Dense)"] == "dense_3 (Dense)"
assert edge_dict["dense_3 (Dense)"] == "add (Add)"
assert edge_dict["add (Add)"] == "add_1 (Add)"
assert edge_dict["dense_4 (Dense)"] == "dense_5 (Dense)"
assert edge_dict["dense_5 (Dense)"] == "dense_6 (Dense)"
assert edge_dict["dense_6 (Dense)"] == "add_1 (Add)"
assert edge_dict["add_1 (Add)"] == "dropout (Dropout)"
assert edge_dict["dropout (Dropout)"] == "dense_7 (Dense)"

file_name = "functional.png"
plot_model(model, file_name)
assert_file_exists(file_name)
Expand Down Expand Up @@ -291,26 +347,40 @@ def call(self, x):


def test_plot_nested_functional_model():
inputs = keras.Input((3,))
x = keras.layers.Dense(4, activation="relu")(inputs)
x = keras.layers.Dense(4, activation="relu")(x)
outputs = keras.layers.Dense(3, activation="relu")(x)
inner_model = keras.Model(inputs, outputs)

inputs = keras.Input((3,))
x = keras.layers.Dense(3, activation="relu", trainable=False)(inputs)
inputs = keras.Input((3,), name="input")
x = keras.layers.Dense(4, activation="relu", name="dense")(inputs)
x = keras.layers.Dense(4, activation="relu", name="dense_1")(x)
outputs = keras.layers.Dense(3, activation="relu", name="dense_2")(x)
inner_model = keras.Model(inputs, outputs, name="inner_model")

inputs = keras.Input((3,), name="input_1")
x = keras.layers.Dense(
3, activation="relu", trainable=False, name="dense_3"
)(inputs)
residual = x
x = inner_model(x)
x += residual
x = keras.layers.Add(name="add")([x, residual])
residual = x
x = keras.layers.Dense(4, activation="relu")(x)
x = keras.layers.Dense(4, activation="relu")(x)
x = keras.layers.Dense(3, activation="relu")(x)
x += residual
x = keras.layers.Dropout(0.5)(x)
outputs = keras.layers.Dense(1, activation="sigmoid")(x)
x = keras.layers.Dense(4, activation="relu", name="dense_4")(x)
x = keras.layers.Dense(4, activation="relu", name="dense_5")(x)
x = keras.layers.Dense(3, activation="relu", name="dense_6")(x)
x = keras.layers.Add(name="add_1")([x, residual])
x = keras.layers.Dropout(0.5, name="dropout")(x)
outputs = keras.layers.Dense(1, activation="sigmoid", name="dense_7")(x)
model = keras.Model(inputs, outputs)

edge_dict = get_edge_dict(model_to_dot(model))

assert edge_dict["input_1 (InputLayer)"] == "dense_3 (Dense)"
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Such statements should be made via self.assertEqual

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I updated the source code as your advice.
Additionally, I removed the main statement also, since, I think it can be replaced by just running ModelVisualizationTest class by pytest.

assert edge_dict["dense_3 (Dense)"] == "add (Add)"
assert edge_dict["inner_model (Functional)"] == "add (Add)"
assert edge_dict["add (Add)"] == "add_1 (Add)"
assert edge_dict["dense_4 (Dense)"] == "dense_5 (Dense)"
assert edge_dict["dense_5 (Dense)"] == "dense_6 (Dense)"
assert edge_dict["dense_6 (Dense)"] == "add_1 (Add)"
assert edge_dict["add_1 (Add)"] == "dropout (Dropout)"
assert edge_dict["dropout (Dropout)"] == "dense_7 (Dense)"

file_name = "nested-functional.png"
plot_model(model, file_name, expand_nested=True)
assert_file_exists(file_name)
Expand Down Expand Up @@ -415,15 +485,22 @@ class ConcatLayer(keras.Layer):
def call(self, xs):
return keras.ops.concatenate(xs, axis=1)

inputs = keras.Input((2,))
inputs = keras.Input((2,), name="input")
a, b = SplitLayer()(inputs)

a = keras.layers.Dense(2)(a)
b = keras.layers.Dense(2)(b)
a = keras.layers.Dense(2, name="dense")(a)
b = keras.layers.Dense(2, name="dense_1")(b)

outputs = ConcatLayer()([a, b])
outputs = ConcatLayer(name="concat_layer")([a, b])
model = keras.Model(inputs, outputs)

edge_dict = get_edge_dict(model_to_dot(model))

assert edge_dict["input (InputLayer)"] == "split_layer (SplitLayer)"
assert edge_dict["split_layer (SplitLayer)"] == "dense_1 (Dense)"
assert edge_dict["dense (Dense)"] == "concat_layer (ConcatLayer)"
assert edge_dict["dense_1 (Dense)"] == "concat_layer (ConcatLayer)"

file_name = "split-functional.png"
plot_model(model, file_name, expand_nested=True)
assert_file_exists(file_name)
Expand Down