Skip to content

Integration tests based on examples #23

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
Feb 4, 2019
Merged

Integration tests based on examples #23

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
61 changes: 60 additions & 1 deletion tests/integration_tests/test_experiment.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -49,7 +49,6 @@ def generate_data(input_features, output_features, filename='test_csv.csv'):
data = [next(df) for _ in range(1000)]

dataframe = pd.DataFrame(data[1:], columns=data[0])

dataframe.to_csv(filename, index=False)

return filename
Expand Down Expand Up @@ -401,6 +400,66 @@ def test_experiment_timeseries(csv_filename):
output_features, data_csv=rel_path)


def test_movie_rating_prediction(csv_filename):
input_features= '[{name: year, type: numerical, min: 1900, max: 2030},' \
'{name: duration, type: numerical, min: 3600, max: 12000},'\
'{name: nominations, type: numerical, min: 0, max: 25},'\
'{name: categories, type: set, max_len: 5, vocab_size: 10}]'
output_features = "[ {name: rating, type: numerical, min: 1, max: 10}]"

# Generate test data
rel_path = generate_data(input_features, output_features, csv_filename)
run_experiment(input_features, output_features, data_csv=rel_path)


def test_example_with_set_output(csv_filename):
image_dest_folder = os.path.join(os.getcwd(), 'generated_images')
input_features_template = Template(
'[{name: image_path, type: image, encoder: ${encoder}, width: 15, '
'height: 15, num_channels: 3, resnet_size: 8, destination_folder: '
'${folder}}]')

output_features = "[ {name: tags, type: set, max_len: 5, vocab_size: 10}]"

for encoder in ['resnet', 'stacked_cnn']:
input_features = input_features_template.substitute(
encoder=encoder,
folder=image_dest_folder)

rel_path = generate_data(input_features, output_features, csv_filename)
run_experiment(input_features, output_features, rel_path)

# Delete the temporary data created
all_images = glob.glob(os.path.join(image_dest_folder, '*.jpg'))
for im in all_images:
os.remove(im)

os.rmdir(image_dest_folder)


def test_visual_question_answering(csv_filename):
image_dest_folder = os.path.join(os.getcwd(), 'generated_images')
input_features= Template(
'[{name: image_path, type: image, encoder: stacked_cnn, width: 15, '
'height: 15, num_channels: 3, resnet_size: 8, destination_folder: '
'${folder}}, {name: question, type: text, vocab_size: 20, max_len: 10,'
'encoder: parallel_cnn, level: word}]').substitute(
folder=image_dest_folder)

output_features = "[ {name: answer, type: sequence, max_len: 5, " \
"vocab_size: 10, decoder: generator, cell_type: lstm}]"

rel_path = generate_data(input_features, output_features, csv_filename)
run_experiment(input_features, output_features, rel_path)

# Delete the temporary data created
all_images = glob.glob(os.path.join(image_dest_folder, '*.jpg'))
for im in all_images:
os.remove(im)

os.rmdir(image_dest_folder)


if __name__ == '__main__':
"""
To run tests individually, run:
Expand Down