gradio/test/test_blocks.py

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import asyncio
import random
import time
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import unittest
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import pytest
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import gradio as gr
from gradio.routes import PredictBody
from gradio.test_data.blocks_configs import XRAY_CONFIG
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pytest_plugins = ("pytest_asyncio",)
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class TestBlocks(unittest.TestCase):
maxDiff = None
def test_xray(self):
def fake_func():
return "Hello There"
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xray_model = lambda diseases, img: {
disease: random.random() for disease in diseases
}
ct_model = lambda diseases, img: {disease: 0.1 for disease in diseases}
with gr.Blocks() as demo:
gr.Markdown(
"""
# Detect Disease From Scan
With this model you can lorem ipsum
- ipsum 1
- ipsum 2
"""
)
disease = gr.CheckboxGroup(
choices=["Covid", "Malaria", "Lung Cancer"], label="Disease to Scan For"
)
with gr.Tabs():
with gr.TabItem("X-ray"):
with gr.Row():
xray_scan = gr.Image()
xray_results = gr.JSON()
xray_run = gr.Button("Run")
xray_run.click(
xray_model, inputs=[disease, xray_scan], outputs=xray_results
)
with gr.TabItem("CT Scan"):
with gr.Row():
ct_scan = gr.Image()
ct_results = gr.JSON()
ct_run = gr.Button("Run")
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ct_run.click(
ct_model, inputs=[disease, ct_scan], outputs=ct_results
)
textbox = gr.Textbox()
demo.load(fake_func, [], [textbox])
config = demo.get_config_file()
config.pop("version") # remove version key
self.assertDictEqual(XRAY_CONFIG, config)
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@pytest.mark.asyncio
async def test_async_function(self):
async def wait():
await asyncio.sleep(0.01)
return True
with gr.Blocks() as demo:
text = gr.Textbox()
button = gr.Button()
button.click(wait, [text], [text])
body = PredictBody(data=1, fn_index=0)
start = time.time()
result = await demo.process_api(body)
end = time.time()
difference = end - start
assert difference >= 0.01
assert result
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if __name__ == "__main__":
unittest.main()