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https://github.com/gradio-app/gradio.git
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9cefd2e90a
* image-editor-examples * add changeset * add changeset * delete changeset * change to process_example() * add changeset * changes for all components until dataset.py * rename * fix checkboxgroup * format * changes * add changeset * changes * add changeset * radio * add changeset * changes * add changeset * changes * examples * remove print * fix * clean * add changeset * fix tests * fix tests * fix test * fix * add changeset * fix video example * add changeset --------- Co-authored-by: gradio-pr-bot <gradio-pr-bot@users.noreply.github.com>
883 lines
28 KiB
Python
883 lines
28 KiB
Python
import asyncio
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import json
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import os
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import shutil
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import subprocess
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import tempfile
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import time
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from pathlib import Path
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from unittest.mock import patch
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import gradio_client as grc
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import pytest
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from gradio_client import media_data
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from gradio_client import utils as client_utils
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from pydub import AudioSegment
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from starlette.testclient import TestClient
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from tqdm import tqdm
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import gradio as gr
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from gradio import utils
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@patch("gradio.utils.get_cache_folder", return_value=Path(tempfile.mkdtemp()))
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class TestExamples:
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def test_handle_single_input(self, patched_cache_folder):
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examples = gr.Examples(["hello", "hi"], gr.Textbox())
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assert examples.processed_examples == [["hello"], ["hi"]]
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examples = gr.Examples([["hello"]], gr.Textbox())
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assert examples.processed_examples == [["hello"]]
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examples = gr.Examples(["test/test_files/bus.png"], gr.Image())
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assert (
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client_utils.encode_file_to_base64(
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examples.processed_examples[0][0]["path"]
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)
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== media_data.BASE64_IMAGE
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)
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def test_handle_multiple_inputs(self, patched_cache_folder):
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examples = gr.Examples(
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[["hello", "test/test_files/bus.png"]], [gr.Textbox(), gr.Image()]
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)
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assert examples.processed_examples[0][0] == "hello"
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assert (
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client_utils.encode_file_to_base64(
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examples.processed_examples[0][1]["path"]
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)
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== media_data.BASE64_IMAGE
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)
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def test_handle_directory(self, patched_cache_folder):
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examples = gr.Examples("test/test_files/images", gr.Image())
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assert len(examples.processed_examples) == 2
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for row in examples.processed_examples:
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for output in row:
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assert (
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client_utils.encode_file_to_base64(output["path"])
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== media_data.BASE64_IMAGE
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)
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def test_handle_directory_with_log_file(self, patched_cache_folder):
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examples = gr.Examples(
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"test/test_files/images_log", [gr.Image(label="im"), gr.Text()]
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)
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ex = client_utils.traverse(
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examples.processed_examples,
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lambda s: client_utils.encode_file_to_base64(s["path"]),
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lambda x: isinstance(x, dict) and Path(x["path"]).exists(),
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)
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assert ex == [
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[media_data.BASE64_IMAGE, "hello"],
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[media_data.BASE64_IMAGE, "hi"],
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]
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for sample in examples.dataset.samples:
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assert os.path.isabs(sample[0]["path"])
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def test_examples_per_page(self, patched_cache_folder):
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examples = gr.Examples(["hello", "hi"], gr.Textbox(), examples_per_page=2)
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assert examples.dataset.get_config()["samples_per_page"] == 2
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def test_no_preprocessing(self, patched_cache_folder):
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with gr.Blocks():
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image = gr.Image()
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textbox = gr.Textbox()
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examples = gr.Examples(
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examples=["test/test_files/bus.png"],
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inputs=image,
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outputs=textbox,
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fn=lambda x: x["path"],
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cache_examples=True,
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preprocess=False,
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)
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prediction = examples.load_from_cache(0)
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assert (
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client_utils.encode_file_to_base64(prediction[0]) == media_data.BASE64_IMAGE
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)
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def test_no_postprocessing(self, patched_cache_folder):
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def im(x):
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return [
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{
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"image": {
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"path": "test/test_files/bus.png",
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},
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"caption": "hi",
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}
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]
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with gr.Blocks():
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text = gr.Textbox()
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gall = gr.Gallery()
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examples = gr.Examples(
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examples=["hi"],
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inputs=text,
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outputs=gall,
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fn=im,
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cache_examples=True,
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postprocess=False,
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)
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prediction = examples.load_from_cache(0)
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file = prediction[0].root[0].image.path
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assert client_utils.encode_url_or_file_to_base64(
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file
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) == client_utils.encode_url_or_file_to_base64("test/test_files/bus.png")
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def test_setting_cache_dir_env_variable(monkeypatch):
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temp_dir = tempfile.mkdtemp()
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monkeypatch.setenv("GRADIO_EXAMPLES_CACHE", temp_dir)
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with gr.Blocks():
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image = gr.Image()
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image2 = gr.Image()
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examples = gr.Examples(
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examples=["test/test_files/bus.png"],
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inputs=image,
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outputs=image2,
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fn=lambda x: x,
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cache_examples=True,
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)
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prediction = examples.load_from_cache(0)
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path_to_cached_file = Path(prediction[0].path)
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assert utils.is_in_or_equal(path_to_cached_file, temp_dir)
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monkeypatch.delenv("GRADIO_EXAMPLES_CACHE", raising=False)
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@patch("gradio.utils.get_cache_folder", return_value=Path(tempfile.mkdtemp()))
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class TestExamplesDataset:
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def test_no_headers(self, patched_cache_folder):
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examples = gr.Examples("test/test_files/images_log", [gr.Image(), gr.Text()])
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assert examples.dataset.headers == []
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def test_all_headers(self, patched_cache_folder):
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examples = gr.Examples(
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"test/test_files/images_log",
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[gr.Image(label="im"), gr.Text(label="your text")],
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)
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assert examples.dataset.headers == ["im", "your text"]
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def test_some_headers(self, patched_cache_folder):
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examples = gr.Examples(
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"test/test_files/images_log", [gr.Image(label="im"), gr.Text()]
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)
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assert examples.dataset.headers == ["im", ""]
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def test_example_caching_relaunch(connect):
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def combine(a, b):
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return a + " " + b
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with gr.Blocks() as demo:
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txt = gr.Textbox(label="Input")
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txt_2 = gr.Textbox(label="Input 2")
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txt_3 = gr.Textbox(value="", label="Output")
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btn = gr.Button(value="Submit")
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btn.click(combine, inputs=[txt, txt_2], outputs=[txt_3])
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gr.Examples(
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[["hi", "Adam"], ["hello", "Eve"]],
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[txt, txt_2],
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txt_3,
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combine,
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cache_examples=True,
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api_name="examples",
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)
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with connect(demo) as client:
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assert client.predict(1, api_name="/examples") == (
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"hello",
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"Eve",
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"hello Eve",
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)
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# Let the server shut down
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time.sleep(1)
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with connect(demo) as client:
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assert client.predict(1, api_name="/examples") == (
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"hello",
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"Eve",
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"hello Eve",
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)
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@patch("gradio.utils.get_cache_folder", return_value=Path(tempfile.mkdtemp()))
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class TestProcessExamples:
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def test_caching(self, patched_cache_folder):
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io = gr.Interface(
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lambda x: f"Hello {x}",
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"text",
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"text",
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examples=[["World"], ["Dunya"], ["Monde"]],
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cache_examples=True,
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)
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prediction = io.examples_handler.load_from_cache(1)
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assert prediction[0] == "Hello Dunya"
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def test_example_caching_relaunch(self, patched_cache_folder, connect):
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def combine(a, b):
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return a + " " + b
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with gr.Blocks() as demo:
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txt = gr.Textbox(label="Input")
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txt_2 = gr.Textbox(label="Input 2")
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txt_3 = gr.Textbox(value="", label="Output")
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btn = gr.Button(value="Submit")
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btn.click(combine, inputs=[txt, txt_2], outputs=[txt_3])
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gr.Examples(
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[["hi", "Adam"], ["hello", "Eve"]],
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[txt, txt_2],
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txt_3,
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combine,
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cache_examples=True,
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api_name="examples",
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)
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with connect(demo) as client:
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assert client.predict(1, api_name="/examples") == (
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"hello",
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"Eve",
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"hello Eve",
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)
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with connect(demo) as client:
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assert client.predict(1, api_name="/examples") == (
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"hello",
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"Eve",
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"hello Eve",
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)
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def test_caching_image(self, patched_cache_folder):
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io = gr.Interface(
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lambda x: x,
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"image",
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"image",
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examples=[["test/test_files/bus.png"]],
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cache_examples=True,
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)
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prediction = io.examples_handler.load_from_cache(0)
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assert client_utils.encode_url_or_file_to_base64(prediction[0].path).startswith(
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"data:image/png;base64,iVBORw0KGgoAAA"
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)
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def test_caching_audio(self, patched_cache_folder):
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io = gr.Interface(
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lambda x: x,
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"audio",
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"audio",
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examples=[["test/test_files/audio_sample.wav"]],
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cache_examples=True,
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)
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prediction = io.examples_handler.load_from_cache(0)
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file = prediction[0].path
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assert client_utils.encode_url_or_file_to_base64(file).startswith(
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"data:audio/wav;base64,UklGRgA/"
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)
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def test_caching_with_update(self, patched_cache_folder):
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io = gr.Interface(
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lambda x: gr.update(visible=False),
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"text",
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"image",
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examples=[["World"], ["Dunya"], ["Monde"]],
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cache_examples=True,
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)
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prediction = io.examples_handler.load_from_cache(1)
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assert prediction[0] == {
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"visible": False,
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"__type__": "update",
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}
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def test_caching_with_mix_update(self, patched_cache_folder):
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io = gr.Interface(
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lambda x: [gr.update(lines=4, value="hello"), "test/test_files/bus.png"],
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"text",
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["text", "image"],
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examples=[["World"], ["Dunya"], ["Monde"]],
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cache_examples=True,
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)
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prediction = io.examples_handler.load_from_cache(1)
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assert prediction[0] == {
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"lines": 4,
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"value": "hello",
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"__type__": "update",
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}
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def test_caching_with_dict(self, patched_cache_folder):
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text = gr.Textbox()
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out = gr.Label()
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io = gr.Interface(
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lambda _: {text: gr.update(lines=4, interactive=False), out: "lion"},
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"textbox",
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[text, out],
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examples=["abc"],
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cache_examples=True,
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)
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prediction = io.examples_handler.load_from_cache(0)
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assert prediction == [
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{"lines": 4, "__type__": "update", "interactive": False},
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gr.Label.data_model(**{"label": "lion", "confidences": None}),
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]
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def test_caching_with_generators(self, patched_cache_folder):
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def test_generator(x):
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for y in range(len(x)):
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yield "Your output: " + x[: y + 1]
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io = gr.Interface(
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test_generator,
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"textbox",
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"textbox",
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examples=["abcdef"],
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cache_examples=True,
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)
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prediction = io.examples_handler.load_from_cache(0)
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assert prediction[0] == "Your output: abcdef"
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def test_caching_with_generators_and_streamed_output(self, patched_cache_folder):
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file_dir = Path(Path(__file__).parent, "test_files")
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audio = str(file_dir / "audio_sample.wav")
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def test_generator(x):
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for y in range(int(x)):
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yield audio, y * 5
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io = gr.Interface(
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test_generator,
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"number",
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[gr.Audio(streaming=True), "number"],
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examples=[3],
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cache_examples=True,
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)
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prediction = io.examples_handler.load_from_cache(0)
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len_input_audio = len(AudioSegment.from_wav(audio))
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len_output_audio = len(AudioSegment.from_wav(prediction[0].path))
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length_ratio = len_output_audio / len_input_audio
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assert round(length_ratio, 1) == 3.0 # might not be exactly 3x
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assert float(prediction[1]) == 10.0
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def test_caching_with_async_generators(self, patched_cache_folder):
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async def test_generator(x):
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for y in range(len(x)):
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yield "Your output: " + x[: y + 1]
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io = gr.Interface(
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test_generator,
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"textbox",
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"textbox",
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examples=["abcdef"],
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cache_examples=True,
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)
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prediction = io.examples_handler.load_from_cache(0)
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assert prediction[0] == "Your output: abcdef"
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def test_raise_helpful_error_message_if_providing_partial_examples(
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self, patched_cache_folder, tmp_path
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):
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def foo(a, b):
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return a + b
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with pytest.warns(
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UserWarning,
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match="^Examples are being cached but not all input components have",
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):
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with pytest.raises(Exception):
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gr.Interface(
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foo,
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inputs=["text", "text"],
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outputs=["text"],
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examples=[["foo"], ["bar"]],
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cache_examples=True,
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)
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with pytest.warns(
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UserWarning,
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match="^Examples are being cached but not all input components have",
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):
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with pytest.raises(Exception):
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gr.Interface(
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foo,
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inputs=["text", "text"],
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outputs=["text"],
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examples=[["foo", "bar"], ["bar", None]],
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cache_examples=True,
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)
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def foo_no_exception(a, b=2):
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return a * b
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gr.Interface(
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foo_no_exception,
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inputs=["text", "number"],
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outputs=["text"],
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examples=[["foo"], ["bar"]],
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cache_examples=True,
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)
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def many_missing(a, b, c):
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return a * b
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|
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with pytest.warns(
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UserWarning,
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match="^Examples are being cached but not all input components have",
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):
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with pytest.raises(Exception):
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gr.Interface(
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many_missing,
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inputs=["text", "number", "number"],
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outputs=["text"],
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examples=[["foo", None, None], ["bar", 2, 3]],
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cache_examples=True,
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)
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def test_caching_with_batch(self, patched_cache_folder):
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def trim_words(words, lens):
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trimmed_words = [word[:length] for word, length in zip(words, lens)]
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return [trimmed_words]
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io = gr.Interface(
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trim_words,
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["textbox", gr.Number(precision=0)],
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["textbox"],
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batch=True,
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max_batch_size=16,
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examples=[["hello", 3], ["hi", 4]],
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cache_examples=True,
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)
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prediction = io.examples_handler.load_from_cache(0)
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assert prediction == ["hel"]
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def test_caching_with_batch_multiple_outputs(self, patched_cache_folder):
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def trim_words(words, lens):
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trimmed_words = [word[:length] for word, length in zip(words, lens)]
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return trimmed_words, lens
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io = gr.Interface(
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trim_words,
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["textbox", gr.Number(precision=0)],
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["textbox", gr.Number(precision=0)],
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batch=True,
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max_batch_size=16,
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examples=[["hello", 3], ["hi", 4]],
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cache_examples=True,
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)
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prediction = io.examples_handler.load_from_cache(0)
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assert prediction == ["hel", "3"]
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|
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def test_caching_with_non_io_component(self, patched_cache_folder):
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def predict(name):
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return name, gr.update(visible=True)
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|
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with gr.Blocks():
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t1 = gr.Textbox()
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with gr.Column(visible=False) as c:
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t2 = gr.Textbox()
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examples = gr.Examples(
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[["John"], ["Mary"]],
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fn=predict,
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inputs=[t1],
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outputs=[t2, c],
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cache_examples=True,
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)
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prediction = examples.load_from_cache(0)
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assert prediction == ["John", {"visible": True, "__type__": "update"}]
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def test_end_to_end(self, patched_cache_folder):
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def concatenate(str1, str2):
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return str1 + str2
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|
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with gr.Blocks() as demo:
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t1 = gr.Textbox()
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t2 = gr.Textbox()
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t1.submit(concatenate, [t1, t2], t2)
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gr.Examples(
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[["Hello,", None], ["Michael", None]],
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inputs=[t1, t2],
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api_name="load_example",
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)
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|
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app, _, _ = demo.launch(prevent_thread_lock=True)
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client = TestClient(app)
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|
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response = client.post("/api/load_example/", json={"data": [0]})
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assert response.json()["data"] == [
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{
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"lines": 1,
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"max_lines": 20,
|
|
"show_label": True,
|
|
"container": True,
|
|
"min_width": 160,
|
|
"autofocus": False,
|
|
"autoscroll": True,
|
|
"elem_classes": [],
|
|
"rtl": False,
|
|
"show_copy_button": False,
|
|
"__type__": "update",
|
|
"visible": True,
|
|
"value": "Hello,",
|
|
"type": "text",
|
|
}
|
|
]
|
|
|
|
response = client.post("/api/load_example/", json={"data": [1]})
|
|
assert response.json()["data"] == [
|
|
{
|
|
"lines": 1,
|
|
"max_lines": 20,
|
|
"show_label": True,
|
|
"container": True,
|
|
"min_width": 160,
|
|
"autofocus": False,
|
|
"autoscroll": True,
|
|
"elem_classes": [],
|
|
"rtl": False,
|
|
"show_copy_button": False,
|
|
"__type__": "update",
|
|
"visible": True,
|
|
"value": "Michael",
|
|
"type": "text",
|
|
}
|
|
]
|
|
|
|
def test_end_to_end_cache_examples(self, patched_cache_folder):
|
|
def concatenate(str1, str2):
|
|
return f"{str1} {str2}"
|
|
|
|
with gr.Blocks() as demo:
|
|
t1 = gr.Textbox()
|
|
t2 = gr.Textbox()
|
|
t1.submit(concatenate, [t1, t2], t2)
|
|
|
|
gr.Examples(
|
|
examples=[["Hello,", "World"], ["Michael", "Jordan"]],
|
|
inputs=[t1, t2],
|
|
outputs=[t2],
|
|
fn=concatenate,
|
|
cache_examples=True,
|
|
api_name="load_example",
|
|
)
|
|
|
|
app, _, _ = demo.launch(prevent_thread_lock=True)
|
|
client = TestClient(app)
|
|
|
|
response = client.post("/api/load_example/", json={"data": [0]})
|
|
assert response.json()["data"] == ["Hello,", "World", "Hello, World"]
|
|
|
|
response = client.post("/api/load_example/", json={"data": [1]})
|
|
assert response.json()["data"] == ["Michael", "Jordan", "Michael Jordan"]
|
|
|
|
|
|
def test_multiple_file_flagging(tmp_path):
|
|
with patch("gradio.utils.get_cache_folder", return_value=tmp_path):
|
|
io = gr.Interface(
|
|
fn=lambda *x: list(x),
|
|
inputs=[
|
|
gr.Image(type="filepath", label="frame 1"),
|
|
gr.Image(type="filepath", label="frame 2"),
|
|
],
|
|
outputs=[gr.Files()],
|
|
examples=[["test/test_files/cheetah1.jpg", "test/test_files/bus.png"]],
|
|
cache_examples=True,
|
|
)
|
|
prediction = io.examples_handler.load_from_cache(0)
|
|
|
|
assert len(prediction[0].root) == 2
|
|
assert all(isinstance(d, gr.FileData) for d in prediction[0].root)
|
|
|
|
|
|
def test_examples_keep_all_suffixes(tmp_path):
|
|
with patch("gradio.utils.get_cache_folder", return_value=Path(tempfile.mkdtemp())):
|
|
file_1 = tmp_path / "foo.bar.txt"
|
|
file_1.write_text("file 1")
|
|
file_2 = tmp_path / "file_2"
|
|
file_2.mkdir(parents=True)
|
|
file_2 = file_2 / "foo.bar.txt"
|
|
file_2.write_text("file 2")
|
|
io = gr.Interface(
|
|
fn=lambda x: x.name,
|
|
inputs=gr.File(),
|
|
outputs=[gr.File()],
|
|
examples=[[str(file_1)], [str(file_2)]],
|
|
cache_examples=True,
|
|
)
|
|
prediction = io.examples_handler.load_from_cache(0)
|
|
assert Path(prediction[0].path).read_text() == "file 1"
|
|
assert prediction[0].orig_name == "foo.bar.txt"
|
|
assert prediction[0].path.endswith("foo.bar.txt")
|
|
prediction = io.examples_handler.load_from_cache(1)
|
|
assert Path(prediction[0].path).read_text() == "file 2"
|
|
assert prediction[0].orig_name == "foo.bar.txt"
|
|
assert prediction[0].path.endswith("foo.bar.txt")
|
|
|
|
|
|
def test_make_waveform_with_spaces_in_filename():
|
|
with tempfile.TemporaryDirectory() as tmpdirname:
|
|
audio = os.path.join(tmpdirname, "test audio.wav")
|
|
shutil.copy("test/test_files/audio_sample.wav", audio)
|
|
waveform = gr.make_waveform(audio)
|
|
assert waveform.endswith(".mp4")
|
|
|
|
try:
|
|
command = [
|
|
"ffprobe",
|
|
"-v",
|
|
"error",
|
|
"-select_streams",
|
|
"v:0",
|
|
"-show_entries",
|
|
"stream=width,height",
|
|
"-of",
|
|
"json",
|
|
waveform,
|
|
]
|
|
|
|
result = subprocess.run(command, capture_output=True, text=True, check=True)
|
|
output = result.stdout
|
|
data = json.loads(output)
|
|
|
|
width = data["streams"][0]["width"]
|
|
height = data["streams"][0]["height"]
|
|
assert width == 1000
|
|
assert height == 400
|
|
|
|
except subprocess.CalledProcessError as e:
|
|
print("Error retrieving resolution of output waveform video:", e)
|
|
|
|
|
|
def test_make_waveform_raises_if_ffmpeg_fails(tmp_path, monkeypatch):
|
|
"""
|
|
Test that make_waveform raises an exception if ffmpeg fails,
|
|
instead of returning a path to a non-existent or empty file.
|
|
"""
|
|
audio = tmp_path / "test audio.wav"
|
|
shutil.copy("test/test_files/audio_sample.wav", audio)
|
|
|
|
def _failing_ffmpeg(*args, **kwargs):
|
|
raise subprocess.CalledProcessError(1, "ffmpeg")
|
|
|
|
monkeypatch.setattr(subprocess, "call", _failing_ffmpeg)
|
|
with pytest.raises(Exception):
|
|
gr.make_waveform(str(audio))
|
|
|
|
|
|
class TestProgressBar:
|
|
@pytest.mark.asyncio
|
|
async def test_progress_bar(self):
|
|
with gr.Blocks() as demo:
|
|
name = gr.Textbox()
|
|
greeting = gr.Textbox()
|
|
button = gr.Button(value="Greet")
|
|
|
|
def greet(s, prog=gr.Progress()):
|
|
prog(0, desc="start")
|
|
time.sleep(0.15)
|
|
for _ in prog.tqdm(range(4), unit="iter"):
|
|
time.sleep(0.15)
|
|
time.sleep(0.15)
|
|
for _ in tqdm(["a", "b", "c"], desc="alphabet"):
|
|
time.sleep(0.15)
|
|
return f"Hello, {s}!"
|
|
|
|
button.click(greet, name, greeting)
|
|
demo.queue(max_size=1).launch(prevent_thread_lock=True)
|
|
|
|
client = grc.Client(demo.local_url)
|
|
job = client.submit("Gradio")
|
|
|
|
status_updates = []
|
|
while not job.done():
|
|
status = job.status()
|
|
update = (
|
|
status.progress_data[0].index if status.progress_data else None,
|
|
status.progress_data[0].desc if status.progress_data else None,
|
|
)
|
|
if update != (None, None) and (
|
|
len(status_updates) == 0 or status_updates[-1] != update
|
|
):
|
|
status_updates.append(update)
|
|
time.sleep(0.05)
|
|
|
|
assert status_updates == [
|
|
(None, "start"),
|
|
(0, None),
|
|
(1, None),
|
|
(2, None),
|
|
(3, None),
|
|
(4, None),
|
|
]
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_progress_bar_track_tqdm(self):
|
|
with gr.Blocks() as demo:
|
|
name = gr.Textbox()
|
|
greeting = gr.Textbox()
|
|
button = gr.Button(value="Greet")
|
|
|
|
def greet(s, prog=gr.Progress(track_tqdm=True)):
|
|
prog(0, desc="start")
|
|
time.sleep(0.15)
|
|
for _ in prog.tqdm(range(4), unit="iter"):
|
|
time.sleep(0.15)
|
|
time.sleep(0.15)
|
|
for _ in tqdm(["a", "b", "c"], desc="alphabet"):
|
|
time.sleep(0.15)
|
|
return f"Hello, {s}!"
|
|
|
|
button.click(greet, name, greeting)
|
|
demo.queue(max_size=1).launch(prevent_thread_lock=True)
|
|
|
|
client = grc.Client(demo.local_url)
|
|
job = client.submit("Gradio")
|
|
|
|
status_updates = []
|
|
while not job.done():
|
|
status = job.status()
|
|
update = (
|
|
status.progress_data[0].index if status.progress_data else None,
|
|
status.progress_data[0].desc if status.progress_data else None,
|
|
)
|
|
if update != (None, None) and (
|
|
len(status_updates) == 0 or status_updates[-1] != update
|
|
):
|
|
status_updates.append(update)
|
|
time.sleep(0.05)
|
|
|
|
assert status_updates == [
|
|
(None, "start"),
|
|
(0, None),
|
|
(1, None),
|
|
(2, None),
|
|
(3, None),
|
|
(4, None),
|
|
(0, "alphabet"),
|
|
(1, "alphabet"),
|
|
(2, "alphabet"),
|
|
]
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_progress_bar_track_tqdm_without_iterable(self):
|
|
def greet(s, _=gr.Progress(track_tqdm=True)):
|
|
with tqdm(total=len(s)) as progress_bar:
|
|
for _c in s:
|
|
progress_bar.update()
|
|
time.sleep(0.15)
|
|
return f"Hello, {s}!"
|
|
|
|
demo = gr.Interface(greet, "text", "text")
|
|
demo.queue().launch(prevent_thread_lock=True)
|
|
|
|
client = grc.Client(demo.local_url)
|
|
job = client.submit("Gradio")
|
|
|
|
status_updates = []
|
|
while not job.done():
|
|
status = job.status()
|
|
update = (
|
|
status.progress_data[0].index if status.progress_data else None,
|
|
status.progress_data[0].unit if status.progress_data else None,
|
|
)
|
|
if update != (None, None) and (
|
|
len(status_updates) == 0 or status_updates[-1] != update
|
|
):
|
|
status_updates.append(update)
|
|
time.sleep(0.05)
|
|
|
|
assert status_updates == [
|
|
(1, "steps"),
|
|
(2, "steps"),
|
|
(3, "steps"),
|
|
(4, "steps"),
|
|
(5, "steps"),
|
|
(6, "steps"),
|
|
]
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_info_and_warning_alerts(self):
|
|
def greet(s):
|
|
for _c in s:
|
|
gr.Info(f"Letter {_c}")
|
|
time.sleep(0.15)
|
|
if len(s) < 5:
|
|
gr.Warning("Too short!")
|
|
time.sleep(0.15)
|
|
return f"Hello, {s}!"
|
|
|
|
demo = gr.Interface(greet, "text", "text")
|
|
demo.queue().launch(prevent_thread_lock=True)
|
|
|
|
client = grc.Client(demo.local_url)
|
|
job = client.submit("Jon")
|
|
|
|
status_updates = []
|
|
while not job.done():
|
|
status = job.status()
|
|
update = status.log
|
|
if update is not None and (
|
|
len(status_updates) == 0 or status_updates[-1] != update
|
|
):
|
|
status_updates.append(update)
|
|
time.sleep(0.05)
|
|
|
|
assert status_updates == [
|
|
("Letter J", "info"),
|
|
("Letter o", "info"),
|
|
("Letter n", "info"),
|
|
("Too short!", "warning"),
|
|
]
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
@pytest.mark.parametrize("async_handler", [True, False])
|
|
async def test_info_isolation(async_handler: bool):
|
|
async def greet_async(name):
|
|
await asyncio.sleep(2)
|
|
gr.Info(f"Hello {name}")
|
|
await asyncio.sleep(1)
|
|
return name
|
|
|
|
def greet_sync(name):
|
|
time.sleep(2)
|
|
gr.Info(f"Hello {name}")
|
|
time.sleep(1)
|
|
return name
|
|
|
|
demo = gr.Interface(
|
|
greet_async if async_handler else greet_sync,
|
|
"text",
|
|
"text",
|
|
concurrency_limit=2,
|
|
)
|
|
demo.launch(prevent_thread_lock=True)
|
|
|
|
async def session_interaction(name, delay=0):
|
|
client = grc.Client(demo.local_url)
|
|
job = client.submit(name)
|
|
|
|
status_updates = []
|
|
while not job.done():
|
|
status = job.status()
|
|
update = status.log
|
|
if update is not None and (
|
|
len(status_updates) == 0 or status_updates[-1] != update
|
|
):
|
|
status_updates.append(update)
|
|
time.sleep(0.05)
|
|
return status_updates[-1][0] if status_updates else None
|
|
|
|
alice_logs, bob_logs = await asyncio.gather(
|
|
session_interaction("Alice"),
|
|
session_interaction("Bob", delay=1),
|
|
)
|
|
|
|
assert alice_logs == "Hello Alice"
|
|
assert bob_logs == "Hello Bob"
|