| """ |
| Tests for all of the components defined in components.py. Tests are divided into two types: |
| 1. test_component_functions() are unit tests that check essential functions of a component, the functions that are checked are documented in the docstring. |
| 2. test_in_interface() are functional tests that check a component's functionalities inside an Interface. Please do not use Interface.launch() in this file, as it slow downs the tests. |
| """ |
|
|
| import filecmp |
| import json |
| import os |
| import pathlib |
| import shutil |
| import tempfile |
| from copy import deepcopy |
| from difflib import SequenceMatcher |
| from pathlib import Path |
| from unittest.mock import MagicMock, patch |
|
|
| import numpy as np |
| import pandas as pd |
| import PIL |
| import pytest |
| import vega_datasets |
| from gradio_client import media_data |
| from gradio_client import utils as client_utils |
| from scipy.io import wavfile |
|
|
| import gradio as gr |
| from gradio import processing_utils, utils |
| from gradio.deprecation import ( |
| GradioDeprecationWarning, |
| GradioUnusedKwargWarning, |
| ) |
|
|
| os.environ["GRADIO_ANALYTICS_ENABLED"] = "False" |
|
|
|
|
| class TestGettingComponents: |
| def test_component_function(self): |
| assert isinstance( |
| gr.components.component("textarea", render=False), gr.templates.TextArea |
| ) |
|
|
| @pytest.mark.parametrize( |
| "component, render, unrender, should_be_rendered", |
| [ |
| (gr.Textbox(render=True), False, True, False), |
| (gr.Textbox(render=False), False, False, False), |
| (gr.Textbox(render=False), True, False, True), |
| ("textbox", False, False, False), |
| ("textbox", True, False, True), |
| ], |
| ) |
| def test_get_component_instance_rendering( |
| self, component, render, unrender, should_be_rendered |
| ): |
| with gr.Blocks(): |
| textbox = gr.components.get_component_instance( |
| component, render=render, unrender=unrender |
| ) |
| assert textbox.is_rendered == should_be_rendered |
|
|
|
|
| def test_raise_warnings(): |
| for c_type, component in zip( |
| ["inputs", "outputs"], [gr.inputs.Textbox, gr.outputs.Label] |
| ): |
| with pytest.warns(UserWarning, match=f"Usage of gradio.{c_type}"): |
| component() |
|
|
|
|
| class TestTextbox: |
| def test_component_functions(self): |
| """ |
| Preprocess, postprocess, serialize, tokenize, get_config |
| """ |
| text_input = gr.Textbox() |
| assert text_input.preprocess("Hello World!") == "Hello World!" |
| assert text_input.postprocess("Hello World!") == "Hello World!" |
| assert text_input.postprocess(None) is None |
| assert text_input.postprocess("Ali") == "Ali" |
| assert text_input.postprocess(2) == "2" |
| assert text_input.postprocess(2.14) == "2.14" |
| assert text_input.serialize("Hello World!", True) == "Hello World!" |
|
|
| assert text_input.tokenize("Hello World! Gradio speaking.") == ( |
| ["Hello", "World!", "Gradio", "speaking."], |
| [ |
| "World! Gradio speaking.", |
| "Hello Gradio speaking.", |
| "Hello World! speaking.", |
| "Hello World! Gradio", |
| ], |
| None, |
| ) |
| text_input.interpretation_replacement = "unknown" |
| assert text_input.tokenize("Hello World! Gradio speaking.") == ( |
| ["Hello", "World!", "Gradio", "speaking."], |
| [ |
| "unknown World! Gradio speaking.", |
| "Hello unknown Gradio speaking.", |
| "Hello World! unknown speaking.", |
| "Hello World! Gradio unknown", |
| ], |
| None, |
| ) |
| assert text_input.get_config() == { |
| "lines": 1, |
| "max_lines": 20, |
| "placeholder": None, |
| "value": "", |
| "name": "textbox", |
| "show_copy_button": False, |
| "show_label": True, |
| "type": "text", |
| "label": None, |
| "container": True, |
| "min_width": 160, |
| "scale": None, |
| "elem_id": None, |
| "elem_classes": None, |
| "visible": True, |
| "interactive": None, |
| "root_url": None, |
| "rtl": False, |
| "text_align": None, |
| "autofocus": False, |
| "selectable": False, |
| "info": None, |
| "autoscroll": True, |
| } |
|
|
| @pytest.mark.asyncio |
| async def test_in_interface_as_input(self): |
| """ |
| Interface, process, interpret, |
| """ |
| iface = gr.Interface(lambda x: x[::-1], "textbox", "textbox") |
| assert iface("Hello") == "olleH" |
| iface = gr.Interface( |
| lambda sentence: max([len(word) for word in sentence.split()]), |
| gr.Textbox(), |
| "number", |
| interpretation="default", |
| ) |
| scores = await iface.interpret( |
| ["Return the length of the longest word in this sentence"] |
| ) |
| assert scores[0]["interpretation"] == [ |
| ("Return", 0.0), |
| (" ", 0), |
| ("the", 0.0), |
| (" ", 0), |
| ("length", 0.0), |
| (" ", 0), |
| ("of", 0.0), |
| (" ", 0), |
| ("the", 0.0), |
| (" ", 0), |
| ("longest", 0.0), |
| (" ", 0), |
| ("word", 0.0), |
| (" ", 0), |
| ("in", 0.0), |
| (" ", 0), |
| ("this", 0.0), |
| (" ", 0), |
| ("sentence", 1.0), |
| (" ", 0), |
| ] |
|
|
| def test_in_interface_as_output(self): |
| """ |
| Interface, process |
| |
| """ |
| iface = gr.Interface(lambda x: x[-1], "textbox", gr.Textbox()) |
| assert iface("Hello") == "o" |
| iface = gr.Interface(lambda x: x / 2, "number", gr.Textbox()) |
| assert iface(10) == "5.0" |
|
|
| def test_static(self): |
| """ |
| postprocess |
| """ |
| component = gr.Textbox("abc") |
| assert component.get_config().get("value") == "abc" |
|
|
| def test_override_template(self): |
| """ |
| override template |
| """ |
| component = gr.TextArea(value="abc") |
| assert component.get_config().get("value") == "abc" |
| assert component.get_config().get("lines") == 7 |
| component = gr.TextArea(value="abc", lines=4) |
| assert component.get_config().get("value") == "abc" |
| assert component.get_config().get("lines") == 4 |
|
|
| def test_faulty_type(self): |
| with pytest.raises( |
| ValueError, match='`type` must be one of "text", "password", or "email".' |
| ): |
| gr.Textbox(type="boo") |
|
|
| def test_max_lines(self): |
| assert gr.Textbox(type="password").get_config().get("max_lines") == 1 |
| assert gr.Textbox(type="email").get_config().get("max_lines") == 1 |
| assert gr.Textbox(type="text").get_config().get("max_lines") == 20 |
| assert gr.Textbox().get_config().get("max_lines") == 20 |
|
|
|
|
| class TestNumber: |
| def test_component_functions(self): |
| """ |
| Preprocess, postprocess, serialize, set_interpret_parameters, get_interpretation_neighbors, get_config |
| |
| """ |
| numeric_input = gr.Number(elem_id="num", elem_classes="first") |
| assert numeric_input.preprocess(3) == 3.0 |
| assert numeric_input.preprocess(None) is None |
| assert numeric_input.postprocess(3) == 3 |
| assert numeric_input.postprocess(3) == 3.0 |
| assert numeric_input.postprocess(2.14) == 2.14 |
| assert numeric_input.postprocess(None) is None |
| assert numeric_input.serialize(3, True) == 3 |
| numeric_input.set_interpret_parameters(steps=3, delta=1, delta_type="absolute") |
| assert numeric_input.get_interpretation_neighbors(1) == ( |
| [-2.0, -1.0, 0.0, 2.0, 3.0, 4.0], |
| {}, |
| ) |
| numeric_input.set_interpret_parameters(steps=3, delta=1, delta_type="percent") |
| assert numeric_input.get_interpretation_neighbors(1) == ( |
| [0.97, 0.98, 0.99, 1.01, 1.02, 1.03], |
| {}, |
| ) |
| assert numeric_input.get_config() == { |
| "value": None, |
| "name": "number", |
| "show_label": True, |
| "step": 1, |
| "label": None, |
| "minimum": None, |
| "maximum": None, |
| "container": True, |
| "min_width": 160, |
| "scale": None, |
| "elem_id": "num", |
| "elem_classes": ["first"], |
| "visible": True, |
| "interactive": None, |
| "root_url": None, |
| "info": None, |
| "precision": None, |
| } |
|
|
| def test_component_functions_integer(self): |
| """ |
| Preprocess, postprocess, serialize, set_interpret_parameters, get_interpretation_neighbors, get_template_context |
| |
| """ |
| numeric_input = gr.Number(precision=0, value=42) |
| assert numeric_input.preprocess(3) == 3 |
| assert numeric_input.preprocess(None) is None |
| assert numeric_input.postprocess(3) == 3 |
| assert numeric_input.postprocess(3) == 3 |
| assert numeric_input.postprocess(2.85) == 3 |
| assert numeric_input.postprocess(None) is None |
| assert numeric_input.serialize(3, True) == 3 |
| numeric_input.set_interpret_parameters(steps=3, delta=1, delta_type="absolute") |
| assert numeric_input.get_interpretation_neighbors(1) == ( |
| [-2.0, -1.0, 0.0, 2.0, 3.0, 4.0], |
| {}, |
| ) |
| numeric_input.set_interpret_parameters(steps=3, delta=1, delta_type="percent") |
| assert numeric_input.get_interpretation_neighbors(100) == ( |
| [97.0, 98.0, 99.0, 101.0, 102.0, 103.0], |
| {}, |
| ) |
| with pytest.raises(ValueError) as error: |
| numeric_input.get_interpretation_neighbors(1) |
| assert error.msg == "Cannot generate valid set of neighbors" |
| numeric_input.set_interpret_parameters( |
| steps=3, delta=1.24, delta_type="absolute" |
| ) |
| with pytest.raises(ValueError) as error: |
| numeric_input.get_interpretation_neighbors(4) |
| assert error.msg == "Cannot generate valid set of neighbors" |
| assert numeric_input.get_config() == { |
| "value": 42, |
| "name": "number", |
| "show_label": True, |
| "step": 1, |
| "label": None, |
| "minimum": None, |
| "maximum": None, |
| "container": True, |
| "min_width": 160, |
| "scale": None, |
| "elem_id": None, |
| "elem_classes": None, |
| "visible": True, |
| "interactive": None, |
| "root_url": None, |
| "info": None, |
| "precision": 0, |
| } |
|
|
| def test_component_functions_precision(self): |
| """ |
| Preprocess, postprocess, serialize, set_interpret_parameters, get_interpretation_neighbors, get_template_context |
| |
| """ |
| numeric_input = gr.Number(precision=2, value=42.3428) |
| assert numeric_input.preprocess(3.231241) == 3.23 |
| assert numeric_input.preprocess(None) is None |
| assert numeric_input.postprocess(-42.1241) == -42.12 |
| assert numeric_input.postprocess(5.6784) == 5.68 |
| assert numeric_input.postprocess(2.1421) == 2.14 |
| assert numeric_input.postprocess(None) is None |
|
|
| @pytest.mark.asyncio |
| async def test_in_interface_as_input(self): |
| """ |
| Interface, process, interpret |
| """ |
| iface = gr.Interface(lambda x: x**2, "number", "textbox") |
| assert iface(2) == "4.0" |
| iface = gr.Interface( |
| lambda x: x**2, "number", "number", interpretation="default" |
| ) |
| scores = (await iface.interpret([2]))[0]["interpretation"] |
| assert scores == [ |
| (1.94, -0.23640000000000017), |
| (1.96, -0.15840000000000032), |
| (1.98, -0.07960000000000012), |
| (2, None), |
| (2.02, 0.08040000000000003), |
| (2.04, 0.16159999999999997), |
| (2.06, 0.24359999999999982), |
| ] |
|
|
| @pytest.mark.asyncio |
| async def test_precision_0_in_interface(self): |
| """ |
| Interface, process, interpret |
| """ |
| iface = gr.Interface(lambda x: x**2, gr.Number(precision=0), "textbox") |
| assert iface(2) == "4" |
| iface = gr.Interface( |
| lambda x: x**2, "number", gr.Number(precision=0), interpretation="default" |
| ) |
| |
| scores = (await iface.interpret([2]))[0]["interpretation"] |
| assert scores == [ |
| (1.94, 0.0), |
| (1.96, 0.0), |
| (1.98, 0.0), |
| (2, None), |
| (2.02, 0.0), |
| (2.04, 0.0), |
| (2.06, 0.0), |
| ] |
|
|
| @pytest.mark.asyncio |
| async def test_in_interface_as_output(self): |
| """ |
| Interface, process, interpret |
| """ |
| iface = gr.Interface(lambda x: int(x) ** 2, "textbox", "number") |
| assert iface(2) == 4.0 |
| iface = gr.Interface( |
| lambda x: x**2, "number", "number", interpretation="default" |
| ) |
| scores = (await iface.interpret([2]))[0]["interpretation"] |
| assert scores == [ |
| (1.94, -0.23640000000000017), |
| (1.96, -0.15840000000000032), |
| (1.98, -0.07960000000000012), |
| (2, None), |
| (2.02, 0.08040000000000003), |
| (2.04, 0.16159999999999997), |
| (2.06, 0.24359999999999982), |
| ] |
|
|
| def test_static(self): |
| """ |
| postprocess |
| """ |
| component = gr.Number() |
| assert component.get_config().get("value") is None |
| component = gr.Number(3) |
| assert component.get_config().get("value") == 3.0 |
|
|
|
|
| class TestSlider: |
| def test_component_functions(self): |
| """ |
| Preprocess, postprocess, serialize, get_config |
| """ |
| slider_input = gr.Slider() |
| assert slider_input.preprocess(3.0) == 3.0 |
| assert slider_input.postprocess(3) == 3 |
| assert slider_input.postprocess(3) == 3 |
| assert slider_input.postprocess(None) == 0 |
| assert slider_input.serialize(3, True) == 3 |
|
|
| slider_input = gr.Slider(10, 20, value=15, step=1, label="Slide Your Input") |
| assert slider_input.get_config() == { |
| "minimum": 10, |
| "maximum": 20, |
| "step": 1, |
| "value": 15, |
| "name": "slider", |
| "show_label": True, |
| "label": "Slide Your Input", |
| "container": True, |
| "min_width": 160, |
| "scale": None, |
| "elem_id": None, |
| "elem_classes": None, |
| "visible": True, |
| "interactive": None, |
| "root_url": None, |
| "info": None, |
| } |
|
|
| @pytest.mark.asyncio |
| async def test_in_interface(self): |
| """ " |
| Interface, process, interpret |
| """ |
| iface = gr.Interface(lambda x: x**2, "slider", "textbox") |
| assert iface(2) == "4" |
| iface = gr.Interface( |
| lambda x: x**2, "slider", "number", interpretation="default" |
| ) |
| scores = (await iface.interpret([2]))[0]["interpretation"] |
| assert scores == [ |
| -4.0, |
| 200.08163265306123, |
| 812.3265306122449, |
| 1832.7346938775513, |
| 3261.3061224489797, |
| 5098.040816326531, |
| 7342.938775510205, |
| 9996.0, |
| ] |
|
|
| def test_static(self): |
| """ |
| postprocess |
| """ |
| component = gr.Slider(0, 100, 5) |
| assert component.get_config().get("value") == 5 |
| component = gr.Slider(0, 100, None) |
| assert component.get_config().get("value") == 0 |
|
|
| @patch("gradio.Slider.get_random_value", return_value=7) |
| def test_slider_get_random_value_on_load(self, mock_get_random_value): |
| slider = gr.Slider(minimum=-5, maximum=10, randomize=True) |
| assert slider.value == 7 |
| assert slider.load_event_to_attach[0]() == 7 |
| assert slider.load_event_to_attach[1] is None |
|
|
| @patch("random.randint", return_value=3) |
| def test_slider_rounds_when_using_default_randomizer(self, mock_randint): |
| slider = gr.Slider(minimum=0, maximum=1, randomize=True, step=0.1) |
| |
| |
| assert slider.get_random_value() == 0.3 |
| mock_randint.assert_called() |
|
|
|
|
| class TestCheckbox: |
| def test_component_functions(self): |
| """ |
| Preprocess, postprocess, serialize, get_config |
| """ |
| bool_input = gr.Checkbox() |
| assert bool_input.preprocess(True) |
| assert bool_input.postprocess(True) |
| assert bool_input.postprocess(True) |
| assert bool_input.serialize(True, True) |
| bool_input = gr.Checkbox(value=True, label="Check Your Input") |
| assert bool_input.get_config() == { |
| "value": True, |
| "name": "checkbox", |
| "show_label": True, |
| "label": "Check Your Input", |
| "container": True, |
| "min_width": 160, |
| "scale": None, |
| "elem_id": None, |
| "elem_classes": None, |
| "visible": True, |
| "interactive": None, |
| "root_url": None, |
| "selectable": False, |
| "info": None, |
| } |
|
|
| @pytest.mark.asyncio |
| async def test_in_interface(self): |
| """ |
| Interface, process, interpret |
| """ |
| iface = gr.Interface(lambda x: 1 if x else 0, "checkbox", "number") |
| assert iface(True) == 1 |
| iface = gr.Interface( |
| lambda x: 1 if x else 0, "checkbox", "number", interpretation="default" |
| ) |
| scores = (await iface.interpret([False]))[0]["interpretation"] |
| assert scores == (None, 1.0) |
| scores = (await iface.interpret([True]))[0]["interpretation"] |
| assert scores == (-1.0, None) |
|
|
|
|
| class TestCheckboxGroup: |
| def test_component_functions(self): |
| """ |
| Preprocess, postprocess, serialize, get_config |
| """ |
| checkboxes_input = gr.CheckboxGroup(["a", "b", "c"]) |
| assert checkboxes_input.preprocess(["a", "c"]) == ["a", "c"] |
| assert checkboxes_input.postprocess(["a", "c"]) == ["a", "c"] |
| assert checkboxes_input.serialize(["a", "c"]) == ["a", "c"] |
|
|
| checkboxes_input = gr.CheckboxGroup(["a", "b"], type="index") |
| assert checkboxes_input.preprocess(["a"]) == [0] |
| assert checkboxes_input.preprocess(["a", "b"]) == [0, 1] |
| assert checkboxes_input.preprocess(["a", "b", "c"]) == [0, 1, None] |
|
|
| |
| |
| checkboxgroup = gr.CheckboxGroup(["a", "b", ["c", "c full"]]) |
| assert checkboxgroup.choices == [("a", "a"), ("b", "b"), ("c", "c full")] |
|
|
| checkboxes_input = gr.CheckboxGroup( |
| value=["a", "c"], |
| choices=["a", "b", "c"], |
| label="Check Your Inputs", |
| ) |
| assert checkboxes_input.get_config() == { |
| "choices": [("a", "a"), ("b", "b"), ("c", "c")], |
| "value": ["a", "c"], |
| "name": "checkboxgroup", |
| "show_label": True, |
| "label": "Check Your Inputs", |
| "container": True, |
| "min_width": 160, |
| "scale": None, |
| "elem_id": None, |
| "elem_classes": None, |
| "visible": True, |
| "interactive": None, |
| "root_url": None, |
| "selectable": False, |
| "type": "value", |
| "info": None, |
| } |
| with pytest.raises(ValueError): |
| gr.CheckboxGroup(["a"], type="unknown") |
|
|
| cbox = gr.CheckboxGroup(choices=["a", "b"], value="c") |
| assert cbox.get_config()["value"] == ["c"] |
| assert cbox.postprocess("a") == ["a"] |
| with pytest.raises(ValueError): |
| gr.CheckboxGroup().as_example("a") |
|
|
| def test_in_interface(self): |
| """ |
| Interface, process |
| """ |
| checkboxes_input = gr.CheckboxGroup(["a", "b", "c"]) |
| iface = gr.Interface(lambda x: "|".join(x), checkboxes_input, "textbox") |
| assert iface(["a", "c"]) == "a|c" |
| assert iface([]) == "" |
| _ = gr.CheckboxGroup(["a", "b", "c"], type="index") |
|
|
|
|
| class TestRadio: |
| def test_component_functions(self): |
| """ |
| Preprocess, postprocess, serialize, get_config |
| |
| """ |
| radio_input = gr.Radio(["a", "b", "c"]) |
| assert radio_input.preprocess("c") == "c" |
| assert radio_input.postprocess("a") == "a" |
| assert radio_input.serialize("a", True) == "a" |
| radio_input = gr.Radio( |
| choices=["a", "b", "c"], default="a", label="Pick Your One Input" |
| ) |
| assert radio_input.get_config() == { |
| "choices": [("a", "a"), ("b", "b"), ("c", "c")], |
| "value": None, |
| "name": "radio", |
| "show_label": True, |
| "label": "Pick Your One Input", |
| "container": True, |
| "min_width": 160, |
| "scale": None, |
| "elem_id": None, |
| "elem_classes": None, |
| "visible": True, |
| "interactive": None, |
| "root_url": None, |
| "selectable": False, |
| "type": "value", |
| "info": None, |
| } |
|
|
| radio = gr.Radio(choices=["a", "b"], type="index") |
| assert radio.preprocess("a") == 0 |
| assert radio.preprocess("b") == 1 |
| assert radio.preprocess("c") is None |
|
|
| |
| |
| radio = gr.Radio(["a", "b", ["c", "c full"]]) |
| assert radio.choices == [("a", "a"), ("b", "b"), ("c", "c full")] |
|
|
| with pytest.raises(ValueError): |
| gr.Radio(["a", "b"], type="unknown") |
|
|
| @pytest.mark.asyncio |
| async def test_in_interface(self): |
| """ |
| Interface, process, interpret |
| """ |
| radio_input = gr.Radio(["a", "b", "c"]) |
| iface = gr.Interface(lambda x: 2 * x, radio_input, "textbox") |
| assert iface("c") == "cc" |
| radio_input = gr.Radio(["a", "b", "c"], type="index") |
| iface = gr.Interface( |
| lambda x: 2 * x, radio_input, "number", interpretation="default" |
| ) |
| assert iface("c") == 4 |
| scores = (await iface.interpret(["b"]))[0]["interpretation"] |
| assert scores == [-2.0, None, 2.0] |
|
|
| def test_update(self): |
| update = gr.Radio.update( |
| choices=[("zeroth", ""), "first", "second"], label="ordinal" |
| ) |
| assert update["choices"] == [ |
| ("zeroth", ""), |
| ("first", "first"), |
| ("second", "second"), |
| ] |
|
|
|
|
| class TestDropdown: |
| def test_component_functions(self): |
| """ |
| Preprocess, postprocess, serialize, get_config |
| """ |
| dropdown_input = gr.Dropdown(["a", "b", ("c", "c full")], multiselect=True) |
| assert dropdown_input.preprocess("a") == "a" |
| assert dropdown_input.postprocess("a") == "a" |
| assert dropdown_input.preprocess("c full") == "c full" |
| assert dropdown_input.postprocess("c full") == "c full" |
|
|
| |
| |
| dropdown_input = gr.Dropdown(["a", "b", ["c", "c full"]]) |
| assert dropdown_input.choices == [("a", "a"), ("b", "b"), ("c", "c full")] |
|
|
| dropdown = gr.Dropdown(choices=["a", "b"], type="index") |
| assert dropdown.preprocess("a") == 0 |
| assert dropdown.preprocess("b") == 1 |
| assert dropdown.preprocess("c") is None |
|
|
| dropdown = gr.Dropdown(choices=["a", "b"], type="index", multiselect=True) |
| assert dropdown.preprocess(["a"]) == [0] |
| assert dropdown.preprocess(["a", "b"]) == [0, 1] |
| assert dropdown.preprocess(["a", "b", "c"]) == [0, 1, None] |
|
|
| dropdown_input_multiselect = gr.Dropdown(["a", "b", ("c", "c full")]) |
| assert dropdown_input_multiselect.preprocess(["a", "c full"]) == ["a", "c full"] |
| assert dropdown_input_multiselect.postprocess(["a", "c full"]) == [ |
| "a", |
| "c full", |
| ] |
| assert dropdown_input_multiselect.serialize(["a", "c full"]) == ["a", "c full"] |
| dropdown_input_multiselect = gr.Dropdown( |
| value=["a", "c"], |
| choices=["a", "b", ("c", "c full")], |
| label="Select Your Inputs", |
| multiselect=True, |
| max_choices=2, |
| ) |
| assert dropdown_input_multiselect.get_config() == { |
| "allow_custom_value": False, |
| "choices": [("a", "a"), ("b", "b"), ("c", "c full")], |
| "value": ["a", "c"], |
| "name": "dropdown", |
| "show_label": True, |
| "label": "Select Your Inputs", |
| "container": True, |
| "min_width": 160, |
| "scale": None, |
| "elem_id": None, |
| "elem_classes": None, |
| "visible": True, |
| "interactive": None, |
| "root_url": None, |
| "multiselect": True, |
| "filterable": True, |
| "max_choices": 2, |
| "selectable": False, |
| "type": "value", |
| "info": None, |
| } |
| with pytest.raises(ValueError): |
| gr.Dropdown(["a"], type="unknown") |
|
|
| dropdown = gr.Dropdown(choices=["a", "b"], value="c") |
| assert dropdown.get_config()["value"] == "c" |
| assert dropdown.postprocess("a") == "a" |
|
|
| def test_in_interface(self): |
| """ |
| Interface, process |
| """ |
| dropdown_input = gr.Dropdown(["a", "b", "c"]) |
| iface = gr.Interface(lambda x: "|".join(x), dropdown_input, "textbox") |
| assert iface(["a", "c"]) == "a|c" |
| assert iface([]) == "" |
|
|
| def test_update(self): |
| update = gr.Dropdown.update( |
| choices=[("zeroth", ""), "first", "second"], label="ordinal" |
| ) |
| assert update["choices"] == [ |
| ("zeroth", ""), |
| ("first", "first"), |
| ("second", "second"), |
| ] |
|
|
|
|
| class TestImage: |
| def test_component_functions(self): |
| """ |
| Preprocess, postprocess, serialize, get_config, _segment_by_slic |
| type: pil, file, filepath, numpy |
| """ |
| img = deepcopy(media_data.BASE64_IMAGE) |
| image_input = gr.Image() |
| assert image_input.preprocess(img).shape == (68, 61, 3) |
| image_input = gr.Image(shape=(25, 25), image_mode="L") |
| assert image_input.preprocess(img).shape == (25, 25) |
| image_input = gr.Image(shape=(30, 10), type="pil") |
| assert image_input.preprocess(img).size == (30, 10) |
| assert image_input.postprocess("test/test_files/bus.png") == img |
| assert image_input.serialize("test/test_files/bus.png") == img |
| image_input = gr.Image(type="filepath") |
| image_temp_filepath = image_input.preprocess(img) |
| assert image_temp_filepath in image_input.temp_files |
|
|
| image_input = gr.Image( |
| source="upload", tool="editor", type="pil", label="Upload Your Image" |
| ) |
| assert image_input.get_config() == { |
| "brush_radius": None, |
| "brush_color": "#000000", |
| "mask_opacity": 0.7, |
| "image_mode": "RGB", |
| "shape": None, |
| "source": "upload", |
| "tool": "editor", |
| "name": "image", |
| "show_share_button": False, |
| "show_download_button": True, |
| "streaming": False, |
| "show_label": True, |
| "label": "Upload Your Image", |
| "container": True, |
| "min_width": 160, |
| "scale": None, |
| "height": None, |
| "width": None, |
| "elem_id": None, |
| "elem_classes": None, |
| "visible": True, |
| "value": None, |
| "interactive": None, |
| "root_url": None, |
| "mirror_webcam": True, |
| "selectable": False, |
| "invert_colors": False, |
| "type": "pil", |
| } |
| assert image_input.preprocess(None) is None |
| image_input = gr.Image(invert_colors=True) |
| assert image_input.preprocess(img) is not None |
| image_input.preprocess(img) |
| file_image = gr.Image(type="filepath") |
| assert isinstance(file_image.preprocess(img), str) |
| with pytest.raises(ValueError): |
| gr.Image(type="unknown") |
| image_input.shape = (30, 10) |
|
|
| |
| y_img = gr.processing_utils.decode_base64_to_image( |
| deepcopy(media_data.BASE64_IMAGE) |
| ) |
| image_output = gr.Image() |
| assert image_output.postprocess(y_img).startswith( |
| "data:image/png;base64,iVBORw0KGgoAAA" |
| ) |
| assert image_output.postprocess(np.array(y_img)).startswith( |
| "data:image/png;base64,iVBORw0KGgoAAA" |
| ) |
| with pytest.raises(ValueError): |
| image_output.postprocess([1, 2, 3]) |
| image_output = gr.Image(type="numpy") |
| assert image_output.postprocess(y_img).startswith("data:image/png;base64,") |
|
|
| @pytest.mark.flaky |
| def test_serialize_url(self): |
| img = "https://gradio-builds.s3.amazonaws.com/demo-files/cheetah-002.jpg" |
| expected = client_utils.encode_url_or_file_to_base64(img) |
| assert gr.Image().serialize(img) == expected |
|
|
| def test_in_interface_as_input(self): |
| """ |
| Interface, process, interpret |
| type: file |
| interpretation: default, shap, |
| """ |
| img = "test/test_files/bus.png" |
| image_input = gr.Image() |
| iface = gr.Interface( |
| lambda x: PIL.Image.open(x).rotate(90, expand=True), |
| gr.Image(shape=(30, 10), type="filepath"), |
| "image", |
| ) |
| output = iface(img) |
| assert PIL.Image.open(output).size == (10, 30) |
| iface = gr.Interface( |
| lambda x: np.sum(x), image_input, "number", interpretation="default" |
| ) |
|
|
| def test_as_example(self): |
| |
| url = "https://gradio-static-files.s3.us-west-2.amazonaws.com/header-image.jpg" |
| assert gr.Image().as_example(url) == url |
|
|
| def test_in_interface_as_output(self): |
| """ |
| Interface, process |
| """ |
|
|
| def generate_noise(height, width): |
| return np.random.randint(0, 256, (height, width, 3)) |
|
|
| iface = gr.Interface(generate_noise, ["slider", "slider"], "image") |
| assert iface(10, 20).endswith(".png") |
|
|
| def test_static(self): |
| """ |
| postprocess |
| """ |
| component = gr.Image("test/test_files/bus.png") |
| assert component.get_config().get("value") == media_data.BASE64_IMAGE |
| component = gr.Image(None) |
| assert component.get_config().get("value") is None |
|
|
|
|
| class TestPlot: |
| @pytest.mark.asyncio |
| async def test_in_interface_as_output(self): |
| """ |
| Interface, process |
| """ |
|
|
| def plot(num): |
| import matplotlib.pyplot as plt |
|
|
| fig = plt.figure() |
| plt.plot(range(num), range(num)) |
| return fig |
|
|
| iface = gr.Interface(plot, "slider", "plot") |
| with utils.MatplotlibBackendMananger(): |
| output = await iface.process_api(fn_index=0, inputs=[10], state={}) |
| assert output["data"][0]["type"] == "matplotlib" |
| assert output["data"][0]["plot"].startswith("data:image/png;base64") |
|
|
| def test_static(self): |
| """ |
| postprocess |
| """ |
| with utils.MatplotlibBackendMananger(): |
| import matplotlib.pyplot as plt |
|
|
| fig = plt.figure() |
| plt.plot([1, 2, 3], [1, 2, 3]) |
|
|
| component = gr.Plot(fig) |
| assert component.get_config().get("value") is not None |
| component = gr.Plot(None) |
| assert component.get_config().get("value") is None |
|
|
| def test_postprocess_altair(self): |
| import altair as alt |
| from vega_datasets import data |
|
|
| cars = data.cars() |
| chart = ( |
| alt.Chart(cars) |
| .mark_point() |
| .encode( |
| x="Horsepower", |
| y="Miles_per_Gallon", |
| color="Origin", |
| ) |
| ) |
| out = gr.Plot().postprocess(chart) |
| assert isinstance(out["plot"], str) |
| assert out["plot"] == chart.to_json() |
|
|
|
|
| class TestAudio: |
| def test_component_functions(self): |
| """ |
| Preprocess, postprocess serialize, get_config, deserialize |
| type: filepath, numpy, file |
| """ |
| x_wav = deepcopy(media_data.BASE64_AUDIO) |
| audio_input = gr.Audio() |
| output1 = audio_input.preprocess(x_wav) |
| assert output1[0] == 8000 |
| assert output1[1].shape == (8046,) |
|
|
| x_wav["is_file"] = True |
| audio_input = gr.Audio(type="filepath") |
| output1 = audio_input.preprocess(x_wav) |
| assert Path(output1).name == "audio_sample-0-100.wav" |
|
|
| assert filecmp.cmp( |
| "test/test_files/audio_sample.wav", |
| audio_input.serialize("test/test_files/audio_sample.wav")["name"], |
| ) |
|
|
| audio_input = gr.Audio(label="Upload Your Audio") |
| assert audio_input.get_config() == { |
| "autoplay": False, |
| "source": "upload", |
| "name": "audio", |
| "show_download_button": True, |
| "show_share_button": False, |
| "show_edit_button": True, |
| "streaming": False, |
| "show_label": True, |
| "label": "Upload Your Audio", |
| "container": True, |
| "min_width": 160, |
| "scale": None, |
| "elem_id": None, |
| "elem_classes": None, |
| "visible": True, |
| "value": None, |
| "interactive": None, |
| "root_url": None, |
| "type": "numpy", |
| "format": "wav", |
| } |
| assert audio_input.preprocess(None) is None |
| x_wav["is_example"] = True |
| x_wav["crop_min"], x_wav["crop_max"] = 1, 4 |
| output2 = audio_input.preprocess(x_wav) |
| assert output2 is not None |
| assert output1 != output2 |
|
|
| audio_input = gr.Audio(type="filepath") |
| assert isinstance(audio_input.preprocess(x_wav), str) |
| with pytest.raises(ValueError): |
| gr.Audio(type="unknown") |
|
|
| |
| gr.Audio((100, np.random.random(size=(1000, 2))), label="Play your audio") |
|
|
| |
| y_audio = client_utils.decode_base64_to_file( |
| deepcopy(media_data.BASE64_AUDIO)["data"] |
| ) |
| audio_output = gr.Audio(type="filepath") |
| assert filecmp.cmp(y_audio.name, audio_output.postprocess(y_audio.name)["name"]) |
| assert audio_output.get_config() == { |
| "autoplay": False, |
| "name": "audio", |
| "show_download_button": True, |
| "show_share_button": False, |
| "show_edit_button": True, |
| "streaming": False, |
| "show_label": True, |
| "label": None, |
| "source": "upload", |
| "container": True, |
| "min_width": 160, |
| "scale": None, |
| "elem_id": None, |
| "elem_classes": None, |
| "visible": True, |
| "value": None, |
| "interactive": None, |
| "root_url": None, |
| "type": "filepath", |
| "format": "wav", |
| } |
| assert audio_output.deserialize( |
| { |
| "name": None, |
| "data": deepcopy(media_data.BASE64_AUDIO)["data"], |
| "is_file": False, |
| } |
| ).endswith(".wav") |
|
|
| output1 = audio_output.postprocess(y_audio.name) |
| output2 = audio_output.postprocess(Path(y_audio.name)) |
| assert output1 == output2 |
|
|
| def test_serialize(self): |
| audio_input = gr.Audio() |
| serialized_input = audio_input.serialize("test/test_files/audio_sample.wav") |
| assert serialized_input["data"] == media_data.BASE64_AUDIO["data"] |
| assert os.path.basename(serialized_input["name"]) == "audio_sample.wav" |
| assert serialized_input["orig_name"] == "audio_sample.wav" |
| assert not serialized_input["is_file"] |
|
|
| def test_tokenize(self): |
| """ |
| Tokenize, get_masked_inputs |
| """ |
| x_wav = deepcopy(media_data.BASE64_AUDIO) |
| audio_input = gr.Audio() |
| tokens, _, _ = audio_input.tokenize(x_wav) |
| assert len(tokens) == audio_input.interpretation_segments |
| x_new = audio_input.get_masked_inputs(tokens, [[1] * len(tokens)])[0] |
| similarity = SequenceMatcher(a=x_wav["data"], b=x_new).ratio() |
| assert similarity > 0.9 |
|
|
| def test_in_interface(self): |
| def reverse_audio(audio): |
| sr, data = audio |
| return (sr, np.flipud(data)) |
|
|
| iface = gr.Interface(reverse_audio, "audio", "audio") |
| reversed_file = iface("test/test_files/audio_sample.wav") |
| reversed_reversed_file = iface(reversed_file) |
| reversed_reversed_data = client_utils.encode_url_or_file_to_base64( |
| reversed_reversed_file |
| ) |
| similarity = SequenceMatcher( |
| a=reversed_reversed_data, b=media_data.BASE64_AUDIO["data"] |
| ).ratio() |
| assert similarity > 0.99 |
|
|
| def test_in_interface_as_output(self): |
| """ |
| Interface, process |
| """ |
|
|
| def generate_noise(duration): |
| return 48000, np.random.randint(-256, 256, (duration, 3)).astype(np.int16) |
|
|
| iface = gr.Interface(generate_noise, "slider", "audio") |
| assert iface(100).endswith(".wav") |
|
|
| def test_audio_preprocess_can_be_read_by_scipy(self): |
| x_wav = deepcopy(media_data.BASE64_MICROPHONE) |
| audio_input = gr.Audio(type="filepath") |
| output = audio_input.preprocess(x_wav) |
| wavfile.read(output) |
|
|
| def test_prepost_process_to_mp3(self): |
| x_wav = deepcopy(media_data.BASE64_MICROPHONE) |
| audio_input = gr.Audio(type="filepath", format="mp3") |
| output = audio_input.preprocess(x_wav) |
| assert output.endswith("mp3") |
| output = audio_input.postprocess( |
| (48000, np.random.randint(-256, 256, (5, 3)).astype(np.int16)) |
| ) |
| assert output["name"].endswith("mp3") |
|
|
|
|
| class TestFile: |
| def test_component_functions(self): |
| """ |
| Preprocess, serialize, get_config, value |
| """ |
| x_file = deepcopy(media_data.BASE64_FILE) |
| file_input = gr.File() |
| output = file_input.preprocess(x_file) |
| assert isinstance(output, tempfile._TemporaryFileWrapper) |
| serialized = file_input.serialize("test/test_files/sample_file.pdf") |
| assert filecmp.cmp( |
| serialized["name"], |
| "test/test_files/sample_file.pdf", |
| ) |
| assert serialized["orig_name"] == "sample_file.pdf" |
| assert output.orig_name == "test/test_files/sample_file.pdf" |
|
|
| x_file["is_file"] = True |
| input1 = file_input.preprocess(x_file) |
| input2 = file_input.preprocess(x_file) |
| assert input1.name == input2.name |
| assert Path(input1.name).name == "sample_file.pdf" |
|
|
| file_input = gr.File(label="Upload Your File") |
| assert file_input.get_config() == { |
| "file_count": "single", |
| "file_types": None, |
| "name": "file", |
| "show_label": True, |
| "label": "Upload Your File", |
| "container": True, |
| "min_width": 160, |
| "scale": None, |
| "elem_id": None, |
| "elem_classes": None, |
| "visible": True, |
| "value": None, |
| "interactive": None, |
| "root_url": None, |
| "selectable": False, |
| "height": None, |
| "type": "file", |
| } |
| assert file_input.preprocess(None) is None |
| x_file["is_example"] = True |
| assert file_input.preprocess(x_file) is not None |
|
|
| zero_size_file = {"name": "document.txt", "size": 0, "data": ""} |
| temp_file = file_input.preprocess(zero_size_file) |
| assert os.stat(temp_file.name).st_size == 0 |
|
|
| file_input = gr.File(type="binary") |
| output = file_input.preprocess(x_file) |
| assert type(output) == bytes |
|
|
| output1 = file_input.postprocess("test/test_files/sample_file.pdf") |
| output2 = file_input.postprocess("test/test_files/sample_file.pdf") |
| assert output1 == output2 |
|
|
| def test_file_type_must_be_list(self): |
| with pytest.raises( |
| ValueError, match="Parameter file_types must be a list. Received str" |
| ): |
| gr.File(file_types=".json") |
|
|
| def test_in_interface_as_input(self): |
| """ |
| Interface, process |
| """ |
| x_file = media_data.BASE64_FILE["name"] |
|
|
| def get_size_of_file(file_obj): |
| return os.path.getsize(file_obj.name) |
|
|
| iface = gr.Interface(get_size_of_file, "file", "number") |
| assert iface(x_file) == 10558 |
|
|
| def test_as_component_as_output(self): |
| """ |
| Interface, process |
| """ |
|
|
| def write_file(content): |
| with open("test.txt", "w") as f: |
| f.write(content) |
| return "test.txt" |
|
|
| iface = gr.Interface(write_file, "text", "file") |
| assert iface("hello world").endswith(".txt") |
|
|
|
|
| class TestUploadButton: |
| def test_component_functions(self): |
| """ |
| preprocess |
| """ |
| x_file = deepcopy(media_data.BASE64_FILE) |
| upload_input = gr.UploadButton() |
| input = upload_input.preprocess(x_file) |
| assert isinstance(input, tempfile._TemporaryFileWrapper) |
|
|
| x_file["is_file"] = True |
| input1 = upload_input.preprocess(x_file) |
| input2 = upload_input.preprocess(x_file) |
| assert input1.name == input2.name |
|
|
| def test_raises_if_file_types_is_not_list(self): |
| with pytest.raises( |
| ValueError, match="Parameter file_types must be a list. Received int" |
| ): |
| gr.UploadButton(file_types=2) |
|
|
|
|
| class TestDataframe: |
| def test_component_functions(self): |
| """ |
| Preprocess, serialize, get_config |
| """ |
| x_data = { |
| "data": [["Tim", 12, False], ["Jan", 24, True]], |
| "headers": ["Name", "Age", "Member"], |
| } |
| dataframe_input = gr.Dataframe(headers=["Name", "Age", "Member"]) |
| output = dataframe_input.preprocess(x_data) |
| assert output["Age"][1] == 24 |
| assert not output["Member"][0] |
| assert dataframe_input.postprocess(x_data) == x_data |
|
|
| dataframe_input = gr.Dataframe( |
| headers=["Name", "Age", "Member"], label="Dataframe Input" |
| ) |
| assert dataframe_input.get_config() == { |
| "value": {"headers": ["Name", "Age", "Member"], "data": [["", "", ""]]}, |
| "selectable": False, |
| "headers": ["Name", "Age", "Member"], |
| "row_count": (1, "dynamic"), |
| "col_count": (3, "dynamic"), |
| "datatype": ["str", "str", "str"], |
| "type": "pandas", |
| "max_rows": 20, |
| "max_cols": None, |
| "overflow_row_behaviour": "paginate", |
| "label": "Dataframe Input", |
| "show_label": True, |
| "scale": None, |
| "min_width": 160, |
| "interactive": None, |
| "visible": True, |
| "elem_id": None, |
| "elem_classes": None, |
| "wrap": False, |
| "root_url": None, |
| "name": "dataframe", |
| "height": 500, |
| "latex_delimiters": [{"display": False, "left": "$", "right": "$"}], |
| } |
| dataframe_input = gr.Dataframe() |
| output = dataframe_input.preprocess(x_data) |
| assert output["Age"][1] == 24 |
| with pytest.raises(ValueError): |
| gr.Dataframe(type="unknown") |
|
|
| dataframe_output = gr.Dataframe() |
| assert dataframe_output.get_config() == { |
| "value": {"headers": [1, 2, 3], "data": [["", "", ""]]}, |
| "selectable": False, |
| "headers": [1, 2, 3], |
| "row_count": (1, "dynamic"), |
| "col_count": (3, "dynamic"), |
| "datatype": ["str", "str", "str"], |
| "type": "pandas", |
| "max_rows": 20, |
| "max_cols": None, |
| "overflow_row_behaviour": "paginate", |
| "label": None, |
| "show_label": True, |
| "scale": None, |
| "min_width": 160, |
| "interactive": None, |
| "visible": True, |
| "elem_id": None, |
| "elem_classes": None, |
| "wrap": False, |
| "root_url": None, |
| "name": "dataframe", |
| "height": 500, |
| "latex_delimiters": [{"display": False, "left": "$", "right": "$"}], |
| } |
|
|
| def test_postprocess(self): |
| """ |
| postprocess |
| """ |
| dataframe_output = gr.Dataframe() |
| output = dataframe_output.postprocess([]) |
| assert output == {"data": [[]], "headers": []} |
| output = dataframe_output.postprocess(np.zeros((2, 2))) |
| assert output == {"data": [[0, 0], [0, 0]], "headers": [1, 2]} |
| output = dataframe_output.postprocess([[1, 3, 5]]) |
| assert output == {"data": [[1, 3, 5]], "headers": [1, 2, 3]} |
| output = dataframe_output.postprocess( |
| pd.DataFrame([[2, True], [3, True], [4, False]], columns=["num", "prime"]) |
| ) |
| assert output == { |
| "headers": ["num", "prime"], |
| "data": [[2, True], [3, True], [4, False]], |
| } |
| with pytest.raises(ValueError): |
| gr.Dataframe(type="unknown") |
|
|
| |
| dataframe_output = gr.Dataframe(headers=["one", "two", "three"]) |
| output = dataframe_output.postprocess([[2, True], [3, True]]) |
| assert output == { |
| "headers": ["one", "two"], |
| "data": [[2, True], [3, True]], |
| } |
| dataframe_output = gr.Dataframe(headers=["one", "two", "three"]) |
| output = dataframe_output.postprocess([[2, True, "ab", 4], [3, True, "cd", 5]]) |
| assert output == { |
| "headers": ["one", "two", "three", 4], |
| "data": [[2, True, "ab", 4], [3, True, "cd", 5]], |
| } |
|
|
| def test_dataframe_postprocess_all_types(self): |
| df = pd.DataFrame( |
| { |
| "date_1": pd.date_range("2021-01-01", periods=2), |
| "date_2": pd.date_range("2022-02-15", periods=2).strftime( |
| "%B %d, %Y, %r" |
| ), |
| "number": np.array([0.2233, 0.57281]), |
| "number_2": np.array([84, 23]).astype(np.int64), |
| "bool": [True, False], |
| "markdown": ["# Hello", "# Goodbye"], |
| } |
| ) |
| component = gr.Dataframe( |
| datatype=["date", "date", "number", "number", "bool", "markdown"] |
| ) |
| output = component.postprocess(df) |
| assert output == { |
| "headers": list(df.columns), |
| "data": [ |
| [ |
| pd.Timestamp("2021-01-01 00:00:00"), |
| "February 15, 2022, 12:00:00 AM", |
| 0.2233, |
| 84, |
| True, |
| "# Hello", |
| ], |
| [ |
| pd.Timestamp("2021-01-02 00:00:00"), |
| "February 16, 2022, 12:00:00 AM", |
| 0.57281, |
| 23, |
| False, |
| "# Goodbye", |
| ], |
| ], |
| } |
|
|
| def test_dataframe_postprocess_only_dates(self): |
| df = pd.DataFrame( |
| { |
| "date_1": pd.date_range("2021-01-01", periods=2), |
| "date_2": pd.date_range("2022-02-15", periods=2), |
| } |
| ) |
| component = gr.Dataframe(datatype=["date", "date"]) |
| output = component.postprocess(df) |
| assert output == { |
| "headers": list(df.columns), |
| "data": [ |
| [ |
| pd.Timestamp("2021-01-01 00:00:00"), |
| pd.Timestamp("2022-02-15 00:00:00"), |
| ], |
| [ |
| pd.Timestamp("2021-01-02 00:00:00"), |
| pd.Timestamp("2022-02-16 00:00:00"), |
| ], |
| ], |
| } |
|
|
|
|
| class TestDataset: |
| def test_preprocessing(self): |
| test_file_dir = Path(__file__).parent / "test_files" |
| bus = str(Path(test_file_dir, "bus.png").resolve()) |
|
|
| dataset = gr.Dataset( |
| components=["number", "textbox", "image", "html", "markdown"], |
| samples=[ |
| [5, "hello", bus, "<b>Bold</b>", "**Bold**"], |
| [15, "hi", bus, "<i>Italics</i>", "*Italics*"], |
| ], |
| ) |
|
|
| assert dataset.preprocess(1) == [ |
| 15, |
| "hi", |
| bus, |
| "<i>Italics</i>", |
| "*Italics*", |
| ] |
|
|
| dataset = gr.Dataset( |
| components=["number", "textbox", "image", "html", "markdown"], |
| samples=[ |
| [5, "hello", bus, "<b>Bold</b>", "**Bold**"], |
| [15, "hi", bus, "<i>Italics</i>", "*Italics*"], |
| ], |
| type="index", |
| ) |
|
|
| assert dataset.preprocess(1) == 1 |
|
|
| radio = gr.Radio(choices=[("name 1", "value 1"), ("name 2", "value 2")]) |
| dataset = gr.Dataset(samples=[["value 1"], ["value 2"]], components=[radio]) |
| assert dataset.samples == [["name 1"], ["name 2"]] |
|
|
| def test_postprocessing(self): |
| test_file_dir = Path(Path(__file__).parent, "test_files") |
| bus = Path(test_file_dir, "bus.png") |
|
|
| dataset = gr.Dataset( |
| components=["number", "textbox", "image", "html", "markdown"], type="index" |
| ) |
|
|
| output = dataset.postprocess( |
| samples=[ |
| [5, "hello", bus, "<b>Bold</b>", "**Bold**"], |
| [15, "hi", bus, "<i>Italics</i>", "*Italics*"], |
| ], |
| ) |
|
|
| assert output == { |
| "samples": [ |
| [5, "hello", bus, "<b>Bold</b>", "**Bold**"], |
| [15, "hi", bus, "<i>Italics</i>", "*Italics*"], |
| ], |
| "__type__": "update", |
| } |
|
|
|
|
| class TestVideo: |
| def test_component_functions(self): |
| """ |
| Preprocess, serialize, deserialize, get_config |
| """ |
| x_video = deepcopy(media_data.BASE64_VIDEO) |
| video_input = gr.Video() |
| output1 = video_input.preprocess(x_video) |
| assert isinstance(output1, str) |
| output2 = video_input.preprocess(x_video) |
| assert output1 == output2 |
|
|
| video_input = gr.Video(include_audio=False) |
| output1 = video_input.preprocess(x_video) |
| output2 = video_input.preprocess(x_video) |
| assert output1 == output2 |
|
|
| video_input = gr.Video(label="Upload Your Video") |
| assert video_input.get_config() == { |
| "autoplay": False, |
| "source": "upload", |
| "name": "video", |
| "show_share_button": False, |
| "show_label": True, |
| "label": "Upload Your Video", |
| "container": True, |
| "min_width": 160, |
| "scale": None, |
| "height": None, |
| "width": None, |
| "elem_id": None, |
| "elem_classes": None, |
| "visible": True, |
| "value": None, |
| "interactive": None, |
| "root_url": None, |
| "mirror_webcam": True, |
| "include_audio": True, |
| "format": None, |
| } |
| assert video_input.preprocess(None) is None |
| x_video["is_example"] = True |
| assert video_input.preprocess(x_video) is not None |
| video_input = gr.Video(format="avi") |
| output_video = video_input.preprocess(x_video) |
| assert output_video[-3:] == "avi" |
| assert "flip" not in output_video |
|
|
| assert filecmp.cmp( |
| video_input.serialize(x_video["name"])[0]["name"], x_video["name"] |
| ) |
|
|
| |
| y_vid_path = "test/test_files/video_sample.mp4" |
| subtitles_path = "test/test_files/s1.srt" |
| video_output = gr.Video() |
| output1 = video_output.postprocess(y_vid_path)[0]["name"] |
| assert output1.endswith("mp4") |
| output2 = video_output.postprocess(y_vid_path)[0]["name"] |
| assert output1 == output2 |
| assert ( |
| video_output.postprocess(y_vid_path)[0]["orig_name"] == "video_sample.mp4" |
| ) |
| output_with_subtitles = video_output.postprocess((y_vid_path, subtitles_path)) |
| assert output_with_subtitles[1]["data"].startswith("data") |
|
|
| assert video_output.deserialize( |
| ( |
| { |
| "name": None, |
| "data": deepcopy(media_data.BASE64_VIDEO)["data"], |
| "is_file": False, |
| }, |
| None, |
| ) |
| ).endswith(".mp4") |
|
|
| p_video = gr.Video() |
| video_with_subtitle = gr.Video() |
| postprocessed_video = p_video.postprocess(Path(y_vid_path)) |
| postprocessed_video_with_subtitle = video_with_subtitle.postprocess( |
| (Path(y_vid_path), Path(subtitles_path)) |
| ) |
|
|
| processed_video = ( |
| { |
| "name": "video_sample.mp4", |
| "data": None, |
| "is_file": True, |
| "orig_name": "video_sample.mp4", |
| }, |
| None, |
| ) |
|
|
| processed_video_with_subtitle = ( |
| { |
| "name": "video_sample.mp4", |
| "data": None, |
| "is_file": True, |
| "orig_name": "video_sample.mp4", |
| }, |
| {"name": None, "data": True, "is_file": False}, |
| ) |
| postprocessed_video[0]["name"] = os.path.basename( |
| postprocessed_video[0]["name"] |
| ) |
| assert processed_video == postprocessed_video |
| postprocessed_video_with_subtitle[0]["name"] = os.path.basename( |
| postprocessed_video_with_subtitle[0]["name"] |
| ) |
| if postprocessed_video_with_subtitle[1]["data"]: |
| postprocessed_video_with_subtitle[1]["data"] = True |
| assert processed_video_with_subtitle == postprocessed_video_with_subtitle |
|
|
| def test_in_interface(self): |
| """ |
| Interface, process |
| """ |
| x_video = media_data.BASE64_VIDEO["name"] |
| iface = gr.Interface(lambda x: x, "video", "playable_video") |
| assert iface(x_video).endswith(".mp4") |
|
|
| def test_with_waveform(self): |
| """ |
| Interface, process |
| """ |
| x_audio = media_data.BASE64_AUDIO["name"] |
| iface = gr.Interface(lambda x: gr.make_waveform(x), "audio", "video") |
| assert iface(x_audio).endswith(".mp4") |
|
|
| def test_video_postprocess_converts_to_playable_format(self): |
| test_file_dir = Path(Path(__file__).parent, "test_files") |
| |
| with tempfile.NamedTemporaryFile( |
| suffix="bad_video.mp4", delete=False |
| ) as tmp_not_playable_vid: |
| bad_vid = str(test_file_dir / "bad_video_sample.mp4") |
| assert not processing_utils.video_is_playable(bad_vid) |
| shutil.copy(bad_vid, tmp_not_playable_vid.name) |
| output = gr.Video().postprocess(tmp_not_playable_vid.name) |
| assert processing_utils.video_is_playable(output[0]["name"]) |
|
|
| |
| with tempfile.NamedTemporaryFile( |
| suffix="playable_but_bad_container.mkv", delete=False |
| ) as tmp_not_playable_vid: |
| bad_vid = str(test_file_dir / "playable_but_bad_container.mkv") |
| assert not processing_utils.video_is_playable(bad_vid) |
| shutil.copy(bad_vid, tmp_not_playable_vid.name) |
| output = gr.Video().postprocess(tmp_not_playable_vid.name) |
| assert processing_utils.video_is_playable(output[0]["name"]) |
|
|
| @patch("pathlib.Path.exists", MagicMock(return_value=False)) |
| @patch("gradio.components.video.FFmpeg") |
| def test_video_preprocessing_flips_video_for_webcam(self, mock_ffmpeg): |
| |
| x_video = deepcopy(media_data.BASE64_VIDEO) |
| video_input = gr.Video(source="webcam") |
| _ = video_input.preprocess(x_video) |
|
|
| |
| output_params = mock_ffmpeg.call_args_list[0][1]["outputs"] |
| assert "hflip" in list(output_params.values())[0] |
| assert "flip" in list(output_params.keys())[0] |
|
|
| mock_ffmpeg.reset_mock() |
| _ = gr.Video( |
| source="webcam", mirror_webcam=False, include_audio=True |
| ).preprocess(x_video) |
| mock_ffmpeg.assert_not_called() |
|
|
| mock_ffmpeg.reset_mock() |
| _ = gr.Video(source="upload", format="mp4", include_audio=True).preprocess( |
| x_video |
| ) |
| mock_ffmpeg.assert_not_called() |
|
|
| mock_ffmpeg.reset_mock() |
| output_file = gr.Video( |
| source="webcam", mirror_webcam=True, format="avi" |
| ).preprocess(x_video) |
| output_params = mock_ffmpeg.call_args_list[0][1]["outputs"] |
| assert "hflip" in list(output_params.values())[0] |
| assert "flip" in list(output_params.keys())[0] |
| assert ".avi" in list(output_params.keys())[0] |
| assert ".avi" in output_file |
|
|
| mock_ffmpeg.reset_mock() |
| output_file = gr.Video( |
| source="webcam", mirror_webcam=False, format="avi", include_audio=False |
| ).preprocess(x_video) |
| output_params = mock_ffmpeg.call_args_list[0][1]["outputs"] |
| assert list(output_params.values())[0] == ["-an"] |
| assert "flip" not in Path(list(output_params.keys())[0]).name |
| assert ".avi" in list(output_params.keys())[0] |
| assert ".avi" in output_file |
|
|
| @pytest.mark.flaky |
| def test_preprocess_url(self): |
| output = gr.Video().preprocess( |
| { |
| "name": "https://gradio-builds.s3.amazonaws.com/demo-files/a.mp4", |
| "is_file": True, |
| "data": None, |
| "size": None, |
| "orig_name": "https://gradio-builds.s3.amazonaws.com/demo-files/a.mp4", |
| } |
| ) |
| assert Path(output).name == "a.mp4" and not client_utils.probe_url(output) |
|
|
|
|
| class TestTimeseries: |
| def test_component_functions(self): |
| """ |
| Preprocess, postprocess, get_config, |
| """ |
| timeseries_input = gr.Timeseries(x="time", y=["retail", "food", "other"]) |
| x_timeseries = { |
| "data": [[1] + [2] * len(timeseries_input.y)] * 4, |
| "headers": [timeseries_input.x] + timeseries_input.y, |
| } |
| output = timeseries_input.preprocess(x_timeseries) |
| assert isinstance(output, pd.core.frame.DataFrame) |
|
|
| timeseries_input = gr.Timeseries( |
| x="time", y="retail", label="Upload Your Timeseries" |
| ) |
| assert timeseries_input.get_config() == { |
| "x": "time", |
| "y": ["retail"], |
| "name": "timeseries", |
| "show_label": True, |
| "label": "Upload Your Timeseries", |
| "colors": None, |
| "container": True, |
| "min_width": 160, |
| "scale": None, |
| "elem_id": None, |
| "elem_classes": None, |
| "visible": True, |
| "value": None, |
| "interactive": None, |
| "root_url": None, |
| } |
| assert timeseries_input.preprocess(None) is None |
| x_timeseries["range"] = (0, 1) |
| assert timeseries_input.preprocess(x_timeseries) is not None |
|
|
| |
|
|
| timeseries_output = gr.Timeseries(label="Disease") |
|
|
| assert timeseries_output.get_config() == { |
| "x": None, |
| "y": None, |
| "name": "timeseries", |
| "show_label": True, |
| "label": "Disease", |
| "colors": None, |
| "container": True, |
| "min_width": 160, |
| "scale": None, |
| "elem_id": None, |
| "elem_classes": None, |
| "visible": True, |
| "value": None, |
| "interactive": None, |
| "root_url": None, |
| } |
| data = {"Name": ["Tom", "nick", "krish", "jack"], "Age": [20, 21, 19, 18]} |
| df = pd.DataFrame(data) |
| assert timeseries_output.postprocess(df) == { |
| "headers": ["Name", "Age"], |
| "data": [["Tom", 20], ["nick", 21], ["krish", 19], ["jack", 18]], |
| } |
|
|
| timeseries_output = gr.Timeseries(y="Age", label="Disease") |
| output = timeseries_output.postprocess(df) |
| assert output == { |
| "headers": ["Name", "Age"], |
| "data": [["Tom", 20], ["nick", 21], ["krish", 19], ["jack", 18]], |
| } |
|
|
|
|
| class TestNames: |
| |
| def test_no_duplicate_uncased_names(self, io_components): |
| unique_subclasses_uncased = {s.__name__.lower() for s in io_components} |
| assert len(io_components) == len(unique_subclasses_uncased) |
|
|
|
|
| class TestLabel: |
| def test_component_functions(self): |
| """ |
| Process, postprocess, deserialize |
| """ |
| y = "happy" |
| label_output = gr.Label() |
| label = label_output.postprocess(y) |
| assert label == {"label": "happy"} |
| with open(label_output.deserialize(label)) as f: |
| assert json.load(f) == label |
|
|
| y = {3: 0.7, 1: 0.2, 0: 0.1} |
| label = label_output.postprocess(y) |
| assert label == { |
| "label": 3, |
| "confidences": [ |
| {"label": 3, "confidence": 0.7}, |
| {"label": 1, "confidence": 0.2}, |
| {"label": 0, "confidence": 0.1}, |
| ], |
| } |
| label_output = gr.Label(num_top_classes=2) |
| label = label_output.postprocess(y) |
|
|
| assert label == { |
| "label": 3, |
| "confidences": [ |
| {"label": 3, "confidence": 0.7}, |
| {"label": 1, "confidence": 0.2}, |
| ], |
| } |
| with pytest.raises(ValueError): |
| label_output.postprocess([1, 2, 3]) |
|
|
| test_file_dir = Path(Path(__file__).parent, "test_files") |
| path = str(Path(test_file_dir, "test_label_json.json")) |
| label_dict = label_output.postprocess(path) |
| assert label_dict["label"] == "web site" |
|
|
| assert label_output.get_config() == { |
| "name": "label", |
| "show_label": True, |
| "num_top_classes": 2, |
| "value": {}, |
| "label": None, |
| "container": True, |
| "min_width": 160, |
| "scale": None, |
| "elem_id": None, |
| "elem_classes": None, |
| "visible": True, |
| "root_url": None, |
| "color": None, |
| "selectable": False, |
| } |
|
|
| def test_color_argument(self): |
| label = gr.Label(value=-10, color="red") |
| assert label.get_config()["color"] == "red" |
| update_1 = gr.Label.update(value="bad", color="brown") |
| assert update_1["color"] == "brown" |
| update_2 = gr.Label.update(value="bad", color="#ff9966") |
| assert update_2["color"] == "#ff9966" |
|
|
| update_3 = gr.Label.update( |
| value={"bad": 0.9, "good": 0.09, "so-so": 0.01}, color="green" |
| ) |
| assert update_3["color"] == "green" |
|
|
| update_4 = gr.Label.update(value={"bad": 0.8, "good": 0.18, "so-so": 0.02}) |
| assert update_4["color"] is None |
|
|
| update_5 = gr.Label.update( |
| value={"bad": 0.8, "good": 0.18, "so-so": 0.02}, color=None |
| ) |
| assert update_5["color"] == "transparent" |
|
|
| def test_in_interface(self): |
| """ |
| Interface, process |
| """ |
| x_img = "test/test_files/bus.png" |
|
|
| def rgb_distribution(img): |
| rgb_dist = np.mean(img, axis=(0, 1)) |
| rgb_dist /= np.sum(rgb_dist) |
| rgb_dist = np.round(rgb_dist, decimals=2) |
| return { |
| "red": rgb_dist[0], |
| "green": rgb_dist[1], |
| "blue": rgb_dist[2], |
| } |
|
|
| iface = gr.Interface(rgb_distribution, "image", "label") |
| output_filepath = iface(x_img) |
| with open(output_filepath) as fp: |
| assert json.load(fp) == { |
| "label": "red", |
| "confidences": [ |
| {"label": "red", "confidence": 0.44}, |
| {"label": "green", "confidence": 0.28}, |
| {"label": "blue", "confidence": 0.28}, |
| ], |
| } |
|
|
|
|
| class TestHighlightedText: |
| def test_postprocess(self): |
| """ |
| postprocess |
| """ |
| component = gr.HighlightedText() |
| result = [ |
| ("", None), |
| ("Wolfgang", "PER"), |
| (" lives in ", None), |
| ("Berlin", "LOC"), |
| ("", None), |
| ] |
| result_ = component.postprocess(result) |
| assert result == result_ |
|
|
| text = "Wolfgang lives in Berlin" |
| entities = [ |
| {"entity": "PER", "start": 0, "end": 8}, |
| {"entity": "LOC", "start": 18, "end": 24}, |
| ] |
| result_ = component.postprocess({"text": text, "entities": entities}) |
| assert result == result_ |
|
|
| text = "Wolfgang lives in Berlin" |
| entities = [ |
| {"entity_group": "PER", "start": 0, "end": 8}, |
| {"entity": "LOC", "start": 18, "end": 24}, |
| ] |
| result_ = component.postprocess({"text": text, "entities": entities}) |
| assert result == result_ |
|
|
| |
| text = "Wolfgang lives in Berlin" |
| entities = [ |
| {"entity": "PER", "start": 0, "end": 4}, |
| {"entity": "PER", "start": 4, "end": 8}, |
| {"entity": "LOC", "start": 18, "end": 24}, |
| ] |
| |
| result_after_merge = [ |
| ("", None), |
| ("Wolfgang", "PER"), |
| (" lives in ", None), |
| ("Berlin", "LOC"), |
| ] |
| result_ = component.postprocess({"text": text, "entities": entities}) |
| assert result != result_ |
| assert result_after_merge != result_ |
|
|
| component = gr.HighlightedText(combine_adjacent=True) |
| result_ = component.postprocess({"text": text, "entities": entities}) |
| assert result_after_merge == result_ |
|
|
| component = gr.HighlightedText() |
|
|
| text = "Wolfgang lives in Berlin" |
| entities = [ |
| {"entity": "LOC", "start": 18, "end": 24}, |
| {"entity": "PER", "start": 0, "end": 8}, |
| ] |
| result_ = component.postprocess({"text": text, "entities": entities}) |
| assert result == result_ |
|
|
| text = "I live there" |
| entities = [] |
| result_ = component.postprocess({"text": text, "entities": entities}) |
| assert [(text, None)] == result_ |
|
|
| text = "Wolfgang" |
| entities = [ |
| {"entity": "PER", "start": 0, "end": 8}, |
| ] |
| result_ = component.postprocess({"text": text, "entities": entities}) |
| assert [("", None), (text, "PER"), ("", None)] == result_ |
|
|
| def test_component_functions(self): |
| """ |
| get_config |
| """ |
| ht_output = gr.HighlightedText(color_map={"pos": "green", "neg": "red"}) |
| assert ht_output.get_config() == { |
| "color_map": {"pos": "green", "neg": "red"}, |
| "name": "highlightedtext", |
| "show_label": True, |
| "label": None, |
| "show_legend": False, |
| "container": True, |
| "min_width": 160, |
| "scale": None, |
| "elem_id": None, |
| "elem_classes": None, |
| "visible": True, |
| "value": None, |
| "root_url": None, |
| "selectable": False, |
| "combine_adjacent": False, |
| "adjacent_separator": "", |
| "interactive": None, |
| } |
|
|
| def test_in_interface(self): |
| """ |
| Interface, process |
| """ |
|
|
| def highlight_vowels(sentence): |
| phrases, cur_phrase = [], "" |
| vowels, mode = "aeiou", None |
| for letter in sentence: |
| letter_mode = "vowel" if letter in vowels else "non" |
| if mode is None: |
| mode = letter_mode |
| elif mode != letter_mode: |
| phrases.append((cur_phrase, mode)) |
| cur_phrase = "" |
| mode = letter_mode |
| cur_phrase += letter |
| phrases.append((cur_phrase, mode)) |
| return phrases |
|
|
| iface = gr.Interface(highlight_vowels, "text", "highlight") |
| output_filepath = iface("Helloooo") |
| with open(output_filepath) as fp: |
| output = json.load(fp) |
| assert output == [ |
| ["H", "non"], |
| ["e", "vowel"], |
| ["ll", "non"], |
| ["oooo", "vowel"], |
| ] |
|
|
|
|
| class TestAnnotatedImage: |
| def test_postprocess(self): |
| """ |
| postprocess |
| """ |
| component = gr.AnnotatedImage() |
| img = np.random.randint(0, 255, (100, 100, 3), dtype=np.uint8) |
| mask1 = [40, 40, 50, 50] |
| mask2 = np.zeros((100, 100), dtype=np.uint8) |
| mask2[10:20, 10:20] = 1 |
|
|
| input = (img, [(mask1, "mask1"), (mask2, "mask2")]) |
| result = component.postprocess(input) |
|
|
| base_img_out, (mask1_out, mask2_out) = result |
| base_img_out = PIL.Image.open(base_img_out["name"]) |
|
|
| assert mask1_out[1] == "mask1" |
|
|
| mask1_img_out = PIL.Image.open(mask1_out[0]["name"]) |
| assert mask1_img_out.size == base_img_out.size |
| mask1_array_out = np.array(mask1_img_out) |
| assert np.max(mask1_array_out[40:50, 40:50]) == 255 |
| assert np.max(mask1_array_out[50:60, 50:60]) == 0 |
|
|
| def test_component_functions(self): |
| ht_output = gr.AnnotatedImage(label="sections", show_legend=False) |
| assert ht_output.get_config() == { |
| "name": "annotatedimage", |
| "show_label": True, |
| "label": "sections", |
| "show_legend": False, |
| "container": True, |
| "min_width": 160, |
| "scale": None, |
| "color_map": None, |
| "height": None, |
| "width": None, |
| "elem_id": None, |
| "elem_classes": None, |
| "visible": True, |
| "value": None, |
| "root_url": None, |
| "selectable": False, |
| } |
|
|
| def test_in_interface(self): |
| def mask(img): |
| top_left_corner = [0, 0, 20, 20] |
| random_mask = np.random.randint(0, 2, img.shape[:2]) |
| return (img, [(top_left_corner, "left corner"), (random_mask, "random")]) |
|
|
| iface = gr.Interface(mask, "image", gr.AnnotatedImage()) |
| output_json = iface("test/test_files/bus.png") |
| with open(output_json) as fp: |
| output = json.load(fp) |
| output_img, (mask1, mask1) = output |
| input_img = PIL.Image.open("test/test_files/bus.png") |
| output_img = PIL.Image.open(output_img["name"]) |
| mask1_img = PIL.Image.open(mask1[0]["name"]) |
|
|
| assert output_img.size == input_img.size |
| assert mask1_img.size == input_img.size |
|
|
|
|
| class TestChatbot: |
| def test_component_functions(self): |
| """ |
| Postprocess, get_config |
| """ |
| chatbot = gr.Chatbot() |
| assert chatbot.postprocess([["You are **cool**\nand fun", "so are *you*"]]) == [ |
| ["You are **cool**\nand fun", "so are *you*"] |
| ] |
|
|
| multimodal_msg = [ |
| [("test/test_files/video_sample.mp4",), "cool video"], |
| [("test/test_files/audio_sample.wav",), "cool audio"], |
| [("test/test_files/bus.png", "A bus"), "cool pic"], |
| [(Path("test/test_files/video_sample.mp4"),), "cool video"], |
| [(Path("test/test_files/audio_sample.wav"),), "cool audio"], |
| [(Path("test/test_files/bus.png"), "A bus"), "cool pic"], |
| ] |
| processed_multimodal_msg = [ |
| [ |
| { |
| "name": "video_sample.mp4", |
| "mime_type": "video/mp4", |
| "alt_text": None, |
| "data": None, |
| "is_file": True, |
| }, |
| "cool video", |
| ], |
| [ |
| { |
| "name": "audio_sample.wav", |
| "mime_type": "audio/wav", |
| "alt_text": None, |
| "data": None, |
| "is_file": True, |
| }, |
| "cool audio", |
| ], |
| [ |
| { |
| "name": "bus.png", |
| "mime_type": "image/png", |
| "alt_text": "A bus", |
| "data": None, |
| "is_file": True, |
| }, |
| "cool pic", |
| ], |
| ] * 2 |
| postprocessed_multimodal_msg = chatbot.postprocess(multimodal_msg) |
| postprocessed_multimodal_msg_base_names = [] |
| for x, y in postprocessed_multimodal_msg: |
| if isinstance(x, dict): |
| x["name"] = os.path.basename(x["name"]) |
| postprocessed_multimodal_msg_base_names.append([x, y]) |
| assert postprocessed_multimodal_msg_base_names == processed_multimodal_msg |
|
|
| preprocessed_multimodal_msg = chatbot.preprocess(processed_multimodal_msg) |
| multimodal_msg_base_names = [] |
| for x, y in multimodal_msg: |
| if isinstance(x, tuple): |
| if len(x) > 1: |
| new_x = (os.path.basename(x[0]), x[1]) |
| else: |
| new_x = (os.path.basename(x[0]),) |
| multimodal_msg_base_names.append([new_x, y]) |
| assert multimodal_msg_base_names == preprocessed_multimodal_msg |
|
|
| assert chatbot.get_config() == { |
| "value": [], |
| "label": None, |
| "show_label": True, |
| "name": "chatbot", |
| "show_share_button": False, |
| "visible": True, |
| "elem_id": None, |
| "elem_classes": None, |
| "container": True, |
| "min_width": 160, |
| "scale": None, |
| "height": None, |
| "root_url": None, |
| "selectable": False, |
| "latex_delimiters": [{"display": True, "left": "$$", "right": "$$"}], |
| "likeable": False, |
| "rtl": False, |
| "show_copy_button": False, |
| "avatar_images": (None, None), |
| "sanitize_html": True, |
| "render_markdown": True, |
| "bubble_full_width": True, |
| } |
|
|
|
|
| class TestJSON: |
| def test_component_functions(self): |
| """ |
| Postprocess |
| """ |
| js_output = gr.JSON() |
| assert js_output.postprocess('{"a":1, "b": 2}'), '"{\\"a\\":1, \\"b\\": 2}"' |
| assert js_output.get_config() == { |
| "container": True, |
| "min_width": 160, |
| "scale": None, |
| "elem_id": None, |
| "elem_classes": None, |
| "visible": True, |
| "value": None, |
| "show_label": True, |
| "label": None, |
| "name": "json", |
| "root_url": None, |
| } |
|
|
| @pytest.mark.asyncio |
| async def test_in_interface(self): |
| """ |
| Interface, process |
| """ |
|
|
| def get_avg_age_per_gender(data): |
| return { |
| "M": int(data[data["gender"] == "M"]["age"].mean()), |
| "F": int(data[data["gender"] == "F"]["age"].mean()), |
| "O": int(data[data["gender"] == "O"]["age"].mean()), |
| } |
|
|
| iface = gr.Interface( |
| get_avg_age_per_gender, |
| gr.Dataframe(headers=["gender", "age"]), |
| "json", |
| ) |
| y_data = [ |
| ["M", 30], |
| ["F", 20], |
| ["M", 40], |
| ["O", 20], |
| ["F", 30], |
| ] |
| assert ( |
| await iface.process_api( |
| 0, [{"data": y_data, "headers": ["gender", "age"]}], state={} |
| ) |
| )["data"][0] == { |
| "M": 35, |
| "F": 25, |
| "O": 20, |
| } |
|
|
|
|
| class TestHTML: |
| def test_component_functions(self): |
| """ |
| get_config |
| """ |
| html_component = gr.components.HTML("#Welcome onboard", label="HTML Input") |
| assert html_component.get_config() == { |
| "value": "#Welcome onboard", |
| "label": "HTML Input", |
| "show_label": True, |
| "visible": True, |
| "elem_id": None, |
| "elem_classes": None, |
| "root_url": None, |
| "name": "html", |
| } |
|
|
| def test_in_interface(self): |
| """ |
| Interface, process |
| """ |
|
|
| def bold_text(text): |
| return f"<strong>{text}</strong>" |
|
|
| iface = gr.Interface(bold_text, "text", "html") |
| assert iface("test") == "<strong>test</strong>" |
|
|
|
|
| class TestMarkdown: |
| def test_component_functions(self): |
| markdown_component = gr.Markdown("# Let's learn about $x$", label="Markdown") |
| assert markdown_component.get_config()["value"] == "# Let's learn about $x$" |
|
|
| def test_in_interface(self): |
| """ |
| Interface, process |
| """ |
| iface = gr.Interface(lambda x: x, "text", "markdown") |
| input_data = " Here's an [image](https://gradio.app/images/gradio_logo.png)" |
| output_data = iface(input_data) |
| assert output_data == input_data.strip() |
|
|
|
|
| class TestModel3D: |
| def test_component_functions(self): |
| """ |
| get_config |
| """ |
| model_component = gr.components.Model3D(None, label="Model") |
| assert model_component.get_config() == { |
| "value": None, |
| "clear_color": [0, 0, 0, 0], |
| "label": "Model", |
| "show_label": True, |
| "container": True, |
| "scale": None, |
| "min_width": 160, |
| "visible": True, |
| "elem_id": None, |
| "elem_classes": None, |
| "root_url": None, |
| "name": "model3d", |
| "camera_position": (None, None, None), |
| "height": None, |
| "zoom_speed": 1, |
| } |
|
|
| file = "test/test_files/Box.gltf" |
| output1 = model_component.postprocess(file) |
| output2 = model_component.postprocess(Path(file)) |
| assert output1 == output2 |
|
|
| def test_in_interface(self): |
| """ |
| Interface, process |
| """ |
| iface = gr.Interface(lambda x: x, "model3d", "model3d") |
| input_data = "test/test_files/Box.gltf" |
| output_data = iface(input_data) |
| assert output_data.endswith(".gltf") |
|
|
|
|
| class TestColorPicker: |
| def test_component_functions(self): |
| """ |
| Preprocess, postprocess, serialize, tokenize, get_config |
| """ |
| color_picker_input = gr.ColorPicker() |
| assert color_picker_input.preprocess("#000000") == "#000000" |
| assert color_picker_input.postprocess("#000000") == "#000000" |
| assert color_picker_input.postprocess(None) is None |
| assert color_picker_input.postprocess("#FFFFFF") == "#FFFFFF" |
| assert color_picker_input.serialize("#000000", True) == "#000000" |
|
|
| color_picker_input.interpretation_replacement = "unknown" |
|
|
| assert color_picker_input.get_config() == { |
| "value": None, |
| "show_label": True, |
| "label": None, |
| "container": True, |
| "min_width": 160, |
| "scale": None, |
| "elem_id": None, |
| "elem_classes": None, |
| "visible": True, |
| "interactive": None, |
| "root_url": None, |
| "name": "colorpicker", |
| "info": None, |
| } |
|
|
| def test_in_interface_as_input(self): |
| """ |
| Interface, process, interpret, |
| """ |
| iface = gr.Interface(lambda x: x, "colorpicker", "colorpicker") |
| assert iface("#000000") == "#000000" |
|
|
| def test_in_interface_as_output(self): |
| """ |
| Interface, process |
| |
| """ |
| iface = gr.Interface(lambda x: x, "colorpicker", gr.ColorPicker()) |
| assert iface("#000000") == "#000000" |
|
|
| def test_static(self): |
| """ |
| postprocess |
| """ |
| component = gr.ColorPicker("#000000") |
| assert component.get_config().get("value") == "#000000" |
|
|
|
|
| class TestCarousel: |
| def test_deprecation(self): |
| test_file_dir = Path(Path(__file__).parent, "test_files") |
| with pytest.raises(DeprecationWarning): |
| gr.Carousel([Path(test_file_dir, "bus.png")]) |
|
|
| def test_deprecation_in_interface(self): |
| with pytest.raises(DeprecationWarning): |
| gr.Interface(lambda x: ["lion.jpg"], "textbox", "carousel") |
|
|
| def test_deprecation_in_blocks(self): |
| with pytest.raises(DeprecationWarning): |
| with gr.Blocks(): |
| gr.Textbox() |
| gr.Carousel() |
|
|
|
|
| class TestGallery: |
| @patch("uuid.uuid4", return_value="my-uuid") |
| def test_gallery(self, mock_uuid): |
| gallery = gr.Gallery() |
| test_file_dir = Path(Path(__file__).parent, "test_files") |
| data = [ |
| client_utils.encode_file_to_base64(Path(test_file_dir, "bus.png")), |
| client_utils.encode_file_to_base64(Path(test_file_dir, "cheetah1.jpg")), |
| ] |
|
|
| with tempfile.TemporaryDirectory() as tmpdir: |
| path = gallery.deserialize(data, tmpdir) |
| assert path.endswith("my-uuid") |
| data_restored = gallery.serialize(path) |
| data_restored = [d[0]["data"] for d in data_restored] |
| assert sorted(data) == sorted(data_restored) |
|
|
| postprocessed_gallery = gallery.postprocess([Path("test/test_files/bus.png")]) |
| processed_gallery = [{"name": "bus.png", "data": None, "is_file": True}] |
| postprocessed_gallery[0]["name"] = os.path.basename( |
| postprocessed_gallery[0]["name"] |
| ) |
| assert processed_gallery == postprocessed_gallery |
|
|
|
|
| class TestState: |
| def test_as_component(self): |
| state = gr.State(value=5) |
| assert state.preprocess(10) == 10 |
| assert state.preprocess("abc") == "abc" |
| assert state.stateful |
|
|
| @pytest.mark.asyncio |
| async def test_in_interface(self): |
| def test(x, y=" def"): |
| return (x + y, x + y) |
|
|
| io = gr.Interface(test, ["text", "state"], ["text", "state"]) |
| result = await io.call_function(0, ["abc"]) |
| assert result["prediction"][0] == "abc def" |
| result = await io.call_function(0, ["abc", result["prediction"][0]]) |
| assert result["prediction"][0] == "abcabc def" |
|
|
| @pytest.mark.asyncio |
| async def test_in_blocks(self): |
| with gr.Blocks() as demo: |
| score = gr.State() |
| btn = gr.Button() |
| btn.click(lambda x: x + 1, score, score) |
|
|
| result = await demo.call_function(0, [0]) |
| assert result["prediction"] == 1 |
| result = await demo.call_function(0, [result["prediction"]]) |
| assert result["prediction"] == 2 |
|
|
| @pytest.mark.asyncio |
| async def test_variable_for_backwards_compatibility(self): |
| with gr.Blocks() as demo: |
| score = gr.Variable() |
| btn = gr.Button() |
| btn.click(lambda x: x + 1, score, score) |
|
|
| result = await demo.call_function(0, [0]) |
| assert result["prediction"] == 1 |
| result = await demo.call_function(0, [result["prediction"]]) |
| assert result["prediction"] == 2 |
|
|
|
|
| def test_dataframe_as_example_converts_dataframes(): |
| df_comp = gr.Dataframe() |
| assert df_comp.as_example(pd.DataFrame({"a": [1, 2, 3, 4], "b": [5, 6, 7, 8]})) == [ |
| [1, 5], |
| [2, 6], |
| [3, 7], |
| [4, 8], |
| ] |
| assert df_comp.as_example(np.array([[1, 2], [3, 4.0]])) == [[1.0, 2.0], [3.0, 4.0]] |
|
|
|
|
| @pytest.mark.parametrize("component", [gr.Model3D, gr.File, gr.Audio]) |
| def test_as_example_returns_file_basename(component): |
| component = component() |
| assert component.as_example("/home/freddy/sources/example.ext") == "example.ext" |
| assert component.as_example(None) == "" |
|
|
|
|
| @patch("gradio.components.IOComponent.as_example") |
| @patch("gradio.components.Image.as_example") |
| @patch("gradio.components.File.as_example") |
| @patch("gradio.components.Dataframe.as_example") |
| @patch("gradio.components.Model3D.as_example") |
| def test_dataset_calls_as_example(*mocks): |
| gr.Dataset( |
| components=[gr.Dataframe(), gr.File(), gr.Image(), gr.Model3D(), gr.Textbox()], |
| samples=[ |
| [ |
| pd.DataFrame({"a": np.array([1, 2, 3])}), |
| "foo.png", |
| "bar.jpeg", |
| "duck.obj", |
| "hello", |
| ] |
| ], |
| ) |
| assert all(m.called for m in mocks) |
|
|
|
|
| cars = vega_datasets.data.cars() |
| stocks = vega_datasets.data.stocks() |
| barley = vega_datasets.data.barley() |
| simple = pd.DataFrame( |
| { |
| "a": ["A", "B", "C", "D", "E", "F", "G", "H", "I"], |
| "b": [28, 55, 43, 91, 81, 53, 19, 87, 52], |
| } |
| ) |
|
|
|
|
| class TestScatterPlot: |
| @patch.dict("sys.modules", {"bokeh": MagicMock(__version__="3.0.3")}) |
| def test_get_config(self): |
| print(gr.ScatterPlot().get_config()) |
| assert gr.ScatterPlot().get_config() == { |
| "caption": None, |
| "elem_id": None, |
| "elem_classes": None, |
| "interactive": None, |
| "label": None, |
| "name": "plot", |
| "bokeh_version": "3.0.3", |
| "show_actions_button": False, |
| "root_url": None, |
| "show_label": True, |
| "container": True, |
| "min_width": 160, |
| "scale": None, |
| "value": None, |
| "visible": True, |
| "x": None, |
| "y": None, |
| "color": None, |
| "size": None, |
| "shape": None, |
| "title": None, |
| "tooltip": None, |
| "x_title": None, |
| "y_title": None, |
| "color_legend_title": None, |
| "size_legend_title": None, |
| "shape_legend_title": None, |
| "color_legend_position": None, |
| "size_legend_position": None, |
| "shape_legend_position": None, |
| "height": None, |
| "width": None, |
| "x_lim": None, |
| "y_lim": None, |
| "x_label_angle": None, |
| "y_label_angle": None, |
| } |
|
|
| def test_no_color(self): |
| plot = gr.ScatterPlot( |
| x="Horsepower", |
| y="Miles_per_Gallon", |
| tooltip="Name", |
| title="Car Data", |
| x_title="Horse", |
| ) |
| output = plot.postprocess(cars) |
| assert sorted(output.keys()) == ["chart", "plot", "type"] |
| config = json.loads(output["plot"]) |
| assert config["encoding"]["x"]["field"] == "Horsepower" |
| assert config["encoding"]["x"]["title"] == "Horse" |
| assert config["encoding"]["y"]["field"] == "Miles_per_Gallon" |
| assert config["title"] == "Car Data" |
| assert "height" not in config |
| assert "width" not in config |
|
|
| def test_no_interactive(self): |
| plot = gr.ScatterPlot( |
| x="Horsepower", y="Miles_per_Gallon", tooltip="Name", interactive=False |
| ) |
| output = plot.postprocess(cars) |
| assert sorted(output.keys()) == ["chart", "plot", "type"] |
| config = json.loads(output["plot"]) |
| assert "selection" not in config |
|
|
| def test_height_width(self): |
| plot = gr.ScatterPlot( |
| x="Horsepower", y="Miles_per_Gallon", height=100, width=200 |
| ) |
| output = plot.postprocess(cars) |
| assert sorted(output.keys()) == ["chart", "plot", "type"] |
| config = json.loads(output["plot"]) |
| assert config["height"] == 100 |
| assert config["width"] == 200 |
|
|
| def test_xlim_ylim(self): |
| plot = gr.ScatterPlot( |
| x="Horsepower", y="Miles_per_Gallon", x_lim=[200, 400], y_lim=[300, 500] |
| ) |
| output = plot.postprocess(cars) |
| config = json.loads(output["plot"]) |
| assert config["encoding"]["x"]["scale"] == {"domain": [200, 400]} |
| assert config["encoding"]["y"]["scale"] == {"domain": [300, 500]} |
|
|
| def test_color_encoding(self): |
| plot = gr.ScatterPlot( |
| x="Horsepower", |
| y="Miles_per_Gallon", |
| tooltip="Name", |
| title="Car Data", |
| color="Origin", |
| ) |
| output = plot.postprocess(cars) |
| config = json.loads(output["plot"]) |
| assert config["encoding"]["color"]["field"] == "Origin" |
| assert config["encoding"]["color"]["scale"] == { |
| "domain": ["USA", "Europe", "Japan"], |
| "range": [0, 1, 2], |
| } |
| assert config["encoding"]["color"]["type"] == "nominal" |
|
|
| def test_two_encodings(self): |
| plot = gr.ScatterPlot( |
| show_label=False, |
| title="Two encodings", |
| x="Horsepower", |
| y="Miles_per_Gallon", |
| color="Acceleration", |
| shape="Origin", |
| ) |
| output = plot.postprocess(cars) |
| config = json.loads(output["plot"]) |
| assert config["encoding"]["color"]["field"] == "Acceleration" |
| assert config["encoding"]["color"]["scale"] == { |
| "domain": [cars.Acceleration.min(), cars.Acceleration.max()], |
| "range": [0, 1], |
| } |
| assert config["encoding"]["color"]["type"] == "quantitative" |
|
|
| assert config["encoding"]["shape"]["field"] == "Origin" |
| assert config["encoding"]["shape"]["type"] == "nominal" |
|
|
| def test_legend_position(self): |
| plot = gr.ScatterPlot( |
| show_label=False, |
| title="Two encodings", |
| x="Horsepower", |
| y="Miles_per_Gallon", |
| color="Acceleration", |
| color_legend_position="none", |
| color_legend_title="Foo", |
| shape="Origin", |
| shape_legend_position="none", |
| shape_legend_title="Bar", |
| size="Acceleration", |
| size_legend_title="Accel", |
| size_legend_position="none", |
| ) |
| output = plot.postprocess(cars) |
| config = json.loads(output["plot"]) |
| assert config["encoding"]["color"]["legend"] is None |
| assert config["encoding"]["shape"]["legend"] is None |
| assert config["encoding"]["size"]["legend"] is None |
|
|
| output = gr.ScatterPlot.update( |
| value=cars, |
| title="Two encodings", |
| x="Horsepower", |
| y="Miles_per_Gallon", |
| color="Acceleration", |
| color_legend_position="top", |
| color_legend_title="Foo", |
| shape="Origin", |
| shape_legend_position="bottom", |
| shape_legend_title="Bar", |
| size="Acceleration", |
| size_legend_title="Accel", |
| size_legend_position="left", |
| ) |
|
|
| config = json.loads(output["value"]["plot"]) |
| assert config["encoding"]["color"]["legend"]["orient"] == "top" |
| assert config["encoding"]["shape"]["legend"]["orient"] == "bottom" |
| assert config["encoding"]["size"]["legend"]["orient"] == "left" |
|
|
| def test_update(self): |
| output = gr.ScatterPlot.update(value=cars, x="Horsepower", y="Miles_per_Gallon") |
| postprocessed = gr.ScatterPlot().postprocess(output["value"]) |
| assert postprocessed == output["value"] |
|
|
| def test_update_visibility(self): |
| output = gr.ScatterPlot.update(visible=False) |
| assert not output["visible"] |
| assert output["value"] is gr.components._Keywords.NO_VALUE |
|
|
| def test_update_errors(self): |
| with pytest.raises( |
| ValueError, match="In order to update plot properties the value parameter" |
| ): |
| gr.ScatterPlot.update(x="foo", y="bar") |
|
|
| with pytest.raises( |
| ValueError, |
| match="In order to update plot properties, the x and y axis data", |
| ): |
| gr.ScatterPlot.update(value=cars, x="foo") |
|
|
| def test_scatterplot_accepts_fn_as_value(self): |
| plot = gr.ScatterPlot( |
| value=lambda: cars.sample(frac=0.1, replace=False), |
| x="Horsepower", |
| y="Miles_per_Gallon", |
| color="Origin", |
| ) |
| assert isinstance(plot.value, dict) |
| assert isinstance(plot.value["plot"], str) |
|
|
|
|
| class TestLinePlot: |
| @patch.dict("sys.modules", {"bokeh": MagicMock(__version__="3.0.3")}) |
| def test_get_config(self): |
| assert gr.LinePlot().get_config() == { |
| "caption": None, |
| "elem_id": None, |
| "elem_classes": None, |
| "interactive": None, |
| "label": None, |
| "name": "plot", |
| "bokeh_version": "3.0.3", |
| "show_actions_button": False, |
| "root_url": None, |
| "show_label": True, |
| "container": True, |
| "min_width": 160, |
| "scale": None, |
| "value": None, |
| "visible": True, |
| "x": None, |
| "y": None, |
| "color": None, |
| "stroke_dash": None, |
| "overlay_point": None, |
| "title": None, |
| "tooltip": None, |
| "x_title": None, |
| "y_title": None, |
| "color_legend_title": None, |
| "stroke_dash_legend_title": None, |
| "color_legend_position": None, |
| "stroke_dash_legend_position": None, |
| "height": None, |
| "width": None, |
| "x_lim": None, |
| "y_lim": None, |
| "x_label_angle": None, |
| "y_label_angle": None, |
| } |
|
|
| def test_no_color(self): |
| plot = gr.LinePlot( |
| x="date", |
| y="price", |
| tooltip=["symbol", "price"], |
| title="Stock Performance", |
| x_title="Trading Day", |
| ) |
| output = plot.postprocess(stocks) |
| assert sorted(output.keys()) == ["chart", "plot", "type"] |
| config = json.loads(output["plot"]) |
| for layer in config["layer"]: |
| assert layer["mark"]["type"] in ["line", "point"] |
| assert layer["encoding"]["x"]["field"] == "date" |
| assert layer["encoding"]["x"]["title"] == "Trading Day" |
| assert layer["encoding"]["y"]["field"] == "price" |
|
|
| assert config["title"] == "Stock Performance" |
| assert "height" not in config |
| assert "width" not in config |
|
|
| def test_height_width(self): |
| plot = gr.LinePlot(x="date", y="price", height=100, width=200) |
| output = plot.postprocess(stocks) |
| assert sorted(output.keys()) == ["chart", "plot", "type"] |
| config = json.loads(output["plot"]) |
| assert config["height"] == 100 |
| assert config["width"] == 200 |
|
|
| output = gr.LinePlot.update(stocks, x="date", y="price", height=100, width=200) |
| config = json.loads(output["value"]["plot"]) |
| assert config["height"] == 100 |
| assert config["width"] == 200 |
|
|
| def test_xlim_ylim(self): |
| plot = gr.LinePlot(x="date", y="price", x_lim=[200, 400], y_lim=[300, 500]) |
| output = plot.postprocess(stocks) |
| config = json.loads(output["plot"]) |
| for layer in config["layer"]: |
| assert layer["encoding"]["x"]["scale"] == {"domain": [200, 400]} |
| assert layer["encoding"]["y"]["scale"] == {"domain": [300, 500]} |
|
|
| def test_color_encoding(self): |
| plot = gr.LinePlot( |
| x="date", y="price", tooltip="symbol", color="symbol", overlay_point=True |
| ) |
| output = plot.postprocess(stocks) |
| config = json.loads(output["plot"]) |
| for layer in config["layer"]: |
| assert layer["encoding"]["color"]["field"] == "symbol" |
| assert layer["encoding"]["color"]["scale"] == { |
| "domain": ["MSFT", "AMZN", "IBM", "GOOG", "AAPL"], |
| "range": [0, 1, 2, 3, 4], |
| } |
| assert layer["encoding"]["color"]["type"] == "nominal" |
| if layer["mark"]["type"] == "point": |
| assert layer["encoding"]["opacity"] == {} |
|
|
| def test_two_encodings(self): |
| output = gr.LinePlot.update( |
| value=stocks, |
| title="Two encodings", |
| x="date", |
| y="price", |
| color="symbol", |
| stroke_dash="symbol", |
| color_legend_title="Color", |
| stroke_dash_legend_title="Stroke Dash", |
| ) |
| config = json.loads(output["value"]["plot"]) |
| for layer in config["layer"]: |
| if layer["mark"]["type"] == "point": |
| assert layer["encoding"]["opacity"] == {"value": 0} |
| if layer["mark"]["type"] == "line": |
| assert layer["encoding"]["strokeDash"]["field"] == "symbol" |
| assert ( |
| layer["encoding"]["strokeDash"]["legend"]["title"] == "Stroke Dash" |
| ) |
|
|
| def test_legend_position(self): |
| plot = gr.LinePlot( |
| value=stocks, |
| title="Two encodings", |
| x="date", |
| y="price", |
| color="symbol", |
| stroke_dash="symbol", |
| color_legend_position="none", |
| stroke_dash_legend_position="none", |
| ) |
| output = plot.postprocess(stocks) |
| config = json.loads(output["plot"]) |
| for layer in config["layer"]: |
| if layer["mark"]["type"] == "point": |
| assert layer["encoding"]["color"]["legend"] is None |
| if layer["mark"]["type"] == "line": |
| assert layer["encoding"]["strokeDash"]["legend"] is None |
| assert layer["encoding"]["color"]["legend"] is None |
|
|
| output = gr.LinePlot.update( |
| value=stocks, |
| title="Two encodings", |
| x="date", |
| y="price", |
| color="symbol", |
| stroke_dash="symbol", |
| color_legend_position="top-right", |
| stroke_dash_legend_position="top-left", |
| ) |
|
|
| config = json.loads(output["value"]["plot"]) |
| for layer in config["layer"]: |
| if layer["mark"]["type"] == "point": |
| assert layer["encoding"]["color"]["legend"]["orient"] == "top-right" |
| if layer["mark"]["type"] == "line": |
| assert layer["encoding"]["strokeDash"]["legend"]["orient"] == "top-left" |
| assert layer["encoding"]["color"]["legend"]["orient"] == "top-right" |
|
|
| def test_update_visibility(self): |
| output = gr.LinePlot.update(visible=False) |
| assert not output["visible"] |
| assert output["value"] is gr.components._Keywords.NO_VALUE |
|
|
| def test_update_errors(self): |
| with pytest.raises( |
| ValueError, match="In order to update plot properties the value parameter" |
| ): |
| gr.LinePlot.update(x="foo", y="bar") |
|
|
| with pytest.raises( |
| ValueError, |
| match="In order to update plot properties, the x and y axis data", |
| ): |
| gr.LinePlot.update(value=stocks, x="foo") |
|
|
| def test_lineplot_accepts_fn_as_value(self): |
| plot = gr.LinePlot( |
| value=lambda: stocks.sample(frac=0.1, replace=False), |
| x="date", |
| y="price", |
| color="symbol", |
| ) |
| assert isinstance(plot.value, dict) |
| assert isinstance(plot.value["plot"], str) |
|
|
|
|
| class TestBarPlot: |
| @patch.dict("sys.modules", {"bokeh": MagicMock(__version__="3.0.3")}) |
| def test_get_config(self): |
| assert gr.BarPlot().get_config() == { |
| "caption": None, |
| "elem_id": None, |
| "elem_classes": None, |
| "interactive": None, |
| "label": None, |
| "name": "plot", |
| "bokeh_version": "3.0.3", |
| "show_actions_button": False, |
| "root_url": None, |
| "show_label": True, |
| "container": True, |
| "min_width": 160, |
| "scale": None, |
| "value": None, |
| "visible": True, |
| "x": None, |
| "y": None, |
| "color": None, |
| "vertical": True, |
| "group": None, |
| "title": None, |
| "tooltip": None, |
| "x_title": None, |
| "y_title": None, |
| "color_legend_title": None, |
| "group_title": None, |
| "color_legend_position": None, |
| "height": None, |
| "width": None, |
| "y_lim": None, |
| "x_label_angle": None, |
| "y_label_angle": None, |
| "sort": None, |
| } |
|
|
| def test_update_defaults_none(self): |
| output = gr.BarPlot.update(simple, x="a", y="b", height=100, width=200) |
| assert all( |
| v is None for k, v in output.items() if k not in ["value", "__type__"] |
| ) |
|
|
| def test_no_color(self): |
| plot = gr.BarPlot( |
| x="a", |
| y="b", |
| tooltip=["a", "b"], |
| title="Made Up Bar Plot", |
| x_title="Variable A", |
| sort="x", |
| ) |
| output = plot.postprocess(simple) |
| assert sorted(output.keys()) == ["chart", "plot", "type"] |
| assert output["chart"] == "bar" |
| config = json.loads(output["plot"]) |
| assert config["encoding"]["x"]["sort"] == "x" |
| assert config["encoding"]["x"]["field"] == "a" |
| assert config["encoding"]["x"]["title"] == "Variable A" |
| assert config["encoding"]["y"]["field"] == "b" |
| assert config["encoding"]["y"]["title"] == "b" |
|
|
| assert config["title"] == "Made Up Bar Plot" |
| assert "height" not in config |
| assert "width" not in config |
|
|
| def test_height_width(self): |
| plot = gr.BarPlot(x="a", y="b", height=100, width=200) |
| output = plot.postprocess(simple) |
| assert sorted(output.keys()) == ["chart", "plot", "type"] |
| config = json.loads(output["plot"]) |
| assert config["height"] == 100 |
| assert config["width"] == 200 |
|
|
| output = gr.BarPlot.update(simple, x="a", y="b", height=100, width=200) |
| config = json.loads(output["value"]["plot"]) |
| assert config["height"] == 100 |
| assert config["width"] == 200 |
|
|
| def test_ylim(self): |
| plot = gr.BarPlot(x="a", y="b", y_lim=[15, 100]) |
| output = plot.postprocess(simple) |
| config = json.loads(output["plot"]) |
| assert config["encoding"]["y"]["scale"] == {"domain": [15, 100]} |
|
|
| def test_horizontal(self): |
| output = gr.BarPlot.update( |
| simple, |
| x="a", |
| y="b", |
| x_title="Variable A", |
| y_title="Variable B", |
| title="Simple Bar Plot with made up data", |
| tooltip=["a", "b"], |
| vertical=False, |
| y_lim=[20, 100], |
| ) |
| assert output["value"]["chart"] == "bar" |
| config = json.loads(output["value"]["plot"]) |
| assert config["encoding"]["x"]["field"] == "b" |
| assert config["encoding"]["x"]["scale"] == {"domain": [20, 100]} |
| assert config["encoding"]["x"]["title"] == "Variable B" |
|
|
| assert config["encoding"]["y"]["field"] == "a" |
| assert config["encoding"]["y"]["title"] == "Variable A" |
|
|
| def test_stack_via_color(self): |
| output = gr.BarPlot.update( |
| barley, |
| x="variety", |
| y="yield", |
| color="site", |
| title="Barley Yield Data", |
| color_legend_title="Site", |
| color_legend_position="bottom", |
| ) |
| config = json.loads(output["value"]["plot"]) |
| assert config["encoding"]["color"]["field"] == "site" |
| assert config["encoding"]["color"]["legend"] == { |
| "title": "Site", |
| "orient": "bottom", |
| } |
| assert config["encoding"]["color"]["scale"] == { |
| "domain": [ |
| "University Farm", |
| "Waseca", |
| "Morris", |
| "Crookston", |
| "Grand Rapids", |
| "Duluth", |
| ], |
| "range": [0, 1, 2, 3, 4, 5], |
| } |
|
|
| def test_group(self): |
| output = gr.BarPlot.update( |
| barley, |
| x="year", |
| y="yield", |
| color="year", |
| group="site", |
| title="Barley Yield by Year and Site", |
| group_title="", |
| tooltip=["yield", "site", "year"], |
| ) |
| config = json.loads(output["value"]["plot"]) |
| assert config["encoding"]["column"] == {"field": "site", "title": ""} |
|
|
| def test_group_horizontal(self): |
| output = gr.BarPlot.update( |
| barley, |
| x="year", |
| y="yield", |
| color="year", |
| group="site", |
| title="Barley Yield by Year and Site", |
| group_title="Site Title", |
| tooltip=["yield", "site", "year"], |
| vertical=False, |
| ) |
| config = json.loads(output["value"]["plot"]) |
| assert config["encoding"]["row"] == {"field": "site", "title": "Site Title"} |
|
|
| def test_barplot_accepts_fn_as_value(self): |
| plot = gr.BarPlot( |
| value=lambda: barley.sample(frac=0.1, replace=False), |
| x="year", |
| y="yield", |
| ) |
| assert isinstance(plot.value, dict) |
| assert isinstance(plot.value["plot"], str) |
|
|
|
|
| class TestCode: |
| def test_component_functions(self): |
| """ |
| Preprocess, postprocess, serialize, get_config |
| """ |
| code = gr.Code() |
|
|
| assert code.preprocess("# hello friends") == "# hello friends" |
| assert code.preprocess("def fn(a):\n return a") == "def fn(a):\n return a" |
|
|
| assert ( |
| code.postprocess( |
| """ |
| def fn(a): |
| return a |
| """ |
| ) |
| == """def fn(a): |
| return a""" |
| ) |
|
|
| test_file_dir = Path(Path(__file__).parent, "test_files") |
| path = str(Path(test_file_dir, "test_label_json.json")) |
| with open(path) as f: |
| assert code.postprocess(path) == path |
| assert code.postprocess((path,)) == f.read() |
|
|
| assert code.serialize("def fn(a):\n return a") == "def fn(a):\n return a" |
| assert code.deserialize("def fn(a):\n return a") == "def fn(a):\n return a" |
|
|
| assert code.get_config() == { |
| "value": None, |
| "language": None, |
| "lines": 5, |
| "name": "code", |
| "show_label": True, |
| "label": None, |
| "container": True, |
| "min_width": 160, |
| "scale": None, |
| "elem_id": None, |
| "elem_classes": None, |
| "visible": True, |
| "interactive": None, |
| "root_url": None, |
| } |
|
|
|
|
| class TestTempFileManagement: |
| def test_hash_file(self): |
| temp_file_manager = gr.File() |
| h1 = temp_file_manager.hash_file("gradio/test_data/cheetah1.jpg") |
| h2 = temp_file_manager.hash_file("gradio/test_data/cheetah1-copy.jpg") |
| h3 = temp_file_manager.hash_file("gradio/test_data/cheetah2.jpg") |
| assert h1 == h2 |
| assert h1 != h3 |
|
|
| @patch("shutil.copy2") |
| def test_make_temp_copy_if_needed(self, mock_copy): |
| temp_file_manager = gr.File() |
|
|
| f = temp_file_manager.make_temp_copy_if_needed("gradio/test_data/cheetah1.jpg") |
| try: |
| os.remove(f) |
| except OSError: |
| pass |
|
|
| f = temp_file_manager.make_temp_copy_if_needed("gradio/test_data/cheetah1.jpg") |
| assert mock_copy.called |
| assert len(temp_file_manager.temp_files) == 1 |
| assert Path(f).name == "cheetah1.jpg" |
|
|
| f = temp_file_manager.make_temp_copy_if_needed("gradio/test_data/cheetah1.jpg") |
| assert len(temp_file_manager.temp_files) == 1 |
|
|
| f = temp_file_manager.make_temp_copy_if_needed( |
| "gradio/test_data/cheetah1-copy.jpg" |
| ) |
| assert len(temp_file_manager.temp_files) == 2 |
| assert Path(f).name == "cheetah1-copy.jpg" |
|
|
| def test_base64_to_temp_file_if_needed(self): |
| temp_file_manager = gr.File() |
|
|
| base64_file_1 = media_data.BASE64_IMAGE |
| base64_file_2 = media_data.BASE64_AUDIO["data"] |
|
|
| f = temp_file_manager.base64_to_temp_file_if_needed(base64_file_1) |
| try: |
| os.remove(f) |
| except OSError: |
| pass |
|
|
| f = temp_file_manager.base64_to_temp_file_if_needed(base64_file_1) |
| assert len(temp_file_manager.temp_files) == 1 |
|
|
| f = temp_file_manager.base64_to_temp_file_if_needed(base64_file_1) |
| assert len(temp_file_manager.temp_files) == 1 |
|
|
| f = temp_file_manager.base64_to_temp_file_if_needed(base64_file_2) |
| assert len(temp_file_manager.temp_files) == 2 |
|
|
| for file in temp_file_manager.temp_files: |
| os.remove(file) |
|
|
| @pytest.mark.flaky |
| @patch("shutil.copyfileobj") |
| def test_download_temp_copy_if_needed(self, mock_copy): |
| temp_file_manager = gr.File() |
| url1 = "https://raw.githubusercontent.com/gradio-app/gradio/main/gradio/test_data/test_image.png" |
| url2 = "https://raw.githubusercontent.com/gradio-app/gradio/main/gradio/test_data/cheetah1.jpg" |
|
|
| f = temp_file_manager.download_temp_copy_if_needed(url1) |
| try: |
| os.remove(f) |
| except OSError: |
| pass |
|
|
| f = temp_file_manager.download_temp_copy_if_needed(url1) |
| assert mock_copy.called |
| assert len(temp_file_manager.temp_files) == 1 |
|
|
| f = temp_file_manager.download_temp_copy_if_needed(url1) |
| assert len(temp_file_manager.temp_files) == 1 |
|
|
| f = temp_file_manager.download_temp_copy_if_needed(url2) |
| assert len(temp_file_manager.temp_files) == 2 |
|
|
|
|
| def test_type_arg_deperecation_warning(): |
| with pytest.warns(GradioUnusedKwargWarning): |
| gr.Video(type="filepath") |
|
|
|
|
| def test_plot_arg_deprecation_warning(): |
| with pytest.warns(GradioDeprecationWarning): |
| gr.Image(plot=True) |
|
|
| with pytest.warns(GradioUnusedKwargWarning): |
| gr.File(plot=True) |
|
|