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261 lines
11 KiB
Python
261 lines
11 KiB
Python
import os
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import pathlib
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import unittest
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import transformers
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import gradio as gr
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"""
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WARNING: These tests have an external dependency: namely that Hugging Face's
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Hub and Space APIs do not change, and they keep their most famous models up.
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So if, e.g. Spaces is down, then these test will not pass.
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"""
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os.environ["GRADIO_ANALYTICS_ENABLED"] = "False"
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class TestHuggingFaceModelAPI(unittest.TestCase):
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def test_audio_to_audio(self):
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model_type = "audio-to-audio"
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interface_info = gr.external.get_huggingface_interface(
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"facebook/xm_transformer_600m-es_en-multi_domain",
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api_key=None,
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alias=model_type,
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)
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self.assertEqual(interface_info["fn"].__name__, model_type)
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self.assertIsInstance(interface_info["inputs"], gr.inputs.Audio)
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self.assertIsInstance(interface_info["outputs"], gr.outputs.Audio)
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def test_question_answering(self):
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model_type = "question-answering"
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interface_info = gr.external.get_huggingface_interface(
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"deepset/roberta-base-squad2", api_key=None, alias=model_type
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)
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self.assertEqual(interface_info["fn"].__name__, model_type)
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self.assertIsInstance(interface_info["inputs"][0], gr.inputs.Textbox)
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self.assertIsInstance(interface_info["inputs"][1], gr.inputs.Textbox)
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self.assertIsInstance(interface_info["outputs"][0], gr.outputs.Textbox)
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self.assertIsInstance(interface_info["outputs"][1], gr.outputs.Label)
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def test_text_generation(self):
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model_type = "text_generation"
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interface_info = gr.external.get_huggingface_interface(
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"gpt2", api_key=None, alias=model_type
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)
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self.assertEqual(interface_info["fn"].__name__, model_type)
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self.assertIsInstance(interface_info["inputs"], gr.inputs.Textbox)
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self.assertIsInstance(interface_info["outputs"], gr.outputs.Textbox)
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def test_summarization(self):
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model_type = "summarization"
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interface_info = gr.external.get_huggingface_interface(
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"facebook/bart-large-cnn", api_key=None, alias=model_type
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)
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self.assertEqual(interface_info["fn"].__name__, model_type)
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self.assertIsInstance(interface_info["inputs"], gr.inputs.Textbox)
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self.assertIsInstance(interface_info["outputs"], gr.outputs.Textbox)
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def test_translation(self):
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model_type = "translation"
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interface_info = gr.external.get_huggingface_interface(
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"facebook/bart-large-cnn", api_key=None, alias=model_type
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)
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self.assertEqual(interface_info["fn"].__name__, model_type)
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self.assertIsInstance(interface_info["inputs"], gr.inputs.Textbox)
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self.assertIsInstance(interface_info["outputs"], gr.outputs.Textbox)
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def test_text2text_generation(self):
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model_type = "text2text-generation"
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interface_info = gr.external.get_huggingface_interface(
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"sshleifer/tiny-mbart", api_key=None, alias=model_type
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)
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self.assertEqual(interface_info["fn"].__name__, model_type)
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self.assertIsInstance(interface_info["inputs"], gr.inputs.Textbox)
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self.assertIsInstance(interface_info["outputs"], gr.outputs.Textbox)
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def test_text_classification(self):
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model_type = "text-classification"
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interface_info = gr.external.get_huggingface_interface(
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"distilbert-base-uncased-finetuned-sst-2-english",
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api_key=None,
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alias=model_type,
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)
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self.assertEqual(interface_info["fn"].__name__, model_type)
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self.assertIsInstance(interface_info["inputs"], gr.inputs.Textbox)
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self.assertIsInstance(interface_info["outputs"], gr.outputs.Label)
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def test_fill_mask(self):
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model_type = "fill-mask"
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interface_info = gr.external.get_huggingface_interface(
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"bert-base-uncased", api_key=None, alias=model_type
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)
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self.assertEqual(interface_info["fn"].__name__, model_type)
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self.assertIsInstance(interface_info["inputs"], gr.inputs.Textbox)
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self.assertIsInstance(interface_info["outputs"], gr.outputs.Label)
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def test_zero_shot_classification(self):
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model_type = "zero-shot-classification"
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interface_info = gr.external.get_huggingface_interface(
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"facebook/bart-large-mnli", api_key=None, alias=model_type
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)
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self.assertEqual(interface_info["fn"].__name__, model_type)
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self.assertIsInstance(interface_info["inputs"][0], gr.inputs.Textbox)
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self.assertIsInstance(interface_info["inputs"][1], gr.inputs.Textbox)
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self.assertIsInstance(interface_info["inputs"][2], gr.inputs.Checkbox)
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self.assertIsInstance(interface_info["outputs"], gr.outputs.Label)
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def test_automatic_speech_recognition(self):
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model_type = "automatic-speech-recognition"
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interface_info = gr.external.get_huggingface_interface(
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"facebook/wav2vec2-base-960h", api_key=None, alias=model_type
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)
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self.assertEqual(interface_info["fn"].__name__, model_type)
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self.assertIsInstance(interface_info["inputs"], gr.inputs.Audio)
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self.assertIsInstance(interface_info["outputs"], gr.outputs.Textbox)
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def test_image_classification(self):
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model_type = "image-classification"
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interface_info = gr.external.get_huggingface_interface(
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"google/vit-base-patch16-224", api_key=None, alias=model_type
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)
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self.assertEqual(interface_info["fn"].__name__, model_type)
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self.assertIsInstance(interface_info["inputs"], gr.inputs.Image)
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self.assertIsInstance(interface_info["outputs"], gr.outputs.Label)
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def test_feature_extraction(self):
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model_type = "feature-extraction"
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interface_info = gr.external.get_huggingface_interface(
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"sentence-transformers/distilbert-base-nli-mean-tokens",
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api_key=None,
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alias=model_type,
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)
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self.assertEqual(interface_info["fn"].__name__, model_type)
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self.assertIsInstance(interface_info["inputs"], gr.inputs.Textbox)
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self.assertIsInstance(interface_info["outputs"], gr.outputs.Dataframe)
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def test_sentence_similarity(self):
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model_type = "text-to-speech"
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interface_info = gr.external.get_huggingface_interface(
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"julien-c/ljspeech_tts_train_tacotron2_raw_phn_tacotron_g2p_en_no_space_train",
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api_key=None,
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alias=model_type,
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)
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self.assertEqual(interface_info["fn"].__name__, model_type)
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self.assertIsInstance(interface_info["inputs"], gr.inputs.Textbox)
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self.assertIsInstance(interface_info["outputs"], gr.outputs.Audio)
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def test_text_to_speech(self):
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model_type = "text-to-speech"
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interface_info = gr.external.get_huggingface_interface(
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"julien-c/ljspeech_tts_train_tacotron2_raw_phn_tacotron_g2p_en_no_space_train",
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api_key=None,
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alias=model_type,
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)
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self.assertEqual(interface_info["fn"].__name__, model_type)
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self.assertIsInstance(interface_info["inputs"], gr.inputs.Textbox)
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self.assertIsInstance(interface_info["outputs"], gr.outputs.Audio)
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def test_text_to_image(self):
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model_type = "text-to-image"
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interface_info = gr.external.get_huggingface_interface(
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"osanseviero/BigGAN-deep-128", api_key=None, alias=model_type
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)
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self.assertEqual(interface_info["fn"].__name__, model_type)
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self.assertIsInstance(interface_info["inputs"], gr.inputs.Textbox)
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self.assertIsInstance(interface_info["outputs"], gr.outputs.Image)
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def test_english_to_spanish(self):
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interface_info = gr.external.get_spaces_interface(
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"abidlabs/english_to_spanish", api_key=None, alias=None
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)
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self.assertIsInstance(interface_info["inputs"][0], gr.inputs.Textbox)
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self.assertIsInstance(interface_info["outputs"][0], gr.outputs.Textbox)
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class TestLoadInterface(unittest.TestCase):
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def test_english_to_spanish(self):
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interface_info = gr.external.load_interface(
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"spaces/abidlabs/english_to_spanish"
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)
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self.assertIsInstance(interface_info["inputs"][0], gr.inputs.Textbox)
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self.assertIsInstance(interface_info["outputs"][0], gr.outputs.Textbox)
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def test_sentiment_model(self):
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interface_info = gr.external.load_interface(
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"models/distilbert-base-uncased-finetuned-sst-2-english",
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alias="sentiment_classifier",
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)
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io = gr.Interface(**interface_info)
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io.api_mode = True
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output = io("I am happy, I love you.")
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self.assertGreater(output["POSITIVE"], 0.5)
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def test_image_classification_model(self):
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interface_info = gr.external.load_interface(
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"models/google/vit-base-patch16-224"
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)
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io = gr.Interface(**interface_info)
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io.api_mode = True
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output = io("test/test_data/lion.jpg")
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self.assertGreater(output["lion"], 0.5)
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def test_translation_model(self):
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interface_info = gr.external.load_interface("models/t5-base")
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io = gr.Interface(**interface_info)
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io.api_mode = True
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output = io("My name is Sarah and I live in London")
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self.assertEquals(output, "Mein Name ist Sarah und ich lebe in London")
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def test_numerical_to_label_space(self):
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interface_info = gr.external.load_interface("spaces/abidlabs/titanic-survival")
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io = gr.Interface(**interface_info)
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io.api_mode = True
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output = io("male", 77, 10)
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self.assertLess(output["Survives"], 0.5)
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def test_speech_recognition_model(self):
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interface_info = gr.external.load_interface(
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"models/jonatasgrosman/wav2vec2-large-xlsr-53-english"
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)
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io = gr.Interface(**interface_info)
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io.api_mode = True
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output = io("test/test_data/test_audio.wav")
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self.assertIsNotNone(output)
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def test_text_to_image_model(self):
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interface_info = gr.external.load_interface(
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"models/osanseviero/BigGAN-deep-128"
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)
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io = gr.Interface(**interface_info)
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io.api_mode = True
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filename = io("chest")
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self.assertTrue(filename.endswith(".jpg") or filename.endswith(".jpeg"))
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def test_image_to_image_space(self):
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def assertIsFile(path):
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if not pathlib.Path(path).resolve().is_file():
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raise AssertionError("File does not exist: %s" % str(path))
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interface_info = gr.external.load_interface("spaces/abidlabs/image-identity")
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io = gr.Interface(**interface_info)
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io.api_mode = True
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output = io("test/test_data/lion.jpg")
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assertIsFile(output)
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class TestLoadFromPipeline(unittest.TestCase):
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def test_question_answering(self):
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p = transformers.pipeline("question-answering")
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io = gr.Interface.from_pipeline(p)
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output = io(
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"My name is Sylvain and I work at Hugging Face in Brooklyn",
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"Where do I work?",
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)
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self.assertIsNotNone(output)
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if __name__ == "__main__":
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unittest.main()
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