diff --git a/docs/examples/huggingface/README.ipynb b/docs/examples/huggingface/README.ipynb index aee20b946..3e29d9f4f 100644 --- a/docs/examples/huggingface/README.ipynb +++ b/docs/examples/huggingface/README.ipynb @@ -23,6 +23,7 @@ "metadata": {}, "outputs": [], "source": [ + "!pip install requests\n", "# Import required dependencies\n", "import requests" ] @@ -437,6 +438,93 @@ ").json()" ] }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "f1d4b24a-4c09-4743-a086-6f8b143711ad", + "metadata": {}, + "source": [ + "### Masked Language Modeling (Optional Japanese Language Example)\n", + "\n", + "We can also serve a masked language model. In the following example, we also build the `huggingface` runtime with the `-E japanese` flag to enable support for Japanese tokenizers. For example, after running the normal project build from the root directory with `make install-dev`, we can install the optional Japanese dependencies in dev mode:" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "63e368ee-a5ef-44b7-aab8-cafd30ab227a", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Overwriting ./model-settings.json\n" + ] + } + ], + "source": [ + "%%writefile ./model-settings.json\n", + "{\n", + " \"name\": \"transformer\",\n", + " \"implementation\": \"mlserver_huggingface.runtime.HuggingFaceRuntime\",\n", + " \"parameters\": {\n", + " \"extra\": {\n", + " \"task\": \"fill-mask\",\n", + " \"pretrained_model\": \"cl-tohoku/bert-base-japanese\",\n", + " \"pretrained_tokenizer\": \"cl-tohoku/bert-base-japanese\"\n", + " }\n", + " }" + ] + }, + { + "cell_type": "markdown", + "id": "72b05244-f52f-41c0-a1bc-a5d11d1c75a0", + "metadata": {}, + "source": [ + "Using the shell to start mlserver like so,\n", + "\n", + "```shell\n", + "mlserver start .\n", + "```\n", + "we can pass inferences like this. Note the `[MASK]` token. The mask token can be different for different models, so check the HuggingFace model config for special tokens." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "b619c852-f35d-4506-91e1-0a1e3bcb7b8b", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'実際 に 空 が 見える の か?'" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from mlserver_huggingface.codecs import HuggingfaceRequestCodec\n", + "import json\n", + "\n", + "# Test sentence: Is the sky really [MASK]?\n", + "test_sentence = \"実際に空が[MASK]のか？\"\n", + "# [MASK] = visible\n", + "expected_output = \"見える\"\n", + "\n", + "inference_request = HuggingfaceRequestCodec.encode_request(\n", + " {\"inputs\": [test_sentence]},\n", + " use_bytes=False,\n", + ")\n", + "json.dumps(inference_request.dict())\n", + "response = requests.post(\"http://localhost:8080/v2/models/transformer/infer\", json=inference_request.dict()).json()\n", + "json.loads(response['outputs'][0]['data'][0])[\"sequence\"]" + ] + }, { "cell_type": "markdown", "id": "fe6655d9", @@ -714,19 +802,11 @@ " report \\\n", " -type=text" ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "0ddcb458", - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "Python 3", "language": "python", "name": "python3" }, @@ -740,7 +820,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.8" + "version": "3.9.5" } }, "nbformat": 4, diff --git a/docs/examples/huggingface/README.md b/docs/examples/huggingface/README.md index b4c3cd1c9..caf5dfda0 100644 --- a/docs/examples/huggingface/README.md +++ b/docs/examples/huggingface/README.md @@ -259,21 +259,67 @@ requests.post( "http://localhost:8080/v2/models/transformer/infer", json=inference_request ).json() ``` +``` +{'model_name': 'transformer', + 'id': '835eabbd-daeb-4423-a64f-a7c4d7c60a9b', + 'parameters': {}, + 'outputs': [{'name': 'output', + 'shape': [1, 1], + 'datatype': 'BYTES', + 'parameters': {'content_type': 'hg_jsonlist'}, + 'data': ['{"label": "NEGATIVE", "score": 0.9996137022972107}']}]} +``` +### Masked Language Modeling (Optional Japanese Language Example) +We can also serve a masked language model. In the following example, we also build the `huggingface` runtime with the `-E japanese` flag to enable support for Japanese tokenizers. For example, after running the normal project build from the root directory with `make install-dev`, we can install the optional Japanese dependencies in dev mode: +`poetry install -E japanese` - {'model_name': 'transformer', - 'id': '835eabbd-daeb-4423-a64f-a7c4d7c60a9b', - 'parameters': {}, - 'outputs': [{'name': 'output', - 'shape': [1, 1], - 'datatype': 'BYTES', - 'parameters': {'content_type': 'hg_jsonlist'}, - 'data': ['{"label": "NEGATIVE", "score": 0.9996137022972107}']}]} +from the `./runtimes/huggingface` level. +```python +%%writefile ./model-settings.json +{ + "name": "model", + "implementation": "mlserver_huggingface.runtime.HuggingFaceRuntime", + "parameters": { + "extra": { + "task": "fill-mask", + "pretrained_model": "cl-tohoku/bert-base-japanese", + "pretrained_tokenizer": "cl-tohoku/bert-base-japanese" + } + } +} +``` +Using the shell to start mlserver like so, +```shell +mlserver start . +``` +we can pass inferences like this. Note the `[MASK]` token. The mask token can be different for different models, so check the HuggingFace model config for special tokens. +```python +from mlserver_huggingface.codecs import HuggingfaceRequestCodec +import json +# Test sentence: Is the sky really [MASK]? +test_sentence = "実際に空が[MASK]のか？" +# [MASK] = visible +expected_output = "見える" +inference_request = HuggingfaceRequestCodec.encode_request( + {"inputs": [test_sentence]}, + use_bytes=False, +) +json.dumps(inference_request.dict()) +response = requests.post("http://localhost:8080/v2/models/transformer/infer", json=inference_request.dict()).json() +json.loads(response['outputs'][0]['data'][0])["sequence"] +``` +``` +Response: +{'model_name': 'transformer', 'id': '9e966d8d-b43d-4ab4-8d47-90e367196233', 'parameters': {}, 'outputs': [{'name': 'output', 'shape': [5, 1], 'datatype': 'BYTES', 'parameters': {'content_type': 'hg_jsonlist'}, 'data': ['{"score": 0.3277095854282379, "token": 11819, "token_str": "\\u3042\\u308b", "sequence": "\\u5b9f\\u969b \\u306b \\u7a7a \\u304c \\u3042\\u308b \\u306e \\u304b?"}', '{"score": 0.10271108895540237, "token": 14656, "token_str": "\\u898b\\u3048\\u308b", "sequence": "\\u5b9f\\u969b \\u306b \\u7a7a \\u304c \\u898b\\u3048\\u308b \\u306e \\u304b?"}', '{"score": 0.08325661718845367, "token": 11835, "token_str": "\\u306a\\u3044", "sequence": "\\u5b9f\\u969b \\u306b \\u7a7a \\u304c \\u306a\\u3044 \\u306e \\u304b?"}', '{"score": 0.036131054162979126, "token": 18413, "token_str": "\\u6b63\\u3057\\u3044", "sequence": "\\u5b9f\\u969b \\u306b \\u7a7a \\u304c \\u6b63\\u3057\\u3044 \\u306e \\u304b?"}', '{"score": 0.029351236298680305, "token": 11820, "token_str": "\\u3044\\u308b", "sequence": "\\u5b9f\\u969b \\u306b \\u7a7a \\u304c \\u3044\\u308b \\u306e \\u304b?"}']}]} +Data: +{'score': 0.3277095854282379, 'token': 11819, 'token_str': 'ある', 'sequence': '実際 に 空 が ある の か?'} +``` ## GPU Acceleration We can also evaluate GPU acceleration, we can test the speed on CPU vs GPU using the following parameters 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"1f69e6b02610ab08654a7f7ac5bdfde9ecac54f944bf253f7a23fc80bf60481c" +content-hash = "ad725a627709de6880c9f0753efbc93d4756b7668e0e1f2f5f5ec3d5547e2117" diff --git a/runtimes/huggingface/pyproject.toml b/runtimes/huggingface/pyproject.toml index 1a65feabb..eb6242ce8 100644 --- a/runtimes/huggingface/pyproject.toml +++ b/runtimes/huggingface/pyproject.toml @@ -12,15 +12,24 @@ python = ">=3.9,<3.12" mlserver = "*" tensorflow = "*" pillow = "*" +tf-keras = "<3.0" optimum = {extras = ["onnxruntime"], version = ">=1.4,<2.0"} pydantic = "<2.0.0" +fugashi = {version = "^1.3.0", optional = true} +unidic = {version = "^1.1.0", optional = true} +unidic-lite = {version = "^1.0.8", optional = true} +ipadic = {version = "^1.0.0", optional = true} [tool.poetry.group.dev.dependencies] mlserver = {path = "../..", develop = true} torch = "2.2.2" transformers = ">=4.30,<5.0" tensorflow = ">=2.12,<2.17" +tf-keras = "<3.0" + +[tool.poetry.extras] +japanese = ["fugashi", "unidic", "unidic-lite", "ipadic"] [build-system] requires = ["poetry-core"] -build-backend = "poetry.core.masonry.api" +build-backend = "poetry.core.masonry.api" \ No newline at end of file diff --git a/runtimes/huggingface/tests/conftest.py b/runtimes/huggingface/tests/conftest.py index 7b6c07998..02744eef2 100644 --- a/runtimes/huggingface/tests/conftest.py +++ b/runtimes/huggingface/tests/conftest.py @@ -9,6 +9,7 @@ # if not provide this command argument, task tests skiped def pytest_addoption(parser): parser.addoption("--test-hg-tasks", action="store_true", default=False) + parser.addoption("--test-ja-support", action="store_true", default=False) @pytest.fixture() diff --git a/runtimes/huggingface/tests/test_tasks/test_japanese_mask_fill.py b/runtimes/huggingface/tests/test_tasks/test_japanese_mask_fill.py new file mode 100644 index 000000000..28781e174 --- /dev/null +++ b/runtimes/huggingface/tests/test_tasks/test_japanese_mask_fill.py @@ -0,0 +1,66 @@ +import pytest +from mlserver.settings import ModelSettings, ModelParameters +from mlserver_huggingface import HuggingFaceRuntime +from mlserver_huggingface.codecs import HuggingfaceRequestCodec + + +""" +Test case summary: + +1. Short sentence with a single masked word. + + +Input: 実際に空が[MASK]のか？ English: Is the sky truly [MASK]? + +Output: ある　ー＞ English: Does the sky truly exist? + +Model: izumi-lab/bert-small-japanese (a 70 MB masked language model +trained on a mask filling task.) + +""" + + +@pytest.mark.parametrize( + "test_sentence,expected_output,model_parameters", + [ + ( + "実際に空が[MASK]のか？", + "ある", + ModelParameters( + extra={ + "task": "fill-mask", + "pretrained_model": "izumi-lab/bert-small-japanese", + "pretrained_tokenizer": "izumi-lab/bert-small-japanese", + } + ), + ) + ], +) +async def test_infer(test_sentence, expected_output, model_parameters, request): + if (not request.config.option.test_hg_tasks) or ( + not request.config.option.test_ja_support + ): + pytest.skip() + + # Get inferences + reqs = HuggingfaceRequestCodec.encode_request( + {"inputs": [test_sentence]}, + use_bytes=False, + ) + + # Load model + bert_japanese_settings = ModelSettings( + name="model", implementation=HuggingFaceRuntime, parameters=model_parameters + ) + + # Create runtime + runtime = HuggingFaceRuntime(bert_japanese_settings) + await runtime.load() + + # Generate response + resp = await runtime.predict(reqs) + decoded = HuggingfaceRequestCodec.decode_response(resp) + + # Get top result + top_result = decoded["output"][0] + assert top_result["token_str"] == expected_output, "Inference is correct!" diff --git a/runtimes/lightgbm/poetry.lock b/runtimes/lightgbm/poetry.lock index 5a60addaa..625a422aa 100644 --- a/runtimes/lightgbm/poetry.lock +++ b/runtimes/lightgbm/poetry.lock @@ -13,87 +13,87 @@ files = [ [[package]] name = "aiohttp" -version = "3.9.3" +version = "3.9.4" description = "Async http client/server framework (asyncio)" optional = false python-versions = ">=3.8" files = [ - {file = "aiohttp-3.9.3-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:939677b61f9d72a4fa2a042a5eee2a99a24001a67c13da113b2e30396567db54"}, - {file = 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