wehub-resource-sync
97 lines
2.6 KiB
Python
97 lines
2.6 KiB
Python
"""
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The ``mlflow.models`` module provides an API for saving machine learning models in
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"flavors" that can be understood by different downstream tools.
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The built-in flavors are:
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- :py:mod:`mlflow.catboost`
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- :py:mod:`mlflow.dspy`
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- :py:mod:`mlflow.h2o`
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- :py:mod:`mlflow.langchain`
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- :py:mod:`mlflow.lightgbm`
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- :py:mod:`mlflow.llama_index`
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- :py:mod:`mlflow.onnx`
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- :py:mod:`mlflow.openai`
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- :py:mod:`mlflow.paddle`
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- :py:mod:`mlflow.pmdarima`
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- :py:mod:`mlflow.prophet`
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- :py:mod:`mlflow.pyfunc`
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- :py:mod:`mlflow.pyspark.ml`
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- :py:mod:`mlflow.pytorch`
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- :py:mod:`mlflow.sklearn`
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- :py:mod:`mlflow.spacy`
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- :py:mod:`mlflow.spark`
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- :py:mod:`mlflow.statsmodels`
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- :py:mod:`mlflow.tensorflow`
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- :py:mod:`mlflow.transformers`
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- :py:mod:`mlflow.xgboost`
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For details, see `MLflow Models guide <https://mlflow.org/docs/latest/ml/model/>`_.
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"""
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from mlflow.models.dependencies_schemas import set_retriever_schema
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from mlflow.models.evaluation import (
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EvaluationArtifact,
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EvaluationMetric,
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EvaluationResult,
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MetricThreshold,
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evaluate,
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list_evaluators,
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make_metric,
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)
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from mlflow.models.flavor_backend import FlavorBackend
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from mlflow.models.model import Model, get_model_info, set_model, update_model_requirements
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from mlflow.models.model_config import ModelConfig
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from mlflow.models.python_api import build_docker
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from mlflow.models.resources import Resource, ResourceType
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from mlflow.utils.environment import infer_pip_requirements
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__all__ = [
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"Model",
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"FlavorBackend",
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"infer_pip_requirements",
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"evaluate",
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"make_metric",
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"EvaluationMetric",
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"EvaluationArtifact",
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"EvaluationResult",
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"get_model_info",
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"set_model",
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"set_retriever_schema",
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"list_evaluators",
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"MetricThreshold",
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"build_docker",
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"Resource",
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"ResourceType",
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"ModelConfig",
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"update_model_requirements",
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]
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# Under skinny-mlflow requirements, the following packages cannot be imported
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# because of lack of numpy/pandas library, so wrap them with try...except block
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try:
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from mlflow.models.python_api import predict
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from mlflow.models.signature import ModelSignature, infer_signature, set_signature
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from mlflow.models.utils import (
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ModelInputExample,
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add_libraries_to_model,
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convert_input_example_to_serving_input,
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validate_schema,
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validate_serving_input,
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)
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__all__ += [
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"ModelSignature",
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"ModelInputExample",
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"infer_signature",
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"validate_schema",
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"add_libraries_to_model",
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"convert_input_example_to_serving_input",
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"set_signature",
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"predict",
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"validate_serving_input",
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]
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except ImportError:
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pass
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