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Merge branch 'main' into ODSC-53010/get_create_model_tests
2 parents 39dad55 + ae91e02 commit ea4fdc4

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-16
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12 files changed

+42
-16
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.github/workflows/run-operators-unit-tests.yml

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@@ -31,7 +31,7 @@ jobs:
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strategy:
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fail-fast: false
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matrix:
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python-version: ["3.8", "3.10.8"]
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python-version: ["3.8"]
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steps:
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- uses: actions/checkout@v4

CODEOWNERS

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* @darenr @mayoor @mrDzurb @VipulMascarenhas @qiuosier

ads/common/serializer.py

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@@ -464,7 +464,7 @@ def from_dict(
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)
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obj = cls(
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**{key: obj_dict.get(key) for key in allowed_fields if key in obj_dict}
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**{key: obj_dict.get(key) for key in allowed_fields}
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)
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for key, value in obj_dict.items():

ads/model/model_artifact_boilerplate/artifact_introspection_test/model_artifact_validate.py

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@@ -29,7 +29,7 @@
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TESTS_PATH = os.path.join(_cwd, "resources", "tests.yaml")
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HTML_PATH = os.path.join(_cwd, "resources", "template.html")
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CONFIG_PATH = os.path.join(_cwd, "resources", "config.yaml")
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PYTHON_VER_PATTERN = "^([3])(\.[6-9])(\.\d+)?$"
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PYTHON_VER_PATTERN = "^([3])(\.([6-9]|1[0-2]))(\.\d+)?$"
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PAR_URL = "https://objectstorage.us-ashburn-1.oraclecloud.com/p/WyjtfVIG0uda-P3-2FmAfwaLlXYQZbvPZmfX1qg0-sbkwEQO6jpwabGr2hMDBmBp/n/ociodscdev/b/service-conda-packs/o/service_pack/index.json"
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TESTS = {

ads/opctl/operator/lowcode/anomaly/model/automlx.py

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@@ -26,8 +26,9 @@ class AutoMLXOperatorModel(AnomalyOperatorBaseModel):
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)
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def _build_model(self) -> pd.DataFrame:
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from automlx import init
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import logging
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try:
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init(engine="ray", engine_opts={"ray_setup": {"_temp_dir": "/tmp/ray-temp"}})
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init(engine="ray", engine_opts={"ray_setup": {"_temp_dir": "/tmp/ray-temp"}}, loglevel=logging.CRITICAL)
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except Exception as e:
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logger.info("Ray already initialized")
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date_column = self.spec.datetime_column.name

ads/opctl/operator/lowcode/forecast/environment.yaml

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@@ -18,3 +18,4 @@ dependencies:
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- optuna==3.1.0
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- oracle-automlx==23.4.1
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- oracle-automlx[forecasting]==23.4.1
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- fire

ads/opctl/operator/lowcode/forecast/model/automlx.py

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@@ -70,17 +70,15 @@ def preprocess(self, data, series_id=None):
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)
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def _build_model(self) -> pd.DataFrame:
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from automlx import init
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from sktime.forecasting.model_selection import temporal_train_test_split
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import logging
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try:
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init(engine="ray", engine_opts={"ray_setup": {"_temp_dir": "/tmp/ray-temp"}})
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init(engine="ray", engine_opts={"ray_setup": {"_temp_dir": "/tmp/ray-temp"}}, loglevel=logging.CRITICAL)
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except Exception as e:
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logger.info("Ray already initialized")
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full_data_dict = self.datasets.get_data_by_series()
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self.models = dict()
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date_column = self.spec.datetime_column.name
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horizon = self.spec.horizon
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self.spec.confidence_interval_width = self.spec.confidence_interval_width or 0.8
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self.forecast_output = ForecastOutput(

docs/source/index.rst

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@@ -79,6 +79,13 @@ Oracle Accelerated Data Science (ADS)
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modules
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.. admonition:: Introducing AI Quick Actions
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:class: note
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Deploy, Fine Tune and Evaluate Large language models such as `Mistral-7B-Instruct-v0.2 <https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2>`__, `CodeLlama-13b-Instruct-hf <https://huggingface.co/codellama/CodeLlama-13b-Instruct-hf>`__, etc with just a couple of clicks.
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Visit `AI Quick Actions documentation <https://github.com/oracle-samples/oci-data-science-ai-samples/tree/main/ai-quick-actions>`__ for the latest information
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.. admonition:: Oracle Accelerated Data Science (ADS)
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:class: note
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docs/source/user_guide/model_serialization/automlmodel.rst

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@@ -23,8 +23,8 @@ Example
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from sklearn.model_selection import train_test_split
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import ads
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import automl
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from automl import init
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import automlx as automl
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from automlx import init
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from ads.model import GenericModel
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from ads.common.model_metadata import UseCaseType
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@@ -48,8 +48,8 @@ Example
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ads.set_auth("resource_principal")
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automl_model = GenericModel(estimator=est, artifact_dir="automl_model_artifact")
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automl_model.prepare(inference_conda_env="automlx_p38_cpu_v1",
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training_conda_env="automlx_p38_cpu_v1",
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automl_model.prepare(inference_conda_env="automlx234_p38_cpu_x86_64_v1",
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training_conda_env="automlx234_p38_cpu_x86_64_v1",
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use_case_type=UseCaseType.BINARY_CLASSIFICATION,
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X_sample=X_test,
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force_overwrite=True)
@@ -70,7 +70,7 @@ Open ``automl_model_artifact/score.py`` and edit the code to instantiate the mod
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from io import StringIO
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import logging
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import sys
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import automl
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import automlx as automl
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import pandas as pd
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import numpy as np
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pyproject.toml

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@@ -179,7 +179,7 @@ pii = [
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"spacy-transformers==1.2.5",
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"spacy==3.6.1",
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]
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llm = ["langchain>=0.1.10", "evaluate>=0.4.0"]
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llm = ["langchain-community<0.0.32", "langchain>=0.1.10,<0.1.14", "evaluate>=0.4.0"]
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aqua = ["jupyter_server"]
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# To reduce backtracking (decrese deps install time) during test/dev env setup reducing number of versions pip is

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