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transforms/universal/hap/ray/Dockerfile

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+ARG BASE_IMAGE=docker.io/rayproject/ray:2.24.0-py310
+FROM ${BASE_IMAGE}
+
+RUN pip install --upgrade --no-cache-dir pip 
+
+# install pytest
+RUN pip install --no-cache-dir pytest
+
+# Copy and install data processing libraries 
+# These are expected to be placed in the docker context before this is run (see the make image).
+COPY --chown=ray:users data-processing-lib-python/ data-processing-lib-python/
+RUN cd data-processing-lib-python && pip install --no-cache-dir -e .
+COPY --chown=ray:users data-processing-lib-ray/ data-processing-lib-ray/ 
+RUN cd data-processing-lib-ray    && pip install --no-cache-dir -e .
+COPY --chown=ray:users python-transform/  python-transform/
+RUN cd python-transform && pip install --no-cache-dir -e .
+
+#COPY requirements.txt requirements.txt
+#RUN pip install --no-cache-dir -r  requirements.txt
+
+COPY --chown=ray:users src/ src/
+COPY --chown=ray:users pyproject.toml pyproject.toml 
+RUN pip install --no-cache-dir -e .
+
+# copy the main() entry point to the image 
+COPY ./src/hap_transform_ray.py .
+
+# copy some of the samples in
+COPY ./src/hap_local_ray.py local/
+
+# copy test
+COPY test/ test/
+COPY test-data/ test-data/
+
+# Set environment
+ENV PYTHONPATH /home/ray
+
+# Put these at the end since they seem to upset the docker cache.
+ARG BUILD_DATE
+ARG GIT_COMMIT
+LABEL build-date=$BUILD_DATE
+LABEL git-commit=$GIT_COMMIT

transforms/universal/hap/ray/Makefile

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+# Define the root of the local git clone for the common rules to be able 
+# know where they are running from.
+REPOROOT=../../../..
+# Include a library of common .transform.* targets which most
+# transforms should be able to reuse.  However, feel free
+# to override/redefine the rules below. 
+include $(REPOROOT)/transforms/.make.transforms
+
+TRANSFORM_NAME=hap
+
+BASE_IMAGE=${RAY_BASE_IMAGE}
+HAP_PYTHON_VERSION= $(DPK_VERSION)
+
+venv::	.transforms.ray-venv
+
+install:: pip install -r requirements.txt
+
+test::	.transforms.ray-test
+
+clean:: .transforms.clean
+
+image:: .transforms.ray-image
+
+test-src:: .transforms.test-src
+
+setup:: .transforms.setup
+
+test-image:: .transforms.ray-test-image
+
+build:: build-dist image
+
+publish: publish-image
+
+publish-image:: .transforms.publish-image-ray
+
+setup:: .transforms.setup
+
+# distribution versions is the same as image version.
+set-versions:
+	$(MAKE) TRANSFORM_PYTHON_VERSION=$(HAP_PYTHON_VERSION) TOML_VERSION=$(HAP_RAY_VERSION) .transforms.set-versions 
+
+build-dist:: set-versions .defaults.build-dist 
+
+publish-dist:: .defaults.publish-dist
+
+run-cli-sample: .transforms.run-cli-ray-sample
+
+run-local-sample: .transforms.run-local-ray-sample
+
+run-s3-sample: .transforms.run-s3-ray-sample
+
+minio-start:	.minio-start
+
+kind-load-image:: .transforms.kind-load-image
+
+docker-load-image: .defaults.docker-load-image
+
+docker-save-image: .defaults.docker-save-image

transforms/universal/hap/ray/README.md

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+# Hate, Abuse, and Profanity (HAP) Annotation
+# HAP Transform for Ray
+Please see the set of
+[transform project conventions](../../../README.md#transform-project-conventions)
+for details on general project conventions, transform configuration,
+testing and IDE set up.
+
+## Summary 
+This project wraps the [hap transform](../python) with a Ray runtime.
+
+## Configuration and command line Options
+
+Configuration and command line options are the same as for the base python transform. 
+
+## Running
+
+### Launched Command Line Options 
+In addition to those available to the transform as defined in [here](../python/README.md),
+the set of 
+[ray launcher](../../../../data-processing-lib/doc/ray-launcher-options.md) are available.

transforms/universal/hap/ray/output/metadata.json

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+{
+  "pipeline": "pipeline_id",
+  "job details": {
+    "job category": "preprocessing",
+    "job name": "hap",
+    "job type": "pure python",
+    "job id": "job_id",
+    "start_time": "2024-10-03 21:38:20",
+    "end_time": "2024-10-03 21:38:29",
+    "status": "success"
+  },
+  "code": {
+    "github": "github",
+    "commit_hash": "12345",
+    "path": "path"
+  },
+  "job_input_params": {
+    "model_name_or_path": "ibm-granite/granite-guardian-hap-38m",
+    "annotation_column": "hap_score",
+    "doc_text_column": "contents",
+    "inference_engine": "CPU",
+    "max_length": 512,
+    "batch_size": 128,
+    "checkpointing": false,
+    "max_files": -1,
+    "random_samples": -1,
+    "files_to_use": [
+      ".parquet"
+    ],
+    "num_processors": 0
+  },
+  "job_output_stats": {
+    "source_files": 2,
+    "source_size": 12124594,
+    "transform execution exception": 1,
+    "result_files": 1,
+    "result_size": 79822,
+    "processing_time": 6.932,
+    "source_doc_count": 50,
+    "result_doc_count": 50
+  },
+  "source": {
+    "name": "/Users/ian/Desktop/data-prep-kit/transforms/universal/hap/python/test-data/input",
+    "type": "path"
+  },
+  "target": {
+    "name": "/Users/ian/Desktop/data-prep-kit/transforms/universal/hap/python/output",
+    "type": "path"
+  }
+}

transforms/universal/hap/ray/pyproject.toml

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+[project]
+name = "dpk_hap_transform_python"
+version = "0.2.2.dev0"
+requires-python = ">=3.10"
+description = "HAP Ray Transform"
+license = {text = "Apache-2.0"}
+readme = {file = "README.md", content-type = "text/markdown"}
+authors = [
+{ name = "Ian Cho", email = "[email protected]" },
+]
+dynamic = ["dependencies"]
+
+
+[build-system]
+requires = ["setuptools>=68.0.0", "wheel", "setuptools_scm[toml]>=7.1.0"]
+build-backend = "setuptools.build_meta"
+
+[tool.setuptools.dynamic]
+dependencies = {file = ["requirements.txt"]}
+
+[project.optional-dependencies]
+dev = [
+    "twine",
+    "pytest>=7.3.2",
+    "pytest-dotenv>=0.5.2",
+    "pytest-env>=1.0.0",
+    "pre-commit>=3.3.2",
+    "pytest-cov>=4.1.0",
+    "pytest-mock>=3.10.0",
+    "moto==5.0.5",
+    "markupsafe==2.0.1",
+]
+
+
+
+[options]
+package_dir = ["src","test"]
+
+[options.packages.find]
+where = ["src/"]
+
+[tool.pytest.ini_options]
+# Currently we use low coverage since we have to run tests separately (see makefile)
+#addopts = "--cov --cov-report term-missing --cov-fail-under 25"
+markers = ["unit: unit tests", "integration: integration tests"]
+
+[tool.coverage.run]
+include = ["src/*"]

transforms/universal/hap/ray/requirements.txt

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+data-prep-toolkit-ray==0.2.2.dev0
+dpk-hap-transform-python==0.2.2.dev0
+nltk==3.9.1
+transformers==4.38.2
+torch==2.4.1
+pandas==2.2.2

transforms/universal/hap/ray/src/hap_local_ray.py

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+# (C) Copyright IBM Corp. 2024.
+# Licensed under the Apache License, Version 2.0 (the “License”);
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#  http://www.apache.org/licenses/LICENSE-2.0
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an “AS IS” BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+################################################################################
+
+
+import ast
+import os
+import sys
+
+from data_processing.utils import ParamsUtils
+from data_processing_ray.runtime.ray import RayTransformLauncher
+from hap_transform_ray import HAPRayTransformConfiguration
+
+
+# create parameters
+input_folder = os.path.abspath(os.path.join(os.path.dirname(__file__), "../test-data/input"))
+output_folder = os.path.abspath(os.path.join(os.path.dirname(__file__), "../output"))
+local_conf = {
+    "input_folder": input_folder,
+    "output_folder": output_folder,
+}
+code_location = {"github": "github", "commit_hash": "12345", "path": "path"}
+
+params = {
+    "data_local_config": ParamsUtils.convert_to_ast(local_conf),
+    "runtime_pipeline_id": "pipeline_id",
+    "runtime_job_id": "job_id",
+    "runtime_code_location": ParamsUtils.convert_to_ast(code_location),
+}
+
+
+hap_params = {
+    "model_name_or_path": 'ibm-granite/granite-guardian-hap-38m',
+    "annotation_column": "hap_score",
+    "doc_text_column": "contents",
+    "inference_engine": "CPU",
+    "max_length": 512,
+    "batch_size": 128,
+}
+
+
+
+if __name__ == "__main__":
+    # Set the simulated command line args
+    sys.argv = ParamsUtils.dict_to_req(d=params | hap_params)
+    # create launcher
+    launcher = RayTransformLauncher(HAPRayTransformConfiguration())
+    # Launch the ray actor(s) to process the input
+    launcher.launch()

transforms/universal/hap/ray/src/hap_s3_ray.py

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+# (C) Copyright IBM Corp. 2024.
+# Licensed under the Apache License, Version 2.0 (the “License”);
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#  http://www.apache.org/licenses/LICENSE-2.0
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an “AS IS” BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+################################################################################
+
+import os
+import sys
+
+from data_processing.utils import ParamsUtils
+from data_processing_ray.runtime.ray import RayTransformLauncher
+from hap_transform_ray import HAPRayTransformConfiguration
+
+
+# create launcher
+launcher = RayTransformLauncher(HAPRayTransformConfiguration())
+# create parameters
+s3_cred = {
+    "access_key": "localminioaccesskey",
+    "secret_key": "localminiosecretkey",
+    "url": "http://localhost:9000",
+}
+
+s3_conf = {
+    "input_folder": "test/hap/input",
+    "output_folder": "test/hap/output",
+}
+worker_options = {"num_cpus": 0.8}
+code_location = {"github": "github", "commit_hash": "12345", "path": "path"}
+params = {
+    # where to run
+    "run_locally": True,
+    # Data access. Only required parameters are specified
+    "data_s3_cred": ParamsUtils.convert_to_ast(s3_cred),
+    "data_s3_config": ParamsUtils.convert_to_ast(s3_conf),
+    # orchestrator
+    "runtime_worker_options": ParamsUtils.convert_to_ast(worker_options),
+    "runtime_num_workers": 3,
+    "runtime_pipeline_id": "pipeline_id",
+    "runtime_job_id": "job_id",
+    "runtime_creation_delay": 0,
+    "runtime_code_location": ParamsUtils.convert_to_ast(code_location),
+}
+
+
+hap_params = {
+    "model_name_or_path": 'ibm-granite/granite-guardian-hap-38m',
+    "annotation_column": "hap_score",
+    "doc_text_column": "contents",
+    "inference_engine": "CPU",
+    "max_length": 512,
+    "batch_size": 128,
+}
+
+
+sys.argv = ParamsUtils.dict_to_req(d=params | hap_params)
+# launch
+launcher.launch()

transforms/universal/hap/ray/src/hap_transform_ray.py

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+# (C) Copyright IBM Corp. 2024.
+# Licensed under the Apache License, Version 2.0 (the “License”);
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#  http://www.apache.org/licenses/LICENSE-2.0
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an “AS IS” BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+################################################################################
+
+from data_processing.utils import get_logger
+from data_processing_ray.runtime.ray import RayTransformLauncher
+from data_processing_ray.runtime.ray.runtime_configuration import RayTransformRuntimeConfiguration
+from hap_transform import HAPTransformConfiguration
+
+
+logger = get_logger(__name__)
+
+
+class HAPRayTransformConfiguration(RayTransformRuntimeConfiguration):
+    """
+    Implements the RayTransformConfiguration for HAP as required by the RayTransformLauncher.
+    """
+
+    def __init__(self):
+        """
+        Initialization
+        :param base_configuration - base configuration class
+        """
+        super().__init__(transform_config=HAPTransformConfiguration())
+
+
+if __name__ == "__main__":
+    launcher = RayTransformLauncher(HAPRayTransformConfiguration())
+    logger.info("Launching hap transform")
+    launcher.launch()
+