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Update unit_test_synthetic.ipynb imports and metadata
- Consolidate imports (os, shutil, Path, yaml) into the initial setup cell. - Add a commented-out cell for configuring XLA_FLAGS for GPU support. - Update notebook metadata to reflect Python 3.10.19. - Remove redundant and empty cells.
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Lines changed: 22 additions & 15 deletions

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notebooks/unit_test_synthetic.ipynb

Lines changed: 22 additions & 15 deletions
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import os\n",
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"#os.environ[\"XLA_FLAGS\"] = \"--xla_gpu_cuda_data_dir=/usr/lib/nvidia-cuda-toolkit\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import logging\n",
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"\n",
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"import os\n",
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"import shutil\n",
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"from pathlib import Path\n",
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"import yaml\n",
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"# --- Make sure your notebook's working directory is the project root ---\n",
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"# (e.g., /home/samorah/_data/ml_binary_classification_gridsearch_hyperOpt/)\n",
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"from pathlib import Path\n",
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"an `ml_grid_object`. It is intended for debugging the data pipeline in isolation.\n",
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"\"\"\"\n",
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"\n",
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"import os\n",
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"import shutil\n",
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"from pathlib import Path\n",
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"\n",
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"import yaml\n",
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"\n",
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"# --- Essential imports from your ml_grid project ---\n",
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"# Ensure your project is installed (e.g., `pip install -e .`) or the path is configured\n",
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"# so these imports can be found.\n",
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" print(\"\\n6. Clean up complete.\")\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"source": [
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"df.sort_values(by='run_time', ascending=False)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.3"
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"version": "3.10.19"
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}
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},
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"nbformat": 4,

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