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Commit 30836ab

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gaurav274jarulraj
gaurav274
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jarulraj
authored
fix: Notebooks fix (#887)
1. Fixed tricky notebook bug by forcefully importing `torch` ahead of all other packages. --------- Co-authored-by: jarulraj <arulraj@gatech.edu>
1 parent 90b6350 commit 30836ab

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-231
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10 files changed

+220
-231
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‎.circleci/config.yml‎

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@@ -47,7 +47,7 @@ workflows:
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# name: "Notebook | v3.11 | Linux"
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# v: "3.11"
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# mode: "NOTEBOOK"
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### LINTER
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## LINTER
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- Linux:
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name: "Linter | Linux"
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v: "3.10"

‎evadb/udfs/tutorials/__init__.py‎

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This file was deleted.

‎evadb/udfs/udf_bootstrap_queries.py‎

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@@ -212,15 +212,25 @@ def init_builtin_udfs(db: EvaDBDatabase, mode: str = "debug") -> None:
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Defaults to 'debug'.
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"""
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# Attempting to import torch module
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# It is necessary to import torch before to avoid encountering a
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# "RuntimeError: random_device could not be read"
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# The suspicion is that importing torch prior to decord resolves this issue
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try:
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import torch # noqa
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except ImportError:
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pass
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# list of UDF queries to load
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queries = [
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mnistcnn_udf_query,
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Fastrcnn_udf_query,
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ArrayCount_udf_query,
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Crop_udf_query,
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Open_udf_query,
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Similarity_udf_query,
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norfair_obj_tracker_query,
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mnistcnn_udf_query,
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chatgpt_udf_query,
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face_detection_udf_query,
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# ocr_udf_query,

‎script/test/test.sh‎

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@@ -111,7 +111,7 @@ fi
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if [[ ( "$OSTYPE" != "msys" ) && ( "$MODE" = "NOTEBOOK" || "$MODE" = "ALL" ) ]];
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then
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PYTHONPATH=./ python -m pytest --durations=5 --nbmake --overwrite "./tutorials" --capture=sys --tb=short -v --log-level=WARNING --nbmake-timeout=3000
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PYTHONPATH=./ python -m pytest --durations=5 --nbmake --overwrite "./tutorials" --capture=sys --tb=short -v --log-level=WARNING --nbmake-timeout=3000 --ignore="tutorials/09-license-plate-fuzzy-join.ipynb" --ignore="tutorials/10-toxicity-classifier-huggingface.ipynb"
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notebook_test_code=$?
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if [ "$notebook_test_code" != "0" ];
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then

‎test/integration_tests/test_create_index_executor.py‎

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@@ -97,6 +97,7 @@ def tearDownClass(cls):
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query = "DROP TABLE testCreateIndexInputTable;"
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execute_query_fetch_all(cls.evadb, query)
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@macos_skip_marker
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def test_should_create_index_faiss(self):
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query = "CREATE INDEX testCreateIndexName ON testCreateIndexFeatTable (feat) USING FAISS;"
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execute_query_fetch_all(self.evadb, query)

‎tutorials/01-mnist.ipynb‎

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@@ -39,7 +39,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"execution_count": 2,
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"id": "b6b7f61d",
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"metadata": {
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"execution": {
@@ -250,6 +250,68 @@
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"\n",
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"plt.show()"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"id": "405b1730",
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"metadata": {},
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"source": [
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"### Drop the function if needed"
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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": 3,
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"id": "829ed2da",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>0</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>UDF MnistImageClassifier successfully dropped</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" 0\n",
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"0 UDF MnistImageClassifier successfully dropped"
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]
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},
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"cursor.drop_udf(\"MnistImageClassifier\").df()"
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]
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}
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],
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"metadata": {

‎tutorials/03-emotion-analysis.ipynb‎

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@@ -50,13 +50,7 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Note: you may need to restart the kernel to use updated packages.\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Note: you may need to restart the kernel to use updated packages.\n",
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"Note: you may need to restart the kernel to use updated packages.\n"
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]
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},
@@ -85,7 +79,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": 4,
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"metadata": {
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"execution": {
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"iopub.execute_input": "2023-06-17T04:34:30.929427Z",
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"File ‘defhappy.mp4’ already there; not retrieving.\r\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"File ‘emotion_detector.py’ already there; not retrieving.\r\n",
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"\r\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"File ‘face_detector.py’ already there; not retrieving.\r\n",
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"\r\n"
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"File 'defhappy.mp4' already there; not retrieving.\n",
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"--2023-06-23 01:50:16-- https://raw.githubusercontent.com/georgia-tech-db/eva/master/evadb/udfs/emotion_detector.py\n",
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"Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.110.133, 185.199.108.133, 185.199.111.133, ...\n",
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"Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.110.133|:443... connected.\n",
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"HTTP request sent, awaiting response... 200 OK\n",
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"Length: 6056 (5.9K) [text/plain]\n",
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"Saving to: 'emotion_detector.py'\n",
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"\n",
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"emotion_detector.py 100%[===================>] 5.91K --.-KB/s in 0s \n",
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"\n",
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"2023-06-23 01:50:16 (31.8 MB/s) - 'emotion_detector.py' saved [6056/6056]\n",
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"\n",
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"--2023-06-23 01:50:16-- https://raw.githubusercontent.com/georgia-tech-db/eva/master/evadb/udfs/face_detector.py\n",
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"Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.109.133, 185.199.111.133, 185.199.108.133, ...\n",
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"Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.109.133|:443... connected.\n",
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"HTTP request sent, awaiting response... 200 OK\n",
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"Length: 2886 (2.8K) [text/plain]\n",
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"Saving to: 'face_detector.py'\n",
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"\n",
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"face_detector.py 100%[===================>] 2.82K --.-KB/s in 0s \n",
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"\n",
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"2023-06-23 01:50:17 (21.1 MB/s) - 'face_detector.py' saved [2886/2886]\n",
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"\n"
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]
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}
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],
@@ -217,7 +217,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"execution_count": 5,
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"metadata": {
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"execution": {
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"iopub.execute_input": "2023-06-17T04:34:33.328551Z",
@@ -254,18 +254,18 @@
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>UDF FaceDetector already exists, nothing added.</td>\n",
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" <td>UDF FaceDetector successfully added to the dat...</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" 0\n",
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"0 UDF FaceDetector already exists, nothing added."
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" 0\n",
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"0 UDF FaceDetector successfully added to the dat..."
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]
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},
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"execution_count": 4,
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"execution_count": 5,
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"metadata": {},
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"output_type": "execute_result"
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}
@@ -608,7 +608,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"execution_count": 6,
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"metadata": {
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"execution": {
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"iopub.execute_input": "2023-06-17T04:34:53.779959Z",
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"shell.execute_reply": "2023-06-17T04:34:53.783057Z"
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}
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},
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"outputs": [],
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>0</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>UDF FaceDetector successfully dropped</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" 0\n",
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"0 UDF FaceDetector successfully dropped"
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]
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},
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"execution_count": 6,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"#cursor.drop(item_name=\"EmotionDetector\", item_type=\"UDF\").df()\n",
623-
"#cursor.drop(item_name=\"FaceDetector\", item_type=\"UDF\").df()"
665+
"cursor.drop_udf(\"EmotionDetector\").df()\n",
666+
"cursor.drop_udf(\"FaceDetector\").df()"
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]
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}
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],

‎tutorials/05-asl-action-recognition.ipynb‎

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@@ -448,6 +448,23 @@
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"\n",
449449
"annotate_video(response, input_path, output_path)"
450450
]
451+
},
452+
{
453+
"attachments": {},
454+
"cell_type": "markdown",
455+
"metadata": {},
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"source": [
457+
"### Dropping User-Defined Function (UDF)"
458+
]
459+
},
460+
{
461+
"cell_type": "code",
462+
"execution_count": null,
463+
"metadata": {},
464+
"outputs": [],
465+
"source": [
466+
"cursor.drop_udf(\"ASLActionRecognition\").df()"
467+
]
451468
}
452469
],
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"metadata": {

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