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Merge branch 'main' into refactoring/#165-Reduce_log_output_in_Codebu…
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ckunki committed Feb 5, 2024
2 parents bed75bc + e5fcd8b commit 7b84c46
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1 change: 1 addition & 0 deletions doc/changes/changes_0.2.0.md
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## Refactoring

* #160: Implemented the PM's recommendations of 2024-01-24.
* #120: Passing the secret store object (sb_config) as a parameter to all functions that need it.
* #165: Reduced log output in Codebuild ai-lab

## Documentation
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"metadata": {},
"outputs": [],
"source": [
"display(get_db_selection_ui())"
"display(get_db_selection_ui(sb_config))"
]
},
{
Expand All @@ -95,7 +95,7 @@
"metadata": {},
"outputs": [],
"source": [
"display(get_db_config_ui())"
"display(get_db_config_ui(sb_config))"
]
},
{
Expand All @@ -117,7 +117,7 @@
"metadata": {},
"outputs": [],
"source": [
"display(get_start_docker_db_ui())"
"display(get_start_docker_db_ui(sb_config))"
]
},
{
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Expand Up @@ -58,7 +58,7 @@
"outputs": [],
"source": [
"%run utils/sme_init_ui.ipynb\n",
"display(get_sme_config_ui())"
"display(get_sme_config_ui(sb_config))"
]
},
{
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Expand Up @@ -35,20 +35,21 @@
"from enum import Enum\n",
"import ipywidgets as widgets\n",
"\n",
"from exasol.secret_store import Secrets\n",
"from exasol.ai_lab_config import AILabConfig as CKey\n",
"\n",
"\n",
"def get_sme_config_ui() -> widgets.Widget:\n",
"def get_sme_config_ui(conf: Secrets) -> widgets.Widget:\n",
"\n",
" inputs = [\n",
" ('Access Key ID', widgets.Password(value=sb_config.get(CKey.aws_access_key_id)), CKey.aws_access_key_id),\n",
" ('Secret Access Key', widgets.Password(value=sb_config.get(CKey.aws_secret_access_key)), CKey.aws_secret_access_key),\n",
" ('Region', widgets.Text(value=sb_config.get(CKey.aws_region)), CKey.aws_region),\n",
" ('Sagemaker AWS Role', widgets.Text(value=sb_config.get(CKey.sme_aws_role)), CKey.sme_aws_role),\n",
" ('Sagemaker S3 Bucket', widgets.Text(value=sb_config.get(CKey.sme_aws_bucket)), CKey.sme_aws_bucket),\n",
" ('Access Key ID', widgets.Password(value=conf.get(CKey.aws_access_key_id)), CKey.aws_access_key_id),\n",
" ('Secret Access Key', widgets.Password(value=conf.get(CKey.aws_secret_access_key)), CKey.aws_secret_access_key),\n",
" ('Region', widgets.Text(value=conf.get(CKey.aws_region)), CKey.aws_region),\n",
" ('Sagemaker AWS Role', widgets.Text(value=conf.get(CKey.sme_aws_role)), CKey.sme_aws_role),\n",
" ('Sagemaker S3 Bucket', widgets.Text(value=conf.get(CKey.sme_aws_bucket)), CKey.sme_aws_bucket),\n",
" ]\n",
"\n",
" return get_generic_config_ui(sb_config, [inputs], ['Set AWS Credentials'])\n"
" return get_generic_config_ui(conf, [inputs], ['Set AWS Credentials'])\n"
]
}
],
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Expand Up @@ -89,7 +89,7 @@
"outputs": [],
"source": [
"%run utils/model_retrieval.ipynb\n",
"load_huggingface_model(MODEL_NAME)"
"load_huggingface_model(sb_config, MODEL_NAME)"
]
},
{
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Expand Up @@ -89,7 +89,7 @@
"outputs": [],
"source": [
"%run utils/model_retrieval.ipynb\n",
"load_huggingface_model(MODEL_NAME)"
"load_huggingface_model(sb_config, MODEL_NAME)"
]
},
{
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Expand Up @@ -90,7 +90,7 @@
"outputs": [],
"source": [
"%run utils/model_retrieval.ipynb\n",
"load_huggingface_model(MODEL_NAME, method='udf')"
"load_huggingface_model(sb_config, MODEL_NAME, method='udf')"
]
},
{
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Expand Up @@ -46,7 +46,7 @@
"outputs": [],
"source": [
"%run utils/te_init_ui.ipynb\n",
"display(get_te_config_ui())"
"display(get_te_config_ui(sb_config))"
]
},
{
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Expand Up @@ -71,7 +71,7 @@
"outputs": [],
"source": [
"%run utils/model_retrieval.ipynb\n",
"load_huggingface_model(MODEL_NAME)"
"load_huggingface_model(sb_config, MODEL_NAME)"
]
},
{
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Expand Up @@ -89,7 +89,7 @@
"outputs": [],
"source": [
"%run utils/model_retrieval.ipynb\n",
"load_huggingface_model(MODEL_NAME)"
"load_huggingface_model(sb_config, MODEL_NAME)"
]
},
{
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Expand Up @@ -80,7 +80,6 @@
"execution_count": null,
"id": "50a8cc23-bba5-4497-8947-9adc8c83a76c",
"metadata": {
"editable": false,
"slideshow": {
"slide_type": ""
},
Expand All @@ -91,7 +90,7 @@
"outputs": [],
"source": [
"%run utils/model_retrieval.ipynb\n",
"load_huggingface_model(MODEL_NAME)"
"load_huggingface_model(sb_config, MODEL_NAME)"
]
},
{
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Expand Up @@ -36,12 +36,14 @@
"metadata": {},
"outputs": [],
"source": [
"def load_huggingface_model_udf(model_name: str) -> None:\n",
"from exasol.secret_store import Secrets\n",
"\n",
"\n",
"def load_huggingface_model_udf(conf: Secrets, model_name: str) -> None:\n",
" \"\"\"\n",
" Loads specified model into BucketFS using a UDF provided with the Transformer Extension.\n",
" There must be a global variable - sb_config - providing access to the secret store holding\n",
" the configuration data.\n",
"\n",
" conf - Access to the secret store holding the configuration data.\n",
" model_name - Name of the model at Huggingface hub, e.g. facebook/nllb-moe-54b.\n",
" \"\"\"\n",
"\n",
Expand All @@ -50,16 +52,16 @@
" from exasol.ai_lab_config import AILabConfig as CKey\n",
"\n",
" sql = f\"\"\"\n",
" SELECT {sb_config.get(CKey.db_schema)}.TE_MODEL_DOWNLOADER_UDF(\n",
" SELECT {conf.get(CKey.db_schema)}.TE_MODEL_DOWNLOADER_UDF(\n",
" '{model_name}',\n",
" '{sb_config.get(CKey.te_models_bfs_dir)}',\n",
" '{sb_config.get(CKey.te_bfs_connection)}',\n",
" '{sb_config.get(CKey.te_hf_connection)}'\n",
" '{conf.get(CKey.te_models_bfs_dir)}',\n",
" '{conf.get(CKey.te_bfs_connection)}',\n",
" '{conf.get(CKey.te_hf_connection)}'\n",
" )\n",
" \"\"\"\n",
"\n",
" with open_pyexasol_connection(sb_config, compression=True) as conn:\n",
" conn.execute(query=get_activation_sql(sb_config))\n",
" with open_pyexasol_connection(conf, compression=True) as conn:\n",
" conn.execute(query=get_activation_sql(conf))\n",
" conn.execute(query=sql)"
]
},
Expand All @@ -80,12 +82,11 @@
"metadata": {},
"outputs": [],
"source": [
"def load_huggingface_model_cli(model_name: str, force_download: bool = False) -> None:\n",
"def load_huggingface_model_cli(conf: Secrets, model_name: str, force_download: bool = False) -> None:\n",
" \"\"\"\n",
" Loads specified model into BucketFS by saving it first to a local drive, as per the command-line interface.\n",
" There must be a global variable - sb_config - providing access to the secret store holding\n",
" the configuration data.\n",
"\n",
" conf - Access to the secret store holding the configuration data.\n",
" model_name - Name of the model at Huggingface hub, e.g. facebook/nllb-moe-54b.\n",
" force_download - If True the model will be reloaded from the hub even if it has been cached before.\n",
" \"\"\"\n",
Expand All @@ -97,11 +98,11 @@
"\n",
" # Make a name for the model sub-directory\n",
" sub_dir = re.sub(r\"[/\\\\?%*:|\\\"<>\\x7F\\x00-\\x1F]\", \"-\", model_name)\n",
" models_dir = sb_config.get(CKey.te_models_cache_dir)\n",
" models_dir = conf.get(CKey.te_models_cache_dir)\n",
" cache_dir = str(Path(models_dir) / sub_dir)\n",
"\n",
" # Upload it to the BucketFS\n",
" upload_model(sb_config, model_name=model_name, cache_dir=cache_dir, force_download=force_download)"
" upload_model(conf, model_name=model_name, cache_dir=cache_dir, force_download=force_download)"
]
},
{
Expand All @@ -121,10 +122,11 @@
"metadata": {},
"outputs": [],
"source": [
"def load_huggingface_model(model_name: str, method: str = 'cli', force_download: bool = False) -> None:\n",
"def load_huggingface_model(conf: Secrets, model_name: str, method: str = 'cli', force_download: bool = False) -> None:\n",
" \"\"\"\n",
" Loads specified model into BucketFS choosing one of the two available methods.\n",
"\n",
" conf - Access to the secret store holding the configuration data.\n",
" model_name - Name of the model at Huggingface hub, e.g. facebook/nllb-moe-54b.\n",
" method - The recognized values are \"udf\" and \"cli\". If the parameter is not set then\n",
" will look for method selection in the configuration. That failed the CLI method\n",
Expand All @@ -134,9 +136,9 @@
"\n",
" method = method.lower()\n",
" if method == 'udf':\n",
" load_huggingface_model_udf(model_name)\n",
" load_huggingface_model_udf(conf, model_name)\n",
" else:\n",
" load_huggingface_model_cli(model_name, force_download=force_download)"
" load_huggingface_model_cli(conf, model_name, force_download=force_download)"
]
},
{
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Expand Up @@ -34,16 +34,17 @@
"source": [
"import ipywidgets as widgets\n",
"\n",
"from exasol.secret_store import Secrets\n",
"from exasol.ai_lab_config import AILabConfig as CKey\n",
"\n",
"\n",
"def get_te_config_ui() -> widgets.Widget:\n",
"def get_te_config_ui(conf: Secrets) -> widgets.Widget:\n",
"\n",
" inputs = [\n",
" ('Access token', widgets.Password(value=sb_config.get(CKey.huggingface_token)), CKey.huggingface_token)\n",
" ]\n",
"\n",
" return get_generic_config_ui(sb_config, [inputs], ['Huggingface Access Parameters'])\n"
" return get_generic_config_ui(conf, [inputs], ['Huggingface Access Parameters'])\n"
]
}
],
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Expand Up @@ -89,7 +89,7 @@
"outputs": [],
"source": [
"%run utils/model_retrieval.ipynb\n",
"load_huggingface_model(MODEL_NAME)"
"load_huggingface_model(sb_config, MODEL_NAME)"
]
},
{
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