{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Kütüphanelerin Yüklenmesi"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"ename": "ValueError",
"evalue": "numpy.dtype size changed, may indicate binary incompatibility. Expected 96 from C header, got 88 from PyObject",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mValueError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[1;32mIn[5], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mdatasets\u001b[39;00m\n\u001b[0;32m 2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mdatasets\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m load_dataset\n\u001b[0;32m 3\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mpandas\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mpd\u001b[39;00m \n",
"File \u001b[1;32mc:\\gitProjects\\deneme\\.venv\\Lib\\site-packages\\datasets\\__init__.py:17\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[38;5;66;03m# Copyright 2020 The HuggingFace Datasets Authors and the TensorFlow Datasets Authors.\u001b[39;00m\n\u001b[0;32m 2\u001b[0m \u001b[38;5;66;03m#\u001b[39;00m\n\u001b[0;32m 3\u001b[0m \u001b[38;5;66;03m# Licensed under the Apache License, Version 2.0 (the \"License\");\u001b[39;00m\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 12\u001b[0m \u001b[38;5;66;03m# See the License for the specific language governing permissions and\u001b[39;00m\n\u001b[0;32m 13\u001b[0m \u001b[38;5;66;03m# limitations under the License.\u001b[39;00m\n\u001b[0;32m 15\u001b[0m __version__ \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m2.20.0\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m---> 17\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01marrow_dataset\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m Dataset\n\u001b[0;32m 18\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01marrow_reader\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m ReadInstruction\n\u001b[0;32m 19\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mbuilder\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m ArrowBasedBuilder, BeamBasedBuilder, BuilderConfig, DatasetBuilder, GeneratorBasedBuilder\n",
"File \u001b[1;32mc:\\gitProjects\\deneme\\.venv\\Lib\\site-packages\\datasets\\arrow_dataset.py:59\u001b[0m\n\u001b[0;32m 57\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mfsspec\u001b[39;00m\n\u001b[0;32m 58\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mnumpy\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mnp\u001b[39;00m\n\u001b[1;32m---> 59\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mpandas\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mpd\u001b[39;00m\n\u001b[0;32m 60\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mpyarrow\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mpa\u001b[39;00m\n\u001b[0;32m 61\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mpyarrow\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcompute\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mpc\u001b[39;00m\n",
"File \u001b[1;32mc:\\gitProjects\\deneme\\.venv\\Lib\\site-packages\\pandas\\__init__.py:50\u001b[0m\n\u001b[0;32m 43\u001b[0m _module \u001b[38;5;241m=\u001b[39m _err\u001b[38;5;241m.\u001b[39mname\n\u001b[0;32m 44\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mImportError\u001b[39;00m(\n\u001b[0;32m 45\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mC extension: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m_module\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m not built. If you want to import \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m 46\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpandas from the source directory, you may need to run \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m 47\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mpython setup.py build_ext\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m to build the C extensions first.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m 48\u001b[0m ) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m_err\u001b[39;00m\n\u001b[1;32m---> 50\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mpandas\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_config\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (\n\u001b[0;32m 51\u001b[0m get_option,\n\u001b[0;32m 52\u001b[0m set_option,\n\u001b[0;32m 53\u001b[0m reset_option,\n\u001b[0;32m 54\u001b[0m describe_option,\n\u001b[0;32m 55\u001b[0m option_context,\n\u001b[0;32m 56\u001b[0m options,\n\u001b[0;32m 57\u001b[0m )\n\u001b[0;32m 59\u001b[0m \u001b[38;5;66;03m# let init-time option registration happen\u001b[39;00m\n\u001b[0;32m 60\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mpandas\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcore\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mconfig_init\u001b[39;00m \u001b[38;5;66;03m# pyright: ignore[reportUnusedImport] # noqa: F401\u001b[39;00m\n",
"File \u001b[1;32mc:\\gitProjects\\deneme\\.venv\\Lib\\site-packages\\pandas\\_config\\__init__.py:20\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m 2\u001b[0m \u001b[38;5;124;03mpandas._config is considered explicitly upstream of everything else in pandas,\u001b[39;00m\n\u001b[0;32m 3\u001b[0m \u001b[38;5;124;03mshould have no intra-pandas dependencies.\u001b[39;00m\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 6\u001b[0m \u001b[38;5;124;03mare initialized.\u001b[39;00m\n\u001b[0;32m 7\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m 8\u001b[0m __all__ \u001b[38;5;241m=\u001b[39m [\n\u001b[0;32m 9\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mconfig\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m 10\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdetect_console_encoding\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 18\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mwarn_copy_on_write\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m 19\u001b[0m ]\n\u001b[1;32m---> 20\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mpandas\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_config\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m config\n\u001b[0;32m 21\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mpandas\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_config\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m dates \u001b[38;5;66;03m# pyright: ignore[reportUnusedImport] # noqa: F401\u001b[39;00m\n\u001b[0;32m 22\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mpandas\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_config\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mconfig\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (\n\u001b[0;32m 23\u001b[0m _global_config,\n\u001b[0;32m 24\u001b[0m describe_option,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 29\u001b[0m set_option,\n\u001b[0;32m 30\u001b[0m )\n",
"File \u001b[1;32mc:\\gitProjects\\deneme\\.venv\\Lib\\site-packages\\pandas\\_config\\config.py:68\u001b[0m\n\u001b[0;32m 58\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mtyping\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (\n\u001b[0;32m 59\u001b[0m TYPE_CHECKING,\n\u001b[0;32m 60\u001b[0m Any,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 64\u001b[0m cast,\n\u001b[0;32m 65\u001b[0m )\n\u001b[0;32m 66\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mwarnings\u001b[39;00m\n\u001b[1;32m---> 68\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mpandas\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_typing\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (\n\u001b[0;32m 69\u001b[0m F,\n\u001b[0;32m 70\u001b[0m T,\n\u001b[0;32m 71\u001b[0m )\n\u001b[0;32m 72\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mpandas\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutil\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_exceptions\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m find_stack_level\n\u001b[0;32m 74\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m TYPE_CHECKING:\n",
"File \u001b[1;32mc:\\gitProjects\\deneme\\.venv\\Lib\\site-packages\\pandas\\_typing.py:198\u001b[0m\n\u001b[0;32m 192\u001b[0m Frequency \u001b[38;5;241m=\u001b[39m Union[\u001b[38;5;28mstr\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mBaseOffset\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n\u001b[0;32m 193\u001b[0m Axes \u001b[38;5;241m=\u001b[39m ListLike\n\u001b[0;32m 195\u001b[0m RandomState \u001b[38;5;241m=\u001b[39m Union[\n\u001b[0;32m 196\u001b[0m \u001b[38;5;28mint\u001b[39m,\n\u001b[0;32m 197\u001b[0m np\u001b[38;5;241m.\u001b[39mndarray,\n\u001b[1;32m--> 198\u001b[0m \u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrandom\u001b[49m\u001b[38;5;241m.\u001b[39mGenerator,\n\u001b[0;32m 199\u001b[0m np\u001b[38;5;241m.\u001b[39mrandom\u001b[38;5;241m.\u001b[39mBitGenerator,\n\u001b[0;32m 200\u001b[0m np\u001b[38;5;241m.\u001b[39mrandom\u001b[38;5;241m.\u001b[39mRandomState,\n\u001b[0;32m 201\u001b[0m ]\n\u001b[0;32m 203\u001b[0m \u001b[38;5;66;03m# dtypes\u001b[39;00m\n\u001b[0;32m 204\u001b[0m NpDtype \u001b[38;5;241m=\u001b[39m Union[\u001b[38;5;28mstr\u001b[39m, np\u001b[38;5;241m.\u001b[39mdtype, type_t[Union[\u001b[38;5;28mstr\u001b[39m, \u001b[38;5;28mcomplex\u001b[39m, \u001b[38;5;28mbool\u001b[39m, \u001b[38;5;28mobject\u001b[39m]]]\n",
"File \u001b[1;32mc:\\gitProjects\\deneme\\.venv\\Lib\\site-packages\\numpy\\__init__.py:351\u001b[0m, in \u001b[0;36m__getattr__\u001b[1;34m(attr)\u001b[0m\n\u001b[0;32m 350\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__dir__\u001b[39m():\n\u001b[1;32m--> 351\u001b[0m public_symbols \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mglobals\u001b[39m()\u001b[38;5;241m.\u001b[39mkeys() \u001b[38;5;241m|\u001b[39m {\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtesting\u001b[39m\u001b[38;5;124m'\u001b[39m}\n\u001b[0;32m 352\u001b[0m public_symbols \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m=\u001b[39m {\n\u001b[0;32m 353\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcore\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmatrixlib\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m 354\u001b[0m \u001b[38;5;66;03m# These were moved in 1.25 and may be deprecated eventually:\u001b[39;00m\n\u001b[0;32m 355\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mModuleDeprecationWarning\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mVisibleDeprecationWarning\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m 356\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mComplexWarning\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mTooHardError\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mAxisError\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m 357\u001b[0m }\n\u001b[0;32m 358\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mlist\u001b[39m(public_symbols)\n",
"File \u001b[1;32mc:\\gitProjects\\deneme\\.venv\\Lib\\site-packages\\numpy\\random\\__init__.py:180\u001b[0m\n\u001b[0;32m 126\u001b[0m __all__ \u001b[38;5;241m=\u001b[39m [\n\u001b[0;32m 127\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mbeta\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[0;32m 128\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mbinomial\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 176\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mzipf\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[0;32m 177\u001b[0m ]\n\u001b[0;32m 179\u001b[0m \u001b[38;5;66;03m# add these for module-freeze analysis (like PyInstaller)\u001b[39;00m\n\u001b[1;32m--> 180\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m _pickle\n\u001b[0;32m 181\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m _common\n\u001b[0;32m 182\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m _bounded_integers\n",
"File \u001b[1;32mc:\\gitProjects\\deneme\\.venv\\Lib\\site-packages\\numpy\\random\\_pickle.py:1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mmtrand\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m RandomState\n\u001b[0;32m 2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_philox\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m Philox\n\u001b[0;32m 3\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_pcg64\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m PCG64, PCG64DXSM\n",
"File \u001b[1;32mnumpy\\\\random\\\\mtrand.pyx:1\u001b[0m, in \u001b[0;36minit numpy.random.mtrand\u001b[1;34m()\u001b[0m\n",
"\u001b[1;31mValueError\u001b[0m: numpy.dtype size changed, may indicate binary incompatibility. Expected 96 from C header, got 88 from PyObject"
]
}
],
"source": [
"from datasets import load_dataset\n",
"import pandas as pd \n"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"ename": "OSError",
"evalue": "[WinError 126] Belirtilen modül bulunamadı. Error loading \"c:\\gitProjects\\deneme\\.venv\\Lib\\site-packages\\torch\\lib\\fbgemm.dll\" or one of its dependencies.",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mOSError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[1;32mIn[7], line 3\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[38;5;66;03m#verileri bart ile eğitme burada koleksiyon içerisindeki veriler tanımlanmalı \u001b[39;00m\n\u001b[0;32m 2\u001b[0m \u001b[38;5;66;03m# Load model directly\u001b[39;00m\n\u001b[1;32m----> 3\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mtransformers\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m AutoModel,AutoTokenizer\n\u001b[0;32m 4\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mtransformers\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (WEIGHTS_NAME, BertConfig,\n\u001b[0;32m 5\u001b[0m BertForQuestionAnswering, BertTokenizer)\n\u001b[0;32m 6\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mtorch\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mdata\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m DataLoader, SequentialSampler, TensorDataset\n",
"File \u001b[1;32mc:\\gitProjects\\deneme\\.venv\\Lib\\site-packages\\transformers\\__init__.py:26\u001b[0m\n\u001b[0;32m 23\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mtyping\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m TYPE_CHECKING\n\u001b[0;32m 25\u001b[0m \u001b[38;5;66;03m# Check the dependencies satisfy the minimal versions required.\u001b[39;00m\n\u001b[1;32m---> 26\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m dependency_versions_check\n\u001b[0;32m 27\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (\n\u001b[0;32m 28\u001b[0m OptionalDependencyNotAvailable,\n\u001b[0;32m 29\u001b[0m _LazyModule,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 48\u001b[0m logging,\n\u001b[0;32m 49\u001b[0m )\n\u001b[0;32m 52\u001b[0m logger \u001b[38;5;241m=\u001b[39m logging\u001b[38;5;241m.\u001b[39mget_logger(\u001b[38;5;18m__name__\u001b[39m) \u001b[38;5;66;03m# pylint: disable=invalid-name\u001b[39;00m\n",
"File \u001b[1;32mc:\\gitProjects\\deneme\\.venv\\Lib\\site-packages\\transformers\\dependency_versions_check.py:16\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[38;5;66;03m# Copyright 2020 The HuggingFace Team. All rights reserved.\u001b[39;00m\n\u001b[0;32m 2\u001b[0m \u001b[38;5;66;03m#\u001b[39;00m\n\u001b[0;32m 3\u001b[0m \u001b[38;5;66;03m# Licensed under the Apache License, Version 2.0 (the \"License\");\u001b[39;00m\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 12\u001b[0m \u001b[38;5;66;03m# See the License for the specific language governing permissions and\u001b[39;00m\n\u001b[0;32m 13\u001b[0m \u001b[38;5;66;03m# limitations under the License.\u001b[39;00m\n\u001b[0;32m 15\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mdependency_versions_table\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m deps\n\u001b[1;32m---> 16\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mversions\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m require_version, require_version_core\n\u001b[0;32m 19\u001b[0m \u001b[38;5;66;03m# define which module versions we always want to check at run time\u001b[39;00m\n\u001b[0;32m 20\u001b[0m \u001b[38;5;66;03m# (usually the ones defined in `install_requires` in setup.py)\u001b[39;00m\n\u001b[0;32m 21\u001b[0m \u001b[38;5;66;03m#\u001b[39;00m\n\u001b[0;32m 22\u001b[0m \u001b[38;5;66;03m# order specific notes:\u001b[39;00m\n\u001b[0;32m 23\u001b[0m \u001b[38;5;66;03m# - tqdm must be checked before tokenizers\u001b[39;00m\n\u001b[0;32m 25\u001b[0m pkgs_to_check_at_runtime \u001b[38;5;241m=\u001b[39m [\n\u001b[0;32m 26\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpython\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m 27\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtqdm\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 37\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpyyaml\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m 38\u001b[0m ]\n",
"File \u001b[1;32mc:\\gitProjects\\deneme\\.venv\\Lib\\site-packages\\transformers\\utils\\__init__.py:34\u001b[0m\n\u001b[0;32m 25\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mconstants\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD, IMAGENET_STANDARD_MEAN, IMAGENET_STANDARD_STD\n\u001b[0;32m 26\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mdoc\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (\n\u001b[0;32m 27\u001b[0m add_code_sample_docstrings,\n\u001b[0;32m 28\u001b[0m add_end_docstrings,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 32\u001b[0m replace_return_docstrings,\n\u001b[0;32m 33\u001b[0m )\n\u001b[1;32m---> 34\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mgeneric\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (\n\u001b[0;32m 35\u001b[0m ContextManagers,\n\u001b[0;32m 36\u001b[0m ExplicitEnum,\n\u001b[0;32m 37\u001b[0m ModelOutput,\n\u001b[0;32m 38\u001b[0m PaddingStrategy,\n\u001b[0;32m 39\u001b[0m TensorType,\n\u001b[0;32m 40\u001b[0m add_model_info_to_auto_map,\n\u001b[0;32m 41\u001b[0m add_model_info_to_custom_pipelines,\n\u001b[0;32m 42\u001b[0m cached_property,\n\u001b[0;32m 43\u001b[0m can_return_loss,\n\u001b[0;32m 44\u001b[0m expand_dims,\n\u001b[0;32m 45\u001b[0m filter_out_non_signature_kwargs,\n\u001b[0;32m 46\u001b[0m find_labels,\n\u001b[0;32m 47\u001b[0m flatten_dict,\n\u001b[0;32m 48\u001b[0m infer_framework,\n\u001b[0;32m 49\u001b[0m is_jax_tensor,\n\u001b[0;32m 50\u001b[0m is_numpy_array,\n\u001b[0;32m 51\u001b[0m is_tensor,\n\u001b[0;32m 52\u001b[0m is_tf_symbolic_tensor,\n\u001b[0;32m 53\u001b[0m is_tf_tensor,\n\u001b[0;32m 54\u001b[0m is_torch_device,\n\u001b[0;32m 55\u001b[0m is_torch_dtype,\n\u001b[0;32m 56\u001b[0m is_torch_tensor,\n\u001b[0;32m 57\u001b[0m reshape,\n\u001b[0;32m 58\u001b[0m squeeze,\n\u001b[0;32m 59\u001b[0m strtobool,\n\u001b[0;32m 60\u001b[0m tensor_size,\n\u001b[0;32m 61\u001b[0m to_numpy,\n\u001b[0;32m 62\u001b[0m to_py_obj,\n\u001b[0;32m 63\u001b[0m torch_float,\n\u001b[0;32m 64\u001b[0m torch_int,\n\u001b[0;32m 65\u001b[0m transpose,\n\u001b[0;32m 66\u001b[0m working_or_temp_dir,\n\u001b[0;32m 67\u001b[0m )\n\u001b[0;32m 68\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mhub\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (\n\u001b[0;32m 69\u001b[0m CLOUDFRONT_DISTRIB_PREFIX,\n\u001b[0;32m 70\u001b[0m HF_MODULES_CACHE,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 96\u001b[0m try_to_load_from_cache,\n\u001b[0;32m 97\u001b[0m )\n\u001b[0;32m 98\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mimport_utils\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (\n\u001b[0;32m 99\u001b[0m ACCELERATE_MIN_VERSION,\n\u001b[0;32m 100\u001b[0m ENV_VARS_TRUE_AND_AUTO_VALUES,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 219\u001b[0m torch_only_method,\n\u001b[0;32m 220\u001b[0m )\n",
"File \u001b[1;32mc:\\gitProjects\\deneme\\.venv\\Lib\\site-packages\\transformers\\utils\\generic.py:462\u001b[0m\n\u001b[0;32m 458\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mtuple\u001b[39m(\u001b[38;5;28mself\u001b[39m[k] \u001b[38;5;28;01mfor\u001b[39;00m k \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mkeys())\n\u001b[0;32m 461\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m is_torch_available():\n\u001b[1;32m--> 462\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mtorch\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_pytree\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01m_torch_pytree\u001b[39;00m\n\u001b[0;32m 464\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_model_output_flatten\u001b[39m(output: ModelOutput) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Tuple[List[Any], \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m_torch_pytree.Context\u001b[39m\u001b[38;5;124m\"\u001b[39m]:\n\u001b[0;32m 465\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mlist\u001b[39m(output\u001b[38;5;241m.\u001b[39mvalues()), \u001b[38;5;28mlist\u001b[39m(output\u001b[38;5;241m.\u001b[39mkeys())\n",
"File \u001b[1;32mc:\\gitProjects\\deneme\\.venv\\Lib\\site-packages\\torch\\__init__.py:148\u001b[0m\n\u001b[0;32m 146\u001b[0m err \u001b[38;5;241m=\u001b[39m ctypes\u001b[38;5;241m.\u001b[39mWinError(ctypes\u001b[38;5;241m.\u001b[39mget_last_error())\n\u001b[0;32m 147\u001b[0m err\u001b[38;5;241m.\u001b[39mstrerror \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m Error loading \u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mdll\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m or one of its dependencies.\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m--> 148\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m err\n\u001b[0;32m 150\u001b[0m kernel32\u001b[38;5;241m.\u001b[39mSetErrorMode(prev_error_mode)\n\u001b[0;32m 153\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_preload_cuda_deps\u001b[39m(lib_folder, lib_name):\n",
"\u001b[1;31mOSError\u001b[0m: [WinError 126] Belirtilen modül bulunamadı. Error loading \"c:\\gitProjects\\deneme\\.venv\\Lib\\site-packages\\torch\\lib\\fbgemm.dll\" or one of its dependencies."
]
}
],
"source": [
"#verileri bart ile eğitme burada koleksiyon içerisindeki veriler tanımlanmalı \n",
"# Load model directly\n",
"from transformers import AutoModel,AutoTokenizer\n",
"from transformers import (WEIGHTS_NAME, BertConfig,\n",
" BertForQuestionAnswering, BertTokenizer)\n",
"from torch.utils.data import DataLoader, SequentialSampler, TensorDataset\n",
"\n",
"#from utils import (get_answer, input_to_squad_example,squad_examples_to_features, to_list)\n",
"import collections\n",
"# Load model directly\n",
"from transformers import AutoTokenizer, AutoModelForSeq2SeqLM"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Train ve Test Verilerine İlişkin Databaselerin İçerisindeki Bilgilerin Alınması "
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"#birleştirilcek dosyaların listesi \n",
"train_files=['C:\\\\gitProjects\\\\oak\\\\data\\\\train-00000-of-00007.parquet','C:\\\\gitProjects\\\\oak\\\\data\\\\train-00001-of-00007.parquet','C:\\\\gitProjects\\\\oak\\\\data\\\\train-00002-of-00007.parquet','C:\\\\gitProjects\\\\oak\\\\data\\\\train-00003-of-00007.parquet','C:\\\\gitProjects\\\\oak\\\\data\\\\train-00004-of-00007.parquet']\n",
"test_files=['C:\\\\gitProjects\\\\oak\\\\data\\\\train-00005-of-00007.parquet','C:\\\\gitProjects\\\\oak\\\\data\\\\train-00006-of-00007.parquet']"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#dosyaları yükleyin ve birleştirin\n",
"train_dfs=[pd.read_parquet(file) for file in train_files]\n",
"test_dfs=[pd.read_parquet(file) for file in test_files]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#parque dosyalarının birleştirilmesi\n",
"train_df=pd.concat(train_dfs,ignore_index=True)\n",
"test_df=pd.concat(test_dfs,ignore_index=True)\n",
"\n",
"print(train_df.head())\n",
"print(train_df.head())"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"ename": "NameError",
"evalue": "name 'train_df' is not defined",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[1;32mIn[2], line 2\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[38;5;66;03m#train ve test dosyaları oluşturma \u001b[39;00m\n\u001b[1;32m----> 2\u001b[0m \u001b[43mtrain_df\u001b[49m\u001b[38;5;241m.\u001b[39mto_parquet(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mC:\u001b[39m\u001b[38;5;130;01m\\\\\u001b[39;00m\u001b[38;5;124mgitProjects\u001b[39m\u001b[38;5;130;01m\\\\\u001b[39;00m\u001b[38;5;124mdeneme\u001b[39m\u001b[38;5;130;01m\\\\\u001b[39;00m\u001b[38;5;124megitim\u001b[39m\u001b[38;5;130;01m\\\\\u001b[39;00m\u001b[38;5;124mtrain_Egitim\u001b[39m\u001b[38;5;130;01m\\\\\u001b[39;00m\u001b[38;5;124mmerged_train.parquet\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m 3\u001b[0m test_df\u001b[38;5;241m.\u001b[39mto_parquet(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mC:\u001b[39m\u001b[38;5;130;01m\\\\\u001b[39;00m\u001b[38;5;124mgitProjects\u001b[39m\u001b[38;5;130;01m\\\\\u001b[39;00m\u001b[38;5;124mdeneme\u001b[39m\u001b[38;5;130;01m\\\\\u001b[39;00m\u001b[38;5;124mtest_Egitim\u001b[39m\u001b[38;5;130;01m\\\\\u001b[39;00m\u001b[38;5;124mmerged_train.parquet\u001b[39m\u001b[38;5;124m'\u001b[39m)\n",
"\u001b[1;31mNameError\u001b[0m: name 'train_df' is not defined"
]
}
],
"source": [
"#train ve test dosyaları oluşturma \n",
"train_df.to_parquet('C:\\\\gitProjects\\\\deneme\\\\egitim\\\\train_Egitim\\\\merged_train.parquet')\n",
"test_df.to_parquet('C:\\\\gitProjects\\\\deneme\\\\test_Egitim\\\\merged_train.parquet')"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" Prompt_ID \\\n",
"0 bb26c95639b18fd88857bf0964cd1fb5 \n",
"1 56743c1870327184e058292a34ce12a8 \n",
"2 88aa2f72d37cb8671ff68a6f481e382b \n",
"3 703c086f7ffd9d8cc0497e82732860c7 \n",
"4 a310cb6ed3f48e721473ec0525239e4e \n",
"\n",
" Prompt \\\n",
"0 What were the crucial factors that contributed... \n",
"1 Create a comprehensive guide to understanding ... \n",
"2 Explore the historical significance and impact... \n",
"3 How can advanced data analytics be leveraged t... \n",
"4 Design a comprehensive diversity training prog... \n",
"\n",
" Response \\\n",
"0 **Crucial Factors Contributing to the Success ... \n",
"1 ## Comprehensive Guide to Weather Front Types:... \n",
"2 ## The Fall of the Berlin Wall: Historical Sig... \n",
"3 **1. Real-Time Sentiment Analysis:**\\n\\n* Anal... \n",
"4 **Phase 1: Awareness and Self-Reflection**\\n\\n... \n",
"\n",
" Category Subcategory \\\n",
"0 Voskhod program Voskhod 1 mission \n",
"1 Science mnemonics Weather front types \n",
"2 Political history The Fall of the Berlin Wall \n",
"3 Test matches Data analytics \n",
"4 Majority–minority relations Diversity training \n",
"\n",
" Prompt_token_length \n",
"0 34 \n",
"1 48 \n",
"2 67 \n",
"3 78 \n",
"4 55 \n",
" Prompt_ID \\\n",
"0 e75b977d9abe55f0d4b33d7ee6a77e43 \n",
"1 da7b42506d0c24c5f1d2371e0f53b8fe \n",
"2 dc1e302eb77f44f32623f958bdf5b1f5 \n",
"3 3e276bb9e578d719809b9654d710d6f5 \n",
"4 3efc98322cc67bcf32abcf25576d6ba1 \n",
"\n",
" Prompt \\\n",
"0 In the grand arena of intellectual discourse, ... \n",
"1 Amidst the tapestry of human knowledge, we inv... \n",
"2 In a world teeming with ideas and viewpoints, ... \n",
"3 Amidst the tapestry of human knowledge, we inv... \n",
"4 In the grand odyssey of intellectual discourse... \n",
"\n",
" Response Category Subcategory \\\n",
"0 In the spirit of the renowned English physicia... None None \n",
"1 Title: The Interplay of Politics and Psycholog... None None \n",
"2 Energy conservation has become a critical topi... None None \n",
"3 Title: Workplace Bullying: A Silent Epidemic\\n... None None \n",
"4 Title: The Grand Odyssey of Grito: A Historica... None None \n",
"\n",
" Prompt_token_length \n",
"0 134 \n",
"1 121 \n",
"2 191 \n",
"3 128 \n",
"4 190 \n"
]
}
],
"source": [
"#test ve train yollarını belirleme ve test, traindeki önemli sütunları alma\n",
"train_file_path=('C:\\\\gitProjects\\\\deneme\\\\egitim\\\\train_Egitim\\\\merged_train.parquet')\n",
"test_file_path=('C:\\\\gitProjects\\\\deneme\\\\egitim\\\\test_Egitim\\\\merged_train.parquet')\n",
"\n",
"train_df=pd.read_parquet(train_file_path,columns=['Prompt_ID','Prompt','Response','Category','Subcategory','Prompt_token_length'])\n",
"test_df=pd.read_parquet(test_file_path,columns=['Prompt_ID','Prompt','Response','Category','Subcategory','Prompt_token_length'])\n",
"\n",
"print(train_df.head())\n",
"print(test_df.head())"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Modelin Tokenizer ve İsminin Girilmesi"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"ename": "OSError",
"evalue": "[WinError 126] Belirtilen modül bulunamadı. Error loading \"c:\\gitProjects\\deneme\\.venv\\Lib\\site-packages\\torch\\lib\\fbgemm.dll\" or one of its dependencies.",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mOSError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[1;32mIn[3], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mtransformers\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m T5Tokenizer, T5ForConditionalGeneration\n\u001b[0;32m 3\u001b[0m tokenizer \u001b[38;5;241m=\u001b[39m T5Tokenizer\u001b[38;5;241m.\u001b[39mfrom_pretrained(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mgoogle/flan-t5-xxl\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m 4\u001b[0m model \u001b[38;5;241m=\u001b[39m T5ForConditionalGeneration\u001b[38;5;241m.\u001b[39mfrom_pretrained(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mgoogle/flan-t5-xxl\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
"File \u001b[1;32mc:\\gitProjects\\deneme\\.venv\\Lib\\site-packages\\transformers\\__init__.py:26\u001b[0m\n\u001b[0;32m 23\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mtyping\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m TYPE_CHECKING\n\u001b[0;32m 25\u001b[0m \u001b[38;5;66;03m# Check the dependencies satisfy the minimal versions required.\u001b[39;00m\n\u001b[1;32m---> 26\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m dependency_versions_check\n\u001b[0;32m 27\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (\n\u001b[0;32m 28\u001b[0m OptionalDependencyNotAvailable,\n\u001b[0;32m 29\u001b[0m _LazyModule,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 48\u001b[0m logging,\n\u001b[0;32m 49\u001b[0m )\n\u001b[0;32m 52\u001b[0m logger \u001b[38;5;241m=\u001b[39m logging\u001b[38;5;241m.\u001b[39mget_logger(\u001b[38;5;18m__name__\u001b[39m) \u001b[38;5;66;03m# pylint: disable=invalid-name\u001b[39;00m\n",
"File \u001b[1;32mc:\\gitProjects\\deneme\\.venv\\Lib\\site-packages\\transformers\\dependency_versions_check.py:16\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[38;5;66;03m# Copyright 2020 The HuggingFace Team. All rights reserved.\u001b[39;00m\n\u001b[0;32m 2\u001b[0m \u001b[38;5;66;03m#\u001b[39;00m\n\u001b[0;32m 3\u001b[0m \u001b[38;5;66;03m# Licensed under the Apache License, Version 2.0 (the \"License\");\u001b[39;00m\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 12\u001b[0m \u001b[38;5;66;03m# See the License for the specific language governing permissions and\u001b[39;00m\n\u001b[0;32m 13\u001b[0m \u001b[38;5;66;03m# limitations under the License.\u001b[39;00m\n\u001b[0;32m 15\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mdependency_versions_table\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m deps\n\u001b[1;32m---> 16\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mversions\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m require_version, require_version_core\n\u001b[0;32m 19\u001b[0m \u001b[38;5;66;03m# define which module versions we always want to check at run time\u001b[39;00m\n\u001b[0;32m 20\u001b[0m \u001b[38;5;66;03m# (usually the ones defined in `install_requires` in setup.py)\u001b[39;00m\n\u001b[0;32m 21\u001b[0m \u001b[38;5;66;03m#\u001b[39;00m\n\u001b[0;32m 22\u001b[0m \u001b[38;5;66;03m# order specific notes:\u001b[39;00m\n\u001b[0;32m 23\u001b[0m \u001b[38;5;66;03m# - tqdm must be checked before tokenizers\u001b[39;00m\n\u001b[0;32m 25\u001b[0m pkgs_to_check_at_runtime \u001b[38;5;241m=\u001b[39m [\n\u001b[0;32m 26\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpython\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m 27\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtqdm\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 37\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpyyaml\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m 38\u001b[0m ]\n",
"File \u001b[1;32mc:\\gitProjects\\deneme\\.venv\\Lib\\site-packages\\transformers\\utils\\__init__.py:34\u001b[0m\n\u001b[0;32m 25\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mconstants\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD, IMAGENET_STANDARD_MEAN, IMAGENET_STANDARD_STD\n\u001b[0;32m 26\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mdoc\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (\n\u001b[0;32m 27\u001b[0m add_code_sample_docstrings,\n\u001b[0;32m 28\u001b[0m add_end_docstrings,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 32\u001b[0m replace_return_docstrings,\n\u001b[0;32m 33\u001b[0m )\n\u001b[1;32m---> 34\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mgeneric\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (\n\u001b[0;32m 35\u001b[0m ContextManagers,\n\u001b[0;32m 36\u001b[0m ExplicitEnum,\n\u001b[0;32m 37\u001b[0m ModelOutput,\n\u001b[0;32m 38\u001b[0m PaddingStrategy,\n\u001b[0;32m 39\u001b[0m TensorType,\n\u001b[0;32m 40\u001b[0m add_model_info_to_auto_map,\n\u001b[0;32m 41\u001b[0m add_model_info_to_custom_pipelines,\n\u001b[0;32m 42\u001b[0m cached_property,\n\u001b[0;32m 43\u001b[0m can_return_loss,\n\u001b[0;32m 44\u001b[0m expand_dims,\n\u001b[0;32m 45\u001b[0m filter_out_non_signature_kwargs,\n\u001b[0;32m 46\u001b[0m find_labels,\n\u001b[0;32m 47\u001b[0m flatten_dict,\n\u001b[0;32m 48\u001b[0m infer_framework,\n\u001b[0;32m 49\u001b[0m is_jax_tensor,\n\u001b[0;32m 50\u001b[0m is_numpy_array,\n\u001b[0;32m 51\u001b[0m is_tensor,\n\u001b[0;32m 52\u001b[0m is_tf_symbolic_tensor,\n\u001b[0;32m 53\u001b[0m is_tf_tensor,\n\u001b[0;32m 54\u001b[0m is_torch_device,\n\u001b[0;32m 55\u001b[0m is_torch_dtype,\n\u001b[0;32m 56\u001b[0m is_torch_tensor,\n\u001b[0;32m 57\u001b[0m reshape,\n\u001b[0;32m 58\u001b[0m squeeze,\n\u001b[0;32m 59\u001b[0m strtobool,\n\u001b[0;32m 60\u001b[0m tensor_size,\n\u001b[0;32m 61\u001b[0m to_numpy,\n\u001b[0;32m 62\u001b[0m to_py_obj,\n\u001b[0;32m 63\u001b[0m torch_float,\n\u001b[0;32m 64\u001b[0m torch_int,\n\u001b[0;32m 65\u001b[0m transpose,\n\u001b[0;32m 66\u001b[0m working_or_temp_dir,\n\u001b[0;32m 67\u001b[0m )\n\u001b[0;32m 68\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mhub\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (\n\u001b[0;32m 69\u001b[0m CLOUDFRONT_DISTRIB_PREFIX,\n\u001b[0;32m 70\u001b[0m HF_MODULES_CACHE,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 96\u001b[0m try_to_load_from_cache,\n\u001b[0;32m 97\u001b[0m )\n\u001b[0;32m 98\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mimport_utils\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (\n\u001b[0;32m 99\u001b[0m ACCELERATE_MIN_VERSION,\n\u001b[0;32m 100\u001b[0m ENV_VARS_TRUE_AND_AUTO_VALUES,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 219\u001b[0m torch_only_method,\n\u001b[0;32m 220\u001b[0m )\n",
"File \u001b[1;32mc:\\gitProjects\\deneme\\.venv\\Lib\\site-packages\\transformers\\utils\\generic.py:462\u001b[0m\n\u001b[0;32m 458\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mtuple\u001b[39m(\u001b[38;5;28mself\u001b[39m[k] \u001b[38;5;28;01mfor\u001b[39;00m k \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mkeys())\n\u001b[0;32m 461\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m is_torch_available():\n\u001b[1;32m--> 462\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mtorch\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_pytree\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01m_torch_pytree\u001b[39;00m\n\u001b[0;32m 464\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_model_output_flatten\u001b[39m(output: ModelOutput) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Tuple[List[Any], \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m_torch_pytree.Context\u001b[39m\u001b[38;5;124m\"\u001b[39m]:\n\u001b[0;32m 465\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mlist\u001b[39m(output\u001b[38;5;241m.\u001b[39mvalues()), \u001b[38;5;28mlist\u001b[39m(output\u001b[38;5;241m.\u001b[39mkeys())\n",
"File \u001b[1;32mc:\\gitProjects\\deneme\\.venv\\Lib\\site-packages\\torch\\__init__.py:148\u001b[0m\n\u001b[0;32m 146\u001b[0m err \u001b[38;5;241m=\u001b[39m ctypes\u001b[38;5;241m.\u001b[39mWinError(ctypes\u001b[38;5;241m.\u001b[39mget_last_error())\n\u001b[0;32m 147\u001b[0m err\u001b[38;5;241m.\u001b[39mstrerror \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m Error loading \u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mdll\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m or one of its dependencies.\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m--> 148\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m err\n\u001b[0;32m 150\u001b[0m kernel32\u001b[38;5;241m.\u001b[39mSetErrorMode(prev_error_mode)\n\u001b[0;32m 153\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_preload_cuda_deps\u001b[39m(lib_folder, lib_name):\n",
"\u001b[1;31mOSError\u001b[0m: [WinError 126] Belirtilen modül bulunamadı. Error loading \"c:\\gitProjects\\deneme\\.venv\\Lib\\site-packages\\torch\\lib\\fbgemm.dll\" or one of its dependencies."
]
}
],
"source": [
"from transformers import T5Tokenizer, T5ForConditionalGeneration\n",
"\n",
"tokenizer = T5Tokenizer.from_pretrained(\"google/flan-t5-xxl\")\n",
"model = T5ForConditionalGeneration.from_pretrained(\"google/flan-t5-xxl\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"MongoDb üzerinden önemli sütunların çekilmesi"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Data successfully loaded into MongoDB.\n"
]
}
],
"source": [
"from pymongo import MongoClient\n",
"import pandas as pd\n",
"\n",
"# MongoDB connection settings\n",
"\n",
"def get_mongodb(database_name='yeniDatabase', collection_name='train', host='localhost', port=27017):\n",
" \"\"\"\n",
" MongoDB connection and collection selection\n",
" \"\"\"\n",
" client = MongoClient(f'mongodb://{host}:{port}/')\n",
" db = client[database_name]\n",
" collection = db[collection_name]\n",
" return collection\n",
"\n",
"# Function to load dataset into MongoDB\n",
"def dataset_read():\n",
" train_file_path = ('C:\\\\gitProjects\\\\deneme\\\\egitim\\\\train_Egitim\\\\merged_train.parquet')\n",
" data = pd.read_parquet(train_file_path, columns=['Prompt_ID', 'Prompt', 'Response', 'Category', 'Subcategory', 'Prompt_token_length'])\n",
" data_dict = data.to_dict(\"records\")\n",
"\n",
" # Get the MongoDB collection\n",
" source_collection = get_mongodb(database_name='yeniDatabase', collection_name='train') # Collection for translation\n",
"\n",
" # Insert data into MongoDB\n",
" source_collection.insert_many(data_dict)\n",
"\n",
" print(\"Data successfully loaded into MongoDB.\")\n",
" return source_collection\n",
"\n",
"# Call the function to load the dataset into MongoDB\n",
"source_collection = dataset_read()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Data successfully loaded into MongoDB.\n"
]
}
],
"source": [
"from pymongo import MongoClient\n",
"import pandas as pd\n",
"\n",
"# MongoDB connection settings\n",
"\n",
"def get_mongodb(database_name='yeniDatabase', collection_name='test', host='localhost', port=27017):\n",
" \"\"\"\n",
" MongoDB connection and collection selection\n",
" \"\"\"\n",
" client = MongoClient(f'mongodb://{host}:{port}/')\n",
" db = client[database_name]\n",
" collection = db[collection_name]\n",
" return collection\n",
"\n",
"# Function to load dataset into MongoDB\n",
"def dataset_read():\n",
" train_file_path = ('C:\\\\gitProjects\\\\deneme\\\\egitim\\\\test_Egitim\\\\merged_train.parquet')\n",
" data = pd.read_parquet(train_file_path, columns=['Prompt_ID', 'Prompt', 'Response', 'Category', 'Subcategory', 'Prompt_token_length'])\n",
" data_dict = data.to_dict(\"records\")\n",
"\n",
" # Get the MongoDB collection\n",
" source_collection = get_mongodb(database_name='yeniDatabase', collection_name='test') # Collection for translation\n",
"\n",
" # Insert data into MongoDB\n",
" source_collection.insert_many(data_dict)\n",
"\n",
" print(\"Data successfully loaded into MongoDB.\")\n",
" return source_collection\n",
"\n",
"# Call the function to load the dataset into MongoDB\n",
"source_collection = dataset_read()"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"c:\\gitProjects\\deneme\\.venv\\Lib\\site-packages\\tqdm\\auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
" from .autonotebook import tqdm as notebook_tqdm\n"
]
},
{
"ename": "OSError",
"evalue": "[WinError 126] Belirtilen modül bulunamadı. Error loading \"c:\\gitProjects\\deneme\\.venv\\Lib\\site-packages\\torch\\lib\\fbgemm.dll\" or one of its dependencies.",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mOSError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[1;32mIn[1], line 2\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[38;5;66;03m# uygulama için kullanılcak olan özelliklerin tanımlanması\u001b[39;00m\n\u001b[1;32m----> 2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mtransformers\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m BertTokenizer,BertForQuestionAnswering,BertConfig\n\u001b[0;32m 3\u001b[0m \u001b[38;5;28;01mclass\u001b[39;00m \u001b[38;5;21;01mQA\u001b[39;00m:\n\u001b[0;32m 4\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__init__\u001b[39m(\u001b[38;5;28mself\u001b[39m,model_path: \u001b[38;5;28mstr\u001b[39m):\n",
"File \u001b[1;32mc:\\gitProjects\\deneme\\.venv\\Lib\\site-packages\\transformers\\__init__.py:26\u001b[0m\n\u001b[0;32m 23\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mtyping\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m TYPE_CHECKING\n\u001b[0;32m 25\u001b[0m \u001b[38;5;66;03m# Check the dependencies satisfy the minimal versions required.\u001b[39;00m\n\u001b[1;32m---> 26\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m dependency_versions_check\n\u001b[0;32m 27\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (\n\u001b[0;32m 28\u001b[0m OptionalDependencyNotAvailable,\n\u001b[0;32m 29\u001b[0m _LazyModule,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 48\u001b[0m logging,\n\u001b[0;32m 49\u001b[0m )\n\u001b[0;32m 52\u001b[0m logger \u001b[38;5;241m=\u001b[39m logging\u001b[38;5;241m.\u001b[39mget_logger(\u001b[38;5;18m__name__\u001b[39m) \u001b[38;5;66;03m# pylint: disable=invalid-name\u001b[39;00m\n",
"File \u001b[1;32mc:\\gitProjects\\deneme\\.venv\\Lib\\site-packages\\transformers\\dependency_versions_check.py:16\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[38;5;66;03m# Copyright 2020 The HuggingFace Team. All rights reserved.\u001b[39;00m\n\u001b[0;32m 2\u001b[0m \u001b[38;5;66;03m#\u001b[39;00m\n\u001b[0;32m 3\u001b[0m \u001b[38;5;66;03m# Licensed under the Apache License, Version 2.0 (the \"License\");\u001b[39;00m\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 12\u001b[0m \u001b[38;5;66;03m# See the License for the specific language governing permissions and\u001b[39;00m\n\u001b[0;32m 13\u001b[0m \u001b[38;5;66;03m# limitations under the License.\u001b[39;00m\n\u001b[0;32m 15\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mdependency_versions_table\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m deps\n\u001b[1;32m---> 16\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mversions\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m require_version, require_version_core\n\u001b[0;32m 19\u001b[0m \u001b[38;5;66;03m# define which module versions we always want to check at run time\u001b[39;00m\n\u001b[0;32m 20\u001b[0m \u001b[38;5;66;03m# (usually the ones defined in `install_requires` in setup.py)\u001b[39;00m\n\u001b[0;32m 21\u001b[0m \u001b[38;5;66;03m#\u001b[39;00m\n\u001b[0;32m 22\u001b[0m \u001b[38;5;66;03m# order specific notes:\u001b[39;00m\n\u001b[0;32m 23\u001b[0m \u001b[38;5;66;03m# - tqdm must be checked before tokenizers\u001b[39;00m\n\u001b[0;32m 25\u001b[0m pkgs_to_check_at_runtime \u001b[38;5;241m=\u001b[39m [\n\u001b[0;32m 26\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpython\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m 27\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtqdm\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 37\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpyyaml\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m 38\u001b[0m ]\n",
"File \u001b[1;32mc:\\gitProjects\\deneme\\.venv\\Lib\\site-packages\\transformers\\utils\\__init__.py:34\u001b[0m\n\u001b[0;32m 25\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mconstants\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD, IMAGENET_STANDARD_MEAN, IMAGENET_STANDARD_STD\n\u001b[0;32m 26\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mdoc\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (\n\u001b[0;32m 27\u001b[0m add_code_sample_docstrings,\n\u001b[0;32m 28\u001b[0m add_end_docstrings,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 32\u001b[0m replace_return_docstrings,\n\u001b[0;32m 33\u001b[0m )\n\u001b[1;32m---> 34\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mgeneric\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (\n\u001b[0;32m 35\u001b[0m ContextManagers,\n\u001b[0;32m 36\u001b[0m ExplicitEnum,\n\u001b[0;32m 37\u001b[0m ModelOutput,\n\u001b[0;32m 38\u001b[0m PaddingStrategy,\n\u001b[0;32m 39\u001b[0m TensorType,\n\u001b[0;32m 40\u001b[0m add_model_info_to_auto_map,\n\u001b[0;32m 41\u001b[0m add_model_info_to_custom_pipelines,\n\u001b[0;32m 42\u001b[0m cached_property,\n\u001b[0;32m 43\u001b[0m can_return_loss,\n\u001b[0;32m 44\u001b[0m expand_dims,\n\u001b[0;32m 45\u001b[0m filter_out_non_signature_kwargs,\n\u001b[0;32m 46\u001b[0m find_labels,\n\u001b[0;32m 47\u001b[0m flatten_dict,\n\u001b[0;32m 48\u001b[0m infer_framework,\n\u001b[0;32m 49\u001b[0m is_jax_tensor,\n\u001b[0;32m 50\u001b[0m is_numpy_array,\n\u001b[0;32m 51\u001b[0m is_tensor,\n\u001b[0;32m 52\u001b[0m is_tf_symbolic_tensor,\n\u001b[0;32m 53\u001b[0m is_tf_tensor,\n\u001b[0;32m 54\u001b[0m is_torch_device,\n\u001b[0;32m 55\u001b[0m is_torch_dtype,\n\u001b[0;32m 56\u001b[0m is_torch_tensor,\n\u001b[0;32m 57\u001b[0m reshape,\n\u001b[0;32m 58\u001b[0m squeeze,\n\u001b[0;32m 59\u001b[0m strtobool,\n\u001b[0;32m 60\u001b[0m tensor_size,\n\u001b[0;32m 61\u001b[0m to_numpy,\n\u001b[0;32m 62\u001b[0m to_py_obj,\n\u001b[0;32m 63\u001b[0m torch_float,\n\u001b[0;32m 64\u001b[0m torch_int,\n\u001b[0;32m 65\u001b[0m transpose,\n\u001b[0;32m 66\u001b[0m working_or_temp_dir,\n\u001b[0;32m 67\u001b[0m )\n\u001b[0;32m 68\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mhub\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (\n\u001b[0;32m 69\u001b[0m CLOUDFRONT_DISTRIB_PREFIX,\n\u001b[0;32m 70\u001b[0m HF_MODULES_CACHE,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 96\u001b[0m try_to_load_from_cache,\n\u001b[0;32m 97\u001b[0m )\n\u001b[0;32m 98\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mimport_utils\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (\n\u001b[0;32m 99\u001b[0m ACCELERATE_MIN_VERSION,\n\u001b[0;32m 100\u001b[0m ENV_VARS_TRUE_AND_AUTO_VALUES,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 219\u001b[0m torch_only_method,\n\u001b[0;32m 220\u001b[0m )\n",
"File \u001b[1;32mc:\\gitProjects\\deneme\\.venv\\Lib\\site-packages\\transformers\\utils\\generic.py:462\u001b[0m\n\u001b[0;32m 458\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mtuple\u001b[39m(\u001b[38;5;28mself\u001b[39m[k] \u001b[38;5;28;01mfor\u001b[39;00m k \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mkeys())\n\u001b[0;32m 461\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m is_torch_available():\n\u001b[1;32m--> 462\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mtorch\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_pytree\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01m_torch_pytree\u001b[39;00m\n\u001b[0;32m 464\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_model_output_flatten\u001b[39m(output: ModelOutput) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Tuple[List[Any], \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m_torch_pytree.Context\u001b[39m\u001b[38;5;124m\"\u001b[39m]:\n\u001b[0;32m 465\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mlist\u001b[39m(output\u001b[38;5;241m.\u001b[39mvalues()), \u001b[38;5;28mlist\u001b[39m(output\u001b[38;5;241m.\u001b[39mkeys())\n",
"File \u001b[1;32mc:\\gitProjects\\deneme\\.venv\\Lib\\site-packages\\torch\\__init__.py:148\u001b[0m\n\u001b[0;32m 146\u001b[0m err \u001b[38;5;241m=\u001b[39m ctypes\u001b[38;5;241m.\u001b[39mWinError(ctypes\u001b[38;5;241m.\u001b[39mget_last_error())\n\u001b[0;32m 147\u001b[0m err\u001b[38;5;241m.\u001b[39mstrerror \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m Error loading \u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mdll\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m or one of its dependencies.\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m--> 148\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m err\n\u001b[0;32m 150\u001b[0m kernel32\u001b[38;5;241m.\u001b[39mSetErrorMode(prev_error_mode)\n\u001b[0;32m 153\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_preload_cuda_deps\u001b[39m(lib_folder, lib_name):\n",
"\u001b[1;31mOSError\u001b[0m: [WinError 126] Belirtilen modül bulunamadı. Error loading \"c:\\gitProjects\\deneme\\.venv\\Lib\\site-packages\\torch\\lib\\fbgemm.dll\" or one of its dependencies."
]
}
],
"source": [
"# uygulama için kullanılcak olan özelliklerin tanımlanması\n",
"from transformers import BertTokenizer,BertForQuestionAnswering,BertConfig\n",
"class QA:\n",
" def __init__(self,model_path: str):\n",
" self.max_seq_length = 384 #max seq\n",
" self.doc_stride = 128 #stride \n",
" self.do_lower_case = False\n",
" self.max_query_length = 30\n",
" self.n_best_size = 3\n",
" self.max_answer_length = 30\n",
" self.version_2_with_negative = False\n",
" #modelin yüklenmesi\n",
" self.model, self.tokenizer = self.load_model(model_path)\n",
" #hangi işlmecinin kullanıldığının belirlenmesi\n",
" if torch.cuda.is_available():\n",
" self.device = 'cuda'\n",
" else:\n",
" self.device = 'cpu'\n",
" self.model.to(self.device)\n",
" self.model.eval()\n",
" \n",
" # This function is used to load the model\n",
" def load_model(self,model_path: str,do_lower_case=False):\n",
" config = BertConfig.from_pretrained(model_path + \"C:\\\\gitProjects\\\\deneme\\\\egitim\\\\train_Egitim\")\n",
" tokenizer = BertTokenizer.from_pretrained(model_path, do_lower_case=do_lower_case)\n",
" model = BertForQuestionAnswering.from_pretrained(model_path, from_tf=False, config=config)\n",
" return model, tokenizer\n"
]
}
],
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