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null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "8d9f42c52f604fb590e77a3f5441ec09": { "model_module": "@jupyter-widgets/controls", "model_name": "DescriptionStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } } } } }, "cells": [ { "cell_type": "markdown", "source": [ "# LISA\n", "\n", "https://github.com/dvlab-research/LISA\n", "\n" ], "metadata": { "id": "rW1smfZpwoKs" } }, { "cell_type": "code", "source": [ "!pip freeze > ./freeze.txt" ], "metadata": { "id": "1NUSA0DPh7CO" }, "execution_count": 3, "outputs": [] }, { "cell_type": "code", "source": [ "%%bash\n", "\n", "cd /content\n", "sudo apt install git-lfs -y\n", "echo \"installed git-lfs\"\n", "git clone https://huggingface.co/spaces/aletrn/lisa-on-cuda\n", "git checkout packaging\n", "# cd lisa-on-cuda\n", "# git pull\n", "echo \"cloned.\"" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "mbt3zCgrIXQd", "outputId": "bd1fe583-a85b-43ea-8eb9-255774e0b409" }, "execution_count": 1, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Reading package lists...\n", "Building dependency tree...\n", "Reading state information...\n", "git-lfs is already the newest version (3.0.2-1ubuntu0.2).\n", "0 upgraded, 0 newly installed, 0 to remove and 35 not upgraded.\n", "installed git-lfs\n", "cloned.\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "\n", "WARNING: apt does not have a stable CLI interface. Use with caution in scripts.\n", "\n", "Cloning into 'lisa-on-cuda'...\n", "Filtering content: 48% (15/31)\rFiltering content: 51% (16/31)\rFiltering content: 54% (17/31)\rFiltering content: 58% (18/31)\rFiltering content: 61% (19/31)\rFiltering content: 64% (20/31), 17.74 MiB | 33.28 MiB/s\rFiltering content: 67% (21/31), 17.74 MiB | 33.28 MiB/s\rFiltering content: 70% (22/31), 17.74 MiB | 33.28 MiB/s\rFiltering content: 74% (23/31), 17.74 MiB | 33.28 MiB/s\rFiltering content: 77% (24/31), 17.74 MiB | 33.28 MiB/s\rFiltering content: 80% (25/31), 17.74 MiB | 33.28 MiB/s\rFiltering content: 83% (26/31), 17.74 MiB | 33.28 MiB/s\rFiltering content: 87% (27/31), 17.74 MiB | 33.28 MiB/s\rFiltering content: 90% (28/31), 17.74 MiB | 33.28 MiB/s\rFiltering content: 93% (29/31), 17.74 MiB | 33.28 MiB/s\rFiltering content: 96% (30/31), 17.74 MiB | 33.28 MiB/s\rFiltering content: 100% (31/31), 17.74 MiB | 33.28 MiB/s\rFiltering content: 100% (31/31), 19.13 MiB | 12.35 MiB/s, done.\n", "fatal: not a git repository (or any of the parent directories): .git\n" ] } ] }, { "cell_type": "code", "source": [ "%%bash\n", "\n", "cd /content/lisa-on-cuda/\n", "git checkout packaging\n", "git log|head" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "d1VEHQ5Zkq-8", "outputId": "72e819bb-433e-408a-b382-5b3c5febc19a" }, "execution_count": 6, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Branch 'packaging' set up to track remote branch 'packaging' from 'origin'.\n", "commit 60fa201359a4a3ae870f114f647a9fd05b7a0d13\n", "Author: alessandro trinca tornidor \n", "Date: Sun Mar 10 19:12:36 2024 +0100\n", "\n", " [refactor] prepare packaging moving all the modules under 'lisa_on_cuda' (renamed from 'model')\n", "\n", "commit 52318ecdc84c7f3e099ad62e05b0bb4956888985\n", "Author: alessandro trinca tornidor \n", "Date: Sun Mar 10 01:30:58 2024 +0100\n", "\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "Switched to a new branch 'packaging'\n" ] } ] }, { "cell_type": "code", "source": [ "!pip freeze\n", "\n", "print(\"ok\")" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "NzJXs40cfFFH", "outputId": "436dbb22-2420-43c5-898c-c9184155c1c3" }, "execution_count": 7, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "absl-py==1.4.0\n", "aiohttp==3.9.3\n", "aiosignal==1.3.1\n", "alabaster==0.7.16\n", "albumentations==1.3.1\n", "altair==4.2.2\n", "annotated-types==0.6.0\n", "anyio==3.7.1\n", "appdirs==1.4.4\n", "argon2-cffi==23.1.0\n", "argon2-cffi-bindings==21.2.0\n", "array-record==0.5.0\n", "arviz==0.15.1\n", "astropy==5.3.4\n", "astunparse==1.6.3\n", "async-timeout==4.0.3\n", "atpublic==4.0\n", "attrs==23.2.0\n", "audioread==3.0.1\n", "autograd==1.6.2\n", "Babel==2.14.0\n", "backcall==0.2.0\n", "beautifulsoup4==4.12.3\n", "bidict==0.23.1\n", "bigframes==0.22.0\n", "bleach==6.1.0\n", "blinker==1.4\n", "blis==0.7.11\n", "blosc2==2.0.0\n", "bokeh==3.3.4\n", "bqplot==0.12.43\n", "branca==0.7.1\n", "build==1.1.1\n", "CacheControl==0.14.0\n", "cachetools==5.3.3\n", "catalogue==2.0.10\n", "certifi==2024.2.2\n", "cffi==1.16.0\n", "chardet==5.2.0\n", "charset-normalizer==3.3.2\n", "chex==0.1.85\n", "click==8.1.7\n", "click-plugins==1.1.1\n", "cligj==0.7.2\n", "cloudpathlib==0.16.0\n", "cloudpickle==2.2.1\n", "cmake==3.27.9\n", "cmdstanpy==1.2.1\n", "colorcet==3.1.0\n", "colorlover==0.3.0\n", "colour==0.1.5\n", "community==1.0.0b1\n", "confection==0.1.4\n", "cons==0.4.6\n", "contextlib2==21.6.0\n", "contourpy==1.2.0\n", "cryptography==42.0.5\n", "cufflinks==0.17.3\n", "cupy-cuda12x==12.2.0\n", "cvxopt==1.3.2\n", "cvxpy==1.3.3\n", "cycler==0.12.1\n", "cymem==2.0.8\n", "Cython==3.0.9\n", "dask==2023.8.1\n", "datascience==0.17.6\n", "db-dtypes==1.2.0\n", "dbus-python==1.2.18\n", "debugpy==1.6.6\n", "decorator==4.4.2\n", "defusedxml==0.7.1\n", "distributed==2023.8.1\n", "distro==1.7.0\n", "dlib==19.24.2\n", "dm-tree==0.1.8\n", "docutils==0.18.1\n", "dopamine-rl==4.0.6\n", "duckdb==0.9.2\n", "earthengine-api==0.1.392\n", "easydict==1.13\n", "ecos==2.0.13\n", "editdistance==0.6.2\n", "eerepr==0.0.4\n", "en-core-web-sm @ https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.7.1/en_core_web_sm-3.7.1-py3-none-any.whl#sha256=86cc141f63942d4b2c5fcee06630fd6f904788d2f0ab005cce45aadb8fb73889\n", "entrypoints==0.4\n", "et-xmlfile==1.1.0\n", "etils==1.7.0\n", "etuples==0.3.9\n", "exceptiongroup==1.2.0\n", "fastai==2.7.14\n", "fastcore==1.5.29\n", "fastdownload==0.0.7\n", "fastjsonschema==2.19.1\n", "fastprogress==1.0.3\n", "fastrlock==0.8.2\n", "filelock==3.13.1\n", "fiona==1.9.5\n", "firebase-admin==5.3.0\n", "Flask==2.2.5\n", "flatbuffers==23.5.26\n", "flax==0.8.1\n", "folium==0.14.0\n", "fonttools==4.49.0\n", "frozendict==2.4.0\n", "frozenlist==1.4.1\n", "fsspec==2023.6.0\n", "future==0.18.3\n", "gast==0.5.4\n", "gcsfs==2023.6.0\n", "GDAL==3.6.4\n", "gdown==4.7.3\n", "geemap==0.32.0\n", "gensim==4.3.2\n", "geocoder==1.38.1\n", "geographiclib==2.0\n", "geopandas==0.13.2\n", "geopy==2.3.0\n", "gin-config==0.5.0\n", "glob2==0.7\n", "google==2.0.3\n", "google-ai-generativelanguage==0.4.0\n", "google-api-core==2.11.1\n", "google-api-python-client==2.84.0\n", "google-auth==2.27.0\n", "google-auth-httplib2==0.1.1\n", "google-auth-oauthlib==1.2.0\n", "google-cloud-aiplatform==1.43.0\n", "google-cloud-bigquery==3.12.0\n", "google-cloud-bigquery-connection==1.12.1\n", "google-cloud-bigquery-storage==2.24.0\n", "google-cloud-core==2.3.3\n", "google-cloud-datastore==2.15.2\n", "google-cloud-firestore==2.11.1\n", "google-cloud-functions==1.13.3\n", "google-cloud-iam==2.14.3\n", "google-cloud-language==2.13.3\n", "google-cloud-resource-manager==1.12.3\n", "google-cloud-storage==2.8.0\n", "google-cloud-translate==3.11.3\n", "google-colab @ file:///colabtools/dist/google-colab-1.0.0.tar.gz#sha256=e916d4e7c3ba6158df864a2e03852211d8fab20abb3db5205b865eedf4be9799\n", "google-crc32c==1.5.0\n", "google-generativeai==0.3.2\n", "google-pasta==0.2.0\n", "google-resumable-media==2.7.0\n", "googleapis-common-protos==1.62.0\n", "googledrivedownloader==0.4\n", "graphviz==0.20.1\n", "greenlet==3.0.3\n", "grpc-google-iam-v1==0.13.0\n", "grpcio==1.62.0\n", "grpcio-status==1.48.2\n", "gspread==3.4.2\n", "gspread-dataframe==3.3.1\n", "gym==0.25.2\n", "gym-notices==0.0.8\n", "h5netcdf==1.3.0\n", "h5py==3.9.0\n", "holidays==0.44\n", "holoviews==1.17.1\n", "html5lib==1.1\n", "httpimport==1.3.1\n", "httplib2==0.22.0\n", "huggingface-hub==0.20.3\n", "humanize==4.7.0\n", "hyperopt==0.2.7\n", "ibis-framework==7.1.0\n", "idna==3.6\n", "imageio==2.31.6\n", "imageio-ffmpeg==0.4.9\n", "imagesize==1.4.1\n", "imbalanced-learn==0.10.1\n", "imgaug==0.4.0\n", "importlib-metadata==7.0.1\n", "importlib_resources==6.1.2\n", "imutils==0.5.4\n", "inflect==7.0.0\n", "iniconfig==2.0.0\n", "intel-openmp==2023.2.3\n", "ipyevents==2.0.2\n", "ipyfilechooser==0.6.0\n", "ipykernel==5.5.6\n", "ipyleaflet==0.18.2\n", "ipython==7.34.0\n", "ipython-genutils==0.2.0\n", "ipython-sql==0.5.0\n", "ipytree==0.2.2\n", "ipywidgets==7.7.1\n", "itsdangerous==2.1.2\n", "jax==0.4.23\n", "jaxlib @ https://storage.googleapis.com/jax-releases/cuda12/jaxlib-0.4.23+cuda12.cudnn89-cp310-cp310-manylinux2014_x86_64.whl#sha256=8e42000672599e7ec0ea7f551acfcc95dcdd0e22b05a1d1f12f97b56a9fce4a8\n", "jeepney==0.7.1\n", "jieba==0.42.1\n", "Jinja2==3.1.3\n", "joblib==1.3.2\n", "jsonpickle==3.0.3\n", "jsonschema==4.19.2\n", "jsonschema-specifications==2023.12.1\n", "jupyter-client==6.1.12\n", "jupyter-console==6.1.0\n", "jupyter-server==1.24.0\n", "jupyter_core==5.7.1\n", "jupyterlab_pygments==0.3.0\n", "jupyterlab_widgets==3.0.10\n", "kaggle==1.5.16\n", "kagglehub==0.2.0\n", "keras==2.15.0\n", "keyring==23.5.0\n", "kiwisolver==1.4.5\n", "langcodes==3.3.0\n", "launchpadlib==1.10.16\n", "lazr.restfulclient==0.14.4\n", "lazr.uri==1.0.6\n", "lazy_loader==0.3\n", "libclang==16.0.6\n", "librosa==0.10.1\n", "lightgbm==4.1.0\n", "linkify-it-py==2.0.3\n", "llvmlite==0.41.1\n", "locket==1.0.0\n", "logical-unification==0.4.6\n", "lxml==4.9.4\n", "malloy==2023.1067\n", "Markdown==3.5.2\n", "markdown-it-py==3.0.0\n", "MarkupSafe==2.1.5\n", "matplotlib==3.7.1\n", "matplotlib-inline==0.1.6\n", "matplotlib-venn==0.11.10\n", "mdit-py-plugins==0.4.0\n", "mdurl==0.1.2\n", "miniKanren==1.0.3\n", "missingno==0.5.2\n", "mistune==0.8.4\n", "mizani==0.9.3\n", "mkl==2023.2.0\n", "ml-dtypes==0.2.0\n", "mlxtend==0.22.0\n", "more-itertools==10.1.0\n", "moviepy==1.0.3\n", "mpmath==1.3.0\n", "msgpack==1.0.8\n", "multidict==6.0.5\n", "multipledispatch==1.0.0\n", "multitasking==0.0.11\n", "murmurhash==1.0.10\n", "music21==9.1.0\n", "natsort==8.4.0\n", "nbclassic==1.0.0\n", "nbclient==0.9.0\n", "nbconvert==6.5.4\n", "nbformat==5.9.2\n", "nest-asyncio==1.6.0\n", "networkx==3.2.1\n", "nibabel==4.0.2\n", "nltk==3.8.1\n", "notebook==6.5.5\n", "notebook_shim==0.2.4\n", "numba==0.58.1\n", "numexpr==2.9.0\n", "numpy==1.25.2\n", "oauth2client==4.1.3\n", "oauthlib==3.2.2\n", "opencv-contrib-python==4.8.0.76\n", "opencv-python==4.8.0.76\n", "opencv-python-headless==4.9.0.80\n", "openpyxl==3.1.2\n", "opt-einsum==3.3.0\n", "optax==0.1.9\n", "orbax-checkpoint==0.4.4\n", "osqp==0.6.2.post8\n", "packaging==23.2\n", "pandas==1.5.3\n", "pandas-datareader==0.10.0\n", "pandas-gbq==0.19.2\n", "pandas-stubs==1.5.3.230304\n", "pandocfilters==1.5.1\n", "panel==1.3.8\n", "param==2.0.2\n", "parso==0.8.3\n", "parsy==2.1\n", "partd==1.4.1\n", "pathlib==1.0.1\n", "patsy==0.5.6\n", "peewee==3.17.1\n", "pexpect==4.9.0\n", "pickleshare==0.7.5\n", "Pillow==9.4.0\n", "pins==0.8.4\n", "pip-tools==6.13.0\n", "platformdirs==4.2.0\n", "plotly==5.15.0\n", "plotnine==0.12.4\n", "pluggy==1.4.0\n", "polars==0.20.2\n", "pooch==1.8.1\n", "portpicker==1.5.2\n", "prefetch-generator==1.0.3\n", "preshed==3.0.9\n", "prettytable==3.10.0\n", "proglog==0.1.10\n", "progressbar2==4.2.0\n", "prometheus_client==0.20.0\n", "promise==2.3\n", "prompt-toolkit==3.0.43\n", "prophet==1.1.5\n", "proto-plus==1.23.0\n", "protobuf==3.20.3\n", "psutil==5.9.5\n", "psycopg2==2.9.9\n", "ptyprocess==0.7.0\n", "py-cpuinfo==9.0.0\n", "py4j==0.10.9.7\n", "pyarrow==14.0.2\n", "pyarrow-hotfix==0.6\n", "pyasn1==0.5.1\n", "pyasn1-modules==0.3.0\n", "pycocotools==2.0.7\n", "pycparser==2.21\n", "pydantic==2.6.3\n", "pydantic_core==2.16.3\n", "pydata-google-auth==1.8.2\n", "pydot==1.4.2\n", "pydot-ng==2.0.0\n", "pydotplus==2.0.2\n", "PyDrive==1.3.1\n", "PyDrive2==1.6.3\n", "pyerfa==2.0.1.1\n", "pygame==2.5.2\n", "Pygments==2.16.1\n", "PyGObject==3.42.1\n", "PyJWT==2.3.0\n", "pymc==5.10.4\n", "pymystem3==0.2.0\n", "PyOpenGL==3.1.7\n", "pyOpenSSL==24.0.0\n", "pyparsing==3.1.1\n", "pyperclip==1.8.2\n", "pyproj==3.6.1\n", "pyproject_hooks==1.0.0\n", "pyshp==2.3.1\n", "PySocks==1.7.1\n", "pytensor==2.18.6\n", "pytest==7.4.4\n", "python-apt @ file:///backend-container/containers/python_apt-0.0.0-cp310-cp310-linux_x86_64.whl#sha256=b209c7165d6061963abe611492f8c91c3bcef4b7a6600f966bab58900c63fefa\n", "python-box==7.1.1\n", "python-dateutil==2.8.2\n", "python-louvain==0.16\n", "python-slugify==8.0.4\n", "python-utils==3.8.2\n", "pytz==2023.4\n", "pyviz_comms==3.0.1\n", "PyWavelets==1.5.0\n", "PyYAML==6.0.1\n", "pyzmq==23.2.1\n", "qdldl==0.1.7.post0\n", "qudida==0.0.4\n", "ratelim==0.1.6\n", "referencing==0.33.0\n", "regex==2023.12.25\n", "requests==2.31.0\n", "requests-oauthlib==1.3.1\n", "requirements-parser==0.5.0\n", "rich==13.7.1\n", "rpds-py==0.18.0\n", "rpy2==3.4.2\n", "rsa==4.9\n", "safetensors==0.4.2\n", "scikit-image==0.19.3\n", "scikit-learn==1.2.2\n", "scipy==1.11.4\n", "scooby==0.9.2\n", "scs==3.2.4.post1\n", "seaborn==0.13.1\n", "SecretStorage==3.3.1\n", "Send2Trash==1.8.2\n", "sentencepiece==0.1.99\n", "shapely==2.0.3\n", "six==1.16.0\n", "sklearn-pandas==2.2.0\n", "smart-open==6.4.0\n", "sniffio==1.3.1\n", "snowballstemmer==2.2.0\n", "sortedcontainers==2.4.0\n", "soundfile==0.12.1\n", "soupsieve==2.5\n", "soxr==0.3.7\n", "spacy==3.7.4\n", "spacy-legacy==3.0.12\n", "spacy-loggers==1.0.5\n", "Sphinx==5.0.2\n", "sphinxcontrib-applehelp==1.0.8\n", "sphinxcontrib-devhelp==1.0.6\n", "sphinxcontrib-htmlhelp==2.0.5\n", "sphinxcontrib-jsmath==1.0.1\n", "sphinxcontrib-qthelp==1.0.7\n", "sphinxcontrib-serializinghtml==1.1.10\n", "SQLAlchemy==2.0.28\n", "sqlglot==19.9.0\n", "sqlparse==0.4.4\n", "srsly==2.4.8\n", "stanio==0.3.0\n", "statsmodels==0.14.1\n", "sympy==1.12\n", "tables==3.8.0\n", "tabulate==0.9.0\n", "tbb==2021.11.0\n", "tblib==3.0.0\n", "tenacity==8.2.3\n", "tensorboard==2.15.2\n", "tensorboard-data-server==0.7.2\n", "tensorflow==2.15.0\n", "tensorflow-datasets==4.9.4\n", "tensorflow-estimator==2.15.0\n", "tensorflow-gcs-config==2.15.0\n", "tensorflow-hub==0.16.1\n", "tensorflow-io-gcs-filesystem==0.36.0\n", "tensorflow-metadata==1.14.0\n", "tensorflow-probability==0.23.0\n", "tensorstore==0.1.45\n", "termcolor==2.4.0\n", "terminado==0.18.0\n", "text-unidecode==1.3\n", "textblob==0.17.1\n", "tf-keras==2.15.0\n", "tf-slim==1.1.0\n", "thinc==8.2.3\n", "threadpoolctl==3.3.0\n", "tifffile==2024.2.12\n", "tinycss2==1.2.1\n", "tokenizers==0.15.2\n", "toml==0.10.2\n", "tomli==2.0.1\n", "toolz==0.12.1\n", "torch @ https://download.pytorch.org/whl/cu121/torch-2.1.0%2Bcu121-cp310-cp310-linux_x86_64.whl#sha256=0d4e8c52a1fcf5ed6cfc256d9a370fcf4360958fc79d0b08a51d55e70914df46\n", "torchaudio @ https://download.pytorch.org/whl/cu121/torchaudio-2.1.0%2Bcu121-cp310-cp310-linux_x86_64.whl#sha256=676bda4042734eda99bc59b2d7f761f345d3cde0cad492ad34e3aefde688c6d8\n", "torchdata==0.7.0\n", "torchsummary==1.5.1\n", "torchtext==0.16.0\n", "torchvision @ https://download.pytorch.org/whl/cu121/torchvision-0.16.0%2Bcu121-cp310-cp310-linux_x86_64.whl#sha256=e76e78d0ad43636c9884b3084ffaea8a8b61f21129fbfa456a5fe734f0affea9\n", "tornado==6.3.3\n", "tqdm==4.66.2\n", "traitlets==5.7.1\n", "traittypes==0.2.1\n", "transformers==4.38.2\n", "triton==2.1.0\n", "tweepy==4.14.0\n", "typer==0.9.0\n", "types-pytz==2024.1.0.20240203\n", "types-setuptools==69.1.0.20240302\n", "typing_extensions==4.10.0\n", "tzlocal==5.2\n", "uc-micro-py==1.0.3\n", "uritemplate==4.1.1\n", "urllib3==2.0.7\n", "vega-datasets==0.9.0\n", "wadllib==1.3.6\n", "wasabi==1.1.2\n", "wcwidth==0.2.13\n", "weasel==0.3.4\n", "webcolors==1.13\n", "webencodings==0.5.1\n", "websocket-client==1.7.0\n", "Werkzeug==3.0.1\n", "widgetsnbextension==3.6.6\n", "wordcloud==1.9.3\n", "wrapt==1.14.1\n", "xarray==2023.7.0\n", "xarray-einstats==0.7.0\n", "xgboost==2.0.3\n", "xlrd==2.0.1\n", "xxhash==3.4.1\n", "xyzservices==2023.10.1\n", "yarl==1.9.4\n", "yellowbrick==1.5\n", "yfinance==0.2.37\n", "zict==3.0.0\n", "zipp==3.17.0\n", "ok\n" ] } ] }, { "cell_type": "code", "source": [ "from datetime import datetime\n", "\n", "print(f\"start notebook: now is {datetime.now()}.\")\n", "\n", "from google.colab import drive\n", "drive.mount('/content/gdrive/')" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "jwcwJ__nPhx-", "outputId": "9365e9d2-9243-4c75-a449-62ea1daed5b7" }, "execution_count": 8, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "start notebook: now is 2024-03-10 18:17:30.651301.\n", "Mounted at /content/gdrive/\n" ] } ] }, { "cell_type": "code", "source": [ "%%bash\n", "rm -rf /root/.cache\n", "mkdir -p \"/content/gdrive/My Drive/lisa_on_gpu_folder/.cache/\"\n", "ln -s \"/content/gdrive/My Drive/lisa_on_gpu_folder/.cache/\" /root/.cache\n", "\n", "pip install pip wheel --upgrade\n", "echo \"ok\"" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "RHo4vB4tRQL8", "outputId": "54cfc19b-2568-4acd-daa8-52e1f31387f8" }, "execution_count": 9, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Requirement already satisfied: pip in /usr/local/lib/python3.10/dist-packages (23.1.2)\n", "Collecting pip\n", " Using cached pip-24.0-py3-none-any.whl (2.1 MB)\n", "Requirement already satisfied: wheel in /usr/local/lib/python3.10/dist-packages (0.42.0)\n", "Installing collected packages: pip\n", " Attempting uninstall: pip\n", " Found existing installation: pip 23.1.2\n", " Uninstalling pip-23.1.2:\n", " Successfully uninstalled pip-23.1.2\n", "Successfully installed pip-24.0\n", "ok\n" ] } ] }, { "cell_type": "code", "source": [ "%%bash\n", "\n", "ls -l \"/content/gdrive/My Drive/lisa_on_gpu_folder/.cache/\"\n", "ls -l \"/root/.cache\"\n", "\n", "echo \"ok\"" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "E_d_5lEKRzyo", "outputId": "81528d6f-9b0b-4854-f84b-ccc1e41755f0" }, "execution_count": 10, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "total 28\n", "drwx------ 2 root root 4096 Mar 8 13:35 http\n", "drwx------ 2 root root 4096 Mar 6 22:56 huggingface\n", "drwx------ 2 root root 4096 Mar 5 14:48 matplotlib\n", "drwx------ 2 root root 4096 Mar 6 22:53 node-gyp\n", "drwx------ 5 root root 4096 Mar 6 22:54 pip\n", "drwx------ 2 root root 4096 Mar 8 21:12 torch\n", "drwx------ 2 root root 4096 Mar 8 13:35 transformers\n", "lrwxrwxrwx 1 root root 51 Mar 10 18:17 /root/.cache -> /content/gdrive/My Drive/lisa_on_gpu_folder/.cache/\n", "ok\n" ] } ] }, { "cell_type": "code", "source": [ "%%bash\n", "\n", "echo \"start uninstalling torchaudio torchdata torchtext\"\n", "pip uninstall -y torchaudio torchdata torchtext -y\n", "echo \"uninstalled: torchaudio torchdata torchtext\"" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "7C5Qjf6JMmGf", "outputId": "63dadc8f-7801-426d-dca2-6feb4d474073" }, "execution_count": 11, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "start uninstalling torchaudio torchdata torchtext\n", "Found existing installation: torchaudio 2.1.0+cu121\n", "Uninstalling torchaudio-2.1.0+cu121:\n", " Successfully uninstalled torchaudio-2.1.0+cu121\n", "Found existing installation: torchdata 0.7.0\n", "Uninstalling torchdata-0.7.0:\n", " Successfully uninstalled torchdata-0.7.0\n", "Found existing installation: torchtext 0.16.0\n", "Uninstalling torchtext-0.16.0:\n", " Successfully uninstalled torchtext-0.16.0\n", "uninstalled: torchaudio torchdata torchtext\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\n" ] } ] }, { "cell_type": "code", "source": [ "# if possible run this step from the terminal\n", "\n", "%cd /content/lisa-on-cuda\n", "!cat requirements_colab.txt\n", "print(\"start installing pytest pytest-cov\")\n", "!pip install pytest pytest-cov\n", "!print(\"installed pytest pytest-cov, installing requirements_colab.txt...\")\n", "!pip install -r requirements_colab.txt\n", "print(\"ok\")" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "rg7Hx-D06PI7", "outputId": "44338e58-9691-4dde-a9f4-eaaf70f8e4a0" }, "execution_count": 15, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "/content/lisa-on-cuda\n", "bitsandbytes==0.43.0\n", "einops==0.7.0\n", "fastapi==0.110.0\n", "gradio==4.21.0\n", "gradio_client==0.12.0\n", "markdown2==2.4.13\n", "nh3==0.2.15\n", "openai==1.13.3\n", "peft==0.9.0\n", "ray==2.9.3\n", "shortuuid==1.0.12\n", "transformers==4.31.0\n", "uvicorn==0.28.0start installing pytest pytest-cov\n", "Requirement already satisfied: pytest in /usr/local/lib/python3.10/dist-packages (7.4.4)\n", "Collecting pytest-cov\n", " Using cached pytest_cov-4.1.0-py3-none-any.whl.metadata (26 kB)\n", "Requirement already satisfied: iniconfig in /usr/local/lib/python3.10/dist-packages (from pytest) (2.0.0)\n", "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from pytest) (23.2)\n", "Requirement already satisfied: pluggy<2.0,>=0.12 in /usr/local/lib/python3.10/dist-packages (from pytest) (1.4.0)\n", "Requirement already satisfied: exceptiongroup>=1.0.0rc8 in /usr/local/lib/python3.10/dist-packages (from pytest) (1.2.0)\n", "Requirement already satisfied: tomli>=1.0.0 in /usr/local/lib/python3.10/dist-packages (from pytest) (2.0.1)\n", "Collecting coverage>=5.2.1 (from coverage[toml]>=5.2.1->pytest-cov)\n", " Using cached coverage-7.4.3-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (8.2 kB)\n", "Using cached pytest_cov-4.1.0-py3-none-any.whl (21 kB)\n", "Using cached coverage-7.4.3-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (234 kB)\n", "Installing collected packages: coverage, pytest-cov\n", "Successfully installed coverage-7.4.3 pytest-cov-4.1.0\n", "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n", "\u001b[0m/bin/bash: -c: line 1: syntax error near unexpected token `\"installed pytest pytest-cov, installing requirements_colab.txt...\"'\n", "/bin/bash: -c: line 1: `print(\"installed pytest pytest-cov, installing requirements_colab.txt...\")'\n", "Collecting bitsandbytes==0.43.0 (from -r requirements_colab.txt (line 1))\n", " Using cached bitsandbytes-0.43.0-py3-none-manylinux_2_24_x86_64.whl.metadata (1.8 kB)\n", "Collecting einops==0.7.0 (from -r requirements_colab.txt (line 2))\n", " Using cached einops-0.7.0-py3-none-any.whl.metadata (13 kB)\n", "Collecting fastapi==0.110.0 (from -r requirements_colab.txt (line 3))\n", " Using cached fastapi-0.110.0-py3-none-any.whl.metadata (25 kB)\n", "Collecting gradio==4.21.0 (from -r requirements_colab.txt (line 4))\n", " Using cached gradio-4.21.0-py3-none-any.whl.metadata (15 kB)\n", "Collecting gradio_client==0.12.0 (from -r requirements_colab.txt (line 5))\n", " Using cached gradio_client-0.12.0-py3-none-any.whl.metadata (7.1 kB)\n", "Collecting markdown2==2.4.13 (from -r requirements_colab.txt (line 6))\n", " Using cached markdown2-2.4.13-py2.py3-none-any.whl.metadata (2.0 kB)\n", "Collecting nh3==0.2.15 (from -r requirements_colab.txt (line 7))\n", " Using cached nh3-0.2.15-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (1.7 kB)\n", "Collecting openai==1.13.3 (from -r requirements_colab.txt (line 8))\n", " Using cached openai-1.13.3-py3-none-any.whl.metadata (18 kB)\n", "Collecting peft==0.9.0 (from -r requirements_colab.txt (line 9))\n", " Using cached peft-0.9.0-py3-none-any.whl.metadata (13 kB)\n", "Collecting ray==2.9.3 (from -r requirements_colab.txt (line 10))\n", " Using cached ray-2.9.3-cp310-cp310-manylinux2014_x86_64.whl.metadata (13 kB)\n", "Collecting shortuuid==1.0.12 (from -r requirements_colab.txt (line 11))\n", " Using cached shortuuid-1.0.12-py3-none-any.whl.metadata 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ruff, python-multipart, orjson, markdown2, h11, einops, colorama, aiofiles, uvicorn, starlette, httpcore, transformers, httpx, fastapi, bitsandbytes, accelerate, ray, peft, openai, gradio_client, gradio\n", " Attempting uninstall: tokenizers\n", " Found existing installation: tokenizers 0.15.2\n", " Uninstalling tokenizers-0.15.2:\n", " Successfully uninstalled tokenizers-0.15.2\n", " Attempting uninstall: transformers\n", " Found existing installation: transformers 4.38.2\n", " Uninstalling transformers-4.38.2:\n", " Successfully uninstalled transformers-4.38.2\n", "Successfully installed accelerate-0.27.2 aiofiles-23.2.1 bitsandbytes-0.43.0 colorama-0.4.6 einops-0.7.0 fastapi-0.110.0 ffmpy-0.3.2 gradio-4.21.0 gradio_client-0.12.0 h11-0.14.0 httpcore-1.0.4 httpx-0.27.0 markdown2-2.4.13 nh3-0.2.15 openai-1.13.3 orjson-3.9.15 peft-0.9.0 pydub-0.25.1 python-multipart-0.0.9 ray-2.9.3 ruff-0.3.2 semantic-version-2.10.0 shellingham-1.5.4 shortuuid-1.0.12 starlette-0.36.3 tokenizers-0.13.3 tomlkit-0.12.0 transformers-4.31.0 uvicorn-0.28.0 websockets-11.0.3\n", "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n", "\u001b[0mok\n" ] } ] }, { "cell_type": "code", "source": [ "!pip list\n", "\n", "print(\"ok\")" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "LLQWY0bGO60Z", "outputId": "d73ba5ab-10f3-4356-c077-2b4ecf966f63" }, "execution_count": 16, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Package Version\n", "-------------------------------- ---------------------\n", "absl-py 1.4.0\n", "accelerate 0.27.2\n", "aiofiles 23.2.1\n", "aiohttp 3.9.3\n", "aiosignal 1.3.1\n", "alabaster 0.7.16\n", "albumentations 1.3.1\n", "altair 4.2.2\n", "annotated-types 0.6.0\n", "anyio 3.7.1\n", "appdirs 1.4.4\n", "argon2-cffi 23.1.0\n", "argon2-cffi-bindings 21.2.0\n", "array-record 0.5.0\n", "arviz 0.15.1\n", "astropy 5.3.4\n", "astunparse 1.6.3\n", "async-timeout 4.0.3\n", "atpublic 4.0\n", "attrs 23.2.0\n", "audioread 3.0.1\n", "autograd 1.6.2\n", "Babel 2.14.0\n", "backcall 0.2.0\n", "beautifulsoup4 4.12.3\n", "bidict 0.23.1\n", "bigframes 0.22.0\n", "bitsandbytes 0.43.0\n", "bleach 6.1.0\n", "blinker 1.4\n", "blis 0.7.11\n", "blosc2 2.0.0\n", "bokeh 3.3.4\n", "bqplot 0.12.43\n", "branca 0.7.1\n", "build 1.1.1\n", "CacheControl 0.14.0\n", "cachetools 5.3.3\n", "catalogue 2.0.10\n", "certifi 2024.2.2\n", "cffi 1.16.0\n", "chardet 5.2.0\n", "charset-normalizer 3.3.2\n", "chex 0.1.85\n", "click 8.1.7\n", "click-plugins 1.1.1\n", "cligj 0.7.2\n", "cloudpathlib 0.16.0\n", "cloudpickle 2.2.1\n", "cmake 3.27.9\n", "cmdstanpy 1.2.1\n", "colorama 0.4.6\n", "colorcet 3.1.0\n", "colorlover 0.3.0\n", "colour 0.1.5\n", "community 1.0.0b1\n", "confection 0.1.4\n", "cons 0.4.6\n", "contextlib2 21.6.0\n", "contourpy 1.2.0\n", "coverage 7.4.3\n", "cryptography 42.0.5\n", "cufflinks 0.17.3\n", "cupy-cuda12x 12.2.0\n", "cvxopt 1.3.2\n", "cvxpy 1.3.3\n", "cycler 0.12.1\n", "cymem 2.0.8\n", "Cython 3.0.9\n", "dask 2023.8.1\n", "datascience 0.17.6\n", "db-dtypes 1.2.0\n", "dbus-python 1.2.18\n", "debugpy 1.6.6\n", "decorator 4.4.2\n", "defusedxml 0.7.1\n", "distributed 2023.8.1\n", "distro 1.7.0\n", "dlib 19.24.2\n", "dm-tree 0.1.8\n", "docutils 0.18.1\n", "dopamine-rl 4.0.6\n", "duckdb 0.9.2\n", "earthengine-api 0.1.392\n", "easydict 1.13\n", "ecos 2.0.13\n", "editdistance 0.6.2\n", "eerepr 0.0.4\n", "einops 0.7.0\n", "en-core-web-sm 3.7.1\n", "entrypoints 0.4\n", "et-xmlfile 1.1.0\n", "etils 1.7.0\n", "etuples 0.3.9\n", "exceptiongroup 1.2.0\n", "fastai 2.7.14\n", "fastapi 0.110.0\n", "fastcore 1.5.29\n", "fastdownload 0.0.7\n", "fastjsonschema 2.19.1\n", "fastprogress 1.0.3\n", "fastrlock 0.8.2\n", "ffmpy 0.3.2\n", "filelock 3.13.1\n", "fiona 1.9.5\n", "firebase-admin 5.3.0\n", "Flask 2.2.5\n", "flatbuffers 23.5.26\n", "flax 0.8.1\n", "folium 0.14.0\n", "fonttools 4.49.0\n", "frozendict 2.4.0\n", "frozenlist 1.4.1\n", "fsspec 2023.6.0\n", "future 0.18.3\n", "gast 0.5.4\n", "gcsfs 2023.6.0\n", "GDAL 3.6.4\n", "gdown 4.7.3\n", "geemap 0.32.0\n", "gensim 4.3.2\n", "geocoder 1.38.1\n", "geographiclib 2.0\n", "geopandas 0.13.2\n", "geopy 2.3.0\n", "gin-config 0.5.0\n", "glob2 0.7\n", "google 2.0.3\n", "google-ai-generativelanguage 0.4.0\n", "google-api-core 2.11.1\n", "google-api-python-client 2.84.0\n", "google-auth 2.27.0\n", "google-auth-httplib2 0.1.1\n", "google-auth-oauthlib 1.2.0\n", "google-cloud-aiplatform 1.43.0\n", "google-cloud-bigquery 3.12.0\n", "google-cloud-bigquery-connection 1.12.1\n", "google-cloud-bigquery-storage 2.24.0\n", "google-cloud-core 2.3.3\n", "google-cloud-datastore 2.15.2\n", "google-cloud-firestore 2.11.1\n", "google-cloud-functions 1.13.3\n", "google-cloud-iam 2.14.3\n", "google-cloud-language 2.13.3\n", "google-cloud-resource-manager 1.12.3\n", "google-cloud-storage 2.8.0\n", "google-cloud-translate 3.11.3\n", "google-colab 1.0.0\n", "google-crc32c 1.5.0\n", "google-generativeai 0.3.2\n", "google-pasta 0.2.0\n", "google-resumable-media 2.7.0\n", "googleapis-common-protos 1.62.0\n", "googledrivedownloader 0.4\n", "gradio 4.21.0\n", "gradio_client 0.12.0\n", "graphviz 0.20.1\n", "greenlet 3.0.3\n", "grpc-google-iam-v1 0.13.0\n", "grpcio 1.62.0\n", "grpcio-status 1.48.2\n", "gspread 3.4.2\n", "gspread-dataframe 3.3.1\n", "gym 0.25.2\n", "gym-notices 0.0.8\n", "h11 0.14.0\n", "h5netcdf 1.3.0\n", "h5py 3.9.0\n", "holidays 0.44\n", "holoviews 1.17.1\n", "html5lib 1.1\n", "httpcore 1.0.4\n", "httpimport 1.3.1\n", "httplib2 0.22.0\n", "httpx 0.27.0\n", "huggingface-hub 0.20.3\n", "humanize 4.7.0\n", "hyperopt 0.2.7\n", "ibis-framework 7.1.0\n", "idna 3.6\n", "imageio 2.31.6\n", "imageio-ffmpeg 0.4.9\n", "imagesize 1.4.1\n", "imbalanced-learn 0.10.1\n", "imgaug 0.4.0\n", "importlib-metadata 7.0.1\n", "importlib_resources 6.1.2\n", "imutils 0.5.4\n", "inflect 7.0.0\n", "iniconfig 2.0.0\n", "intel-openmp 2023.2.3\n", "ipyevents 2.0.2\n", "ipyfilechooser 0.6.0\n", "ipykernel 5.5.6\n", "ipyleaflet 0.18.2\n", "ipython 7.34.0\n", "ipython-genutils 0.2.0\n", "ipython-sql 0.5.0\n", "ipytree 0.2.2\n", "ipywidgets 7.7.1\n", "itsdangerous 2.1.2\n", "jax 0.4.23\n", "jaxlib 0.4.23+cuda12.cudnn89\n", "jeepney 0.7.1\n", "jieba 0.42.1\n", "Jinja2 3.1.3\n", "joblib 1.3.2\n", "jsonpickle 3.0.3\n", "jsonschema 4.19.2\n", "jsonschema-specifications 2023.12.1\n", "jupyter-client 6.1.12\n", "jupyter-console 6.1.0\n", "jupyter_core 5.7.1\n", "jupyter-server 1.24.0\n", "jupyterlab_pygments 0.3.0\n", "jupyterlab_widgets 3.0.10\n", "kaggle 1.5.16\n", "kagglehub 0.2.0\n", "keras 2.15.0\n", "keyring 23.5.0\n", "kiwisolver 1.4.5\n", "langcodes 3.3.0\n", "launchpadlib 1.10.16\n", "lazr.restfulclient 0.14.4\n", "lazr.uri 1.0.6\n", "lazy_loader 0.3\n", "libclang 16.0.6\n", "librosa 0.10.1\n", "lightgbm 4.1.0\n", "linkify-it-py 2.0.3\n", "llvmlite 0.41.1\n", "locket 1.0.0\n", "logical-unification 0.4.6\n", "lxml 4.9.4\n", "malloy 2023.1067\n", "Markdown 3.5.2\n", "markdown-it-py 3.0.0\n", "markdown2 2.4.13\n", "MarkupSafe 2.1.5\n", "matplotlib 3.7.1\n", "matplotlib-inline 0.1.6\n", "matplotlib-venn 0.11.10\n", "mdit-py-plugins 0.4.0\n", "mdurl 0.1.2\n", "miniKanren 1.0.3\n", "missingno 0.5.2\n", "mistune 0.8.4\n", "mizani 0.9.3\n", "mkl 2023.2.0\n", "ml-dtypes 0.2.0\n", "mlxtend 0.22.0\n", "more-itertools 10.1.0\n", "moviepy 1.0.3\n", "mpmath 1.3.0\n", "msgpack 1.0.8\n", "multidict 6.0.5\n", "multipledispatch 1.0.0\n", "multitasking 0.0.11\n", "murmurhash 1.0.10\n", "music21 9.1.0\n", "natsort 8.4.0\n", "nbclassic 1.0.0\n", "nbclient 0.9.0\n", "nbconvert 6.5.4\n", "nbformat 5.9.2\n", "nest-asyncio 1.6.0\n", "networkx 3.2.1\n", "nh3 0.2.15\n", "nibabel 4.0.2\n", "nltk 3.8.1\n", "notebook 6.5.5\n", "notebook_shim 0.2.4\n", "numba 0.58.1\n", "numexpr 2.9.0\n", "numpy 1.25.2\n", "oauth2client 4.1.3\n", "oauthlib 3.2.2\n", "openai 1.13.3\n", "opencv-contrib-python 4.8.0.76\n", "opencv-python 4.8.0.76\n", "opencv-python-headless 4.9.0.80\n", "openpyxl 3.1.2\n", "opt-einsum 3.3.0\n", "optax 0.1.9\n", "orbax-checkpoint 0.4.4\n", "orjson 3.9.15\n", "osqp 0.6.2.post8\n", "packaging 23.2\n", "pandas 1.5.3\n", "pandas-datareader 0.10.0\n", "pandas-gbq 0.19.2\n", "pandas-stubs 1.5.3.230304\n", "pandocfilters 1.5.1\n", "panel 1.3.8\n", "param 2.0.2\n", "parso 0.8.3\n", "parsy 2.1\n", "partd 1.4.1\n", "pathlib 1.0.1\n", "patsy 0.5.6\n", "peewee 3.17.1\n", "peft 0.9.0\n", "pexpect 4.9.0\n", "pickleshare 0.7.5\n", "Pillow 9.4.0\n", "pins 0.8.4\n", "pip 24.0\n", "pip-tools 6.13.0\n", "platformdirs 4.2.0\n", "plotly 5.15.0\n", "plotnine 0.12.4\n", "pluggy 1.4.0\n", "polars 0.20.2\n", "pooch 1.8.1\n", "portpicker 1.5.2\n", "prefetch-generator 1.0.3\n", "preshed 3.0.9\n", "prettytable 3.10.0\n", "proglog 0.1.10\n", "progressbar2 4.2.0\n", "prometheus_client 0.20.0\n", "promise 2.3\n", "prompt-toolkit 3.0.43\n", "prophet 1.1.5\n", "proto-plus 1.23.0\n", "protobuf 3.20.3\n", "psutil 5.9.5\n", "psycopg2 2.9.9\n", "ptyprocess 0.7.0\n", "py-cpuinfo 9.0.0\n", "py4j 0.10.9.7\n", "pyarrow 14.0.2\n", "pyarrow-hotfix 0.6\n", "pyasn1 0.5.1\n", "pyasn1-modules 0.3.0\n", "pycocotools 2.0.7\n", "pycparser 2.21\n", "pydantic 2.6.3\n", "pydantic_core 2.16.3\n", "pydata-google-auth 1.8.2\n", "pydot 1.4.2\n", "pydot-ng 2.0.0\n", "pydotplus 2.0.2\n", "PyDrive 1.3.1\n", "PyDrive2 1.6.3\n", "pydub 0.25.1\n", "pyerfa 2.0.1.1\n", "pygame 2.5.2\n", "Pygments 2.16.1\n", "PyGObject 3.42.1\n", "PyJWT 2.3.0\n", "pymc 5.10.4\n", "pymystem3 0.2.0\n", "PyOpenGL 3.1.7\n", "pyOpenSSL 24.0.0\n", "pyparsing 3.1.1\n", "pyperclip 1.8.2\n", "pyproj 3.6.1\n", "pyproject_hooks 1.0.0\n", "pyshp 2.3.1\n", "PySocks 1.7.1\n", "pytensor 2.18.6\n", "pytest 7.4.4\n", "pytest-cov 4.1.0\n", "python-apt 0.0.0\n", "python-box 7.1.1\n", "python-dateutil 2.8.2\n", "python-louvain 0.16\n", "python-multipart 0.0.9\n", "python-slugify 8.0.4\n", "python-utils 3.8.2\n", "pytz 2023.4\n", "pyviz_comms 3.0.1\n", "PyWavelets 1.5.0\n", "PyYAML 6.0.1\n", "pyzmq 23.2.1\n", "qdldl 0.1.7.post0\n", "qudida 0.0.4\n", "ratelim 0.1.6\n", "ray 2.9.3\n", "referencing 0.33.0\n", "regex 2023.12.25\n", "requests 2.31.0\n", "requests-oauthlib 1.3.1\n", "requirements-parser 0.5.0\n", "rich 13.7.1\n", "rpds-py 0.18.0\n", "rpy2 3.4.2\n", "rsa 4.9\n", "ruff 0.3.2\n", "safetensors 0.4.2\n", "scikit-image 0.19.3\n", "scikit-learn 1.2.2\n", "scipy 1.11.4\n", "scooby 0.9.2\n", "scs 3.2.4.post1\n", "seaborn 0.13.1\n", "SecretStorage 3.3.1\n", "semantic-version 2.10.0\n", "Send2Trash 1.8.2\n", "sentencepiece 0.1.99\n", "setuptools 67.7.2\n", "shapely 2.0.3\n", "shellingham 1.5.4\n", "shortuuid 1.0.12\n", "six 1.16.0\n", "sklearn-pandas 2.2.0\n", "smart-open 6.4.0\n", "sniffio 1.3.1\n", "snowballstemmer 2.2.0\n", "sortedcontainers 2.4.0\n", "soundfile 0.12.1\n", "soupsieve 2.5\n", "soxr 0.3.7\n", "spacy 3.7.4\n", "spacy-legacy 3.0.12\n", "spacy-loggers 1.0.5\n", "Sphinx 5.0.2\n", "sphinxcontrib-applehelp 1.0.8\n", "sphinxcontrib-devhelp 1.0.6\n", "sphinxcontrib-htmlhelp 2.0.5\n", "sphinxcontrib-jsmath 1.0.1\n", "sphinxcontrib-qthelp 1.0.7\n", "sphinxcontrib-serializinghtml 1.1.10\n", "SQLAlchemy 2.0.28\n", "sqlglot 19.9.0\n", "sqlparse 0.4.4\n", "srsly 2.4.8\n", "stanio 0.3.0\n", "starlette 0.36.3\n", "statsmodels 0.14.1\n", "sympy 1.12\n", "tables 3.8.0\n", "tabulate 0.9.0\n", "tbb 2021.11.0\n", "tblib 3.0.0\n", "tenacity 8.2.3\n", "tensorboard 2.15.2\n", "tensorboard-data-server 0.7.2\n", "tensorflow 2.15.0\n", "tensorflow-datasets 4.9.4\n", "tensorflow-estimator 2.15.0\n", "tensorflow-gcs-config 2.15.0\n", "tensorflow-hub 0.16.1\n", "tensorflow-io-gcs-filesystem 0.36.0\n", "tensorflow-metadata 1.14.0\n", "tensorflow-probability 0.23.0\n", "tensorstore 0.1.45\n", "termcolor 2.4.0\n", "terminado 0.18.0\n", "text-unidecode 1.3\n", "textblob 0.17.1\n", "tf-keras 2.15.0\n", "tf-slim 1.1.0\n", "thinc 8.2.3\n", "threadpoolctl 3.3.0\n", "tifffile 2024.2.12\n", "tinycss2 1.2.1\n", "tokenizers 0.13.3\n", "toml 0.10.2\n", "tomli 2.0.1\n", "tomlkit 0.12.0\n", "toolz 0.12.1\n", "torch 2.1.0+cu121\n", "torchsummary 1.5.1\n", "torchvision 0.16.0+cu121\n", "tornado 6.3.3\n", "tqdm 4.66.2\n", "traitlets 5.7.1\n", "traittypes 0.2.1\n", "transformers 4.31.0\n", "triton 2.1.0\n", "tweepy 4.14.0\n", "typer 0.9.0\n", "types-pytz 2024.1.0.20240203\n", "types-setuptools 69.1.0.20240302\n", "typing_extensions 4.10.0\n", "tzlocal 5.2\n", "uc-micro-py 1.0.3\n", "uritemplate 4.1.1\n", "urllib3 2.0.7\n", "uvicorn 0.28.0\n", "vega-datasets 0.9.0\n", "wadllib 1.3.6\n", "wasabi 1.1.2\n", "wcwidth 0.2.13\n", "weasel 0.3.4\n", "webcolors 1.13\n", "webencodings 0.5.1\n", "websocket-client 1.7.0\n", "websockets 11.0.3\n", "Werkzeug 3.0.1\n", "wheel 0.42.0\n", "widgetsnbextension 3.6.6\n", "wordcloud 1.9.3\n", "wrapt 1.14.1\n", "xarray 2023.7.0\n", "xarray-einstats 0.7.0\n", "xgboost 2.0.3\n", "xlrd 2.0.1\n", "xxhash 3.4.1\n", "xyzservices 2023.10.1\n", "yarl 1.9.4\n", "yellowbrick 1.5\n", "yfinance 0.2.37\n", "zict 3.0.0\n", "zipp 3.17.0\n", "ok\n" ] } ] }, { "cell_type": "code", "source": [ "%cd /content/lisa-on-cuda/\n", "\n", "try:\n", " from lisa_on_cuda.utils import app_helpers, constants, utils\n", "except KeyError as ke:\n", " print(ke)\n", " raise ke\n", "\n", "print(\"ok\")" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "5ZTfd2uu-ii0", "outputId": "7fe562f2-2b9c-40e1-f7b7-8b3c53666d1e" }, "execution_count": 17, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "/content/lisa-on-cuda\n", "ok\n" ] } ] }, { "cell_type": "code", "source": [ "import logging\n", "from lisa_on_cuda.utils import utils\n", "import matplotlib.pyplot as plt\n", "\n", "logging.basicConfig(level=logging.INFO, force = True)\n", "\n", "_vars = utils.create_placeholder_variables()\n", "print(\"_vars:\", _vars[\"no_seg_out\"].shape)\n", "print(\"_vars:\", _vars.keys())\n", "print(\"ok\")" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "a8YNIvLRQePo", "outputId": "7252dd85-f07d-48f8-e627-b635c2120fc1" }, "execution_count": 18, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "INFO:root:placeholders_folder:/content/lisa-on-cuda/resources/placeholders.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "_vars: (512, 512, 3)\n", "_vars: dict_keys(['no_seg_out', 'error_happened'])\n", "ok\n" ] } ] }, { "cell_type": "code", "source": [ "from torch.cuda import empty_cache\n", "\n", "logging.info(\"cleaning torch cache...\")\n", "empty_cache()\n", "logging.info(\"torch cache emptied!\")" ], "metadata": { "id": "bjVsT54SVjRt", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "8bb6ccbc-fddf-49d3-d6d9-f15c001bf55c" }, "execution_count": 19, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "INFO:root:cleaning torch cache...\n", "INFO:root:torch cache emptied!\n" ] } ] }, { "cell_type": "code", "source": [ "from datetime import datetime\n", "\n", "print(f\"start the creation of the inference function, now is {datetime.now()}.\")\n", "test_args_parse = app_helpers.parse_args([])\n", "inference_fn = app_helpers.get_inference_model_by_args(test_args_parse)\n", "print(\"created inference_fn!\")" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 319, "referenced_widgets": [ "e968b46a1ecb485fa9f164f6ec0f5569", "759af27e6e3e439f9a8739c470d9b4ed", "5d5bd7bb543c44c48acb5a38d0e2b392", "77f3526c940841ec8c3d3bb1da85dbc8", "5eca36e7aa8a4775911eeb4c8684af6d", "944fa9555ead4941aa855bbd35a4f5d7", "2ad8fb9acc93495ca60d355ea4b0c161", "a03fbfb4742342758d99d4354a9191e5", "e7f6ff163e4846388f621f41ad287bfb", "de68261aa80941afb2759b764aa10226", "8d9f42c52f604fb590e77a3f5441ec09" ] }, "id": "aJHut43ETK3P", "outputId": "63e17ff8-44e0-4158-8e4b-6bcab33ccc78" }, "execution_count": 20, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "INFO:root:args_to_parse:Namespace(version='xinlai/LISA-13B-llama2-v1-explanatory', vis_save_path='./vis_output', precision='fp16', image_size=1024, model_max_length=512, lora_r=8, vision_tower='openai/clip-vit-large-patch14', local_rank=0, load_in_8bit=False, load_in_4bit=True, use_mm_start_end=True, conv_type='llava_v1'), creating model...\n", "INFO:root:starting model preparation...\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "start the creation of the inference function, now is 2024-03-10 18:22:28.101518.\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:88: UserWarning: \n", "The secret `HF_TOKEN` does not exist in your Colab secrets.\n", "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n", "You will be able to reuse this secret in all of your notebooks.\n", "Please note that authentication is recommended but still optional to access public models or datasets.\n", " warnings.warn(\n", "You are using the legacy behaviour of the . This means that tokens that come after special tokens will not be properly handled. We recommend you to read the related pull request available at https://github.com/huggingface/transformers/pull/24565\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "Loading checkpoint shards: 0%| | 0/3 [00:00, input_image type: .\n", "INFO:root:input_str: Where can the driver see the car speed in this image? Please output segmentation mask., input_image: .\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "start inference using inference_fn, now is 2024-03-10 18:34:33.689389.\n", "input_prompt:Where can the driver see the car speed in this image? Please output segmentation mask..\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "INFO:root:image_clip type: .\n", "INFO:root:preprocess started\n", "INFO:root:preprocess ended\n", "INFO:root:image_clip type: .\n", "/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py:1270: UserWarning: You have modified the pretrained model configuration to control generation. This is a deprecated strategy to control generation and will be removed soon, in a future version. Please use a generation configuration file (see https://huggingface.co/docs/transformers/main_classes/text_generation )\n", " warnings.warn(\n", "INFO:root:found n 1 prediction masks, text_output type: , text_output: Sure, [SEG] ..\n", "INFO:root:output_image type: .\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "output_str: ASSISTANT: Sure, [SEG] . ....\n", "shape mask: (1536, 2048), type: , dtype: uint8 #\n", "shape img: (1536, 2048, 3) #\n", "ok\n" ] } ] }, { "cell_type": "code", "source": [ "\n", "interp = 'bilinear'\n", "fig, axs = plt.subplots(nrows=1, ncols=2, figsize=(10, 10), sharey=True)\n", "axs[0].set_title('output_image')\n", "axs[0].imshow(output_image, interpolation=interp)\n", "\n", "axs[1].set_title('output_mask')\n", "axs[1].imshow(output_mask, interpolation=interp)\n", "print(\"ok\")" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 365 }, "id": "euOi0BKETQXG", "outputId": "40c339d4-28b2-4e39-ab15-f2f8198d76fe" }, "execution_count": 22, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "ok\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": 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\n" }, "metadata": {} } ] }, { "cell_type": "code", "source": [ "import cv2\n", "from PIL import Image\n", "from lisa_on_cuda.utils import utils\n", "\n", "\"\"\"\n", "# current_example_path = str(utils.ROOT / \"tests\" / \"imgs\" / f\"example{idx_example+1}_mask_0.png\")\n", "current_example_path = str(utils.ROOT / \"tests\" / \"imgs\" / f\"example1c_mask_0.png\")\n", "\n", "im = Image.fromarray(output_mask)\n", "im.save(current_example_path)\n", "\"\"\"\n", "\n", "expected_images_path = utils.ROOT / \"tests\" / \"imgs\"\n", "example1_path = str(expected_images_path / f\"example{idx_example+1}_mask_0.png\")\n", "logging.info(f\"example1_path:{example1_path}.\")\n", "mod_path = str(expected_images_path / \"example1_mask_0_broken.png\")\n", "logging.info(f\"mod_path:{mod_path}.\")\n", "expected_mask = cv2.imread(example1_path, cv2.IMREAD_GRAYSCALE)\n", "print(f\"img check type:{type(expected_mask)}, {expected_mask.shape}. {expected_mask.dtype}.\")\n", "plt.imshow(expected_mask)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 506 }, "id": "0PEXxxgwVRRn", "outputId": "f3d69a09-159d-434f-f6d1-326cc862ea75" }, "execution_count": 23, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "INFO:root:example1_path:/content/lisa-on-cuda/tests/imgs/example1_mask_0.png.\n", "INFO:root:mod_path:/content/lisa-on-cuda/tests/imgs/example1_mask_0_broken.png.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "img check type:, (1536, 2048). uint8.\n" ] }, { "output_type": "execute_result", "data": { "text/plain": [ "" ] }, "metadata": {}, "execution_count": 23 }, { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": 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\n" }, "metadata": {} } ] }, { "cell_type": "code", "source": [ "import numpy as np\n", "\n", "max_diff = 0.02\n", "tot = output_mask.size\n", "count = np.sum(output_mask != expected_mask)\n", "perc = 100 * count / tot\n", "\n", "logging.info(f\"perc of different pixels between output_mask and expected_mask: {perc:.2f}!\")\n", "try:\n", " assert np.array_equal(output_mask, expected_mask)\n", "except AssertionError:\n", " try:\n", " logging.error(\"failed equality assertion!\")\n", " logging.info(f\"assert now that perc diff between ndarrays is minor than {max_diff}.\")\n", " assert perc < max_diff\n", " except AssertionError as ae:\n", " logging.error(\"failed all assertions, writing debug files...\")\n", " import datetime\n", " now_str = datetime.datetime.now().strftime(\"%Y%m%d%H%M%S\")\n", " output_folder = utils.ROOT / \"tests\" / \"imgs\"\n", " prefix = f\"broken_test_example{idx_example + 1}_{now_str}\"\n", " cv2.imwrite(\n", " str(output_folder / f\"{prefix}.png\"),\n", " output_mask\n", " )\n", " with open(output_folder / f\"{prefix}__input_prompt.txt\",\n", " \"w\") as dst:\n", " dst.write(input_prompt)\n", " with open(output_folder / f\"{prefix}__output_str.txt\",\n", " \"w\") as dst:\n", " dst.write(output_str)\n", " logging.info(f\"Written files with prefix '{prefix}' in {output_folder} folder.\")\n", " raise ae\n", "logging.info(\"end\")\n", "print(\"end\")\n" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "sZy30KDUVVJ_", "outputId": "4efff579-535a-40af-dcec-bb475f1600d2" }, "execution_count": 24, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "INFO:root:perc of different pixels between output_mask and expected_mask: 0.00!\n", "INFO:root:end\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "end\n" ] } ] }, { "cell_type": "code", "source": [ "%%bash\n", "\n", "ls -l /root/.cache/huggingface/hub/models--xinlai--LISA*/*/*\n", "\n", "echo \"end!\"" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "d7HoGCK_6ePE", "outputId": "4a188f51-b1c1-4995-fc68-76cf06c65643" }, "execution_count": 25, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "-rw------- 1 root root 132 Mar 8 21:11 /root/.cache/huggingface/hub/models--xinlai--LISA-13B-llama2-v1-explanatory/blobs/2b103309349551440a34d2718b641a167aefed46\n", "-rw------- 1 root root 1223 Mar 8 21:02 /root/.cache/huggingface/hub/models--xinlai--LISA-13B-llama2-v1-explanatory/blobs/4bd3c5012fec5ab010949190f40f407164f5c0f2\n", "-rw------- 1 root root 9904165024 Mar 8 21:05 /root/.cache/huggingface/hub/models--xinlai--LISA-13B-llama2-v1-explanatory/blobs/4f07ec63b01e37f6d703037064186d5aae7c3af01f5c17b030f9cfa60c2c2071\n", "-rw------- 1 root root 8864213656 Mar 8 21:08 /root/.cache/huggingface/hub/models--xinlai--LISA-13B-llama2-v1-explanatory/blobs/50ac03c112dcc0b405889dd4bedda93ff65ecaa16fe880a018ea419c6f31a5bd\n", "-rw------- 1 root root 744 Mar 8 21:02 /root/.cache/huggingface/hub/models--xinlai--LISA-13B-llama2-v1-explanatory/blobs/5410e42d470550c1292a32f630a49b0285ff6432\n", "-rw------- 1 root root 95614 Mar 8 21:02 /root/.cache/huggingface/hub/models--xinlai--LISA-13B-llama2-v1-explanatory/blobs/6ee1bb2e7ee95d6cf370a0501c3be7554d58c883\n", "-rw------- 1 root root 65 Mar 8 21:02 /root/.cache/huggingface/hub/models--xinlai--LISA-13B-llama2-v1-explanatory/blobs/9cbe171002fb4cc8fcb0f6aaa6bd86d8664f74f6\n", "-rw------- 1 root root 499723 Mar 8 21:02 /root/.cache/huggingface/hub/models--xinlai--LISA-13B-llama2-v1-explanatory/blobs/9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347\n", "-rw------- 1 root root 9948759150 Mar 8 21:04 /root/.cache/huggingface/hub/models--xinlai--LISA-13B-llama2-v1-explanatory/blobs/ac55a74eeeff7c594faefc59ec28cf2351eb2caf4e2ef747a72e566802bf0f79\n", "-rw------- 1 root root 435 Mar 8 21:02 /root/.cache/huggingface/hub/models--xinlai--LISA-13B-llama2-v1-explanatory/blobs/f928b2409a393d47ce0d9fe519f17e048a471eca\n", "-rw------- 1 root root 40 Mar 8 21:02 /root/.cache/huggingface/hub/models--xinlai--LISA-13B-llama2-v1-explanatory/refs/main\n", "\n", "/root/.cache/huggingface/hub/models--xinlai--LISA-13B-llama2-v1-explanatory/snapshots/3b7570861d792f9ca13c7c8db92aede0022b9fe0:\n", "total 5\n", "lrw------- 1 root root 52 Mar 8 21:02 added_tokens.json -> ../../blobs/9cbe171002fb4cc8fcb0f6aaa6bd86d8664f74f6\n", "lrw------- 1 root root 52 Mar 8 21:02 config.json -> ../../blobs/4bd3c5012fec5ab010949190f40f407164f5c0f2\n", "lrw------- 1 root root 52 Mar 8 21:11 generation_config.json -> ../../blobs/2b103309349551440a34d2718b641a167aefed46\n", "lrw------- 1 root root 76 Mar 8 21:04 pytorch_model-00001-of-00003.bin -> ../../blobs/ac55a74eeeff7c594faefc59ec28cf2351eb2caf4e2ef747a72e566802bf0f79\n", "lrw------- 1 root root 76 Mar 8 21:05 pytorch_model-00002-of-00003.bin -> ../../blobs/4f07ec63b01e37f6d703037064186d5aae7c3af01f5c17b030f9cfa60c2c2071\n", "lrw------- 1 root root 76 Mar 8 21:08 pytorch_model-00003-of-00003.bin -> ../../blobs/50ac03c112dcc0b405889dd4bedda93ff65ecaa16fe880a018ea419c6f31a5bd\n", "lrw------- 1 root root 52 Mar 8 21:02 pytorch_model.bin.index.json -> ../../blobs/6ee1bb2e7ee95d6cf370a0501c3be7554d58c883\n", "lrw------- 1 root root 52 Mar 8 21:02 special_tokens_map.json -> ../../blobs/f928b2409a393d47ce0d9fe519f17e048a471eca\n", "lrw------- 1 root root 52 Mar 8 21:02 tokenizer_config.json -> ../../blobs/5410e42d470550c1292a32f630a49b0285ff6432\n", "lrw------- 1 root root 76 Mar 8 21:02 tokenizer.model -> ../../blobs/9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347\n", "end\n" ] } ] }, { "cell_type": "code", "source": [ "from os import listxattr\n", "from datetime import datetime\n", "\n", "print(f\"start notebook: now is {datetime.now()}.\")" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "W7fsszLV7YCK", "outputId": "0e78182a-fea7-48fa-eba1-544ac3150342" }, "execution_count": 26, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "start notebook: now is 2024-03-10 18:34:45.188229.\n" ] } ] }, { "cell_type": "code", "source": [ "#!pip freeze > /tmp/lista.txt\n", "#!for x in $(cat /content/lisa-on-cuda/requirements_colab.txt); do grep $x /tmp/lista.txt; done > /tmp/lista.1.txt\n", "#!%cat /tmp/lista.1.txt" ], "metadata": { "id": "1h1eIdUibJXo" }, "execution_count": 27, "outputs": [] } ] }