Part 1: create the conda env for the project (base) ren2@Ren2:~/data2/mengya/mengya_code/main_ImageCaptioning.pytorch$ conda create -n Captioning_Zoo python=3.8 Collecting package metadata (current_repodata.json): done Solving environment: done ==> WARNING: A newer version of conda exists. <== current version: 4.10.1 latest version: 4.11.0 Please update conda by running $ conda update -n base -c defaults conda ## Package Plan ## environment location: /home/ren2/anaconda3/envs/Captioning_Zoo added / updated specs: - python=3.8 The following NEW packages will be INSTALLED: _libgcc_mutex pkgs/main/linux-64::_libgcc_mutex-0.1-main _openmp_mutex pkgs/main/linux-64::_openmp_mutex-4.5-1_gnu ca-certificates pkgs/main/linux-64::ca-certificates-2021.10.26-h06a4308_2 certifi pkgs/main/linux-64::certifi-2021.10.8-py38h06a4308_0 ld_impl_linux-64 pkgs/main/linux-64::ld_impl_linux-64-2.35.1-h7274673_9 libffi pkgs/main/linux-64::libffi-3.3-he6710b0_2 libgcc-ng pkgs/main/linux-64::libgcc-ng-9.3.0-h5101ec6_17 libgomp pkgs/main/linux-64::libgomp-9.3.0-h5101ec6_17 libstdcxx-ng pkgs/main/linux-64::libstdcxx-ng-9.3.0-hd4cf53a_17 ncurses pkgs/main/linux-64::ncurses-6.3-h7f8727e_2 openssl pkgs/main/linux-64::openssl-1.1.1l-h7f8727e_0 pip pkgs/main/linux-64::pip-21.2.4-py38h06a4308_0 python pkgs/main/linux-64::python-3.8.12-h12debd9_0 readline pkgs/main/linux-64::readline-8.1-h27cfd23_0 setuptools pkgs/main/linux-64::setuptools-58.0.4-py38h06a4308_0 sqlite pkgs/main/linux-64::sqlite-3.36.0-hc218d9a_0 tk pkgs/main/linux-64::tk-8.6.11-h1ccaba5_0 wheel pkgs/main/noarch::wheel-0.37.0-pyhd3eb1b0_1 xz pkgs/main/linux-64::xz-5.2.5-h7b6447c_0 zlib pkgs/main/linux-64::zlib-1.2.11-h7b6447c_3 Proceed ([y]/n)? Preparing transaction: done Verifying transaction: done Executing transaction: done # # To activate this environment, use # # $ conda activate Captioning_Zoo # # To deactivate an active environment, use # # $ conda deactivate (base) ren2@Ren2:~/data2/mengya/mengya_code/main_ImageCaptioning.pytorch$ conda activate Captioning_Zoo (Captioning_Zoo) ren2@Ren2:~/data2/mengya/mengya_code/main_ImageCaptioning.pytorch$ conda list # packages in environment at /home/ren2/anaconda3/envs/Captioning_Zoo: # # Name Version Build Channel _libgcc_mutex 0.1 main _openmp_mutex 4.5 1_gnu ca-certificates 2021.10.26 h06a4308_2 certifi 2021.10.8 py38h06a4308_0 ld_impl_linux-64 2.35.1 h7274673_9 libffi 3.3 he6710b0_2 libgcc-ng 9.3.0 h5101ec6_17 libgomp 9.3.0 h5101ec6_17 libstdcxx-ng 9.3.0 hd4cf53a_17 ncurses 6.3 h7f8727e_2 openssl 1.1.1l h7f8727e_0 pip 21.2.4 py38h06a4308_0 python 3.8.12 h12debd9_0 readline 8.1 h27cfd23_0 setuptools 58.0.4 py38h06a4308_0 sqlite 3.36.0 hc218d9a_0 tk 8.6.11 h1ccaba5_0 wheel 0.37.0 pyhd3eb1b0_1 xz 5.2.5 h7b6447c_0 zlib 1.2.11 h7b6447c_3 (Captioning_Zoo) ren2@Ren2:~/data2/mengya/mengya_code/main_ImageCaptioning.pytorch$ conda install pytorch torchvision torchaudio cudatoolkit=11.3 -c pytorch Collecting package metadata (current_repodata.json): done Solving environment: done ==> WARNING: A newer version of conda exists. <== current version: 4.10.1 latest version: 4.11.0 Please update conda by running $ conda update -n base -c defaults conda ## Package Plan ## environment location: /home/ren2/anaconda3/envs/Captioning_Zoo added / updated specs: - cudatoolkit=11.3 - pytorch - torchaudio - torchvision The following packages will be downloaded: package | build ---------------------------|----------------- torchaudio-0.10.0 | py38_cu113 4.5 MB pytorch ------------------------------------------------------------ Total: 4.5 MB The following NEW packages will be INSTALLED: blas pkgs/main/linux-64::blas-1.0-mkl bzip2 pkgs/main/linux-64::bzip2-1.0.8-h7b6447c_0 cudatoolkit pkgs/main/linux-64::cudatoolkit-11.3.1-h2bc3f7f_2 ffmpeg pytorch/linux-64::ffmpeg-4.3-hf484d3e_0 freetype pkgs/main/linux-64::freetype-2.11.0-h70c0345_0 giflib pkgs/main/linux-64::giflib-5.2.1-h7b6447c_0 gmp pkgs/main/linux-64::gmp-6.2.1-h2531618_2 gnutls pkgs/main/linux-64::gnutls-3.6.15-he1e5248_0 intel-openmp pkgs/main/linux-64::intel-openmp-2021.4.0-h06a4308_3561 jpeg pkgs/main/linux-64::jpeg-9d-h7f8727e_0 lame pkgs/main/linux-64::lame-3.100-h7b6447c_0 lcms2 pkgs/main/linux-64::lcms2-2.12-h3be6417_0 libiconv pkgs/main/linux-64::libiconv-1.15-h63c8f33_5 libidn2 pkgs/main/linux-64::libidn2-2.3.2-h7f8727e_0 libpng pkgs/main/linux-64::libpng-1.6.37-hbc83047_0 libtasn1 pkgs/main/linux-64::libtasn1-4.16.0-h27cfd23_0 libtiff pkgs/main/linux-64::libtiff-4.2.0-h85742a9_0 libunistring pkgs/main/linux-64::libunistring-0.9.10-h27cfd23_0 libuv pkgs/main/linux-64::libuv-1.40.0-h7b6447c_0 libwebp pkgs/main/linux-64::libwebp-1.2.0-h89dd481_0 libwebp-base pkgs/main/linux-64::libwebp-base-1.2.0-h27cfd23_0 lz4-c pkgs/main/linux-64::lz4-c-1.9.3-h295c915_1 mkl pkgs/main/linux-64::mkl-2021.4.0-h06a4308_640 mkl-service pkgs/main/linux-64::mkl-service-2.4.0-py38h7f8727e_0 mkl_fft pkgs/main/linux-64::mkl_fft-1.3.1-py38hd3c417c_0 mkl_random pkgs/main/linux-64::mkl_random-1.2.2-py38h51133e4_0 nettle pkgs/main/linux-64::nettle-3.7.3-hbbd107a_1 numpy pkgs/main/linux-64::numpy-1.21.2-py38h20f2e39_0 numpy-base pkgs/main/linux-64::numpy-base-1.21.2-py38h79a1101_0 olefile pkgs/main/noarch::olefile-0.46-pyhd3eb1b0_0 openh264 pkgs/main/linux-64::openh264-2.1.0-hd408876_0 pillow pkgs/main/linux-64::pillow-8.4.0-py38h5aabda8_0 pytorch pytorch/linux-64::pytorch-1.10.0-py3.8_cuda11.3_cudnn8.2.0_0 pytorch-mutex pytorch/noarch::pytorch-mutex-1.0-cuda six pkgs/main/noarch::six-1.16.0-pyhd3eb1b0_0 torchaudio pytorch/linux-64::torchaudio-0.10.0-py38_cu113 torchvision pytorch/linux-64::torchvision-0.11.1-py38_cu113 typing_extensions pkgs/main/noarch::typing_extensions-3.10.0.2-pyh06a4308_0 zstd pkgs/main/linux-64::zstd-1.4.9-haebb681_0 Proceed ([y]/n)? Downloading and Extracting Packages torchaudio-0.10.0 | 4.5 MB | ################################################################################################################################### | 100% Preparing transaction: done Verifying transaction: done Executing transaction: - By downloading and using the CUDA Toolkit conda packages, you accept the terms and conditions of the CUDA End User License Agreement (EULA): https://docs.nvidia.com/cuda/eula/index.html done (Captioning_Zoo) ren2@Ren2:~/data2/mengya/mengya_code/main_ImageCaptioning.pytorch$ conda list # packages in environment at /home/ren2/anaconda3/envs/Captioning_Zoo: # # Name Version Build Channel _libgcc_mutex 0.1 main _openmp_mutex 4.5 1_gnu blas 1.0 mkl bzip2 1.0.8 h7b6447c_0 ca-certificates 2021.10.26 h06a4308_2 certifi 2021.10.8 py38h06a4308_0 cudatoolkit 11.3.1 h2bc3f7f_2 ffmpeg 4.3 hf484d3e_0 pytorch freetype 2.11.0 h70c0345_0 giflib 5.2.1 h7b6447c_0 gmp 6.2.1 h2531618_2 gnutls 3.6.15 he1e5248_0 intel-openmp 2021.4.0 h06a4308_3561 jpeg 9d h7f8727e_0 lame 3.100 h7b6447c_0 lcms2 2.12 h3be6417_0 ld_impl_linux-64 2.35.1 h7274673_9 libffi 3.3 he6710b0_2 libgcc-ng 9.3.0 h5101ec6_17 libgomp 9.3.0 h5101ec6_17 libiconv 1.15 h63c8f33_5 libidn2 2.3.2 h7f8727e_0 libpng 1.6.37 hbc83047_0 libstdcxx-ng 9.3.0 hd4cf53a_17 libtasn1 4.16.0 h27cfd23_0 libtiff 4.2.0 h85742a9_0 libunistring 0.9.10 h27cfd23_0 libuv 1.40.0 h7b6447c_0 libwebp 1.2.0 h89dd481_0 libwebp-base 1.2.0 h27cfd23_0 lz4-c 1.9.3 h295c915_1 mkl 2021.4.0 h06a4308_640 mkl-service 2.4.0 py38h7f8727e_0 mkl_fft 1.3.1 py38hd3c417c_0 mkl_random 1.2.2 py38h51133e4_0 ncurses 6.3 h7f8727e_2 nettle 3.7.3 hbbd107a_1 numpy 1.21.2 py38h20f2e39_0 numpy-base 1.21.2 py38h79a1101_0 olefile 0.46 pyhd3eb1b0_0 openh264 2.1.0 hd408876_0 openssl 1.1.1l h7f8727e_0 pillow 8.4.0 py38h5aabda8_0 pip 21.2.4 py38h06a4308_0 python 3.8.12 h12debd9_0 pytorch 1.10.0 py3.8_cuda11.3_cudnn8.2.0_0 pytorch pytorch-mutex 1.0 cuda pytorch readline 8.1 h27cfd23_0 setuptools 58.0.4 py38h06a4308_0 six 1.16.0 pyhd3eb1b0_0 sqlite 3.36.0 hc218d9a_0 tk 8.6.11 h1ccaba5_0 torchaudio 0.10.0 py38_cu113 pytorch torchvision 0.11.1 py38_cu113 pytorch typing_extensions 3.10.0.2 pyh06a4308_0 wheel 0.37.0 pyhd3eb1b0_1 xz 5.2.5 h7b6447c_0 zlib 1.2.11 h7b6447c_3 zstd 1.4.9 haebb681_0 (Captioning_Zoo) ren2@Ren2:~/data2/mengya/mengya_code/main_ImageCaptioning.pytorch$ python tools/train.py --cfg configs/fc.yml --id fc Traceback (most recent call last): File "tools/train.py", line 8, in <module> from torch.utils.tensorboard import SummaryWriter File "/home/ren2/anaconda3/envs/Captioning_Zoo/lib/python3.8/site-packages/torch/utils/tensorboard/__init__.py", line 1, in <module> import tensorboard ModuleNotFoundError: No module named 'tensorboard' (Captioning_Zoo) ren2@Ren2:~/data2/mengya/mengya_code/main_ImageCaptioning.pytorch$ pip install tensorboard Collecting tensorboard Using cached tensorboard-2.7.0-py3-none-any.whl (5.8 MB) Collecting markdown>=2.6.8 Using cached Markdown-3.3.6-py3-none-any.whl (97 kB) Collecting werkzeug>=0.11.15 Using cached Werkzeug-2.0.2-py3-none-any.whl (288 kB) Collecting absl-py>=0.4 Using cached absl_py-1.0.0-py3-none-any.whl (126 kB) Requirement already satisfied: setuptools>=41.0.0 in /home/ren2/anaconda3/envs/Captioning_Zoo/lib/python3.8/site-packages (from tensorboard) (58.0.4) Collecting tensorboard-data-server<0.7.0,>=0.6.0 Using cached tensorboard_data_server-0.6.1-py3-none-manylinux2010_x86_64.whl (4.9 MB) Collecting google-auth<3,>=1.6.3 Using cached google_auth-2.3.3-py2.py3-none-any.whl (155 kB) Collecting requests<3,>=2.21.0 Using cached requests-2.26.0-py2.py3-none-any.whl (62 kB) Collecting protobuf>=3.6.0 Using cached protobuf-3.19.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.1 MB) Collecting google-auth-oauthlib<0.5,>=0.4.1 Using cached google_auth_oauthlib-0.4.6-py2.py3-none-any.whl (18 kB) Collecting tensorboard-plugin-wit>=1.6.0 Using cached tensorboard_plugin_wit-1.8.0-py3-none-any.whl (781 kB) Requirement already satisfied: numpy>=1.12.0 in /home/ren2/anaconda3/envs/Captioning_Zoo/lib/python3.8/site-packages (from tensorboard) (1.21.2) Collecting grpcio>=1.24.3 Downloading grpcio-1.42.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (4.0 MB) |████████████████████████████████| 4.0 MB 10.5 MB/s Requirement already satisfied: wheel>=0.26 in /home/ren2/anaconda3/envs/Captioning_Zoo/lib/python3.8/site-packages (from tensorboard) (0.37.0) Requirement already satisfied: six in /home/ren2/anaconda3/envs/Captioning_Zoo/lib/python3.8/site-packages (from absl-py>=0.4->tensorboard) (1.16.0) Collecting rsa<5,>=3.1.4 Using cached rsa-4.8-py3-none-any.whl (39 kB) Collecting pyasn1-modules>=0.2.1 Using cached pyasn1_modules-0.2.8-py2.py3-none-any.whl (155 kB) Collecting cachetools<5.0,>=2.0.0 Using cached cachetools-4.2.4-py3-none-any.whl (10 kB) Collecting requests-oauthlib>=0.7.0 Using cached requests_oauthlib-1.3.0-py2.py3-none-any.whl (23 kB) Collecting importlib-metadata>=4.4 Using cached importlib_metadata-4.8.2-py3-none-any.whl (17 kB) Collecting zipp>=0.5 Using cached zipp-3.6.0-py3-none-any.whl (5.3 kB) Collecting pyasn1<0.5.0,>=0.4.6 Using cached pyasn1-0.4.8-py2.py3-none-any.whl (77 kB) Requirement already satisfied: certifi>=2017.4.17 in /home/ren2/anaconda3/envs/Captioning_Zoo/lib/python3.8/site-packages (from requests<3,>=2.21.0->tensorboard) (2021.10.8) Collecting charset-normalizer~=2.0.0 Using cached charset_normalizer-2.0.9-py3-none-any.whl (39 kB) Collecting urllib3<1.27,>=1.21.1 Using cached urllib3-1.26.7-py2.py3-none-any.whl (138 kB) Collecting idna<4,>=2.5 Using cached idna-3.3-py3-none-any.whl (61 kB) Collecting oauthlib>=3.0.0 Using cached oauthlib-3.1.1-py2.py3-none-any.whl (146 kB) Installing collected packages: urllib3, pyasn1, idna, charset-normalizer, zipp, rsa, requests, pyasn1-modules, oauthlib, cachetools, requests-oauthlib, importlib-metadata, google-auth, werkzeug, tensorboard-plugin-wit, tensorboard-data-server, protobuf, markdown, grpcio, google-auth-oauthlib, absl-py, tensorboard Successfully installed absl-py-1.0.0 cachetools-4.2.4 charset-normalizer-2.0.9 google-auth-2.3.3 google-auth-oauthlib-0.4.6 grpcio-1.42.0 idna-3.3 importlib-metadata-4.8.2 markdown-3.3.6 oauthlib-3.1.1 protobuf-3.19.1 pyasn1-0.4.8 pyasn1-modules-0.2.8 requests-2.26.0 requests-oauthlib-1.3.0 rsa-4.8 tensorboard-2.7.0 tensorboard-data-server-0.6.1 tensorboard-plugin-wit-1.8.0 urllib3-1.26.7 werkzeug-2.0.2 zipp-3.6.0 (Captioning_Zoo) ren2@Ren2:~/data2/mengya/mengya_code/main_ImageCaptioning.pytorch$ python tools/train.py --cfg configs/fc.yml --id fc Traceback (most recent call last): File "tools/train.py", line 18, in <module> import captioning.utils.opts as opts ModuleNotFoundError: No module named 'captioning' (Captioning_Zoo) ren2@Ren2:~/data2/mengya/mengya_code/main_ImageCaptioning.pytorch$ python -m pip install -e . Obtaining file:///home/ren2/data2/mengya/mengya_code/main_ImageCaptioning.pytorch Installing collected packages: captioning Running setup.py develop for captioning Successfully installed captioning-0.0.1 (Captioning_Zoo) ren2@Ren2:~/data2/mengya/mengya_code/main_ImageCaptioning.pytorch$ python tools/train.py --cfg configs/fc.yml --id fc Hugginface transformers not installed; please visit https://github.com/huggingface/transformers meshed-memory-transformer not installed; please run `pip install git+https://github.com/ruotianluo/meshed-memory-transformer.git` Traceback (most recent call last): File "tools/train.py", line 20, in <module> from captioning.data.dataloader import * File "/home/ren2/data2/mengya/mengya_code/main_ImageCaptioning.pytorch/captioning/data/dataloader.py", line 6, in <module> import h5py ModuleNotFoundError: No module named 'h5py' (Captioning_Zoo) ren2@Ren2:~/data2/mengya/mengya_code/main_ImageCaptioning.pytorch$ pip install h5py Collecting h5py Downloading h5py-3.6.0-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (4.5 MB) |████████████████████████████████| 4.5 MB 11.0 MB/s Requirement already satisfied: numpy>=1.14.5 in /home/ren2/anaconda3/envs/Captioning_Zoo/lib/python3.8/site-packages (from h5py) (1.21.2) Installing collected packages: h5py Successfully installed h5py-3.6.0 (Captioning_Zoo) ren2@Ren2:~/data2/mengya/mengya_code/main_ImageCaptioning.pytorch$ python tools/train.py --cfg configs/fc.yml --id fc Hugginface transformers not installed; please visit https://github.com/huggingface/transformers meshed-memory-transformer not installed; please run `pip install git+https://github.com/ruotianluo/meshed-memory-transformer.git` Traceback (most recent call last): File "tools/train.py", line 20, in <module> from captioning.data.dataloader import * File "/home/ren2/data2/mengya/mengya_code/main_ImageCaptioning.pytorch/captioning/data/dataloader.py", line 7, in <module> from lmdbdict import lmdbdict ModuleNotFoundError: No module named 'lmdbdict' (Captioning_Zoo) ren2@Ren2:~/data2/mengya/mengya_code/main_ImageCaptioning.pytorch$ pip install lmdbdict Collecting lmdbdict Using cached lmdbdict-0.2.2-py3-none-any.whl (6.0 kB) Collecting lmdb Downloading lmdb-1.2.1-cp38-cp38-manylinux2010_x86_64.whl (306 kB) |████████████████████████████████| 306 kB 11.4 MB/s Installing collected packages: lmdb, lmdbdict Successfully installed lmdb-1.2.1 lmdbdict-0.2.2 (Captioning_Zoo) ren2@Ren2:~/data2/mengya/mengya_code/main_ImageCaptioning.pytorch$ python tools/train.py --cfg configs/fc.yml --id fc Hugginface transformers not installed; please visit https://github.com/huggingface/transformers meshed-memory-transformer not installed; please run `pip install git+https://github.com/ruotianluo/meshed-memory-transformer.git` Traceback (most recent call last): File "tools/train.py", line 21, in <module> import skimage.io ModuleNotFoundError: No module named 'skimage' (Captioning_Zoo) ren2@Ren2:~/data2/mengya/mengya_code/main_ImageCaptioning.pytorch$ pip install scikit-image Collecting scikit-image Downloading scikit_image-0.19.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (60.7 MB) |████████████████████████████████| 60.7 MB 10.5 MB/s Requirement already satisfied: numpy>=1.17.0 in /home/ren2/anaconda3/envs/Captioning_Zoo/lib/python3.8/site-packages (from scikit-image) (1.21.2) Requirement already satisfied: pillow!=7.1.0,!=7.1.1,!=8.3.0,>=6.1.0 in /home/ren2/anaconda3/envs/Captioning_Zoo/lib/python3.8/site-packages (from scikit-image) (8.4.0) Collecting imageio>=2.4.1 Using cached imageio-2.13.3-py3-none-any.whl (3.3 MB) Collecting tifffile>=2019.7.26 Downloading tifffile-2021.11.2-py3-none-any.whl (178 kB) |████████████████████████████████| 178 kB 11.1 MB/s Collecting networkx>=2.2 Using cached networkx-2.6.3-py3-none-any.whl (1.9 MB) Collecting scipy>=1.4.1 Downloading scipy-1.7.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (39.3 MB) |████████████████████████████████| 39.3 MB 12.2 MB/s Collecting packaging>=20.0 Using cached packaging-21.3-py3-none-any.whl (40 kB) Collecting PyWavelets>=1.1.1 Downloading PyWavelets-1.2.0-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.whl (6.3 MB) |████████████████████████████████| 6.3 MB 11.0 MB/s Collecting pyparsing!=3.0.5,>=2.0.2 Using cached pyparsing-3.0.6-py3-none-any.whl (97 kB) Installing collected packages: pyparsing, tifffile, scipy, PyWavelets, packaging, networkx, imageio, scikit-image Successfully installed PyWavelets-1.2.0 imageio-2.13.3 networkx-2.6.3 packaging-21.3 pyparsing-3.0.6 scikit-image-0.19.0 scipy-1.7.3 tifffile-2021.11.2 (Captioning_Zoo) ren2@Ren2:~/data2/mengya/mengya_code/main_ImageCaptioning.pytorch$ python tools/train.py --cfg configs/fc.yml --id fc Hugginface transformers not installed; please visit https://github.com/huggingface/transformers meshed-memory-transformer not installed; please run `pip install git+https://github.com/ruotianluo/meshed-memory-transformer.git` Warning: coco-caption not available Traceback (most recent call last): File "tools/train.py", line 295, in <module> opt = opts.parse_opt() File "/home/ren2/data2/mengya/mengya_code/main_ImageCaptioning.pytorch/captioning/utils/opts.py", line 232, in parse_opt from .config import CfgNode File "/home/ren2/data2/mengya/mengya_code/main_ImageCaptioning.pytorch/captioning/utils/config.py", line 7, in <module> import yaml ModuleNotFoundError: No module named 'yaml' (Captioning_Zoo) ren2@Ren2:~/data2/mengya/mengya_code/main_ImageCaptioning.pytorch$ pip install pyyaml Collecting pyyaml Downloading PyYAML-6.0-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (701 kB) |████████████████████████████████| 701 kB 11.0 MB/s Installing collected packages: pyyaml Successfully installed pyyaml-6.0 (Captioning_Zoo) ren2@Ren2:~/data2/mengya/mengya_code/main_ImageCaptioning.pytorch$ python tools/train.py --cfg configs/fc.yml --id fc Hugginface transformers not installed; please visit https://github.com/huggingface/transformers meshed-memory-transformer not installed; please run `pip install git+https://github.com/ruotianluo/meshed-memory-transformer.git` Warning: coco-caption not available Traceback (most recent call last): File "tools/train.py", line 295, in <module> opt = opts.parse_opt() File "/home/ren2/data2/mengya/mengya_code/main_ImageCaptioning.pytorch/captioning/utils/opts.py", line 232, in parse_opt from .config import CfgNode File "/home/ren2/data2/mengya/mengya_code/main_ImageCaptioning.pytorch/captioning/utils/config.py", line 8, in <module> from yacs.config import CfgNode as _CfgNode ModuleNotFoundError: No module named 'yacs' (Captioning_Zoo) ren2@Ren2:~/data2/mengya/mengya_code/main_ImageCaptioning.pytorch$ pip install yacs Collecting yacs Using cached yacs-0.1.8-py3-none-any.whl (14 kB) Requirement already satisfied: PyYAML in /home/ren2/anaconda3/envs/Captioning_Zoo/lib/python3.8/site-packages (from yacs) (6.0) Installing collected packages: yacs Successfully installed yacs-0.1.8 (Captioning_Zoo) ren2@Ren2:~/data2/mengya/mengya_code/main_ImageCaptioning.pytorch$ python tools/train.py --cfg configs/fc.yml --id fc Hugginface transformers not installed; please visit https://github.com/huggingface/transformers meshed-memory-transformer not installed; please run `pip install git+https://github.com/ruotianluo/meshed-memory-transformer.git` Warning: coco-caption not available DataLoader loading json file: data/cocotalk.json vocab size is 9487 DataLoader loading h5 file: data/cocotalk_fc data/cocotalk_att data/cocotalk_box data/cocotalk_label.h5 max sequence length in data is 16 read 123287 image features assigned 113287 images to split train assigned 5000 images to split val assigned 5000 images to split test Read data: 0.00609278678894043 /home/ren2/anaconda3/envs/Captioning_Zoo/lib/python3.8/site-packages/torch/nn/parallel/_functions.py:68: UserWarning: Was asked to gather along dimension 0, but all input tensors were scalars; will instead unsqueeze and return a vector. warnings.warn('Was asked to gather along dimension 0, but all ' iter 0 (epoch 0), train_loss = 9.191, time/batch = 5.047 Read data: 0.00029587745666503906 iter 1 (epoch 0), train_loss = 9.060, time/batch = 0.073 Read data: 0.00022864341735839844 iter 2 (epoch 0), train_loss = 8.898, time/batch = 0.075 Read data: 0.00017642974853515625 iter 3 (epoch 0), train_loss = 8.774, time/batch = 0.065 ===================================================== Part 2: lack other captioning model pip install matplotlib pip install -U gensim pip install git+https://github.com/huggingface/transformers.git pip install git+https://github.com/ruotianluo/meshed-memory-transformer.git FileNotFoundError: [Errno 2] No such file or directory: '/coco-caption/pycocoevalcap/wmd/data/GoogleNews-vectors-negative300.bin' You can download the word2vec: https://s3.amazonaws.com/dl4j-distribution/GoogleNews-vectors-negative300.bin.gz (Solution is from https://github.com/UVa-NLP/VMASK/issues/3, https://stackoverflow.com/questions/46433778/import-googlenews-vectors-negative300-bin) wget -c "https://s3.amazonaws.com/dl4j-distribution/GoogleNews-vectors-negative300.bin.gz" This downloads the GZIP compressed file that you can uncompress using: gzip -d GoogleNews-vectors-negative300.bin.gz You can then use the below command to get wordVector. from gensim import models w = models.KeyedVectors.load_word2vec_format('../GoogleNews-vectors-negative300.bin', binary=True) ======================================================= Part3: evluation metric: SPICE metric issue Solution: cd path/coco-caption ./get_stanford_models.sh Refer to https://github.com/tylin/coco-caption 1) You will first need to download the Stanford CoreNLP 3.6.0 code and models for use by SPICE. To do this, run: ./get_stanford_models.sh 2) Note: SPICE will try to create a cache of parsed sentences in ./pycocoevalcap/spice/cache/. This dramatically speeds up repeated evaluations. The cache directory can be moved by setting 'CACHE_DIR' in ./pycocoevalcap/spice. In the same file, caching can be turned off by removing the '-cache' argument to 'spice_cmd'. ModuleNotFoundError: No module named 'pyemd' conda install -c conda-forge pyemd Some solution from other people. But these reasons are not proper for my case. https://blog.csdn.net/sunny0722/article/details/119946804 https://blog.csdn.net/bit_coders/article/details/120840271 https://github.com/jiasenlu/NeuralBabyTalk/issues/9
