tensorflow-gpu version

[eric-yyjau]

FYR: Tested ok under tensorflow-gpu==1.14.0

Errors using tensorflow-gpu==1.12.0

module 'tensorflow' has no attribute 'custom_gradient'

Errors using tensorflow-gpu==1.13.1

failed to run optimizer arithmeticoptimizer, stage removestackstridedslicesameaxis node

Testing command

python demos/demo_slam.py --dataset=scannet --n_keyframes=3

Here's my conda enviroments.yml

name: py37-deepv2d
channels:
  - defaults
dependencies:
  - _libgcc_mutex=0.1=main
  - _tflow_select=2.1.0=gpu
  - absl-py=0.7.1=py37_0
  - astor=0.7.1=py37_0
  - blas=1.0=mkl
  - c-ares=1.15.0=h7b6447c_1
  - ca-certificates=2019.5.15=0
  - certifi=2019.3.9=py37_0
  - cudatoolkit=10.0.130=0
  - cudnn=7.6.0=cuda10.0_0
  - cupti=10.0.130=0
  - gast=0.2.2=py37_0
  - grpcio=1.16.1=py37hf8bcb03_1
  - h5py=2.9.0=py37h7918eee_0
  - hdf5=1.10.4=hb1b8bf9_0
  - intel-openmp=2019.4=243
  - keras-applications=1.0.8=py_0
  - keras-preprocessing=1.1.0=py_1
  - libedit=3.1.20181209=hc058e9b_0
  - libffi=3.2.1=hd88cf55_4
  - libgcc-ng=9.1.0=hdf63c60_0
  - libgfortran-ng=7.3.0=hdf63c60_0
  - libprotobuf=3.8.0=hd408876_0
  - libstdcxx-ng=9.1.0=hdf63c60_0
  - markdown=3.1.1=py37_0
  - mkl=2019.4=243
  - mkl_fft=1.0.12=py37ha843d7b_0
  - mkl_random=1.0.2=py37hd81dba3_0
  - mock=3.0.5=py37_0
  - ncurses=6.1=he6710b0_1
  - numpy=1.16.4=py37h7e9f1db_0
  - numpy-base=1.16.4=py37hde5b4d6_0
  - openssl=1.1.1c=h7b6447c_1
  - pip=19.1.1=py37_0
  - protobuf=3.8.0=py37he6710b0_0
  - python=3.7.3=h0371630_0
  - readline=7.0=h7b6447c_5
  - scipy=1.2.1=py37h7c811a0_0
  - setuptools=41.0.1=py37_0
  - six=1.12.0=py37_0
  - sqlite=3.28.0=h7b6447c_0
  - tensorboard=1.13.1=py37hf484d3e_0
  - tensorflow=1.13.1=gpu_py37hc158e3b_0
  - tensorflow-base=1.13.1=gpu_py37h8d69cac_0
  - tensorflow-estimator=1.13.0=py_0
  - tensorflow-gpu=1.13.1=h0d30ee6_0
  - termcolor=1.1.0=py37_1
  - tk=8.6.8=hbc83047_0
  - werkzeug=0.15.4=py_0
  - wheel=0.33.4=py37_0
  - xz=5.2.4=h14c3975_4
  - zlib=1.2.11=h7b6447c_3
  - pip:
    - attrs==19.1.0
    - backcall==0.1.0
    - bleach==3.1.0
    - cycler==0.10.0
    - decorator==4.4.0
    - defusedxml==0.6.0
    - easydict==1.9
    - entrypoints==0.3
    - google-pasta==0.1.8
    - ipykernel==5.1.1
    - ipython==7.5.0
    - ipython-genutils==0.2.0
    - jedi==0.13.3
    - jinja2==2.10.1
    - jsonschema==3.0.1
    - jupyter-client==5.2.4
    - jupyter-core==4.4.0
    - jupyterlab==0.35.6
    - jupyterlab-server==0.2.0
    - kiwisolver==1.1.0
    - markupsafe==1.1.1
    - matplotlib==3.1.0
    - mistune==0.8.4
    - nbconvert==5.5.0
    - nbformat==4.4.0
    - notebook==5.7.8
    - opencv-python==3.4.5.20
    - pandas==0.24.2
    - pandocfilters==1.4.2
    - parso==0.4.0
    - pexpect==4.7.0
    - pickleshare==0.7.5
    - prometheus-client==0.7.0
    - prompt-toolkit==2.0.9
    - ptyprocess==0.6.0
    - pygments==2.4.2
    - pyparsing==2.4.0
    - pyrsistent==0.15.2
    - python-dateutil==2.8.0
    - pytz==2019.1
    - pyyaml==5.3
    - pyzmq==18.0.1
    - seaborn==0.9.0
    - send2trash==1.5.0
    - terminado==0.8.2
    - testpath==0.4.2
    - toposort==1.5
    - tornado==6.0.2
    - tqdm==4.43.0
    - traitlets==4.3.2
    - vtk==8.1.2
    - wcwidth==0.1.7
    - webencodings==0.5.1
    - wrapt==1.12.0
prefix: /home/yoyee/miniconda3/envs/py37-deepv2d

[zachteed]

Tensorflow 1.12.0 should have custom_gradient. What happens when you run these commands?

>>> import tensorflow as tf
>>> tf.__version__
'1.12.0'
>>> tf.custom_gradient
<function custom_gradient at 0x7f6ce8e7ff28>