InvalidArgumentError: Incompatible shapes: [100,24,24,1] vs. [100,10,10,1]

[akashcmd]

Hi @tjvandal and other collaborators,
I tried to run bash run_job.sh but it showed this same error. I am stuck with this error since a week now and am not able to find a solution to it. Could you please help me urgently.

Note : The data is downloaded successfully and completely. I have the following files and the files in scratch folder.

Error

Exception has occurred: InvalidArgumentError
Incompatible shapes: [100,24,24,1] vs. [100,10,10,1]
	 [[Node: loss/sub = Sub[T=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"](hidden_2/conv2d/BiasAdd, loss/cond/Merge)]]

Caused by op u'loss/sub', defined at:
  File "/opt/anaconda3/envs/reaps27/lib/python2.7/runpy.py", line 174, in _run_module_as_main
    "__main__", fname, loader, pkg_name)
  File "/opt/anaconda3/envs/reaps27/lib/python2.7/runpy.py", line 72, in _run_code
    exec code in run_globals
  File "/Users/akashcmd/.vscode/extensions/ms-python.python-2021.12.1559732655/pythonFiles/lib/python/debugpy/__main__.py", line 45, in <module>
    cli.main()
  File "/Users/akashcmd/.vscode/extensions/ms-python.python-2021.12.1559732655/pythonFiles/lib/python/debugpy/../debugpy/server/cli.py", line 444, in main
    run()
  File "/Users/akashcmd/.vscode/extensions/ms-python.python-2021.12.1559732655/pythonFiles/lib/python/debugpy/../debugpy/server/cli.py", line 285, in run_file
    runpy.run_path(target_as_str, run_name=compat.force_str("__main__"))
  File "/opt/anaconda3/envs/reaps27/lib/python2.7/runpy.py", line 252, in run_path
    return _run_module_code(code, init_globals, run_name, path_name)
  File "/opt/anaconda3/envs/reaps27/lib/python2.7/runpy.py", line 82, in _run_module_code
    mod_name, mod_fname, mod_loader, pkg_name)
  File "/opt/anaconda3/envs/reaps27/lib/python2.7/runpy.py", line 72, in _run_code
    exec code in run_globals
  File "/Users/akashcmd/Projects/deepsd/train.py", line 157, in <module>
    train()
  File "/Users/akashcmd/Projects/deepsd/train.py", line 97, in train
    is_training=is_training)
  File "/Users/akashcmd/Projects/deepsd/srcnn-tensorflow/srcnn/srcnn.py", line 47, in __init__
    self._build_graph()
  File "/Users/akashcmd/Projects/deepsd/srcnn-tensorflow/srcnn/srcnn.py", line 114, in _build_graph
    self.loss = self._loss(_prediction_norm)
  File "/Users/akashcmd/Projects/deepsd/srcnn-tensorflow/srcnn/srcnn.py", line 83, in _loss
    err = tf.square(predictions - _y)
  File "/opt/anaconda3/envs/reaps27/lib/python2.7/site-packages/tensorflow/python/ops/math_ops.py", line 894, in binary_op_wrapper
    return func(x, y, name=name)
  File "/opt/anaconda3/envs/reaps27/lib/python2.7/site-packages/tensorflow/python/ops/gen_math_ops.py", line 4636, in _sub
    "Sub", x=x, y=y, name=name)
  File "/opt/anaconda3/envs/reaps27/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
    op_def=op_def)
  File "/opt/anaconda3/envs/reaps27/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2956, in create_op
    op_def=op_def)
  File "/opt/anaconda3/envs/reaps27/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1470, in __init__
    self._traceback = self._graph._extract_stack()  # pylint: disable=protected-access

InvalidArgumentError (see above for traceback): Incompatible shapes: [100,24,24,1] vs. [100,10,10,1]
	 [[Node: loss/sub = Sub[T=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"](hidden_2/conv2d/BiasAdd, loss/cond/Merge)]]
  File "/Users/akashcmd/Projects/deepsd/train.py", line 135, in train
    feed_dict=feed_dict(True))
  File "/Users/akashcmd/Projects/deepsd/train.py", line 157, in <module>
    train()

Steps to Reproduce

1. Run prism.py with python 2.7 and download the required files
2. Run bash run_job.sh

Reopening Issue : #8

[akashcmd]

I am using MacOs with Apple Silicon M1 chip.

I have setup the following conda environment :

name: reaps27
channels:
  - pytorch
  - menpo
  - anaconda
  - conda-forge
  - defaults
dependencies:
  - autopep8=1.6.0=pyhd3eb1b0_0
  - backports=1.1=pyhd3eb1b0_0
  - backports.functools_lru_cache=1.6.4=pyhd3eb1b0_0
  - backports_abc=0.5=py_1
  - blas=1.0=mkl
  - bleach=1.5.0=py27_0
  - bzip2=1.0.8=h1de35cc_0
  - ca-certificates=2022.4.26=hecd8cb5_0
  - cairo=1.14.12=hc4e6be7_4
  - certifi=2020.6.20=pyhd3eb1b0_3
  - curl=7.67.0=ha441bb4_0
  - cycler=0.10.0=py27hfc73c78_0
  - enum34=1.1.6=py27_1
  - expat=2.4.4=he9d5cce_0
  - fontconfig=2.13.1=ha9ee91d_0
  - freetype=2.11.0=hd8bbffd_0
  - freexl=1.0.6=h9ed2024_0
  - funcsigs=1.0.2=py27hb9f6266_0
  - functools32=3.2.3.2=py27_1
  - futures=3.3.0=py27_0
  - gdal=2.3.3=py27hbe65578_0
  - geos=3.7.1=h0a44026_0
  - gettext=0.21.0=h7535e17_0
  - giflib=5.1.4=h1de35cc_1
  - glib=2.56.2=hd9629dc_0
  - hdf4=4.2.13=h39711bb_2
  - hdf5=1.10.4=hfa1e0ec_0
  - html5lib=0.9999999=py27_0
  - icu=58.2=h0a44026_3
  - intel-openmp=2022.0.0=hecd8cb5_3615
  - jpeg=9e=hca72f7f_0
  - json-c=0.13.1=h3efe00b_0
  - kealib=1.4.7=hf5ed860_6
  - kiwisolver=1.1.0=py27h0a44026_0
  - krb5=1.16.4=hddcf347_0
  - libblas=3.9.0=1_h43114d0_netlib
  - libboost=1.67.0=hebc422b_4
  - libcblas=3.9.0=3_h7d47d6b_netlib
  - libcurl=7.67.0=h051b688_0
  - libcxx=12.0.0=h2f01273_0
  - libdap4=3.19.1=h3d3e54a_0
  - libedit=3.1.20210910=hca72f7f_0
  - libffi=3.3=hb1e8313_2
  - libgdal=2.3.3=h0950a36_0
  - libgfortran=4.0.0=7_5_0_h1a10cd1_23
  - libgfortran4=7.5.0=h1a10cd1_23
  - libiconv=1.16=hca72f7f_2
  - libkml=1.3.0=hbe12b63_4
  - liblapack=3.9.0=3_h7d47d6b_netlib
  - libnetcdf=4.6.1=hd5207e6_2
  - libpng=1.6.37=ha441bb4_0
  - libpq=11.5=h31a01ba_2
  - libprotobuf=3.11.2=hd9629dc_0
  - libspatialite=4.3.0a=h644ec7d_19
  - libssh2=1.10.0=h0a4fc7d_0
  - libtiff=4.1.0=hcb84e12_0
  - libxml2=2.9.14=hbf8cd5e_0
  - llvm-openmp=12.0.0=h0dcd299_1
  - lz4-c=1.8.1.2=h1de35cc_0
  - markdown=3.1.1=py27_0
  - matplotlib=2.2.3=py27h54f8f79_0
  - mkl=2019.4=233
  - mkl-service=2.3.0=py27hfbe908c_0
  - mkl_fft=1.0.15=py27h5e564d8_0
  - mkl_random=1.1.0=py27ha771720_0
  - mock=3.0.5=py27_0
  - ncurses=6.3=hca72f7f_2
  - numpy=1.15.4=py27hbb3c62a_1002
  - opencv=2.4.11=py27_1
  - openjpeg=2.4.0=h66ea3da_0
  - openssl=1.1.1o=hca72f7f_0
  - pandas=0.24.2=py27h86efe34_0
  - pcre=8.45=h23ab428_0
  - pip=19.3.1=py27_0
  - pixman=0.40.0=h9ed2024_1
  - poppler=0.65.0=ha097c24_1
  - poppler-data=0.4.11=hecd8cb5_0
  - postgresql=11.5=h26bc10f_2
  - proj4=5.2.0=h0a44026_1
  - protobuf=3.11.2=py27h0a44026_0
  - pycodestyle=2.7.0=pyhd3eb1b0_0
  - pyparsing=2.4.7=pyhd3eb1b0_0
  - python=2.7.18=h47d645e_1
  - python-dateutil=2.8.2=pyhd3eb1b0_0
  - pytz=2021.3=pyhd3eb1b0_0
  - readline=8.1.2=hca72f7f_1
  - scikit-learn=0.20.3=py27h27c97d8_0
  - scipy=1.2.1=py27h7e0e109_2
  - setuptools=44.0.0=py27_0
  - singledispatch=3.7.0=pyhd3eb1b0_1001
  - six=1.16.0=pyhd3eb1b0_1
  - sqlite=3.38.5=h707629a_0
  - subprocess32=3.5.4=py27h1de35cc_0
  - tbb=4.3_20141023=0
  - tensorboard=0.4.0rc3=py27_2
  - tensorflow=1.4.0=py27_0
  - tk=8.6.12=h5d9f67b_0
  - toml=0.10.2=pyhd3eb1b0_0
  - tornado=5.1.1=py27h1de35cc_0
  - tzcode=2022e=hb7f2c08_0
  - webencodings=0.5.1=py27_1
  - werkzeug=1.0.1=pyhd3eb1b0_0
  - wheel=0.37.1=pyhd3eb1b0_0
  - xarray=0.11.3=py27_0
  - xerces-c=3.2.3=h48eee30_0
  - xz=5.2.5=hca72f7f_1
  - zlib=1.2.12=h4dc903c_2
  - zstd=1.3.7=h5bba6e5_0

[jsmoraga-fathom]

I have the exact same problem described by @akashcmd. My environment looks like this:

Name Version Build Channel

_libgcc_mutex 0.1 main
asn1crypto 1.2.0 py27_0
backports 1.0 py_2
backports.functools_lru_cache 1.5 py_2
backports_abc 0.5 py27_0
blas 1.0 mkl
bleach 1.5.0 py27_0 conda-forge
bzip2 1.0.8 h7b6447c_0
ca-certificates 2023.5.7 hbcca054_0 conda-forge
cairo 1.14.12 h8948797_3
certifi 2019.11.28 py27h8c360ce_1 conda-forge
cffi 1.13.1 py27h2e261b9_0
chardet 3.0.4 py27_1003
conda 4.7.12 py27_0
conda-package-handling 1.6.0 py27h7b6447c_0
cryptography 2.8 py27h1ba5d50_0
curl 7.65.3 hbc83047_0
cycler 0.10.0 py27_0
dbus 1.13.12 h746ee38_0
enum34 1.1.6 py27_1
expat 2.2.6 he6710b0_0
fontconfig 2.13.0 h9420a91_0
freetype 2.9.1 h8a8886c_1
freexl 1.0.5 h14c3975_0
funcsigs 1.0.2 py27_0
functools32 3.2.3.2 py27_1
futures 3.3.0 py27_0
gdal 2.3.3 py27hbb2a789_0
geos 3.7.1 he6710b0_0
giflib 5.1.4 h14c3975_1
glib 2.63.1 h5a9c865_0
graphite2 1.3.13 h58526e2_1001 conda-forge
gst-plugins-base 1.14.0 hbbd80ab_1
gstreamer 1.14.0 hb453b48_1
harfbuzz 1.8.8 hffaf4a1_0
hdf4 4.2.13 h3ca952b_2
hdf5 1.10.4 hb1b8bf9_0
html5lib 0.9999999 py27_0 conda-forge
icu 58.2 h9c2bf20_1
idna 2.8 py27_0
intel-openmp 2019.4 243
ipaddress 1.0.23 py_0
jpeg 9b h024ee3a_2
json-c 0.13.1 h1bed415_0
kealib 1.4.7 hd0c454d_6
kiwisolver 1.1.0 py27he6710b0_0
krb5 1.16.1 h173b8e3_7
libboost 1.67.0 h46d08c1_4
libcurl 7.65.3 h20c2e04_0
libdap4 3.19.1 h6ec2957_0
libedit 3.1.20181209 hc058e9b_0
libffi 3.2.1 hd88cf55_4
libgcc-ng 9.1.0 hdf63c60_0
libgdal 2.3.3 h2e7e64b_0
libgfortran-ng 7.3.0 hdf63c60_0
libkml 1.3.0 h590aaf7_4
libnetcdf 4.6.1 h11d0813_2
libpng 1.6.37 hbc83047_0
libpq 11.2 h20c2e04_0
libprotobuf 3.9.2 hd408876_0
libspatialite 4.3.0a hb08deb6_19
libssh2 1.8.2 h1ba5d50_0
libstdcxx-ng 9.1.0 hdf63c60_0
libtiff 4.1.0 h2733197_0
libuuid 1.0.3 h1bed415_2
libxcb 1.13 h1bed415_1
libxml2 2.9.9 hea5a465_1
markdown 3.1.1 py27_0
matplotlib 2.2.3 py27hb69df0a_0
mkl 2019.4 243
mkl-service 2.3.0 py27he904b0f_0
mkl_fft 1.0.15 py27ha843d7b_0
mkl_random 1.1.0 py27hd6b4f25_0
mock 3.0.5 py27_0
ncurses 6.1 he6710b0_1
numpy 1.16.5 py27h7e9f1db_0
numpy-base 1.16.5 py27hde5b4d6_0
olefile 0.46 py27_0
opencv 2.4.11 nppy27_0 menpo
openjpeg 2.3.0 h05c96fa_1
openssl 1.1.1h h516909a_0 conda-forge
pandas 0.24.2 py27he6710b0_0
pango 1.40.14 he752989_2 conda-forge
pcre 8.43 he6710b0_0
pillow 6.2.1 py27h34e0f95_0
pip 19.3.1 py27_0
pixman 0.38.0 h7b6447c_0
poppler 0.65.0 h581218d_1
poppler-data 0.4.9 0
proj4 5.2.0 he6710b0_1
protobuf 3.9.2 py27he6710b0_0
pycosat 0.6.3 py27h14c3975_0
pycparser 2.19 py27_0
pyopenssl 19.0.0 py27_0
pyparsing 2.4.2 py_0
pyqt 5.9.2 py27h05f1152_2
pysocks 1.7.1 py27_0
python 2.7.17 h9bab390_0
python-dateutil 2.8.1 py_0
python_abi 2.7 1_cp27mu conda-forge
pytz 2019.3 py_0
qt 5.9.7 h5867ecd_1
readline 7.0 h7b6447c_5
requests 2.22.0 py27_0
ruamel_yaml 0.15.46 py27h14c3975_0
scikit-learn 0.20.3 py27hd81dba3_0
scipy 1.2.1 py27h7c811a0_0
setuptools 41.6.0 py27_0
singledispatch 3.4.0.3 py27_0
sip 4.19.8 py27hf484d3e_0
six 1.12.0 py27_0
sqlite 3.30.1 h7b6447c_0
subprocess32 3.5.4 py27h7b6447c_0
tensorflow 1.4.1 0
tensorflow-base 1.4.1 py27hd00c003_2
tensorflow-tensorboard 1.5.1 py27hf484d3e_1
tk 8.6.8 hbc83047_0
tornado 5.1.1 py27h7b6447c_0
tqdm 4.36.1 py_0
urllib3 1.24.2 py27_0
webencodings 0.5.1 py27_1
werkzeug 0.16.0 py_0
wheel 0.33.6 py27_0
xarray 0.11.3 py27_0
xerces-c 3.2.2 h780794e_0
xz 5.2.4 h14c3975_4
yaml 0.1.7 had09818_2
zlib 1.2.11 h7b6447c_3
zstd 1.3.7 h0b5b093_0

Have you got any idea, @tjvandal? Thanks!