Hello
I successfully installed keras and TensorFlow backend with install_keras(). I
attached the installation log as keras_install_log.txt. After that I tried to
download mnist data with dataset_mnist() function. However I got the following
error message:
#----------------------------------------------------------------------------
> library(keras)
> mnist <- dataset_mnist()
Using TensorFlow backend.
Error: ImportError: Traceback (most recent call last):
File
"C:\Users\user\MINICO~1\envs\R-TENS~1\lib\site-packages\tensorflow\python\pywrap_tensorflow_internal.py",
line 14, in swig_import_helper return importlib.import_module(mname)
File "C:\Users\user\MINICO~1\envs\R-TENS~1\lib\importlib\__init__.py", line
126, in import_module return _bootstrap._gcd_import(name[level:], package,
level)
File "<frozen importlib._bootstrap>", line 994, in _gcd_import
File "<frozen importlib._bootstrap>", line 971, in _find_and_load
File "<frozen importlib._bootstrap>", line 955, in _find_and_load_unlocked
File "<frozen importlib._bootstrap>", line 658, in _load_unlocked
File "<frozen importlib._bootstrap>", line 571, in module_from_spec
File "<frozen importlib._bootstrap_external>", line 922, in create_module
File "<frozen importlib._bootstrap>", line 219, in _call_with_frames_removed
ImportError: DLL load failed with error code -1073741795
During handling of the above exce
#---------------------------------------------------------------------------------------
I also attached the error message as error_message.txt
How can I fix this problem.
Thanks
> library(keras)
> install_keras()
Creating r-tensorflow conda environment for TensorFlow installation...
Fetching package metadata .............
Solving package specifications: .
Package plan for installation in environment
C:\Users\user\MINICO~1\envs\r-tensorflow:
The following NEW packages will be INSTALLED:
certifi: 2019.3.9-py36_0
pip: 19.0.3-py36_0
python: 3.6.8-h9f7ef89_7
setuptools: 40.8.0-py36_0
sqlite: 3.27.2-he774522_0
vc: 14.1-h0510ff6_4
vs2015_runtime: 14.15.26706-h3a45250_0
wheel: 0.33.1-py36_0
wincertstore: 0.2-py36h7fe50ca_0
vs2015_runtime 100% |###############################| Time: 0:00:05 394.52 kB/s
vc-14.1-h0510f 100% |###############################| Time: 0:00:00 687.53 kB/s
sqlite-3.27.2- 100% |###############################| Time: 0:00:02 408.91 kB/s
python-3.6.8-h 100% |###############################| Time: 0:00:57 370.52 kB/s
certifi-2019.3 100% |###############################| Time: 0:00:00 463.10 kB/s
setuptools-40. 100% |###############################| Time: 0:00:01 438.73 kB/s
wheel-0.33.1-p 100% |###############################| Time: 0:00:00 493.57 kB/s
pip-19.0.3-py3 100% |###############################| Time: 0:00:04 404.28 kB/s
#
# To activate this environment, use:
# > activate r-tensorflow
#
# To deactivate an active environment, use:
# > deactivate
#
# * for power-users using bash, you must source
#
Fetching package metadata ...............
Solving package specifications: .
Package plan for installation in environment
C:\Users\user\MINICO~1\envs\r-tensorflow:
The following NEW packages will be INSTALLED:
absl-py: 0.7.1-py36_0 conda-forge
asn1crypto: 0.24.0-py36_1003 conda-forge
astor: 0.7.1-py_0 conda-forge
blas: 1.0-mkl
ca-certificates: 2019.3.9-hecc5488_0 conda-forge
cffi: 1.12.2-py36hb32ad35_1 conda-forge
chardet: 3.0.4-py36_1003 conda-forge
cryptography: 2.5-py36h74b6da3_1 conda-forge
freetype: 2.10.0-h5db478b_0 conda-forge
gast: 0.2.2-py_0 conda-forge
grpcio: 1.16.0-py36hbb4b082_1000 conda-forge
h5py: 2.9.0-nompi_py36h3cb27cb_1102 conda-forge
hdf5: 1.10.4-nompi_hcc15c50_1106 conda-forge
icc_rt: 2019.0.0-h0cc432a_1
idna: 2.8-py36_1000 conda-forge
intel-openmp: 2019.3-203
jpeg: 9c-hfa6e2cd_1001 conda-forge
keras: 2.2.4-py36_0 conda-forge
keras-applications: 1.0.4-py_1 conda-forge
keras-preprocessing: 1.0.2-py_1 conda-forge
libblas: 3.8.0-4_mkl conda-forge
libcblas: 3.8.0-4_mkl conda-forge
libgpuarray: 0.7.6-hfa6e2cd_1003 conda-forge
liblapack: 3.8.0-4_mkl conda-forge
libpng: 1.6.36-h7602738_1000 conda-forge
libprotobuf: 3.7.0-h1a1b453_2 conda-forge
libtiff: 4.0.10-h36446d0_1001 conda-forge
m2w64-gcc-libgfortran: 5.3.0-6
m2w64-gcc-libs: 5.3.0-7
m2w64-gcc-libs-core: 5.3.0-7
m2w64-gmp: 6.1.0-2
m2w64-libwinpthread-git: 5.0.0.4634.697f757-2
mako: 1.0.7-py_1 conda-forge
markdown: 2.6.11-py_0 conda-forge
markupsafe: 1.1.1-py36hfa6e2cd_0 conda-forge
mkl: 2019.1-144
msys2-conda-epoch: 20160418-1
numpy: 1.16.2-py36h8078771_1 conda-forge
olefile: 0.46-py_0 conda-forge
openssl: 1.0.2r-hfa6e2cd_0 conda-forge
pillow: 5.4.1-py36h9a613e6_1000 conda-forge
protobuf: 3.7.0-py36he025d50_0 conda-forge
pycparser: 2.19-py36_1 conda-forge
pygpu: 0.7.6-py36h452e1ab_1000 conda-forge
pyopenssl: 19.0.0-py36_0 conda-forge
pyreadline: 2.1-py36_1000 conda-forge
pysocks: 1.6.8-py36_1002 conda-forge
pyyaml: 5.1-py36hfa6e2cd_0 conda-forge
requests: 2.21.0-py36_1000 conda-forge
scipy: 1.2.1-py36h29ff71c_0
six: 1.12.0-py36_1000 conda-forge
tensorboard: 1.10.0-py36_0 conda-forge
tensorflow: 1.10.0-py36_0 conda-forge
tensorflow-hub: 0.3.0-py_0 conda-forge
termcolor: 1.1.0-py_2 conda-forge
theano: 1.0.4-py36h6538335_1000 conda-forge
tk: 8.6.9-hfa6e2cd_1001 conda-forge
urllib3: 1.24.1-py36_1000 conda-forge
vs2015_win-64: 14.0.25123-h17c34da_3 conda-forge
werkzeug: 0.15.1-py_0 conda-forge
win_inet_pton: 1.1.0-py36_0 conda-forge
yaml: 0.1.7-hfa6e2cd_1001 conda-forge
zlib: 1.2.11-h2fa13f4_1004 conda-forge
blas-1.0-mkl.t 100% |###############################| Time: 0:00:00 1.55 MB/s
ca-certificate 100% |###############################| Time: 0:00:00 431.19 kB/s
icc_rt-2019.0. 100% |###############################| Time: 0:00:24 401.36 kB/s
intel-openmp-2 100% |###############################| Time: 0:00:04 417.10 kB/s
msys2-conda-ep 100% |###############################| Time: 0:00:00 688.33 kB/s
vs2015_win-64- 100% |###############################| Time: 0:00:00 665.22 kB/s
m2w64-gmp-6.1. 100% |###############################| Time: 0:00:01 437.72 kB/s
m2w64-libwinpt 100% |###############################| Time: 0:00:00 492.60 kB/s
mkl-2019.1-144 100% |###############################| Time: 0:07:31 367.54 kB/s
jpeg-9c-hfa6e2 100% |###############################| Time: 0:00:00 435.98 kB/s
libblas-3.8.0- 100% |###############################| Time: 0:00:10 366.87 kB/s
libgpuarray-0. 100% |###############################| Time: 0:00:00 465.30 kB/s
m2w64-gcc-libs 100% |###############################| Time: 0:00:00 425.98 kB/s
openssl-1.0.2r 100% |###############################| Time: 0:00:16 354.42 kB/s
tk-8.6.9-hfa6e 100% |###############################| Time: 0:00:12 307.78 kB/s
yaml-0.1.7-hfa 100% |###############################| Time: 0:00:00 363.30 kB/s
zlib-1.2.11-h2 100% |###############################| Time: 0:00:00 419.65 kB/s
hdf5-1.10.4-no 100% |###############################| Time: 0:01:42 356.79 kB/s
libcblas-3.8.0 100% |###############################| Time: 0:00:09 408.28 kB/s
liblapack-3.8. 100% |###############################| Time: 0:00:09 405.06 kB/s
libpng-1.6.36- 100% |###############################| Time: 0:00:03 416.57 kB/s
libprotobuf-3. 100% |###############################| Time: 0:00:05 416.89 kB/s
libtiff-4.0.10 100% |###############################| Time: 0:00:02 443.01 kB/s
m2w64-gcc-libg 100% |###############################| Time: 0:00:00 452.12 kB/s
asn1crypto-0.2 100% |###############################| Time: 0:00:00 359.17 kB/s
astor-0.7.1-py 100% |###############################| Time: 0:00:00 613.60 kB/s
chardet-3.0.4- 100% |###############################| Time: 0:00:00 397.98 kB/s
freetype-2.10. 100% |###############################| Time: 0:00:01 413.89 kB/s
gast-0.2.2-py_ 100% |###############################| Time: 0:00:00 517.65 kB/s
idna-2.8-py36_ 100% |###############################| Time: 0:00:00 419.99 kB/s
m2w64-gcc-libs 100% |###############################| Time: 0:00:01 437.75 kB/s
markdown-2.6.1 100% |###############################| Time: 0:00:00 327.46 kB/s
markupsafe-1.1 100% |###############################| Time: 0:00:00 565.70 kB/s
numpy-1.16.2-p 100% |###############################| Time: 0:00:12 340.12 kB/s
olefile-0.46-p 100% |###############################| Time: 0:00:00 549.48 kB/s
pycparser-2.19 100% |###############################| Time: 0:00:00 291.87 kB/s
pyreadline-2.1 100% |###############################| Time: 0:00:00 211.44 kB/s
pyyaml-5.1-py3 100% |###############################| Time: 0:00:00 466.58 kB/s
six-1.12.0-py3 100% |###############################| Time: 0:00:00 1.36 MB/s
termcolor-1.1. 100% |###############################| Time: 0:00:00 2.92 MB/s
werkzeug-0.15. 100% |###############################| Time: 0:00:00 273.66 kB/s
win_inet_pton- 100% |###############################| Time: 0:00:00 580.63 kB/s
absl-py-0.7.1- 100% |###############################| Time: 0:00:00 357.82 kB/s
cffi-1.12.2-py 100% |###############################| Time: 0:00:00 398.58 kB/s
h5py-2.9.0-nom 100% |###############################| Time: 0:00:03 273.20 kB/s
mako-1.0.7-py_ 100% |###############################| Time: 0:00:00 130.42 kB/s
pillow-5.4.1-p 100% |###############################| Time: 0:00:02 308.92 kB/s
pysocks-1.6.8- 100% |###############################| Time: 0:00:00 544.14 kB/s
scipy-1.2.1-py 100% |###############################| Time: 0:00:49 298.90 kB/s
cryptography-2 100% |###############################| Time: 0:00:01 463.36 kB/s
grpcio-1.16.0- 100% |###############################| Time: 0:00:02 328.97 kB/s
protobuf-3.7.0 100% |###############################| Time: 0:00:01 347.05 kB/s
pygpu-0.7.6-py 100% |###############################| Time: 0:00:01 433.41 kB/s
pyopenssl-19.0 100% |###############################| Time: 0:00:00 356.25 kB/s
tensorboard-1. 100% |###############################| Time: 0:00:09 359.36 kB/s
theano-1.0.4-p 100% |###############################| Time: 0:00:12 321.46 kB/s
tensorflow-1.1 100% |###############################| Time: 0:00:59 569.64 kB/s
urllib3-1.24.1 100% |###############################| Time: 0:00:00 2.37 MB/s
requests-2.21. 100% |###############################| Time: 0:00:00 2.76 MB/s
tensorflow-hub 100% |###############################| Time: 0:00:00 7.43 MB/s
keras-applicat 100% |###############################| Time: 0:00:00 3.77 MB/s
keras-2.2.4-py 100% |###############################| Time: 0:00:00 2.32 MB/s
keras-preproce 100% |###############################| Time: 0:00:00 863.89 kB/s
Installation complete.
Restarting R session...
> > library(keras)
> mnist <- dataset_mnist()
Using TensorFlow backend.
Error: ImportError: Traceback (most recent call last):
File
"C:\Users\user\MINICO~1\envs\R-TENS~1\lib\site-packages\tensorflow\python\pywrap_tensorflow_internal.py",
line 14, in swig_import_helper
return importlib.import_module(mname)
File "C:\Users\user\MINICO~1\envs\R-TENS~1\lib\importlib\__init__.py", line
126, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "<frozen importlib._bootstrap>", line 994, in _gcd_import
File "<frozen importlib._bootstrap>", line 971, in _find_and_load
File "<frozen importlib._bootstrap>", line 955, in _find_and_load_unlocked
File "<frozen importlib._bootstrap>", line 658, in _load_unlocked
File "<frozen importlib._bootstrap>", line 571, in module_from_spec
File "<frozen importlib._bootstrap_external>", line 922, in create_module
File "<frozen importlib._bootstrap>", line 219, in _call_with_frames_removed
ImportError: DLL load failed with error code -1073741795
During handling of the above exce______________________________________________
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