Problem with keras or tensorflow in anaconda

Question

I never had any problems running my python code, till yesterday. I installed keras and tensorflow on my anaconda environment. Thaught everything is fine but got this error:

C:\Users\Uporabnik\anaconda3\envs\MLProjects\lib\site-packages\tensorflow\python\framework\dtypes.py:516: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
  _np_qint8 = np.dtype([("qint8", np.int8, 1)])
C:\Users\Uporabnik\anaconda3\envs\MLProjects\lib\site-packages\tensorflow\python\framework\dtypes.py:517: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
  _np_quint8 = np.dtype([("quint8", np.uint8, 1)])
C:\Users\Uporabnik\anaconda3\envs\MLProjects\lib\site-packages\tensorflow\python\framework\dtypes.py:518: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
  _np_qint16 = np.dtype([("qint16", np.int16, 1)])
C:\Users\Uporabnik\anaconda3\envs\MLProjects\lib\site-packages\tensorflow\python\framework\dtypes.py:519: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
  _np_quint16 = np.dtype([("quint16", np.uint16, 1)])
C:\Users\Uporabnik\anaconda3\envs\MLProjects\lib\site-packages\tensorflow\python\framework\dtypes.py:520: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
  _np_qint32 = np.dtype([("qint32", np.int32, 1)])
C:\Users\Uporabnik\anaconda3\envs\MLProjects\lib\site-packages\tensorflow\python\framework\dtypes.py:525: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
  np_resource = np.dtype([("resource", np.ubyte, 1)])
C:\Users\Uporabnik\anaconda3\envs\MLProjects\lib\site-packages\h5py\__init__.py:39: UserWarning: h5py is running against HDF5 1.10.5 when it was built against 1.10.6, this may cause problems
  '{0}.{1}.{2}'.format(*version.hdf5_built_version_tuple)
Warning! ***HDF5 library version mismatched error***
The HDF5 header files used to compile this application do not match
the version used by the HDF5 library to which this application is linked.
Data corruption or segmentation faults may occur if the application continues.
This can happen when an application was compiled by one version of HDF5 but
linked with a different version of static or shared HDF5 library.
You should recompile the application or check your shared library related
settings such as 'LD_LIBRARY_PATH'.
You can, at your own risk, disable this warning by setting the environment
variable 'HDF5_DISABLE_VERSION_CHECK' to a value of '1'.
Setting it to 2 or higher will suppress the warning messages totally.
Headers are 1.10.6, library is 1.10.5
        SUMMARY OF THE HDF5 CONFIGURATION
        =================================

General Information:
-------------------
                   HDF5 Version: 1.10.5
                  Configured on: 2019-03-04
                  Configured by: Visual Studio 15 2017 Win64
                    Host system: Windows-10.0.17763
              Uname information: Windows
                       Byte sex: little-endian
             Installation point: C:/Program Files/HDF5

Compiling Options:
------------------
                     Build Mode: 
              Debugging Symbols: 
                        Asserts: 
                      Profiling: 
             Optimization Level: 

Linking Options:
----------------
                      Libraries: 
  Statically Linked Executables: OFF
                        LDFLAGS: /machine:x64
                     H5_LDFLAGS: 
                     AM_LDFLAGS: 
                Extra libraries: 
                       Archiver: 
                         Ranlib: 

Languages:
----------
                              C: yes
                     C Compiler: C:/Program Files (x86)/Microsoft Visual Studio/2017/Community/VC/Tools/MSVC/14.16.27023/bin/Hostx86/x64/cl.exe 19.16.27027.1
                       CPPFLAGS: 
                    H5_CPPFLAGS: 
                    AM_CPPFLAGS: 
                         CFLAGS:  /DWIN32 /D_WINDOWS /W3
                      H5_CFLAGS: 
                      AM_CFLAGS: 
               Shared C Library: YES
               Static C Library: YES

                        Fortran: OFF
               Fortran Compiler:  
                  Fortran Flags: 
               H5 Fortran Flags: 
               AM Fortran Flags: 
         Shared Fortran Library: YES
         Static Fortran Library: YES

                            C++: ON
                   C++ Compiler: C:/Program Files (x86)/Microsoft Visual Studio/2017/Community/VC/Tools/MSVC/14.16.27023/bin/Hostx86/x64/cl.exe 19.16.27027.1
                      C++ Flags: /DWIN32 /D_WINDOWS /W3 /GR /EHsc
                   H5 C++ Flags: 
                   AM C++ Flags: 
             Shared C++ Library: YES
             Static C++ Library: YES

                            JAVA: OFF
                   JAVA Compiler:  

Features:
---------
                   Parallel HDF5: OFF
Parallel Filtered Dataset Writes: 
              Large Parallel I/O: 
              High-level library: ON
                    Threadsafety: OFF
             Default API mapping: v110
  With deprecated public symbols: ON
          I/O filters (external):  DEFLATE DECODE ENCODE
                             MPE: 
                      Direct VFD: 
                         dmalloc: 
  Packages w/ extra debug output: 
                     API Tracing: OFF
            Using memory checker: OFF
 Memory allocation sanity checks: OFF
          Function Stack Tracing: OFF
       Strict File Format Checks: OFF
    Optimization Instrumentation: 
Bye...

I tried conda install -c anaconda hdf5=1.10.6 and conda install -c anaconda hdf5=1.10.5 , in every case but none of that worked, I also reinstalled keras but didn't help.

Answer 1

The hdf installation at C:/Program Files/HDF5 is probably shadowing the conda installed version and is therefor causing issues. Try uninstalling it