Yet another “h5py is running against HDF5 1.10.5 when it was built against 1.10.4” error while trying to run OpenMMD

[Marietto2008]

Hello.

I'm trying to directly convert real-person videos to the motion of animation models (i.e. Miku, Anmicius) following the instructions located here :

https://github.com/peterljq/OpenMMD

and here :

https://www.youtube.com/watch?v=hKx6jl9a5-I

after having issued all the commands proposed,this is what happens :

C:\Users\marietto2020\Desktop\MMD\OpenMMD\OpenMMD 1.0\3d-pose-baseline-vmd (tensorflow) λ openposeto3d

´╗┐es (40 sloc) 1.62 KB "´╗┐es" is not recognized as an internal or external command or as a batch file. Please input the path of result from OpenPose Execution: JSON folder Input is limited to English characters and numbers. Ôûáthe path of result from OpenPose Execution (JSON folder): json

The max number of people in your video. If no input and press Enter, the number of be set to default: 1 person. The max number of people in your video: 1

If you want the detailed information of GIF, input yes. If no input and press Enter, the generation setting of GIF will be set to default. warn If you input warn, then no GIF will be generated. the detailed information[yes/no/warn]: yes C:\Users\marietto2020.conda\envs\tensorflow\lib\site-packages\h5py__init__.py:40: UserWarning: h5py is running against HDF5 1.10.5 when it was built against 1.10.4, 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 1.10.4, 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 14 2015 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 14.0/VC/bin/x86_amd64/cl.exe 19.0.24218.1
                   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 14.0/VC/bin/x86_amd64/cl.exe 19.0.24218.1
                  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...

and the process stops there. How to fix the warning / error ? thanks.

[kmuehlbauer]

@Marietto2008 If this is still an issue for you, please provide the complete output of conda list and conda info within the activated environment.

[romankht84]

Conda List:

Name Version Build Channel

_tflow_select 2.2.0 eigen absl-py 0.9.0 py37_0 astor 0.8.1 pypi_0 pypi attrs 19.3.0 py_0 backcall 0.1.0 py37_0 blas 1.0 mkl bleach 3.1.4 py_0 blinker 1.4 py37_0 boto 2.49.0 py37_0 boto3 1.9.66 py37_0 botocore 1.12.189 py_0 ca-certificates 2020.1.1 0 cachetools 3.1.1 py_0 certifi 2020.4.5.1 py37_0 cffi 1.14.0 py37h7a1dbc1_0 chardet 3.0.4 py37_1003 click 7.1.2 py_0 colorama 0.4.3 py_0 cryptography 2.9.2 py37h7a1dbc1_0 decorator 4.4.2 py_0 defusedxml 0.6.0 py_0 docutils 0.16 py37_0 entrypoints 0.3 py37_0 gast 0.2.2 pypi_0 pypi gensim 3.8.0 py37hf9181ef_0 google-api-core 1.17.0 py37h21ff451_0 google-auth 1.14.1 py_0 google-auth-oauthlib 0.4.1 py_2 google-cloud-core 1.3.0 py_0 google-cloud-storage 1.28.0 py_0 google-pasta 0.2.0 py_0 google-resumable-media 0.5.0 py_1 googleapis-common-protos 1.51.0 py37h21ff451_2 grpcio 1.28.1 pypi_0 pypi h5py 2.10.0 py37h5e291fa_0 hdf5 1.10.4 h7ebc959_0 icc_rt 2019.0.0 h0cc432a_1 idna 2.9 py_1 importlib-metadata 1.6.0 pypi_0 pypi importlib_metadata 1.5.0 py37_0 intel-openmp 2020.0 166 ipykernel 5.1.4 py37h39e3cac_0 ipython 7.13.0 py37h5ca1d4c_0 ipython_genutils 0.2.0 py37_0 jedi 0.17.0 py37_0 jinja2 2.11.2 py_0 jmespath 0.9.4 py_0 joblib 0.14.1 py_0 jsonschema 3.2.0 py37_0 jupyter_client 6.1.3 py_0 jupyter_core 4.6.3 py37_0 keras 2.3.1 0 keras-applications 1.0.8 py_0 keras-base 2.3.1 py37_0 keras-preprocessing 1.1.0 py_1 libprotobuf 3.11.4 h7bd577a_0 libsodium 1.0.16 h9d3ae62_0 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 markdown 3.2.2 pypi_0 pypi markupsafe 1.1.1 py37he774522_0 mistune 0.8.4 py37he774522_0 mkl 2020.0 166 mkl-service 2.3.0 py37hb782905_0 mkl_fft 1.0.15 py37h14836fe_0 mkl_random 1.1.0 py37h675688f_0 msys2-conda-epoch 20160418 1 nbconvert 5.6.1 py37_0 nbformat 5.0.6 py_0 nltk 3.4.5 py37_0 notebook 6.0.3 py37_0 numpy 1.18.4 pypi_0 pypi numpy-base 1.18.1 py37hc3f5095_1 oauthlib 3.1.0 py_0 openssl 1.1.1g he774522_0 opt-einsum 3.2.1 pypi_0 pypi opt_einsum 3.1.0 py_0 pandas 1.0.3 py37h47e9c7a_0 pandoc 2.2.3.2 0 pandocfilters 1.4.2 py37_1 parso 0.7.0 py_0 pickleshare 0.7.5 py37_0 pip 20.0.2 py37_3 prometheus_client 0.7.1 py_0 prompt-toolkit 3.0.4 py_0 prompt_toolkit 3.0.4 0 protobuf 3.11.3 pypi_0 pypi pyasn1 0.4.8 py_0 pyasn1-modules 0.2.7 py_0 pycparser 2.20 py_0 pygments 2.6.1 py_0 pyjwt 1.7.1 py37_0 pyopenssl 19.1.0 py37_0 pyreadline 2.1 py37_1 pyrsistent 0.16.0 py37he774522_0 pysocks 1.7.1 py37_0 python 3.7.7 h81c818b_4 python-dateutil 2.8.1 py_0 pytz 2020.1 py_0 pywin32 227 py37he774522_1 pywinpty 0.5.7 py37_0 pyyaml 5.3.1 py37he774522_0 pyzmq 18.1.1 py37ha925a31_0 requests 2.23.0 py37_0 requests-oauthlib 1.3.0 py_0 rsa 4.0 py_0 s3transfer 0.1.13 py37_0 scikit-learn 0.22.1 py37h6288b17_0 scipy 1.4.1 py37h9439919_0 send2trash 1.5.0 py37_0 setuptools 46.1.3 py37_0 six 1.14.0 py37_0 smart_open 2.0.0 py_0 sqlite 3.31.1 h2a8f88b_1 tensorboard 1.15.0 pypi_0 pypi tensorflow 1.15.0 pypi_0 pypi tensorflow-base 2.1.0 eigen_py37h49b2757_0 tensorflow-estimator 1.15.1 pypi_0 pypi tensorflow-hub 0.8.0 pypi_0 pypi termcolor 1.1.0 pypi_0 pypi terminado 0.8.3 py37_0 testpath 0.4.4 py_0 tornado 6.0.4 py37he774522_1 traitlets 4.3.3 py37_0 urllib3 1.25.8 py37_0 vc 14.1 h0510ff6_4 vs2015_runtime 14.16.27012 hf0eaf9b_1 wcwidth 0.1.9 py_0 webencodings 0.5.1 py37_1 werkzeug 1.0.1 pypi_0 pypi wheel 0.34.2 py37_0 win_inet_pton 1.1.0 py37_0 wincertstore 0.2 py37_0 winpty 0.4.3 4 wrapt 1.12.1 py37he774522_1 yaml 0.1.7 hc54c509_2 zeromq 4.3.1 h33f27b4_3 zipp 3.1.0 py_0 zlib 1.2.11 h62dcd97_4

---

---

Conda Info

active environment : tensorflowBEFOREh5pyCHANGES active env location : D:\Software\phd\AnacondaInstalled\envs\tensorflowBEFOREh5pyCHANGES shell level : 1 user config file : C:\Users\Muhammad Roman.condarc populated config files : C:\Users\Muhammad Roman.condarc conda version : 4.8.2 conda-build version : 3.18.11 python version : 3.7.6.final.0 virtual packages : __cuda=10.2 base environment : D:\Software\phd\AnacondaInstalled (writable) channel URLs : https://repo.anaconda.com/pkgs/main/win-64 https://repo.anaconda.com/pkgs/main/noarch https://repo.anaconda.com/pkgs/r/win-64 https://repo.anaconda.com/pkgs/r/noarch https://repo.anaconda.com/pkgs/msys2/win-64 https://repo.anaconda.com/pkgs/msys2/noarch package cache : D:\Software\phd\AnacondaInstalled\pkgs C:\Users\Muhammad Roman.conda\pkgs C:\Users\Muhammad Roman\AppData\Local\conda\conda\pkgs envs directories : D:\Software\phd\AnacondaInstalled\envs C:\Users\Muhammad Roman.conda\envs C:\Users\Muhammad Roman\AppData\Local\conda\conda\envs platform : win-64 user-agent : conda/4.8.2 requests/2.22.0 CPython/3.7.6 Windows/10 Windows/10.0.17134 administrator : False netrc file : None offline mode : False

Note: It works fine when I work with other notebooks. The problem occurs only when I try to access elmo model from an https url. I guess the built and run are on different versions. If I could only remove the warning and execute my code that would be sufficient for me. Please find my code below:

`import tensorflow as tf import tensorflow_hub as hub import pandas as pd from sklearn import preprocessing import keras import numpy as np

url = "https://tfhub.dev/google/elmo/2" embed = hub.Module(url)

data = pd.read_csv('Data/spam.csv', encoding='latin-1')

y = list(data['v1']) x = list(data['v2'])

le = preprocessing.LabelEncoder() le.fit(y)

def encode(le, labels): enc = le.transform(labels) return keras.utils.to_categorical(enc)

def decode(le, one_hot): dec = np.argmax(one_hot, axis=1) return le.inverse_transform(dec)

test = encode(le, ['ham', 'spam', 'ham', 'ham'])

untest = decode(le, test)

x_enc = x y_enc = encode(le, y)

x_train = np.asarray(x_enc[:50]) y_train = np.asarray(y_enc[:50])

x_test = np.asarray(x_enc[50:]) y_test = np.asarray(y_enc[50:])

from keras.layers import Input, Lambda, Dense from keras.models import Model import keras.backend as K

def ELMoEmbedding(x): return embed(tf.squeeze(tf.cast(x, tf.string)), signature="default", as_dict=True)["default"]

input_text = Input(shape=(1,), dtype=tf.string) embedding = Lambda(ELMoEmbedding, output_shape=(1024, ))(input_text)

print(embedding)`

Sometimes I get the error, other times the kernel dies.

[jakirkham]

@romankht84 , is it possible to reproduce this with h5py alone?

[romankht84]

@romankht84 , is it possible to reproduce this with h5py alone?

in simple words? :)

[jakirkham]

Do you have an example only using h5py?

[shoujomami]

Hello i have that issu too , how do i reduce back h5py 1.10.4 from 1.10.5?

[rahulbhadja]

i have same issue please help me

[scopatz]

How are you installing openmmd?

[rahulbhadja]

after switching windows to ubantu my issue resolved

[27shree23]

please help