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deepfakes / faceswap

Deepfakes Software For All
https://www.faceswap.dev
GNU General Public License v3.0
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All the configurations are successful, but the training will make this error. I guess it is the version of the library but I did install it. #692

Closed l1uw3n closed 5 years ago

l1uw3n commented 5 years ago

04/04/2019 08:51:24 MainProcess training_0 _base name DEBUG model name: 'original' 04/04/2019 08:51:24 MainProcess training_0 _base rename_legacy DEBUG No legacy files to rename 04/04/2019 08:51:24 MainProcess training_0 _base load_state_info DEBUG Loading Input Shape from State file 04/04/2019 08:51:24 MainProcess training_0 _base load_state_info DEBUG Setting input shape from state file: (64, 64, 3) 04/04/2019 08:51:24 MainProcess training_0 original add_networks DEBUG Adding networks 04/04/2019 08:51:24 MainProcess training_0 nn_blocks upscale DEBUG inp: Tensor("input_1:0", shape=(?, 8, 8, 512), dtype=float32), filters: 256, kernel_size: 3, use_instance_norm: False, kwargs: {}) 04/04/2019 08:51:24 MainProcess training_0 nn_blocks upscale DEBUG inp: Tensor("pixel_shuffler_1/Reshape_1:0", shape=(?, 16, 16, 256), dtype=float32), filters: 128, kernel_size: 3, use_instance_norm: False, kwargs: {}) 04/04/2019 08:51:24 MainProcess training_0 nn_blocks upscale DEBUG inp: Tensor("pixel_shuffler_2/Reshape_1:0", shape=(?, 32, 32, 128), dtype=float32), filters: 64, kernel_size: 3, use_instance_norm: False, kwargs: {}) 04/04/2019 08:51:24 MainProcess training_0 _base add_network DEBUG network_type: 'decoder', side: 'a', network: '<keras.engine.training.Model object at 0x7f7ba259f710>' 04/04/2019 08:51:24 MainProcess training_0 _base name DEBUG model name: 'original' 04/04/2019 08:51:24 MainProcess training_0 _base add_network DEBUG name: 'decoder_a', filename: 'original_decoder_A.h5' 04/04/2019 08:51:24 MainProcess training_0 _base init DEBUG Initializing NNMeta: (filename: '/home/lw/workspace/faceswap/workspace/model/original_decoder_A.h5', network_type: 'decoder', side: 'a', network: <keras.engine.training.Model object at 0x7f7ba259f710> 04/04/2019 08:51:27 MainProcess training_0 _base init DEBUG Initialized NNMeta 04/04/2019 08:51:27 MainProcess training_0 nn_blocks upscale DEBUG inp: Tensor("input_2:0", shape=(?, 8, 8, 512), dtype=float32), filters: 256, kernel_size: 3, use_instance_norm: False, kwargs: {}) 04/04/2019 08:51:27 MainProcess training_0 nn_blocks upscale DEBUG inp: Tensor("pixel_shuffler_4/Reshape_1:0", shape=(?, 16, 16, 256), dtype=float32), filters: 128, kernel_size: 3, use_instance_norm: False, kwargs: {}) 04/04/2019 08:51:27 MainProcess training_0 nn_blocks upscale DEBUG inp: Tensor("pixel_shuffler_5/Reshape_1:0", shape=(?, 32, 32, 128), dtype=float32), filters: 64, kernel_size: 3, use_instance_norm: False, kwargs: {}) 04/04/2019 08:51:27 MainProcess training_0 _base add_network DEBUG network_type: 'decoder', side: 'b', network: '<keras.engine.training.Model object at 0x7f7ba0536ef0>' 04/04/2019 08:51:27 MainProcess training_0 _base name DEBUG model name: 'original' 04/04/2019 08:51:27 MainProcess training_0 _base add_network DEBUG name: 'decoder_b', filename: 'original_decoder_B.h5' 04/04/2019 08:51:27 MainProcess training_0 _base init DEBUG Initializing NNMeta: (filename: '/home/lw/workspace/faceswap/workspace/model/original_decoder_B.h5', network_type: 'decoder', side: 'b', network: <keras.engine.training.Model object at 0x7f7ba0536ef0> 04/04/2019 08:51:27 MainProcess training_0 _base init DEBUG Initialized NNMeta 04/04/2019 08:51:27 MainProcess training_0 nn_blocks conv DEBUG inp: Tensor("input_3:0", shape=(?, 64, 64, 3), dtype=float32), filters: 128, kernel_size: 5, strides: 2, use_instance_norm: False, kwargs: {}) 04/04/2019 08:51:27 MainProcess training_0 nn_blocks conv DEBUG inp: Tensor("leaky_re_lu_7/LeakyRelu:0", shape=(?, 32, 32, 128), dtype=float32), filters: 256, kernel_size: 5, strides: 2, use_instance_norm: False, kwargs: {}) 04/04/2019 08:51:27 MainProcess training_0 nn_blocks conv DEBUG inp: Tensor("leaky_re_lu_8/LeakyRelu:0", shape=(?, 16, 16, 256), dtype=float32), filters: 512, kernel_size: 5, strides: 2, use_instance_norm: False, kwargs: {}) 04/04/2019 08:51:27 MainProcess training_0 nn_blocks conv DEBUG inp: Tensor("leaky_re_lu_9/LeakyRelu:0", shape=(?, 8, 8, 512), dtype=float32), filters: 1024, kernel_size: 5, strides: 2, use_instance_norm: False, kwargs: {}) 04/04/2019 08:51:27 MainProcess training_0 nn_blocks upscale DEBUG inp: Tensor("reshape_1/Reshape:0", shape=(?, 4, 4, 1024), dtype=float32), filters: 512, kernel_size: 3, use_instance_norm: False, kwargs: {}) 04/04/2019 08:51:27 MainProcess training_0 _base add_network DEBUG network_type: 'encoder', side: 'None', network: '<keras.engine.training.Model object at 0x7f7ba0426b38>' 04/04/2019 08:51:27 MainProcess training_0 _base name DEBUG model name: 'original' 04/04/2019 08:51:27 MainProcess training_0 _base add_network DEBUG name: 'encoder', filename: 'original_encoder.h5' 04/04/2019 08:51:27 MainProcess training_0 _base init DEBUG Initializing NNMeta: (filename: '/home/lw/workspace/faceswap/workspace/model/original_encoder.h5', network_type: 'encoder', side: 'None', network: <keras.engine.training.Model object at 0x7f7ba0426b38> 04/04/2019 08:51:27 MainProcess training_0 _base init DEBUG Initialized NNMeta 04/04/2019 08:51:27 MainProcess training_0 original add_networks DEBUG Added networks 04/04/2019 08:51:27 MainProcess training_0 _base load_models DEBUG Load model: (swapped: False) 04/04/2019 08:51:27 MainProcess training_0 _base models_exist DEBUG Pre-existing models exist: True 04/04/2019 08:51:27 MainProcess training_0 _base models_exist DEBUG Pre-existing models exist: True 04/04/2019 08:51:27 MainProcess training_0 _base map_models DEBUG Map models: (swapped: False) 04/04/2019 08:51:27 MainProcess training_0 _base map_models DEBUG Mapped models: (models_map: {'a': {'decoder': '/home/lw/workspace/faceswap/workspace/model/original_decoder_A.h5'}, 'b': {'decoder': '/home/lw/workspace/faceswap/workspace/model/original_decoder_B.h5'}}) 04/04/2019 08:51:27 MainProcess training_0 _base load DEBUG Loading model: '/home/lw/workspace/faceswap/workspace/model/original_decoder_A.h5' 04/04/2019 08:51:27 MainProcess training_0 _base load WARNING Failed loading existing training data. Generating new models 04/04/2019 08:51:27 MainProcess training_0 _base load DEBUG Exception: Unable to create group (no write intent on file) 04/04/2019 08:51:27 MainProcess training_0 original build_autoencoders DEBUG Initializing model 04/04/2019 08:51:27 MainProcess training_0 original build_autoencoders DEBUG Adding Autoencoder. Side: a 04/04/2019 08:51:27 MainProcess training_0 multithreading run DEBUG Error in thread (training_0): Tensor("conv2d_9/kernel:0", shape=(5, 5, 3, 128), dtype=float32_ref) must be from the same graph as Tensor("face:0", shape=(?, 64, 64, 3), dtype=float32). 04/04/2019 08:51:27 MainProcess MainThread train monitor_console DEBUG Thread error detected 04/04/2019 08:51:27 MainProcess MainThread train monitor_console DEBUG Closed Console Monitor 04/04/2019 08:51:27 MainProcess MainThread train end_thread DEBUG Ending Training thread 04/04/2019 08:51:27 MainProcess MainThread train end_thread CRITICAL Error caught! Exiting... 04/04/2019 08:51:27 MainProcess MainThread multithreading join DEBUG Joining Threads: 'training' 04/04/2019 08:51:27 MainProcess MainThread multithreading join DEBUG Joining Thread: 'training_0' 04/04/2019 08:51:27 MainProcess MainThread multithreading join ERROR Caught exception in thread: 'training_0' Traceback (most recent call last): File "/home/lw/workspace/faceswap/lib/cli.py", line 107, in execute_script process.process() File "/home/lw/workspace/faceswap/scripts/train.py", line 101, in process self.end_thread(thread, err) File "/home/lw/workspace/faceswap/scripts/train.py", line 126, in end_thread thread.join() File "/home/lw/workspace/faceswap/lib/multithreading.py", line 443, in join raise thread.err[1].with_traceback(thread.err[2]) File "/home/lw/workspace/faceswap/lib/multithreading.py", line 381, in run self._target(*self._args, *self._kwargs) File "/home/lw/workspace/faceswap/scripts/train.py", line 152, in training raise err File "/home/lw/workspace/faceswap/scripts/train.py", line 140, in training model = self.load_model() File "/home/lw/workspace/faceswap/scripts/train.py", line 169, in load_model predict=False) File "/home/lw/workspace/faceswap/plugins/train/model/original.py", line 24, in init super().init(args, kwargs) File "/home/lw/workspace/faceswap/plugins/train/model/_base.py", line 85, in init self.build() File "/home/lw/workspace/faceswap/plugins/train/model/_base.py", line 148, in build self.build_autoencoders() File "/home/lw/workspace/faceswap/plugins/train/model/original.py", line 46, in build_autoencoders output = decoder(self.networks["encoder"].network(inputs[0])) File "/home/lw/anaconda3/lib/python3.6/site-packages/keras/engine/base_layer.py", line 457, in call output = self.call(inputs, kwargs) File "/home/lw/anaconda3/lib/python3.6/site-packages/keras/engine/network.py", line 564, in call outputtensors, , _ = self.run_internal_graph(inputs, masks) File "/home/lw/anaconda3/lib/python3.6/site-packages/keras/engine/network.py", line 721, in run_internal_graph layer.call(computed_tensor, **kwargs)) File "/home/lw/anaconda3/lib/python3.6/site-packages/keras/layers/convolutional.py", line 171, in call dilation_rate=self.dilation_rate) File "/home/lw/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py", line 3650, in conv2d data_format=tf_data_format) File "/home/lw/anaconda3/lib/python3.6/site-packages/tensorflow/python/ops/nn_ops.py", line 767, in convolution with ops.name_scope(name, "convolution", [input, filter]) as name: File "/home/lw/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 6023, in enter g = _get_graph_from_inputs(self._values) File "/home/lw/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 5664, in _get_graph_from_inputs _assert_same_graph(original_graph_element, graph_element) File "/home/lw/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 5600, in _assert_same_graph original_item)) ValueError: Tensor("conv2d_9/kernel:0", shape=(5, 5, 3, 128), dtype=float32_ref) must be from the same graph as Tensor("face:0", shape=(?, 64, 64, 3), dtype=float32).

============ System Information ============ encoding: UTF-8 git_branch: Not Found git_commits: Not Found gpu_cuda: 9.1 gpu_cudnn: Not Found. Check Conda packages for Conda cuDNN gpu_devices: GPU_0: GeForce GTX 1080 Ti, GPU_1: GeForce GTX 1080 Ti gpu_driver: 390.48 gpu_vram: GPU_0: 11178MB, GPU_1: 11178MB os_machine: x86_64 os_platform: Linux-3.10.0-862.14.4.el7.x86_64-x86_64-with-centos-7.6.1810-Core os_release: 3.10.0-862.14.4.el7.x86_64 py_command: faceswap.py train -A workspace/data_src -B workspace/data_dst -m workspace/model/ py_conda_version: conda 4.6.8 py_implementation: CPython py_version: 3.6.2 py_virtual_env: False sys_cores: 8 sys_processor: x86_64 sys_ram: Total: 64197MB, Available: 56213MB, Used: 6920MB, Free: 20615MB

=============== Pip Packages =============== absl-py==0.7.1 alabaster==0.7.10 anaconda-client==1.6.5 anaconda-navigator==1.6.8 anaconda-project==0.8.0 asn1crypto==0.22.0 astor==0.7.1 astroid==1.5.3 astropy==2.0.2 Babel==2.5.0 backports.shutil-get-terminal-size==1.0.0 backports.weakref==1.0rc1 beautifulsoup4==4.6.0 bitarray==0.8.1 bkcharts==0.2 blaze==0.11.3 bleach==1.5.0 bokeh==0.12.7 boto==2.48.0 Bottleneck==1.2.1 certifi==2017.7.27.1 cffi==1.10.0 chardet==3.0.4 click==6.7 cloudpickle==0.4.0 clyent==1.2.2 cmake==3.13.3 colorama==0.3.9 conda==4.6.8 conda-build==3.0.23 conda-verify==2.0.0 contextlib2==0.5.5 cryptography==2.0.3 cycler==0.10.0 Cython==0.26.1 cytoolz==0.8.2 dask==0.15.2 datashape==0.5.4 decorator==4.4.0 distributed==1.18.3 dlib==19.17.0 docutils==0.14 easydict==1.9 entrypoints==0.2.3 et-xmlfile==1.0.1 face-recognition==1.2.3 face-recognition-models==0.3.0 fastcache==1.0.2 ffmpy==0.2.2 filelock==2.0.12 Flask==0.12.2 Flask-Cors==3.0.3 gast==0.2.2 gevent==1.2.2 glob2==0.5 glog==0.3.1 gmpy2==2.0.8 greenlet==0.4.12 grpcio==1.19.0 h5py==2.9.0 heapdict==1.0.0 html5lib==0.9999999 idna==2.6 imageio==2.2.0 imagesize==0.7.1 ipykernel==4.6.1 ipython==6.1.0 ipython-genutils==0.2.0 ipywidgets==7.0.0 isort==4.2.15 itsdangerous==0.24 jdcal==1.3 jedi==0.10.2 Jinja2==2.9.6 jsonschema==2.6.0 jupyter-client==5.1.0 jupyter-console==5.2.0 jupyter-core==4.3.0 jupyterlab==0.27.0 jupyterlab-launcher==0.4.0 Keras==2.2.4 Keras-Applications==1.0.7 Keras-Preprocessing==1.0.9 kiwisolver==1.0.1 lazy-object-proxy==1.3.1 llvmlite==0.20.0 locket==0.2.0 lxml==3.8.0 Markdown==3.1 MarkupSafe==1.0 matplotlib==2.2.2 mccabe==0.6.1 mistune==0.7.4 mkl-fft==1.0.11 mkl-random==1.0.2 mock==2.0.0 mpmath==0.19 msgpack-python==0.4.8 multipledispatch==0.4.9 navigator-updater==0.1.0 nbconvert==5.3.1 nbformat==4.4.0 networkx==2.2 nltk==3.2.4 nose==1.3.7 notebook==5.0.0 numba==0.35.0+10.g143f70e90 numexpr==2.6.2 numpy==1.15.4 numpydoc==0.7.0 nvidia-ml-py==375.53.1 nvidia-ml-py3==7.352.0 odo==0.5.1 olefile==0.44 opencv-python==4.0.0.21 openpyxl==2.4.8 packaging==16.8 pandas==0.20.3 pandocfilters==1.4.2 partd==0.3.8 path.py==10.3.1 pathlib==1.0.1 pathlib2==2.3.0 patsy==0.4.1 pbr==5.1.3 pep8==1.7.0 pexpect==4.2.1 pickleshare==0.7.4 Pillow==6.0.0 pkginfo==1.4.1 ply==3.10 prompt-toolkit==1.0.15 protobuf==3.7.0 psutil==5.6.1 ptyprocess==0.5.2 py==1.4.34 pycodestyle==2.3.1 pycosat==0.6.3 pycparser==2.18 pycrypto==2.6.1 pycurl==7.43.0 pyflakes==1.5.0 Pygments==2.2.0 pylint==1.7.2 pyodbc==4.0.17 pyOpenSSL==17.2.0 pyparsing==2.2.0 PySocks==1.6.7 pytest==3.2.1 python-dateutil==2.6.1 python-gflags==3.1.2 pytz==2017.2 PyWavelets==0.5.2 PyYAML==3.12 pyzmq==16.0.2 Qt==0.2.1 QtAwesome==0.4.4 qtconsole==4.3.1 QtPy==1.3.1 redis==3.2.1 requests==2.18.4 rope==0.10.5 ruamel-yaml==0.11.14 scikit-image==0.15.0 scikit-learn==0.20.3 scipy==0.19.1 seaborn==0.8 simplegeneric==0.8.1 singledispatch==3.4.0.3 six==1.10.0 snowballstemmer==1.2.1 sortedcollections==0.5.3 sortedcontainers==1.5.7 Sphinx==1.6.3 sphinxcontrib-websupport==1.0.1 spyder==3.2.3 SQLAlchemy==1.1.13 statsmodels==0.8.0 sympy==1.1.1 tables==3.4.2 tblib==1.3.2 tensorboard==1.12.2 tensorflow-estimator==1.13.0 tensorflow-gpu==1.12.0 tensorflow-tensorboard==0.1.8 termcolor==1.1.0 terminado==0.6 testpath==0.3.1 toolz==0.8.2 toposort==1.5 tornado==4.5.2 tqdm==4.31.1 traitlets==4.3.2 typing==3.6.2 unicodecsv==0.14.1 urllib3==1.22 wcwidth==0.1.7 webencodings==0.5.1 Werkzeug==0.12.2 widgetsnbextension==3.0.2 wrapt==1.10.11 xlrd==1.1.0 XlsxWriter==0.9.8 xlwt==1.3.0 zict==0.1.2

============== Conda Packages ==============

packages in environment at /home/lw/anaconda3:

#

Name Version Build Channel

_ipyw_jlab_nb_ext_conf 0.1.0 py36he11e457_0 defaults absl-py 0.7.1 pypi_0 pypi alabaster 0.7.10 py36h306e16b_0 defaults anaconda 5.0.0.1 py36hfb0b618_1 defaults anaconda-client 1.6.5 py36h19c0dcd_0 defaults anaconda-navigator 1.6.8 py36h672ccc7_0 defaults anaconda-project 0.8.0 py36h29abdf5_0 defaults asn1crypto 0.22.0 py36h265ca7c_1 defaults astor 0.7.1 pypi_0 pypi astroid 1.5.3 py36hbdb9df2_0 defaults astropy 2.0.2 py36ha51211e_4 defaults babel 2.5.0 py36h7d14adf_0 defaults backports 1.0 py36hfa02d7e_1 defaults backports-weakref 1.0rc1 pypi_0 pypi backports.shutil_get_terminal_size 1.0.0 py36hfea85ff_2 defaults beautifulsoup4 4.6.0 py36h49b8c8c_1 defaults bitarray 0.8.1 py36h5834eb8_0 defaults bkcharts 0.2 py36h735825a_0 defaults blas 1.0 mkl https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main blaze 0.11.3 py36h4e06776_0 defaults bleach 1.5.0 pypi_0 pypi bokeh 0.12.7 py36h169c5fd_1 defaults boto 2.48.0 py36h6e4cd66_1 defaults bottleneck 1.2.1 py36haac1ea0_0 defaults ca-certificates 2017.08.26 h1d4fec5_0 defaults cairo 1.14.10 h58b644b_4 defaults certifi 2017.7.27.1 py36h8b7b77e_0 defaults cffi 1.10.0 py36had8d393_1 defaults chardet 3.0.4 py36h0f667ec_1 defaults click 6.7 py36h5253387_0 defaults cloudpickle 0.4.0 py36h30f8c20_0 defaults clyent 1.2.2 py36h7e57e65_1 defaults cmake 3.13.3 pypi_0 pypi colorama 0.3.9 py36h489cec4_0 defaults conda 4.6.8 py36_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main conda-build 3.0.23 py36h1da9bb0_0 defaults conda-env 2.6.0 1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main conda-verify 2.0.0 py36h98955d8_0 defaults contextlib2 0.5.5 py36h6c84a62_0 defaults cryptography 2.0.3 py36ha225213_1 defaults curl 7.55.1 hcb0b314_2 defaults cycler 0.10.0 py36h93f1223_0 defaults cython 0.26.1 py36h21c49d0_0 defaults cytoolz 0.8.2 py36h708bfd4_0 defaults dask 0.15.2 py36h9b48dc4_0 defaults dask-core 0.15.2 py36h0f988a8_0 defaults datashape 0.5.4 py36h3ad6b5c_0 defaults dbus 1.10.22 h3b5a359_0 defaults decorator 4.4.0 pypi_0 pypi distributed 1.18.3 py36h73cd4ae_0 defaults dlib 19.17.0 pypi_0 pypi docutils 0.14 py36hb0f60f5_0 defaults easydict 1.9 pypi_0 pypi entrypoints 0.2.3 py36h1aec115_2 defaults et_xmlfile 1.0.1 py36hd6bccc3_0 defaults expat 2.2.4 hc00ebd1_1 defaults face-recognition 1.2.3 pypi_0 pypi face-recognition-models 0.3.0 pypi_0 pypi fastcache 1.0.2 py36h5b0c431_0 defaults ffmpy 0.2.2 pypi_0 pypi filelock 2.0.12 py36hacfa1f5_0 defaults flask 0.12.2 py36hb24657c_0 defaults flask-cors 3.0.3 py36h2d857d3_0 defaults fontconfig 2.12.4 h88586e7_1 defaults freetype 2.8 h52ed37b_0 defaults gast 0.2.2 pypi_0 pypi get_terminal_size 1.0.0 haa9412d_0 defaults gevent 1.2.2 py36h2fe25dc_0 defaults glib 2.53.6 hc861d11_1 defaults glob2 0.5 py36h2c1b292_1 defaults glog 0.3.1 pypi_0 pypi gmp 6.1.2 hb3b607b_0 defaults gmpy2 2.0.8 py36h55090d7_1 defaults graphite2 1.3.10 hc526e54_0 defaults greenlet 0.4.12 py36h2d503a6_0 defaults grpcio 1.19.0 pypi_0 pypi gst-plugins-base 1.12.2 he3457e5_0 defaults gstreamer 1.12.2 h4f93127_0 defaults h5py 2.9.0 pypi_0 pypi harfbuzz 1.5.0 h2545bd6_0 defaults hdf5 1.10.1 hb0523eb_0 defaults heapdict 1.0.0 py36h79797d7_0 defaults html5lib 0.9999999 pypi_0 pypi icu 58.2 h211956c_0 defaults idna 2.6 py36h82fb2a8_1 defaults imageio 2.2.0 py36he555465_0 defaults imagesize 0.7.1 py36h52d8127_0 defaults intel-openmp 2018.0.0 h15fc484_7 defaults ipykernel 4.6.1 py36hbf841aa_0 defaults ipython 6.1.0 py36hc72a948_1 defaults ipython_genutils 0.2.0 py36hb52b0d5_0 defaults ipywidgets 7.0.0 py36h7b55c3a_0 defaults isort 4.2.15 py36had401c0_0 defaults itsdangerous 0.24 py36h93cc618_1 defaults jbig 2.1 hdba287a_0 defaults jdcal 1.3 py36h4c697fb_0 defaults jedi 0.10.2 py36h552def0_0 defaults jinja2 2.9.6 py36h489bce4_1 defaults jpeg 9b habf39ab_1 defaults jsonschema 2.6.0 py36h006f8b5_0 defaults jupyter 1.0.0 py36h9896ce5_0 defaults jupyter_client 5.1.0 py36h614e9ea_0 defaults jupyter_console 5.2.0 py36he59e554_1 defaults jupyter_core 4.3.0 py36h357a921_0 defaults jupyterlab 0.27.0 py36h86377d0_2 defaults jupyterlab_launcher 0.4.0 py36h4d8058d_0 defaults keras 2.2.4 pypi_0 pypi keras-applications 1.0.7 pypi_0 pypi keras-preprocessing 1.0.9 pypi_0 pypi kiwisolver 1.0.1 pypi_0 pypi lazy-object-proxy 1.3.1 py36h10fcdad_0 defaults libedit 3.1 heed3624_0 defaults libffi 3.2.1 h4deb6c0_3 defaults libgcc-ng 8.2.0 hdf63c60_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main libgfortran-ng 7.2.0 h6fcbd8e_1 defaults libpng 1.6.32 hda9c8bc_2 defaults libsodium 1.0.13 h31c71d8_2 defaults libssh2 1.8.0 h8c220ad_2 defaults libstdcxx-ng 7.2.0 h24385c6_1 defaults libtiff 4.0.8 h90200ff_9 defaults libtool 2.4.6 hd50d1a6_0 defaults libxcb 1.12 he6ee5dd_2 defaults libxml2 2.9.4 h6b072ca_5 defaults libxslt 1.1.29 hcf9102b_5 defaults llvmlite 0.20.0 py36_0 defaults locket 0.2.0 py36h787c0ad_1 defaults lxml 3.8.0 py36h6c6e760_0 defaults lzo 2.10 hc0eb8fc_0 defaults markdown 3.1 pypi_0 pypi markupsafe 1.0 py36hd9260cd_1 defaults matplotlib 2.2.2 pypi_0 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torzdf commented 5 years ago

py_virtual_env: False My advice is to install into a virtual environment. You have a lot of packages installed, and troubleshooting potential conflicts would not be a great use of time.