我使用TensorFlow创建了一个CNN，以便在大学集群中使用它。 CNN在Mac上运行TensorFlow 1.10的Anaconda env可以在Mac上正常工作，这里是我在工作环境中使用的所有软件包：
name: CNN_env
channels:
- conda-forge
- defaults
dependencies:
- _ipyw_jlab_nb_ext_conf=0.1.0=py36h2fc01ae_0
- absl-py=0.7.0=py36_0
- alabaster=0.7.12=py36_0
- anaconda=custom=py36ha4fed55_0
- anaconda-client=1.6.14=py36_0
- anaconda-navigator=1.9.6=py36_0
- anaconda-project=0.8.2=py36h9ee5d53_0
- appnope=0.1.0=py36hf537a9a_0
- appscript=1.0.1=py36h9e71e49_1
- asn1crypto=0.24.0=py36_0
- astor=0.7.1=py_0
- astroid=1.6.3=py36_0
- astropy=3.0.2=py36h917ab60_1
- attrs=18.1.0=py36_0
- autopep8=1.4.3=py36_0
- babel=2.5.3=py36_0
- backcall=0.1.0=py36_0
- backports=1.0=py36ha3c1827_1
- backports.shutil_get_terminal_size=1.0.0=py36hd7a2ee4_2
- beautifulsoup4=4.6.0=py36h72d3c9f_1
- bitarray=0.8.1=py36h1de35cc_1
- bkcharts=0.2=py36h073222e_0
- blas=1.0=mkl
- blaze=0.11.3=py36h02e7a37_0
- bleach=2.1.3=py36_0
- blosc=1.14.3=hd9629dc_0
- bokeh=0.12.16=py36_0
- boto=2.48.0=py36hdbc59ac_1
- bottleneck=1.2.1=py36hbd380ad_0
- bzip2=1.0.6=h1de35cc_5
- c-ares=1.14.0=h470a237_0
- ca-certificates=2019.1.23=0
- certifi=2019.3.9=py36_0
- cffi=1.11.5=py36h342bebf_0
- chardet=3.0.4=py36h96c241c_1
- click=6.7=py36hec950be_0
- cloudpickle=0.5.3=py36_0
- clyent=1.2.2=py36hae3ad88_0
- colorama=0.3.9=py36hd29a30c_0
- conda=4.6.8=py36_0
- conda-build=3.10.5=py36_0
- conda-env=2.6.0=h36134e3_0
- conda-verify=2.0.0=py36he837df3_0
- contextlib2=0.5.5=py36hd66e5e7_0
- cryptography=2.6.1=py36ha12b0ac_0
- curl=7.64.0=ha441bb4_2
- cycler=0.10.0=py36hfc81398_0
- cython=0.28.2=py36h1de35cc_0
- cytoolz=0.9.0.1=py36h1de35cc_0
- dask=0.17.5=py36_0
- dask-core=0.17.5=py36_0
- datashape=0.5.4=py36hfb22df8_0
- dbus=1.13.2=h760590f_1
- decorator=4.3.0=py36_0
- distributed=1.21.8=py36_0
- docutils=0.14=py36hbfde631_0
- entrypoints=0.2.3=py36hd81d71f_2
- et_xmlfile=1.0.1=py36h1315bdc_0
- expat=2.2.5=hb8e80ba_0
- fastcache=1.0.2=py36h1de35cc_2
- filelock=3.0.4=py36_0
- flask=1.0.2=py36_1
- flask-cors=3.0.4=py36_0
- freetype=2.8=h12048fb_1
- gast=0.2.0=py_0
- get_terminal_size=1.0.0=h7520d66_0
- gettext=0.19.8.1=h15daf44_3
- gevent=1.3.0=py36h1de35cc_0
- glib=2.56.1=h35bc53a_0
- glob2=0.6=py36h94c9186_0
- gmp=6.1.2=hb37e062_1
- gmpy2=2.0.8=py36hf9c35bd_2
- greenlet=0.4.13=py36h1de35cc_0
- grpcio=1.12.1=py36hd9629dc_0
- h5py=2.7.1=py36ha8ecd60_2
- hdf5=1.10.2=hfa1e0ec_1
- heapdict=1.0.0=py36_2
- html5lib=1.0.1=py36h2f9c1c0_0
- icu=58.2=h4b95b61_1
- idna=2.6=py36h8628d0a_1
- imageio=2.3.0=py36_0
- imagesize=1.0.0=py36_0
- intel-openmp=2018.0.0=8
- ipykernel=4.8.2=py36_0
- ipython=6.4.0=py36_0
- ipython_genutils=0.2.0=py36h241746c_0
- ipywidgets=7.2.1=py36_0
- isort=4.3.4=py36_0
- itsdangerous=0.24=py36h49fbb8d_1
- jbig=2.1=h4d881f8_0
- jdcal=1.4=py36_0
- jedi=0.12.0=py36_1
- jinja2=2.10=py36hd36f9c5_0
- jpeg=9b=he5867d9_2
- jsonschema=2.6.0=py36hb385e00_0
- jupyter=1.0.0=py36_4
- jupyter_client=5.2.3=py36_0
- jupyter_console=5.2.0=py36hccf5b1c_1
- jupyter_core=4.4.0=py36h79cf704_0
- jupyterlab=0.32.1=py36_0
- jupyterlab_launcher=0.10.5=py36_0
- kiwisolver=1.0.1=py36h792292d_0
- krb5=1.16.1=hddcf347_7
- lazy-object-proxy=1.3.1=py36h2fbbe47_0
- libcurl=7.64.0=h051b688_2
- libcxx=4.0.1=h579ed51_0
- libcxxabi=4.0.1=hebd6815_0
- libedit=3.1.20170329=hb402a30_2
- libffi=3.2.1=h475c297_4
- libgfortran=3.0.1=h93005f0_2
- libiconv=1.15=hdd342a3_7
- libpng=1.6.34=he12f830_0
- libprotobuf=3.6.0=hd28b015_0
- libsodium=1.0.16=h3efe00b_0
- libssh2=1.8.0=ha12b0ac_4
- libtiff=4.0.9=hcb84e12_1
- libxml2=2.9.8=hab757c2_1
- libxslt=1.1.32=hb819dd2_0
- llvmlite=0.23.1=py36hc454e04_0
- locket=0.2.0=py36hca03003_1
- lxml=4.2.1=py36h7166777_0
- lzo=2.10=h362108e_2
- markdown=2.6.11=py_0
- markupsafe=1.0=py36h3a1e703_1
- matplotlib=2.2.2=py36ha7267d0_0
- mccabe=0.6.1=py36hdaeb55d_0
- mistune=0.8.3=py36h1de35cc_1
- mkl=2018.0.2=1
- mkl-service=1.1.2=py36h7ea6df4_4
- mkl_fft=1.0.1=py36h917ab60_0
- mkl_random=1.0.1=py36h78cc56f_0
- more-itertools=4.1.0=py36_0
- mpc=1.0.3=h7a72875_5
- mpfr=3.1.5=h711e7fd_2
- mpmath=1.0.0=py36hf1b8295_2
- msgpack-python=0.5.6=py36h04f5b5a_0
- multipledispatch=0.5.0=py36_0
- navigator-updater=0.2.1=py36_0
- nbconvert=5.3.1=py36h810822e_0
- nbformat=4.4.0=py36h827af21_0
- ncurses=6.1=h0a44026_0
- networkx=2.1=py36_0
- nltk=3.3.0=py36_0
- nose=1.3.7=py36h73fae2b_2
- notebook=5.5.0=py36_0
- numba=0.38.0=py36h1702cab_0
- numexpr=2.6.5=py36h057f876_0
- numpy=1.14.3=py36h9bb19eb_1
- numpy-base=1.14.3=py36h479e554_1
- numpydoc=0.8.0=py36_0
- odo=0.5.1=py36hc1af34a_0
- olefile=0.45.1=py36_0
- openpyxl=2.5.3=py36_0
- openssl=1.1.1b=h1de35cc_1
- packaging=17.1=py36_0
- pandas=0.23.0=py36h1702cab_0
- pandoc=1.19.2.1=ha5e8f32_1
- pandocfilters=1.4.2=py36h3b0b094_1
- parso=0.2.0=py36_0
- partd=0.3.8=py36hf5c4cb8_0
- path.py=11.0.1=py36_0
- pathlib2=2.3.2=py36_0
- patsy=0.5.0=py36_0
- pcre=8.42=h378b8a2_0
- pep8=1.7.1=py36_0
- pexpect=4.5.0=py36_0
- pickleshare=0.7.4=py36hf512f8e_0
- pillow=5.1.0=py36hfcce615_0
- pkginfo=1.4.2=py36_1
- pluggy=0.6.0=py36hb1d0581_0
- ply=3.11=py36_0
- prompt_toolkit=1.0.15=py36haeda067_0
- protobuf=3.6.0=py36hfc679d8_0
- psutil=5.4.5=py36h1de35cc_0
- ptyprocess=0.5.2=py36he6521c3_0
- py=1.5.3=py36_0
- pycodestyle=2.4.0=py36_0
- pycosat=0.6.3=py36hee92d8f_0
- pycparser=2.18=py36h724b2fc_1
- pycrypto=2.6.1=py36h1de35cc_8
- pycurl=7.43.0.2=py36ha12b0ac_0
- pyflakes=1.6.0=py36hea45e83_0
- pygments=2.2.0=py36h240cd3f_0
- pylint=1.8.4=py36_0
- pyodbc=4.0.23=py36h0a44026_0
- pyopenssl=18.0.0=py36_0
- pyparsing=2.2.0=py36hb281f35_0
- pyqt=5.9.2=py36h11d3b92_0
- pysocks=1.6.8=py36_0
- pytables=3.4.3=py36h5ca999c_2
- pytest=3.5.1=py36_0
- pytest-arraydiff=0.2=py36_0
- pytest-astropy=0.3.0=py36_0
- pytest-doctestplus=0.1.3=py36_0
- pytest-openfiles=0.3.0=py36_0
- pytest-remotedata=0.2.1=py36_0
- python=3.6.8=haf84260_0
- python-dateutil=2.7.3=py36_0
- python.app=2=py36_8
- pytz=2018.4=py36_0
- pywavelets=0.5.2=py36h2710a04_0
- pyyaml=3.12=py36h2ba1e63_1
- pyzmq=17.0.0=py36h1de35cc_1
- qt=5.9.5=h02808f3_0
- qtawesome=0.4.4=py36h468c6fb_0
- qtconsole=4.3.1=py36hd96c0ff_0
- qtpy=1.4.1=py36_0
- readline=7.0=hc1231fa_4
- requests=2.18.4=py36h4516966_1
- rope=0.10.7=py36h68959ac_0
- ruamel_yaml=0.15.35=py36h1de35cc_1
- scikit-image=0.13.1=py36h1de35cc_1
- scikit-learn=0.19.1=py36hffbff8c_0
- scipy=1.1.0=py36hcaad992_0
- seaborn=0.8.1=py36h595ecd9_0
- send2trash=1.5.0=py36_0
- setuptools=39.1.0=py36_0
- simplegeneric=0.8.1=py36_2
- singledispatch=3.4.0.3=py36hf20db9d_0
- sip=4.19.8=py36h0a44026_0
- six=1.11.0=py36h0e22d5e_1
- snappy=1.1.7=he62c110_3
- snowballstemmer=1.2.1=py36h6c7b616_0
- sortedcollections=0.6.1=py36_0
- sortedcontainers=1.5.10=py36_0
- sphinx=1.7.4=py36_0
- sphinxcontrib=1.0=py36h9364dc8_1
- sphinxcontrib-websupport=1.0.1=py36h92f4a7a_1
- spyder=3.2.8=py36_0
- sqlalchemy=1.2.7=py36hb402a30_0
- sqlite=3.26.0=ha441bb4_0
- statsmodels=0.9.0=py36h917ab60_0
- sympy=1.1.1=py36h7f3cf04_0
- tblib=1.3.2=py36hda67792_0
- tensorboard=1.10.0=py36_0
- tensorflow=1.10.0=py36_0
- termcolor=1.1.0=py_2
- terminado=0.8.1=py36_1
- testpath=0.3.1=py36h625a49b_0
- tk=8.6.8=ha441bb4_0
- toolz=0.9.0=py36_0
- tornado=5.0.2=py36_0
- traitlets=4.3.2=py36h65bd3ce_0
- typing=3.6.4=py36_0
- unicodecsv=0.14.1=py36he531d66_0
- unixodbc=2.3.6=h3efe00b_0
- urllib3=1.22=py36h68b9469_0
- wcwidth=0.1.7=py36h8c6ec74_0
- webencodings=0.5.1=py36h3b9701d_1
- werkzeug=0.14.1=py36_0
- wheel=0.31.1=py36_0
- widgetsnbextension=3.2.1=py36_0
- wrapt=1.10.11=py36hc29e774_0
- xlrd=1.1.0=py36h336f4a2_1
- xlsxwriter=1.0.4=py36_0
- xlwings=0.11.8=py36_0
- xlwt=1.2.0=py36h5ad1178_0
- xz=5.2.4=h1de35cc_4
- yaml=0.1.7=hc338f04_2
- zeromq=4.2.5=h378b8a2_0
- zict=0.1.3=py36h71da714_0
- zlib=1.2.11=hf3cbc9b_2
- pip:
- enum34==1.1.6
- pip==18.1
- prettytensor==0.7.4
prefix: /Users/matteo/anaconda3
但是如果我尝试在集群上创建相同的env并运行相同的代码，它将无法正常工作，并且出现此错误：
2019-03-22 13:48:57.392457: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 FMA
2019-03-22 13:48:57.397469: I tensorflow/core/common_runtime/process_util.cc:69] Creating new thread pool with default inter op setting: 2. Tune using inter_op_parallelism_threads for best performance.
TRAINING MODE
2019-03-22 13:49:04.088494: E tensorflow/core/common_runtime/executor.cc:630] Executor failed to create kernel. Not found: No registered '_MklConv2DWithBias' OpKernel for CPU devices compatible with node {{node Conv1/conv2d/BiasAdd}} = _MklConv2DWithBias[T=DT_DOUBLE, _kernel="MklOp", data_format="NHWC", dilations=[1, 1, 1, 1], padding="VALID", strides=[1, 2, 2, 1], use_cudnn_on_gpu=true, _device="/job:localhost/replica:0/task:0/device:CPU:0"](input_layer/Reshape, conv2d/kernel/read, conv2d/bias/read, DMT/_0, DMT/_1, DMT/_2)
(OpKernel was found, but attributes didn't match)
. Registered: device='CPU'; label='MklOp'; T in [DT_FLOAT]
[[{{node Conv1/conv2d/BiasAdd}} = _MklConv2DWithBias[T=DT_DOUBLE, _kernel="MklOp", data_format="NHWC", dilations=[1, 1, 1, 1], padding="VALID", strides=[1, 2, 2, 1], use_cudnn_on_gpu=true, _device="/job:localhost/replica:0/task:0/device:CPU:0"](input_layer/Reshape, conv2d/kernel/read, conv2d/bias/read, DMT/_0, DMT/_1, DMT/_2)]]
Traceback (most recent call last):
File "/home/mdonato/.conda/envs/cnn_genetic/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1292, in _do_call
return fn(*args)
File "/home/mdonato/.conda/envs/cnn_genetic/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1277, in _run_fn
options, feed_dict, fetch_list, target_list, run_metadata)
File "/home/mdonato/.conda/envs/cnn_genetic/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1367, in _call_tf_sessionrun
run_metadata)
tensorflow.python.framework.errors_impl.NotFoundError: No registered '_MklConv2DWithBias' OpKernel for CPU devices compatible with node {{node Conv1/conv2d/BiasAdd}} = _MklConv2DWithBias[T=DT_DOUBLE, _kernel="MklOp", data_format="NHWC", dilations=[1, 1, 1, 1], padding="VALID", strides=[1, 2, 2, 1], use_cudnn_on_gpu=true, _device="/job:localhost/replica:0/task:0/device:CPU:0"](input_layer/Reshape, conv2d/kernel/read, conv2d/bias/read, DMT/_0, DMT/_1, DMT/_2)
(OpKernel was found, but attributes didn't match)
. Registered: device='CPU'; label='MklOp'; T in [DT_FLOAT]
[[{{node Conv1/conv2d/BiasAdd}} = _MklConv2DWithBias[T=DT_DOUBLE, _kernel="MklOp", data_format="NHWC", dilations=[1, 1, 1, 1], padding="VALID", strides=[1, 2, 2, 1], use_cudnn_on_gpu=true, _device="/job:localhost/replica:0/task:0/device:CPU:0"](input_layer/Reshape, conv2d/kernel/read, conv2d/bias/read, DMT/_0, DMT/_1, DMT/_2)]]
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "cnn_mnist_beta5.py", line 146, in <module>
sess.run(train_op)
File "/home/mdonato/.conda/envs/cnn_genetic/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 887, in run
run_metadata_ptr)
File "/home/mdonato/.conda/envs/cnn_genetic/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1110, in _run
feed_dict_tensor, options, run_metadata)
File "/home/mdonato/.conda/envs/cnn_genetic/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1286, in _do_run
run_metadata)
File "/home/mdonato/.conda/envs/cnn_genetic/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1308, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.NotFoundError: No registered '_MklConv2DWithBias' OpKernel for CPU devices compatible with node {{node Conv1/conv2d/BiasAdd}} = _MklConv2DWithBias[T=DT_DOUBLE, _kernel="MklOp", data_format="NHWC", dilations=[1, 1, 1, 1], padding="VALID", strides=[1, 2, 2, 1], use_cudnn_on_gpu=true, _device="/job:localhost/replica:0/task:0/device:CPU:0"](input_layer/Reshape, conv2d/kernel/read, conv2d/bias/read, DMT/_0, DMT/_1, DMT/_2)
(OpKernel was found, but attributes didn't match)
. Registered: device='CPU'; label='MklOp'; T in [DT_FLOAT]
[[{{node Conv1/conv2d/BiasAdd}} = _MklConv2DWithBias[T=DT_DOUBLE, _kernel="MklOp", data_format="NHWC", dilations=[1, 1, 1, 1], padding="VALID", strides=[1, 2, 2, 1], use_cudnn_on_gpu=true, _device="/job:localhost/replica:0/task:0/device:CPU:0"](input_layer/Reshape, conv2d/kernel/read, conv2d/bias/read, DMT/_0, DMT/_1, DMT/_2)]]
Caused by op 'Conv1/conv2d/BiasAdd', defined at:
File "cnn_mnist_beta5.py", line 100, in <module>
logits = cnn_model_fn(X_batch, MODE)
File "/home/mdonato/cnn_genetic_beta5/cnn_model_fn_v2.py", line 28, in cnn_model_fn
padding="valid",
File "/home/mdonato/.conda/envs/cnn_genetic/lib/python3.6/site-packages/tensorflow/python/layers/convolutional.py", line 417, in conv2d
return layer.apply(inputs)
File "/home/mdonato/.conda/envs/cnn_genetic/lib/python3.6/site-packages/tensorflow/python/keras/engine/base_layer.py", line 828, in apply
return self.__call__(inputs, *args, **kwargs)
File "/home/mdonato/.conda/envs/cnn_genetic/lib/python3.6/site-packages/tensorflow/python/layers/base.py", line 364, in __call__
outputs = super(Layer, self).__call__(inputs, *args, **kwargs)
File "/home/mdonato/.conda/envs/cnn_genetic/lib/python3.6/site-packages/tensorflow/python/keras/engine/base_layer.py", line 769, in __call__
outputs = self.call(inputs, *args, **kwargs)
File "/home/mdonato/.conda/envs/cnn_genetic/lib/python3.6/site-packages/tensorflow/python/keras/layers/convolutional.py", line 210, in call
outputs = nn.bias_add(outputs, self.bias, data_format='NHWC')
File "/home/mdonato/.conda/envs/cnn_genetic/lib/python3.6/site-packages/tensorflow/python/ops/nn_ops.py", line 1507, in bias_add
return gen_nn_ops.bias_add(value, bias, data_format=data_format, name=name)
File "/home/mdonato/.conda/envs/cnn_genetic/lib/python3.6/site-packages/tensorflow/python/ops/gen_nn_ops.py", line 687, in bias_add
"BiasAdd", value=value, bias=bias, data_format=data_format, name=name)
File "/home/mdonato/.conda/envs/cnn_genetic/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "/home/mdonato/.conda/envs/cnn_genetic/lib/python3.6/site-packages/tensorflow/python/util/deprecation.py", line 488, in new_func
return func(*args, **kwargs)
File "/home/mdonato/.conda/envs/cnn_genetic/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 3272, in create_op
op_def=op_def)
File "/home/mdonato/.conda/envs/cnn_genetic/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1768, in __init__
self._traceback = tf_stack.extract_stack()
NotFoundError (see above for traceback): No registered '_MklConv2DWithBias' OpKernel for CPU devices compatible with node {{node Conv1/conv2d/BiasAdd}} = _MklConv2DWithBias[T=DT_DOUBLE, _kernel="MklOp", data_format="NHWC", dilations=[1, 1, 1, 1], padding="VALID", strides=[1, 2, 2, 1], use_cudnn_on_gpu=true, _device="/job:localhost/replica:0/task:0/device:CPU:0"](input_layer/Reshape, conv2d/kernel/read, conv2d/bias/read, DMT/_0, DMT/_1, DMT/_2)
(OpKernel was found, but attributes didn't match)
. Registered: device='CPU'; label='MklOp'; T in [DT_FLOAT]
[[{{node Conv1/conv2d/BiasAdd}} = _MklConv2DWithBias[T=DT_DOUBLE, _kernel="MklOp", data_format="NHWC", dilations=[1, 1, 1, 1], padding="VALID", strides=[1, 2, 2, 1], use_cudnn_on_gpu=true, _device="/job:localhost/replica:0/task:0/device:CPU:0"](input_layer/Reshape, conv2d/kernel/read, conv2d/bias/read, DMT/_0, DMT/_1, DMT/_2)]]
这是集群环境的规格：
name: cnn_genetic
channels:
- defaults
dependencies:
- _tflow_select=2.3.0=mkl
- absl-py=0.7.0=py36_0
- alabaster=0.7.12=py36_0
- anaconda-client=1.7.2=py36_0
- anaconda=custom=py36hbbc8b67_0
- anaconda-project=0.8.2=py36_0
- asn1crypto=0.24.0=py36_0
- astor=0.7.1=py36_0
- astroid=2.2.5=py36_0
- astropy=3.1.2=py36h7b6447c_0
- atomicwrites=1.3.0=py_0
- attrs=19.1.0=py_0
- babel=2.6.0=py36_0
- backcall=0.1.0=py36_0
- backports=1.0=py36_1
- backports.os=0.1.1=py36_0
- backports.shutil_get_terminal_size=1.0.0=py36_2
- beautifulsoup4=4.7.1=py36_1
- bitarray=0.8.3=py36h14c3975_0
- bkcharts=0.2=py36_0
- blas=1.0=mkl
- blaze=0.11.3=py36_0
- bleach=3.1.0=py36_0
- blosc=1.15.0=hd408876_0
- bokeh=1.0.4=py36_0
- boto=2.49.0=py36_0
- bottleneck=1.2.1=py36h035aef0_1
- bzip2=1.0.6=h14c3975_5
- c-ares=1.15.0=h7b6447c_1
- ca-certificates=2019.1.23=0
- cairo=1.14.12=h8948797_3
- certifi=2019.3.9=py36_0
- cffi=1.12.2=py36h2e261b9_1
- chardet=3.0.4=py36_1
- click=7.0=py36_0
- cloudpickle=0.8.0=py36_0
- clyent=1.2.2=py36_1
- colorama=0.4.1=py36_0
- contextlib2=0.5.5=py36_0
- cryptography=2.6.1=py36h1ba5d50_0
- curl=7.64.0=hbc83047_2
- cycler=0.10.0=py36_0
- cython=0.29.6=py36he6710b0_0
- cytoolz=0.9.0.1=py36h14c3975_1
- dask=1.1.4=py_0
- dask-core=1.1.4=py_0
- datashape=0.5.4=py36_1
- dbus=1.13.6=h746ee38_0
- decorator=4.4.0=py_0
- defusedxml=0.5.0=py36_1
- distributed=1.26.0=py36_1
- docutils=0.14=py36_0
- entrypoints=0.3=py36_0
- et_xmlfile=1.0.1=py36_0
- expat=2.2.6=he6710b0_0
- fastcache=1.0.2=py36h14c3975_2
- filelock=3.0.10=py36_0
- flask=1.0.2=py36_1
- flask-cors=3.0.7=py36_0
- fontconfig=2.13.0=h9420a91_0
- freetype=2.9.1=h8a8886c_1
- fribidi=1.0.5=h7b6447c_0
- gast=0.2.2=py36_0
- get_terminal_size=1.0.0=haa9412d_0
- gevent=1.4.0=py36h7b6447c_0
- glib=2.56.2=hd408876_0
- glob2=0.6=py36_1
- gmp=6.1.2=h6c8ec71_1
- gmpy2=2.0.8=py36h10f8cd9_2
- graphite2=1.3.13=h23475e2_0
- greenlet=0.4.15=py36h7b6447c_0
- grpcio=1.16.1=py36hf8bcb03_1
- gst-plugins-base=1.14.0=hbbd80ab_1
- gstreamer=1.14.0=hb453b48_1
- h5py=2.9.0=py36h7918eee_0
- harfbuzz=1.8.8=hffaf4a1_0
- hdf5=1.10.4=hb1b8bf9_0
- heapdict=1.0.0=py36_2
- html5lib=1.0.1=py36_0
- icu=58.2=h9c2bf20_1
- idna=2.8=py36_0
- imageio=2.5.0=py36_0
- imagesize=1.1.0=py36_0
- importlib_metadata=0.8=py36_0
- intel-openmp=2019.3=199
- ipykernel=5.1.0=py36h39e3cac_0
- ipython=7.3.0=py36h39e3cac_0
- ipython_genutils=0.2.0=py36_0
- ipywidgets=7.4.2=py36_0
- isort=4.3.15=py36_0
- itsdangerous=1.1.0=py36_0
- jbig=2.1=hdba287a_0
- jdcal=1.4=py36_0
- jedi=0.13.3=py36_0
- jeepney=0.4=py36_0
- jinja2=2.10=py36_0
- jpeg=9b=h024ee3a_2
- jsonschema=3.0.1=py36_0
- jupyter=1.0.0=py36_7
- jupyter_client=5.2.4=py36_0
- jupyter_console=6.0.0=py36_0
- jupyter_core=4.4.0=py36_0
- jupyterlab=0.35.4=py36hf63ae98_0
- jupyterlab_server=0.2.0=py36_0
- keras-applications=1.0.7=py_0
- keras-preprocessing=1.0.9=py_0
- keyring=18.0.0=py36_0
- kiwisolver=1.0.1=py36hf484d3e_0
- krb5=1.16.1=h173b8e3_7
- lazy-object-proxy=1.3.1=py36h14c3975_2
- libarchive=3.3.3=h5d8350f_5
- libcurl=7.64.0=h20c2e04_2
- libedit=3.1.20181209=hc058e9b_0
- libffi=3.2.1=hd88cf55_4
- libgcc-ng=8.2.0=hdf63c60_1
- libgfortran-ng=7.3.0=hdf63c60_0
- liblief=0.9.0=h7725739_2
- libpng=1.6.36=hbc83047_0
- libprotobuf=3.6.1=hd408876_0
- libsodium=1.0.16=h1bed415_0
- libssh2=1.8.0=h1ba5d50_4
- libstdcxx-ng=8.2.0=hdf63c60_1
- libtiff=4.0.10=h2733197_2
- libtool=2.4.6=h7b6447c_5
- libuuid=1.0.3=h1bed415_2
- libxcb=1.13=h1bed415_1
- libxml2=2.9.9=he19cac6_0
- libxslt=1.1.33=h7d1a2b0_0
- llvmlite=0.28.0=py36hd408876_0
- locket=0.2.0=py36_1
- lxml=4.3.2=py36hefd8a0e_0
- lz4-c=1.8.1.2=h14c3975_0
- lzo=2.10=h49e0be7_2
- markdown=3.0.1=py36_0
- markupsafe=1.1.1=py36h7b6447c_0
- matplotlib=3.0.3=py36h5429711_0
- mccabe=0.6.1=py36_1
- mistune=0.8.4=py36h7b6447c_0
- mkl=2019.3=199
- mkl-service=1.1.2=py36he904b0f_5
- mkl_fft=1.0.10=py36ha843d7b_0
- mkl_random=1.0.2=py36hd81dba3_0
- more-itertools=6.0.0=py36_0
- mpc=1.1.0=h10f8cd9_1
- mpfr=4.0.1=hdf1c602_3
- mpmath=1.1.0=py36_0
- msgpack-python=0.6.1=py36hfd86e86_1
- multipledispatch=0.6.0=py36_0
- nbconvert=5.4.1=py_2
- nbformat=4.4.0=py36_0
- ncurses=6.1=he6710b0_1
- networkx=2.2=py36_1
- nltk=3.4=py36_1
- nose=1.3.7=py36_2
- notebook=5.7.6=py36_0
- numba=0.43.0=py36h962f231_0
- numexpr=2.6.9=py36h9e4a6bb_0
- numpy=1.16.2=py36h7e9f1db_0
- numpy-base=1.16.2=py36hde5b4d6_0
- numpydoc=0.8.0=py36_0
- odo=0.5.1=py36_0
- olefile=0.46=py36_0
- openpyxl=2.6.1=py_0
- openssl=1.1.1b=h7b6447c_1
- packaging=19.0=py36_0
- pandas=0.24.2=py36he6710b0_0
- pandoc=2.2.3.2=0
- pandocfilters=1.4.2=py36_1
- pango=1.42.4=h049681c_0
- parso=0.3.4=py36_0
- partd=0.3.10=py_0
- patchelf=0.9=he6710b0_3
- path.py=11.5.0=py36_0
- pathlib2=2.3.3=py36_0
- patsy=0.5.1=py36_0
- pcre=8.43=he6710b0_0
- pep8=1.7.1=py36_0
- pexpect=4.6.0=py36_0
- pickleshare=0.7.5=py36_0
- pillow=5.4.1=py36h34e0f95_0
- pip=19.0.3=py36_0
- pixman=0.38.0=h7b6447c_0
- pkginfo=1.5.0.1=py36_0
- pluggy=0.9.0=py36_0
- ply=3.11=py36_0
- prometheus_client=0.6.0=py36_0
- prompt_toolkit=2.0.9=py36_0
- protobuf=3.6.1=py36he6710b0_0
- psutil=5.6.1=py36h7b6447c_0
- ptyprocess=0.6.0=py36_0
- py=1.8.0=py36_0
- py-lief=0.9.0=py36h7725739_2
- pycodestyle=2.5.0=py36_0
- pycosat=0.6.3=py36h14c3975_0
- pycparser=2.19=py36_0
- pycrypto=2.6.1=py36h14c3975_9
- pycurl=7.43.0.2=py36h1ba5d50_0
- pyflakes=2.1.1=py36_0
- pygments=2.3.1=py36_0
- pylint=2.3.1=py36_0
- pyodbc=4.0.26=py36he6710b0_0
- pyopenssl=19.0.0=py36_0
- pyparsing=2.3.1=py36_0
- pyqt=5.9.2=py36h05f1152_2
- pyrsistent=0.14.11=py36h7b6447c_0
- pysocks=1.6.8=py36_0
- pytables=3.5.1=py36h71ec239_0
- pytest=4.3.1=py36_0
- pytest-arraydiff=0.3=py36h39e3cac_0
- pytest-astropy=0.5.0=py36_0
- pytest-doctestplus=0.3.0=py36_0
- pytest-openfiles=0.3.2=py36_0
- pytest-remotedata=0.3.1=py36_0
- python=3.6.8=h0371630_0
- python-dateutil=2.8.0=py36_0
- python-libarchive-c=2.8=py36_6
- pytz=2018.9=py36_0
- pywavelets=1.0.2=py36hdd07704_0
- pyyaml=5.1=py36h7b6447c_0
- pyzmq=18.0.0=py36he6710b0_0
- qt=5.9.7=h5867ecd_1
- qtawesome=0.5.7=py_0
- qtconsole=4.4.3=py36_0
- qtpy=1.7.0=py_0
- readline=7.0=h7b6447c_5
- requests=2.21.0=py36_0
- rope=0.12.0=py36_0
- ruamel_yaml=0.15.46=py36h14c3975_0
- scikit-image=0.14.2=py36he6710b0_0
- scikit-learn=0.20.3=py36hd81dba3_0
- scipy=1.2.1=py36h7c811a0_0
- seaborn=0.9.0=py36_0
- secretstorage=3.1.1=py36_0
- send2trash=1.5.0=py36_0
- setuptools=40.8.0=py36_0
- simplegeneric=0.8.1=py36_2
- singledispatch=3.4.0.3=py36_0
- sip=4.19.8=py36hf484d3e_0
- six=1.12.0=py36_0
- snappy=1.1.7=hbae5bb6_3
- snowballstemmer=1.2.1=py36_0
- sortedcollections=1.1.2=py36_0
- sortedcontainers=2.1.0=py36_0
- soupsieve=1.8=py36_0
- sphinx=1.8.5=py36_0
- sphinxcontrib=1.0=py36_1
- sphinxcontrib-websupport=1.1.0=py36_1
- spyder=3.3.3=py36_0
- spyder-kernels=0.4.2=py36_0
- sqlalchemy=1.3.1=py36h7b6447c_0
- sqlite=3.27.2=h7b6447c_0
- statsmodels=0.9.0=py36h035aef0_0
- sympy=1.3=py36_0
- tblib=1.3.2=py36_0
- tensorboard=1.11.0=py36hf484d3e_0
- tensorflow=1.11.0=mkl_py36ha6f0bda_0
- tensorflow-base=1.11.0=mkl_py36h3c3e929_0
- termcolor=1.1.0=py36_1
- terminado=0.8.1=py36_1
- testpath=0.4.2=py36_0
- tk=8.6.8=hbc83047_0
- toolz=0.9.0=py36_0
- tornado=6.0.1=py36h7b6447c_0
- tqdm=4.31.1=py_0
- traitlets=4.3.2=py36_0
- typed-ast=1.3.1=py36h7b6447c_0
- unicodecsv=0.14.1=py36_0
- unixodbc=2.3.7=h14c3975_0
- urllib3=1.24.1=py36_0
- wcwidth=0.1.7=py36_0
- webencodings=0.5.1=py36_1
- werkzeug=0.14.1=py36_0
- wheel=0.33.1=py36_0
- widgetsnbextension=3.4.2=py36_0
- wrapt=1.11.1=py36h7b6447c_0
- wurlitzer=1.0.2=py36_0
- xlrd=1.2.0=py36_0
- xlsxwriter=1.1.5=py36_0
- xlwt=1.3.0=py36_0
- xz=5.2.4=h14c3975_4
- yaml=0.1.7=had09818_2
- zeromq=4.3.1=he6710b0_3
- zict=0.1.4=py36_0
- zipp=0.3.3=py_0
- zlib=1.2.11=h7b6447c_3
- zstd=1.3.7=h0b5b093_0
- pip:
- libarchive-c==2.8
- lief==0.9.0
- msgpack==0.6.1
- tables==3.5.1
prefix: /home/mdonato/.conda/envs/cnn_genetic
如果有人能告诉我为什么它不起作用，我将非常感激。谢谢您的宝贵时间。
答案 0 :(得分：0)
我解决了安装Keras的问题
conda install -c conda-forge keras-applications
该命令会自动将TensorFlow从1.13降级到我需要的1.10。