Under cygwin console:
$ python3.8
Python 3.8.7 (default, Jan 26 2021, 07:37:32)
[GCC 10.2.0] on cygwin
Type "help", "copyright", "credits" or "license" for more information.
```>>> import socket as s```
```>>> s.socketpair()```
File "\<stdin\>", line 1, in <module>
File "/usr/lib/python3.8/socket.py", line 571, in socketpair
```a, b = _socket.socketpair(family, type, proto)```
SystemError: <built-in function socketpair> returned NULL without setting an error
but...
$ python2.7
Python 2.7.18 (default, Jan 2 2021, 09:22:32)
[GCC 10.2.0] on cygwin
Type "help", "copyright", "credits" or "license" for more information.
```>>> import socket as s```
```>>> s.socketpair()```
(<socket object, fd=3, family=1, type=1, protocol=0>, <socket object, fd=4, family=1, type=1,
protocol=0>)
I don't know where to look! :((
THX
The new versions implement a workaround similar to your idea
https://sourceware.org/pipermail/cygwin/2021-February/247684.html
Related
Why after using unittest.mock.mock add_spec methods of mock are disappearing?
from unittest.mock import Mock
m = Mock(spec=str)
print(hasattr(m, 'lower')) # True
m.mock_add_spec(['foo'],)
print(hasattr(m, 'lower')) # False
print(hasattr(m, 'foo')) # True
From the docs:
Only attributes on the spec can be fetched as attributes from the
mock.
TBH I don't quite get this line but obviously method with name "add" should not shrink the count of methods :)
Python version:
Python 3.10.9 (main, Dec 7 2022, 01:12:00) [GCC 9.4.0] on linux
I'm trying to use a julia function from a streamlit app. Created a toy example to test the interaction, simply returning a matrix from a julia functions based on a single parameter to specify the value of the diagonal elements.
Will also note at the outset that both julia_import_method = "api_compiled_false" and julia_import_method = "main_include" works when importing the function in Spyder IDE (rather than at the command line to launch the streamlit app via streamlit run streamlit_julia_test.py).
My project directory looks like:
├── my_project_directory
│ ├── julia_test.jl
│ └── streamlit_julia_test.py
The julia function is in julia_test.jl and just simply returns a matrix with diagonals specified by the v parameter:
function get_matrix_from_julia(v::Int)
m=[v 0
0 v]
return m
end
The streamlit app is streamlit_julia_test.py and is defined as:
import os
from io import BytesIO
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
import streamlit as st
# options:
# main_include
# api_compiled_false
# dont_import_julia
julia_import_method = "api_compiled_false"
if julia_import_method == "main_include":
# works in Spyder IDE
import julia
from julia import Main
Main.include("julia_test.jl")
elif julia_import_method == "api_compiled_false":
# works in Spyder IDE
from julia.api import Julia
jl = Julia(compiled_modules=False)
this_dir = os.getcwd()
julia_test_path = """include(\""""+ this_dir + """/julia_test.jl\"""" +")"""
print(julia_test_path)
jl.eval(julia_test_path)
get_matrix_from_julia = jl.eval("get_matrix_from_julia")
elif julia_import_method == "dont_import_julia":
print("Not importing ")
else:
ValueError("Not handling this case:" + julia_import_method)
st.header('Using Julia in Streamlit App Example')
st.text("Using Method:" + julia_import_method)
matrix_element = st.selectbox('Set Matrix Diagonal to:', [1,2,3])
matrix_numpy = np.array([[matrix_element,0],[0,matrix_element]])
col1, col2 = st.columns([4,4])
with col1:
fig, ax = plt.subplots(figsize=(5,5))
sns.heatmap(matrix_numpy, ax = ax, cmap="Blues",annot=True)
ax.set_title('Matrix Using Python Numpy')
buf = BytesIO()
fig.savefig(buf, format="png")
st.image(buf)
with col2:
if julia_import_method == "dont_import_julia":
matrix_julia = matrix_numpy
else:
matrix_julia = get_matrix_from_julia(matrix_element)
fig, ax = plt.subplots(figsize=(5,5))
sns.heatmap(matrix_julia, ax = ax, cmap="Blues",annot=True)
ax.set_title('Matrix from External Julia Script')
buf = BytesIO()
fig.savefig(buf, format="png")
st.image(buf)
If the app were working correctly, it would look like this (which can be reproduced by setting the julia_import_method = "dont_import_julia" on line 13):
Testing
When I try julia_import_method = "main_include", I get the well known error:
julia.core.UnsupportedPythonError: It seems your Julia and PyJulia setup are not supported.
Julia executable:
julia
Python interpreter and libpython used by PyCall.jl:
/Users/myusername/opt/anaconda3/bin/python3
/Users/myusername/opt/anaconda3/lib/libpython3.9.dylib
Python interpreter used to import PyJulia and its libpython.
/Users/myusername/opt/anaconda3/bin/python
/Users/myusername/opt/anaconda3/lib/libpython3.9.dylib
Your Python interpreter "/Users/myusername/opt/anaconda3/bin/python"
is statically linked to libpython. Currently, PyJulia does not fully
support such Python interpreter.
The easiest workaround is to pass `compiled_modules=False` to `Julia`
constructor. To do so, first *reboot* your Python REPL (if this happened
inside an interactive session) and then evaluate:
>>> from julia.api import Julia
>>> jl = Julia(compiled_modules=False)
Another workaround is to run your Python script with `python-jl`
command bundled in PyJulia. You can simply do:
$ python-jl PATH/TO/YOUR/SCRIPT.py
See `python-jl --help` for more information.
For more information, see:
https://pyjulia.readthedocs.io/en/latest/troubleshooting.html
As suggested, when I set julia_import_method = "api_compiled_false", I get a seg fault:
include("my_project_directory/julia_test.jl")
2022-04-03 10:23:13.406 Traceback (most recent call last):
File "/Users/myusername/opt/anaconda3/lib/python3.9/site-packages/streamlit/script_runner.py", line 430, in _run_script
exec(code, module.__dict__)
File "my_project_directory/streamlit_julia_test.py", line 25, in <module>
jl = Julia(compiled_modules=False)
File "/Users/myusername/.local/lib/python3.9/site-packages/julia/core.py", line 502, in __init__
if not self.api.was_initialized: # = jl_is_initialized()
File "/Users/myusername/.local/lib/python3.9/site-packages/julia/libjulia.py", line 114, in __getattr__
return getattr(self.libjulia, name)
File "/Users/myusername/opt/anaconda3/lib/python3.9/ctypes/__init__.py", line 395, in __getattr__
func = self.__getitem__(name)
File "/Users/myuserame/opt/anaconda3/lib/python3.9/ctypes/__init__.py", line 400, in __getitem__
func = self._FuncPtr((name_or_ordinal, self))
AttributeError: dlsym(0x21b8e5840, was_initialized): symbol not found
signal (11): Segmentation fault: 11
in expression starting at none:0
Allocations: 35278345 (Pool: 35267101; Big: 11244); GC: 36
zsh: segmentation fault streamlit run streamlit_julia_test.py
I've also tried the alternative recommendation provided in the PyJulia response message regarding the use of:
python-jl my_project_directory/streamlit_julia_test.py
But I get this error when running the python-jl command:
INTEL MKL ERROR: dlopen(/Users/myusername/opt/anaconda3/lib/libmkl_intel_thread.1.dylib, 0x0009): Library not loaded: #rpath/libiomp5.dylib
Referenced from: /Users/myusername/opt/anaconda3/lib/libmkl_intel_thread.1.dylib
Reason: tried: '/Applications/Julia-1.7.app/Contents/Resources/julia/bin/../lib/libiomp5.dylib' (no such file), '/usr/local/lib/libiomp5.dylib' (no such file), '/usr/lib/libiomp5.dylib' (no such file).
Intel MKL FATAL ERROR: Cannot load libmkl_intel_thread.1.dylib.
So I'm stuck, thanks in advance for a modified reproducible example or instructions for the following system specs!
System specs:
Mac OS Monterey 12.2.1 (Chip - Mac M1 Pro)
Python 3.9.7
Julia 1.7.2
PyJulia 0.5.8.dev
Streamlit 1.7.0
yes we can use it streamlit_julia_test.py NumPy for instance
import os
import time
CONSOLE = "/dev/tty0"
logfd = None
def log_me(logstr):
global logfd
global CONSOLE
print(time.strftime("%c")+": "+logstr)
if not logfd:
if not os.path.exists(CONSOLE):
return
logfd = open(CONSOLE, "a")
if not logfd:
return
logfd.write(logstr+"\n")
logfd.flush()
return
test.py
from consolelog import log_me
print ("Hello World!")
log_me("This is a Hello World script")
log_me("Logging 2nd time to see how it works.")
log_me("loging 3rd time")
The same code is working when used with python2 but throwing error 29 illegal seek when run with python3
[root#869ebe33-77e8-41b4-918b-eafda978fd98 ~]# python test.py
Hello World!
Wed Apr 14 07:37:03 2021: This is a Hello World script
Wed Apr 14 07:37:03 2021: Logging 2nd time to see how it works.
Wed Apr 14 07:37:03 2021: loging 3rd time
output with python3
[root#869ebe33-77e8-41b4-918b-eafda978fd98 ~]# python3 test.py
Hello World!
Wed Apr 14 07:37:10 2021: This is a Hello World script
Traceback (most recent call last):
File "test.py", line 4, in
log_me("This is a Hello World script")
File "/root/consolelog.py", line 14, in log_me
logfd = open(CONSOLE, "a")
OSError: [Errno 29] Illegal seek
with python3.x append doesn't work with open(/dev/tty0) so we have to use write instead of append.
System information
OS Platform and Distribution: Linux CentOS7.2
TensorFlow Serving installed from (source or binary): Source
TensorFlow Serving version: r1.9
Python Version: 3.6.2
Describe the problem
The centos7.2 install python2.7 defaultly, I want to build tensorflow-serving for python3, So I use the pyenv to install a python3.6.2, and in the pyenv virtualenv, I cloned the tensorflow/serving r1.9, to bazel build it from source. But the at last it failed becase of "import mork" error. I saw in the serving/tools/bazel.rc file, it use the /usr/bin/python as python runner, so I changed the file to my python3.6.2, but failed again. with error like
" _mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)
ImportError: /home/pyenv/.cache/bazel/_bazel_pyenv/3e832003f40725f2f414b6fe95aca127/execroot/tf_serving/bazel-out/host/bin/external/org_tensorflow/tensorflow/tools/api/generator/create_python_api.runfiles/org_tensorflow/tensorflow/python/_pywrap_tensorflow_internal.so: undefined symbol: _Py_FalseStruct"
Exact Steps to Reproduce
I changed the bazel.rc file as follows
build:cuda --crosstool_top=#local_config_cuda//crosstool:toolchain
build:cuda --define=using_cuda=true --define=using_cuda_nvcc=true
build --action_env PYTHON_BIN_PATH="/home/pyenv/.pyenv/versions/tensorflow-serving/bin/python"
build --define PYTHON_BIN_PATH=/home/pyenv/.pyenv/versions/tensorflow-serving/bin/python # tensorflow-serving is a virtualenv from python3.6.2 installed by pyenv
build --spawn_strategy=standalone --genrule_strategy=standalone
test --spawn_strategy=standalone --genrule_strategy=standalone
run --spawn_strategy=standalone --genrule_strategy=standalone
build --define=grpc_no_ares=true
build --define with_hdfs_support=true # support HDFS
# TODO(b/69809703): Remove once no longer required for TensorFlow to build.
build --copt=-DGEMMLOWP_ALLOW_SLOW_SCALAR_FALLBACK
Source code / logs
the built also failed, the error log is as follows
ERROR:
/home/pyenv/.cache/bazel/_bazel_pyenv/3e832003f40725f2f414b6fe95aca127/external/org_tensorflow/tensorflow/BUILD:541:1: Executing genrule #org_tensorflow//tensorflow:python_api_gen failed (Exit 1): bash failed: error executing command
(cd /home/pyenv/.cache/bazel/_bazel_pyenv/3e832003f40725f2f414b6fe95aca127/execroot/tf_serving && \
exec env - \
PATH=/home/pyenv/.pyenv/plugins/pyenv-virtualenv/shims:/home/pyenv/.pyenv/shims:/home/pyenv/.pyenv/bin:/usr/local/ffmpeg/bin/:/opt/jdk1.8.0_112/bin:/usr/local/bin:/usr/bin:/usr/local/sbin:/usr/sbin:/home/pyenv/.local/bin:/home/pyenv/bin \
PYTHON_BIN_PATH=/home/pyenv/.pyenv/versions/tensorflow-serving/bin/python \
/bin/bash -c 'source external/bazel_tools/tools/genrule/genrule-setup.sh; bazel-out/host/bin/external/org_tensorflow/tensorflow/tools/api/generator/create_python_api --root_init_template=external/org_tensorflow/tensorflow/api_template.__init__.py --apidir=bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/app/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/bitwise/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/compat/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/data/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/distributions/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/distributions/bijectors/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/errors/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/estimator/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/estimator/export/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/estimator/inputs/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/feature_column/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/gfile/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/graph_util/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/image/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/initializers/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/activations/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/applications/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/applications/densenet/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/applications/inception_resnet_v2/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/applications/inception_v3/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/applications/mobilenet/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/applications/nasnet/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/applications/resnet50/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/applications/vgg16/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/applications/vgg19/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/applications/xception/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/backend/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/callbacks/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/constraints/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/datasets/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/datasets/boston_housing/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/datasets/cifar10/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/datasets/cifar100/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/datasets/fashion_mnist/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/datasets/imdb/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/datasets/mnist/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/datasets/reuters/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/estimator/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/initializers/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/layers/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/losses/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/metrics/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/models/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/optimizers/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/preprocessing/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/preprocessing/image/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/preprocessing/sequence/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/preprocessing/text/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/regularizers/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/utils/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/wrappers/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/keras/wrappers/scikit_learn/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/layers/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/linalg/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/logging/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/losses/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/manip/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/math/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/metrics/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/nn/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/nn/rnn_cell/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/profiler/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/python_io/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/resource_loader/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/strings/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/saved_model/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/saved_model/builder/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/saved_model/constants/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/saved_model/loader/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/saved_model/main_op/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/saved_model/signature_constants/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/saved_model/signature_def_utils/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/saved_model/tag_constants/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/saved_model/utils/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/sets/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/sparse/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/spectral/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/summary/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/sysconfig/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/test/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/train/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/train/queue_runner/__init__.py bazel-out/k8-opt/genfiles/external/org_tensorflow/tensorflow/user_ops/__init__.py')
Traceback (most recent call last):
File "/home/pyenv/.cache/bazel/_bazel_pyenv/3e832003f40725f2f414b6fe95aca127/execroot/tf_serving/bazel-out/host/bin/external/org_tensorflow/tensorflow/tools/api/generator/create_python_api.runfiles/tf_serving/../org_tensorflow/tensorflow/tools/api/generator/create_python_api.py", line 27, in <module>
from tensorflow.python.util import tf_decorator
File "/home/pyenv/.cache/bazel/_bazel_pyenv/3e832003f40725f2f414b6fe95aca127/execroot/tf_serving/bazel-out/host/bin/external/org_tensorflow/tensorflow/tools/api/generator/create_python_api.runfiles/org_tensorflow/tensorflow/python/__init__.py", line 49, in <module>
from tensorflow.python import pywrap_tensorflow
File "/home/pyenv/.cache/bazel/_bazel_pyenv/3e832003f40725f2f414b6fe95aca127/execroot/tf_serving/bazel-out/host/bin/external/org_tensorflow/tensorflow/tools/api/generator/create_python_api.runfiles/org_tensorflow/tensorflow/python/pywrap_tensorflow.py", line 74, in <module>
raise ImportError(msg)
ImportError: Traceback (most recent call last):
File "/home/pyenv/.cache/bazel/_bazel_pyenv/3e832003f40725f2f414b6fe95aca127/execroot/tf_serving/bazel-out/host/bin/external/org_tensorflow/tensorflow/tools/api/generator/create_python_api.runfiles/org_tensorflow/tensorflow/python/pywrap_tensorflow.py", line 58, in <module>
from tensorflow.python.pywrap_tensorflow_internal import *
File "/home/pyenv/.cache/bazel/_bazel_pyenv/3e832003f40725f2f414b6fe95aca127/execroot/tf_serving/bazel-out/host/bin/external/org_tensorflow/tensorflow/tools/api/generator/create_python_api.runfiles/org_tensorflow/tensorflow/python/pywrap_tensorflow_internal.py", line 28, in <module>
_pywrap_tensorflow_internal = swig_import_helper()
File "/home/pyenv/.cache/bazel/_bazel_pyenv/3e832003f40725f2f414b6fe95aca127/execroot/tf_serving/bazel-out/host/bin/external/org_tensorflow/tensorflow/tools/api/generator/create_python_api.runfiles/org_tensorflow/tensorflow/python/pywrap_tensorflow_internal.py", line 24, in swig_import_helper
_mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)
ImportError: /home/pyenv/.cache/bazel/_bazel_pyenv/3e832003f40725f2f414b6fe95aca127/execroot/tf_serving/bazel-out/host/bin/external/org_tensorflow/tensorflow/tools/api/generator/create_python_api.runfiles/org_tensorflow/tensorflow/python/_pywrap_tensorflow_internal.so: undefined symbol: _Py_FalseStruct
Then how can I build tensorflow-serving r1.9 with python3.6.2 support on CentOS7?
change the tools/bazel.rc to config python path can resolve this problem.
but this seems not true for tensorflow-serving r1.10 or r1.11
When I try to retrain spacy english model, as I have found in the examples, It fails:
Python 3.6.2 (v3.6.2:5fd33b5926, Jul 16 2017, 20:11:06)
[GCC 4.2.1 (Apple Inc. build 5666) (dot 3)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import spacy
>>> from spacy.tokens import Doc
>>> from spacy.gold import GoldParse
>>>
>>> nlp = spacy.load('en')
>>> doc = Doc(nlp.vocab, words=['Who', 'is', 'Shaka', 'Khan', '?'])
>>> gold = GoldParse(doc, [(1, 'nsubj'), (1, 'ROOT'), (3, 'compound'), (1, 'dobj'), (1, 'punct')])
>>> nlp.parser(doc)
>>> gold
<spacy.gold.GoldParse object at 0x114008a58>
>>> nlp.parser.update( doc, gold )
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "spacy/syntax/parser.pyx", line 320, in spacy.syntax.parser.Parser.update (spacy/syntax/parser.cpp:10286)
File "spacy/syntax/arc_eager.pyx", line 357, in spacy.syntax.arc_eager.ArcEager.preprocess_gold (spacy/syntax/arc_eager.cpp:7888)
AttributeError: 'NoneType' object has no attribute 'upper'
What am I doing wrong here? Any help is appreciated.
As Ghislain PUTOIS (#ghpu) answered me on spacy support chatroom, the doc seems to be slightly outdated, see instead https://github.com/explosion/spaCy/blob/master/examples/training/train_parser.py, where gold heads and deps are now separated.