Cannot download tf_nightly-1.14.0 about tf-seal

[Wixee]

And I find a bug when I try to build tf_nightly 1.14 from https://github.com/capeprivacy/tensorflow.

env:
ubuntu 20.04(WSL)
g++ 9.3.0
bazel 0.26.1

ERROR: /home/wixee/.cache/bazel/_bazel_wixee/f60087e168a450f0f32faca0e4b96746/external/grpc/BUILD:507:1: C++ compilation of rule '@grpc//:gpr_base' failed (Exit 1) gcc failed: error executing command /usr/bin/gcc -U_FORTIFY_SOURCE -fstack-protector -Wall -Wunused-but-set-parameter -Wno-free-nonheap-object -fno-omit-frame-pointer -g0 -O2 '-D_FORTIFY_SOURCE=1' -DNDEBUG -ffunction-sections ... (remaining 27 argument(s) skipped)
Use --sandbox_debug to see verbose messages from the sandbox
external/grpc/src/core/lib/gpr/log_linux.cc:43:13: error: ambiguating new declaration of 'long int gettid()'
43 | static long gettid(void) { return syscall(__NR_gettid); }
| ^~~~~~
In file included from /usr/include/unistd.h:1170,
from external/grpc/src/core/lib/gpr/log_linux.cc:41:
/usr/include/x86_64-linux-gnu/bits/unistd_ext.h:34:16: note: old declaration '__pid_t gettid()'
34 | extern __pid_t gettid (void) __THROW;
| ^~~~~~
external/grpc/src/core/lib/gpr/log_linux.cc:43:13: warning: 'long int gettid()' defined but not used [-Wunused-function]
43 | static long gettid(void) { return syscall(__NR_gettid); }
| ^~~~~~
Target //tensorflow/tools/pip_package:build_pip_package failed to build
Use --verbose_failures to see the command lines of failed build steps.
INFO: Elapsed time: 447.916s, Critical Path: 25.77s
INFO: 218 processes: 218 processwrapper-sandbox.
FAILED: Build did NOT complete successfully

[Wixee]

Well, I solved this problem by myself.

1. download grpc from the url in tensorflow/tensorflow/workspace.bzl. (https://github.com/grpc/grpc/archive/4566c2a29ebec0835643b972eb99f4306c4234a3.tar.gz)
2. unzip the package, change the function name gettid to sys_gettid in grpc/src/core/lib/gpr/log_linux.cc, grpc/src/core/lib/gpr/log_posix.cc, grpc/src/core/lib/iomgr/ev_epollex_linux.cc, then package the grpc to a new tar package with the original file name.
3. use nginx, move the new tar package to /var/www/html and start the service nginx.
4. modify the sha256sum of grpc package in tensorflow/tensorflow/workspace.bzl to the sha256 of the new package.
5. build
   And be sure to use numpy < 1.19.0, or there will be another issue.

I spend nearly 7 hours to build it. LOL