巴泽尔没有找到tensorflow包C++代码示例
问题描述:
我尽量让this example工作,但每次我尝试建立与巴泽尔我收到此错误信息的程序:巴泽尔没有找到tensorflow包C++代码示例
bazel build //code:label_image
ERROR: /home/jonas/tensorflow/code/BUILD:12:1: no such package 'tensorflow': BUILD file not found on package path and referenced by '//code:label_image'.
ERROR: /home/jonas/tensorflow/code/BUILD:12:1: no such package 'tensorflow': BUILD file not found on package path and referenced by '//code:label_image'.
ERROR: /home/jonas/tensorflow/code/BUILD:12:1: no such package 'tensorflow': BUILD file not found on package path and referenced by '//code:label_image'.
ERROR: /home/jonas/tensorflow/code/BUILD:12:1: no such package 'tensorflow': BUILD file not found on package path and referenced by '//code:label_image'.
ERROR: /home/jonas/tensorflow/code/BUILD:12:1: no such package 'tensorflow': BUILD file not found on package path and referenced by '//code:label_image'.
ERROR: Analysis of target '//code:label_image' failed; build aborted.
INFO: Elapsed time: 1.261s
我救的确切源代码从github在一个名为code
的目录中。我通过pip:pip3 install --upgrade tensorflow
在(主动)虚拟环境中安装了tensorflow
。我使用arch linux。
为什么bazel找不到合适的包?我对bazel/tensorflow很陌生。这些软件包在哪里保存?我必须在某处明确指定它们吗?
答
通常情况下,从使用Bazel的项目中提取子文件夹并单独构建它不起作用。
如果你看看label_image
文件夹的构建文件,你会看到这个定义的C++二进制:
cc_binary(
name = "label_image",
srcs = [
"main.cc",
],
linkopts = select({
"//tensorflow:android": [
"-pie",
"-landroid",
"-ljnigraphics",
"-llog",
"-lm",
"-z defs",
"-s",
"-Wl,--exclude-libs,ALL",
],
"//conditions:default": ["-lm"],
}),
deps = select({
"//tensorflow:android": [
# cc:cc_ops is used to include image ops (for label_image)
# Jpg, gif, and png related code won't be included
"//tensorflow/cc:cc_ops",
"//tensorflow/core:android_tensorflow_lib",
# cc:android_tensorflow_image_op is for including jpeg/gif/png
# decoder to enable real-image evaluation on Android
"//tensorflow/core/kernels:android_tensorflow_image_op",
],
"//conditions:default": [
"//tensorflow/cc:cc_ops",
"//tensorflow/core:core_cpu",
"//tensorflow/core:framework",
"//tensorflow/core:framework_internal",
"//tensorflow/core:lib",
"//tensorflow/core:protos_all_cc",
"//tensorflow/core:tensorflow",
],
}),
)
此规则告诉巴泽勒什么label_image
二进制需要待建。值得注意的是,它有依赖关系(deps
)和链接选项(linkopts
)指向tensorflow工作空间的根(//tensorflow
,由WORKSPACE
文件定义),这是从解压缩的子文件夹中缺失的。这就是为什么Bazel抱怨它无法找到包裹tensorflow
。
构建label_image
二进制文件的最简单方法是从tensorflow项目中构建它,因为路径已经建立。
我明白了,谢谢。从github下载完整的项目并在那里运行示例构建,还是需要事先构建一些东西才能使其工作? – Jonas
是的,如果您还没有,请按照自述文件中特定于Tensorflow的附加步骤下载模型定义。 – Jin