application/x-troff            t tr roff        # Troff file
application/x-troff-man        man              # Troff with MAN macros
application/x-troff-me         me               # Troff with ME macros
application/x-troff-ms         ms               # Troff with MS macros
application/x-ustar            ustar            # Ustar file
application/vnd.ms-access      mdb mda mde      # MS Access

  val safari12iOS = sslLabsClients.first { it.userAgent == "Safari" && it.platform == "iOS 12.3.1" }
  val safari12Osx =
    sslLabsClients.first { it.userAgent == "Safari" && it.platform == "MacOS 10.14.6 Beta" }

  val okhttp = currentOkHttp(ianaSuitesNew)

  val okHttp_4_10 = historicOkHttp("4.10")
  val okHttp_3_14 = historicOkHttp("3.14")
  val okHttp_3_13 = historicOkHttp("3.13")

    ),
    WINDOWS(
        "Windows",
        androidHome = """C:\Program Files\android\sdk""",
        jprofilerHome = """C:\Program Files\jprofiler\jprofiler11.1.4""",
        perfTestWorkingDir = "P:/",
    ),
    MACOS(
        "Mac",
        androidHome = "/opt/android/sdk",
        jprofilerHome = "/Applications/JProfiler11.1.4.app",
        defaultArch = Arch.AARCH64
    );

package(
    # copybara:uncomment default_applicable_licenses = ["//tensorflow:license"],
    default_visibility = ["//visibility:private"],
    licenses = ["notice"],
)

# Filesystem implementation for POSIX environments: Linux, MacOS, Android, etc.
tf_cc_shared_object(
    name = "libposix_filesystem.so",
    framework_so = [],
    linkstatic = False,
    visibility = ["//visibility:public"],
    deps = [":posix_filesystem_impl"],
)

==============================================================================*/
#ifndef TENSORFLOW_C_EAGER_TFE_CANCELLATION_MANAGER_INTERNAL_H_
#define TENSORFLOW_C_EAGER_TFE_CANCELLATION_MANAGER_INTERNAL_H_

#include "tensorflow/c/conversion_macros.h"
#include "tensorflow/core/framework/cancellation.h"

struct TFE_CancellationManager;
typedef struct TFE_CancellationManager TFE_CancellationManager;

namespace tensorflow {

You can create and use environment variables in the shell, without needing Python:

=== "Linux, macOS, Windows Bash"

    <div class="termy">

    ```console
    // You could create an env var MY_NAME with
    $ export MY_NAME="Wade Wilson"

    // Then you could use it with other programs, like

==============================================================================*/
#ifndef TENSORFLOW_C_EAGER_TFE_OP_ATTRS_INTERNAL_H_
#define TENSORFLOW_C_EAGER_TFE_OP_ATTRS_INTERNAL_H_

#include "tensorflow/c/conversion_macros.h"
#include "tensorflow/c/eager/abstract_op_attrs.h"
#include "tensorflow/c/tf_status.h"
#include "tensorflow/core/framework/attr_value.pb.h"

// An equivalent of a tensorflow::NameAttrList protocol buffer, but used in ways

)

cc_library(
    name = "grappler_hdrs",
    hdrs = ["grappler.h"],
    visibility = ["//tensorflow:internal"],
    deps = [
        "//tensorflow/c:c_api",
        "//tensorflow/c:c_api_macros",
        "//tensorflow/c:tf_status_headers",
    ],
)

cc_library(
    name = "grappler",
    srcs = ["grappler.cc"],
    hdrs = [
        "grappler.h",
        "grappler_internal.h",
    ],

因此，通常会将它们提供为由应用程序读取的环境变量。

## 环境变量

!!! tip
    如果您已经知道什么是"环境变量"以及如何使用它们，请随意跳到下面的下一节。

环境变量（也称为"env var"）是一种存在于 Python 代码之外、存在于操作系统中的变量，可以被您的 Python 代码（或其他程序）读取。

您可以在 shell 中创建和使用环境变量，而无需使用 Python：

=== "Linux、macOS、Windows Bash"

    <div class="termy">

    ```console
    // 您可以创建一个名为 MY_NAME 的环境变量
    $ export MY_NAME="Wade Wilson"

    // 然后您可以与其他程序一起使用它，例如
    $ echo "Hello $MY_NAME"

    Hello Wade Wilson

==============================================================================*/
#ifndef TENSORFLOW_C_EAGER_TFE_CONTEXT_INTERNAL_H_
#define TENSORFLOW_C_EAGER_TFE_CONTEXT_INTERNAL_H_

#include "tensorflow/c/conversion_macros.h"
#include "tensorflow/c/eager/immediate_execution_context.h"

// Wraps a pointer to a context implementation.
//
// WARNING: Since the underlying object could be ref-counted a user of this