load(
    "//tensorflow:tensorflow.bzl",
    "tf_cc_test",
)
load("//tensorflow:tensorflow.default.bzl", "filegroup")
load("//tensorflow/core/platform:rules_cc.bzl", "cc_library")

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

# Currently pybind extension shared objects must use only C API headers since

        `tf.keras.utils.is_interactive_logging_enabled()` to check if
        interactive logging is enabled.
    *   Changed default value for the `verbose` argument of `Model.evaluate()`
        and `Model.predict()` to `"auto"`, which defaults to `verbose=1` for
        most cases and defaults to `verbose=2` when used with
        `ParameterServerStrategy` or with interactive logging disabled.

    "tf_copts",
    "tf_cuda_library",
    "tf_custom_op_library",
    "tf_kernel_library",
)
load("//tensorflow:tensorflow.default.bzl", "filegroup", "tf_cuda_cc_test")
load(
    "//tensorflow/core/tpu:build_defs.bzl",
    "if_libtpu_tf_status",
)

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

filegroup(
    name = "safe_ptr_hdr",

dependencies are always used. \
See https://github.com/bazelbuild/rules_python/ for more details.

### Specifying the Python version

Note: Only a number of minor Python versions are supported at any given time.

By default, the lowest supported version is used.

To set a different version, use the `TF_PYTHON_VERSION` environment variable,
e.g.

```
export TF_PYTHON_VERSION=3.11
```

# modular framework.
load("//tensorflow:tensorflow.bzl", "tf_cc_test")
load("//tensorflow/core/platform:rules_cc.bzl", "cc_library")

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

# This is only for plugins
cc_library(
    name = "filesystem_interface",
    hdrs = ["filesystem_interface.h"],

#
#   Note: new files created from the container are owned by "root".
#   You can run e.g. `docker exec tf chown -R $(id -u):$(id -g) build_output`
#   to transfer ownership to your user.
#
# Docker is enabled by default on Linux. You may disable it if you prefer:
# export TFCI=py311,linux_x86,no_docker

# Advanced: Use Remote Build Execution (RBE) (internal developers only)
#

# Description:
# Graph C API.

load("//tensorflow/core/platform:rules_cc.bzl", "cc_library")
load(
    "//tensorflow:tensorflow.bzl",
    "tf_cc_test",
)

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

cc_library(
    name = "grappler_hdrs",
    hdrs = ["grappler.h"],
    visibility = ["//tensorflow:internal"],
    deps = [

    [following API review practices](https://github.com/tensorflow/community/blob/master/governance/api-reviews.md).
*   When you contribute a new feature to TensorFlow, the maintenance burden is
    (by default) transferred to the TensorFlow team. This means that the benefit
    of the contribution must be compared against the cost of maintaining the
    feature.

    define_values = {"__TENSORFLOW_NO_LGPL_DEPS__": "1"},
    visibility = ["//visibility:public"],
)

# Config setting that disables the default logger, only logging
# to registered TFLogSinks
config_setting(
    name = "no_default_logger",
    define_values = {"no_default_logger": "true"},
    visibility = ["//visibility:public"],
)

config_setting(
    name = "force_rtti",
    define_values = {

TensorFlow server (`tf.train.Server`). The TensorFlow server is intended for
internal communication only. It is not built for use in untrusted environments
or networks.

For performance reasons, the default TensorFlow server does not include any
authorization protocol and sends messages unencrypted. It accepts connections
from anywhere, and executes the graphs it is sent without performing any checks.