1.  It must be a bug/performance issue or a feature request or a build issue or
    a documentation issue (for small doc fixes please send a PR instead).
1.  Make sure the Issue Template is filled out.
1.  The issue should be related to the repo it is created in.

**Here's why we have this policy:** We want to focus on the work that benefits
the whole community, e.g., fixing bugs and adding features. Individual support

Build/Install - Performance - Support - Feature Request - Documentation Feature
Request - Documentation Bug - Others validations: required: true - type:
markdown attributes: value: | Please make sure that this is a bug. As per our
[GitHub Policy](https://github.com/tensorflow/tensorflow/blob/master/ISSUES.md),we
only address code/doc bugs, performance issues, feature requests and
build/installation issues on GitHub.

*   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.
*   Full new features (e.g., a new op implementing a cutting-edge algorithm)
    typically will live in

    *   `CategoryCrossing`: create new categorical features representing
        co-occurrences of previous categorical feature values
    *   `Hashing`: the hashing trick, for large-vocabulary categorical features
    *   `Discretization`: turn continuous numerical features into categorical
        features by binning their values
*   Improved **image preprocessing** layers: `CenterCrop`, `Rescaling`

        ":linux_aarch64",
        ":linux_armhf",
    ],
)

config_setting(
    name = "freebsd",
    values = {"cpu": "freebsd"},
    visibility = ["//visibility:public"],
)

# Features that are default ON are handled differently below.
#
config_setting(
    name = "no_gcp_support",
    define_values = {"no_gcp_support": "true"},
    visibility = ["//visibility:public"],
)

)

cc_library(
    name = "dlpack",
    srcs = ["dlpack.cc"],
    hdrs = ["dlpack.h"],
    copts = tf_copts() + [
        "-fexceptions",
        "-fno-strict-aliasing",
    ],
    features = ["-use_header_modules"],
    visibility = ["//tensorflow:__subpackages__"],
    deps = [
        ":c_api",
        ":c_api_experimental",
        ":tfe_tensorhandle_internal",

//tensorflow/python:compare_test_proto_py
//tensorflow/python/framework:test_ops_2
//tensorflow/python/framework:test_file_system.so
//tensorflow/python/debug:grpc_tensorflow_server.par
//tensorflow/python/feature_column:vocabulary_testdata
//tensorflow/python/util:nest_test_main_lib
//tensorflow/lite/experimental/examples/lstm:rnn_cell
//tensorflow/lite/experimental/examples/lstm:rnn_cell.py

build:windows --host_copt=/D_USE_MATH_DEFINES

# Windows has a relatively short command line limit, which TF has begun to hit.
# See https://docs.bazel.build/versions/main/windows.html
build:windows --features=compiler_param_file
build:windows --features=archive_param_file

# Speed Windows compile times. Available in VS 16.4 (we are on 16.11). See
# https://groups.google.com/a/tensorflow.org/d/topic/build/SsW98Eo7l3o/discussion

# Install Chocolatey and packages
RUN Invoke-Expression ((New-Object Net.WebClient).DownloadString('https://chocolatey.org/install.ps1')); \
    $env:PATH = [Environment]::GetEnvironmentVariable('PATH', 'Machine'); \
    choco feature enable -n allowGlobalConfirmation; \
    choco install 7zip; \
    choco install 7zip.install; \
    choco install 7zip.portable; \
    choco install anaconda2 --version 5.0.1; \

//tensorflow/python:mixed_precision
//tensorflow/python:tf_optimizer
//tensorflow/python:compare_test_proto_py
//tensorflow/python/framework:test_file_system.so
//tensorflow/python/debug:grpc_tensorflow_server.par
//tensorflow/python/feature_column:vocabulary_testdata
//tensorflow/python/util:nest_test_main_lib
//tensorflow/lite/experimental/examples/lstm:rnn_cell
//tensorflow/lite/experimental/examples/lstm:rnn_cell.py