bazel cquery --keep_going 'deps(//tensorflow/tools/pip_package:wheel)' | sort -u > $BATS_TEST_TMPDIR/pip_deps
  # Find all Python py_test targets not tagged "no_pip" or "manual", excluding
  # any targets in ignored packages. Combine this list of targets into a bazel
  # query list (e.g. the list becomes "target+target2+target3")

load("@python//3.10:defs.bzl", compile_pip_requirements_3_10 = "compile_pip_requirements")
load("@python//3.11:defs.bzl", compile_pip_requirements_3_11 = "compile_pip_requirements")
load("@python//3.12:defs.bzl", compile_pip_requirements_3_12 = "compile_pip_requirements")
load("@python//3.9:defs.bzl", compile_pip_requirements_3_9 = "compile_pip_requirements")

        ":with_tpu_support_define",
        ":with_tpu_support_flag",
    ],
    visibility = ["//visibility:public"],
)

# Specifies via a config setting if this is a mobile build or not, makes
# it easier to combine settings later.
selects.config_setting_group(
    name = "mobile",
    match_any = [
        ":android",
        ":chromiumos",

debugging information with `--config=dbg`, as issues occur on Linux if
there is too much debug info (see [this GitHub
issue](https://github.com/tensorflow/tensorflow/issues/48919) for context). If
you want to debug a kernel, you can compile specific files with `-g` using the
`--per_file_copt` bazel option. For example, if you want to debug the Identity
op, which are in files starting with `identity_op`, you can run

```bash

    *   Argument `jit_compile` in `Model.compile()` now applies to
        `Model.evaluate()` and `Model.predict()`. Setting `jit_compile=True` in
        `compile()` compiles the model's training, evaluation, and inference
        steps to [XLA](https://www.tensorflow.org/xla). Note that
        `jit_compile=True` may not necessarily work for all models.