same implementation as their `tf.losses` equivalent.
*   For Keras model, the individual call of `Model.evaluate` uses no cached data
    for evaluation, while `Model.fit` uses cached data when `validation_data`
    arg is provided for better performance.
*   Adds a `save_traces` argument to `model.save`/ `tf.keras.models.save_model`

    deps = [
        "//tensorflow/c:env",
    ],
)

cc_library(
    name = "cleanup",
    hdrs = ["cleanup.h"],
)

cc_library(
    name = "ram_file_block_cache",
    srcs = ["ram_file_block_cache.cc"],
    hdrs = ["ram_file_block_cache.h"],
    deps = [
        ":cleanup",
        "//tensorflow/c:env",
        "//tensorflow/c:logging",
        "//tensorflow/c:tf_status",

# Cache pushes are limited to TF's CI system.
build:tf_public_cache_push --config=tf_public_cache --remote_upload_local_results=true --google_default_credentials
# Public cache for macOS builds
build:tf_public_macos_cache --remote_cache="https://storage.googleapis.com/tensorflow-macos-bazel-cache/oct2023" --remote_upload_local_results=false