#      Ex. disk_cache -- Use a local cache
#      Ex. public_cache -- Use TF's public cache (read-only)
#      Ex. public_cache_push -- Use TF's public cache (read and write, Googlers only)
#      Ex. rbe        -- Use RBE for faster builds (Googlers only; see below)
#      Ex. no_docker  -- Disable docker on enabled platforms
#    See full examples below for more details on these. Some other modifiers are:

    [`tf.debugging`](https://www.tensorflow.org/versions/master/api_docs/python/tf/debugging),
    [`tf.dtypes`](https://www.tensorflow.org/versions/master/api_docs/python/tf/dtypes),
    [`tf.image`](https://www.tensorflow.org/versions/master/api_docs/python/tf/image),
    [`tf.io`](https://www.tensorflow.org/versions/master/api_docs/python/tf/io),
    [`tf.linalg`](https://www.tensorflow.org/versions/master/api_docs/python/tf/linalg),

// creating a new op every time. If `raw_device_name` is `NULL` or empty, it
// does not set the device name. If it's not `NULL`, then it attempts to parse
// and set the device name. It's effectively `TFE_OpSetDevice`, but it is faster
// than separately calling it because if the existing op has the same
// `raw_device_name`, it skips parsing and just leave as it is.
TF_CAPI_EXPORT extern void TFE_OpReset(TFE_Op* op_to_reset,

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

# Sometimes Bazel reports darwin_x86_64 as "darwin" and sometimes as
# "darwin_x86_64". The former shows up when building on a Mac x86_64 host for a Mac x86_64 target.
# The latter shows up when cross-compiling for Mac x86_64 from a Mac ARM machine and in internal
# Google builds.
config_setting(
    name = "macos_x86_64_default",
    constraint_values = if_google(

# their dependencies. It's a rewritten version of the "smoke test", an older
# Python script that was very difficult to understand. See
# https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/pip_package/pip_smoke_test.py
@test "Pip package includes all required //tensorflow dependencies" {
  # grep patterns for packages whose dependencies can be ignored

          - https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/toolchains/remote_config/configs.bzl

cc_library(
    name = "posix_filesystem_helper",
    srcs = ["posix_filesystem_helper.cc"],
    hdrs = ["posix_filesystem_helper.h"],
    deps = [":copy_file"],
)

# On Linux, we can copy files faster using `sendfile`. But not elsewhere.
# Hence, this private library to select which implementation to use.
cc_library(
    name = "copy_file",
    srcs = select({
        "//tensorflow:linux_x86_64": ["copy_file_linux.cc"],

  //
  // Like GradientTape::RecordOperation, this method takes the operation type
  // `op_type` (e.g. "Add"), the operation's inputs (`input_tensors`,
  // `input_tensor_id`, and `input_dtypes`; the latter two are somewhat
  // redundant but taken as arguments to avoid repeatedly fetching these values
  // between calls to ShouldRecord and Accumulator), and its outputs
  // (`output_tensors`).
  //

  // caller of event_mgr->ThenExecute() blocks on the completion of the callback
  // (as in the case of ConstOp kernel creation on GPU, which involves copying a
  // CPU tensor to GPU).
  // Setting a larger thread pool does not help with the Swift caller, as we use
  // a different TFE context for each thread of execution (for running graph
  // functions, and their send/recvs corountines).

# TODO: also enable this flag after fixing the visibility violations
# build --incompatible_config_setting_private_default_visibility

# Default options should come above this line.

# Android configs. Bazel needs to have --cpu and --fat_apk_cpu both set to the
# target CPU to build transient dependencies correctly. See
# https://docs.bazel.build/versions/master/user-manual.html#flag--fat_apk_cpu