# matches the /search/ regular expression. "print $N" prints the Nth "field",
# where fields are strings separated by whitespace.
export TF_VER_MAJOR=$(awk '/#define TF_MAJOR_VERSION/ {print $3}' tensorflow/core/public/version.h)
export TF_VER_MINOR=$(awk '/#define TF_MINOR_VERSION/ {print $3}' tensorflow/core/public/version.h)
export TF_VER_PATCH=$(awk '/#define TF_PATCH_VERSION/ {print $3}' tensorflow/core/public/version.h)

  TF_NewWritableFile(full_path, &h, status);
  if (TF_GetCode(status) != TF_OK) {
    fprintf(stderr, "TF_NewWritableFile failed: %s\n", TF_Message(status));
    return 1;
  }
  fprintf(stderr, "wrote %s\n", full_path);
  free(full_path);
  TF_CloseWritableFile(h, status);
  if (TF_GetCode(status) != TF_OK) {
    fprintf(stderr, "TF_CloseWritableFile failed: %s\n", TF_Message(status));
  }
  TF_StringStreamDone(s);

  return nullptr;
}

}  // end namespace tracing
}  // end namespace tensorflow

// =============================================================================
// Public C API entry points
//
// These are only the generic entry points for the C API. This file does not
// have any visibility into the graph/eager implementation and is only providing
// C bindings to the abstract classes defined in the

python="$venv/bin/python3"
"$python" -m pip install *.whl $TFCI_PYTHON_VERIFY_PIP_INSTALL_ARGS
if [[ "$TFCI_WHL_IMPORT_TEST_ENABLE" == "1" ]]; then
  "$python" -c 'import tensorflow as tf; t1=tf.constant([1,2,3,4]); t2=tf.constant([5,6,7,8]); print(tf.add(t1,t2).shape)'
  "$python" -c 'import sys; import tensorflow as tf; sys.exit(0 if "keras" in tf.keras.__name__ else 1)'
fi
# VERY basic check to ensure the [and-cuda] package variant is installable.

        the environment variable `TF_DETERMINISTIC_OPS` to `"true"` or `"1"`.
*   `tf.print`:
    *   Bug fix in `tf.print()` with `OrderedDict` where if an `OrderedDict`
        didn't have the keys sorted, the keys and values were not being printed
        in accordance with their correct mapping.
*   `tf.train.Checkpoint`:

        "//tensorflow/core/platform:statusor",
        "//tensorflow/core/platform:stringpiece",
        "//tensorflow/core/platform:types",
        "//tensorflow/core/profiler/internal:print_model_analysis",
        "//tensorflow/core/profiler/lib:traceme",
        "//tensorflow/core/profiler/rpc/client:profiler_client_impl",
        "//tensorflow/core/profiler/rpc:profiler_server_impl",

  print('    %s' % config['cudnn_include_dir'])

  if 'tensorrt_version' in config:
    print('Found TensorRT %s in:' % config['tensorrt_version'])
    print('    %s' % config['tensorrt_library_dir'])
    print('    %s' % config['tensorrt_include_dir'])

  if config.get('nccl_version', None):
    print('Found NCCL %s in:' % config['nccl_version'])
    print('    %s' % config['nccl_library_dir'])

}

@test "Wheel conforms to upstream size limitations" {
    WHEEL_MEGABYTES=$(stat --format %s "$TF_WHEEL" | awk '{print int($1/(1024*1024))}')
    # Googlers: search for "test_tf_whl_size"
    case "$TF_WHEEL" in
        # CPU:
        *cpu*manylinux*) LARGEST_OK_SIZE=220 ;;
        # GPU:
        *manylinux*)     LARGEST_OK_SIZE=580 ;;

Here are the affected tests:
EOF
    while read dep; do
      echo "For dependency $dep:"
      # For every missing dependency, find the tests which directly depend on
      # it, and print that list for debugging. Not really clear if this is
      # helpful since the only examples I've seen are enormous.
      bazel cquery "rdeps(kind(py_test, $(cat $BATS_TEST_TMPDIR/deps)), $dep, 1)"

build --define tsl_protobuf_header_only=true

build --define=use_fast_cpp_protos=true
build --define=allow_oversize_protos=true

build --spawn_strategy=standalone
build -c opt

# Make Bazel print out all options from rc files.
build --announce_rc

# TODO(mihaimaruseac): Document this option or remove if no longer needed
build --define=grpc_no_ares=true