)

load("@python//:defs.bzl", "interpreter")
load("@rules_python//python:pip.bzl", "package_annotation", "pip_parse")

NUMPY_ANNOTATIONS = {
    "numpy": package_annotation(
        additive_build_content = """\
filegroup(
    name = "includes",
    srcs = glob(["site-packages/numpy/core/include/**/*.h"]),
)
cc_library(
    name = "numpy_headers",
    hdrs = [":includes"],

        "//tensorflow/c/eager:c_api_experimental",
        "//tensorflow/c/eager:tfe_context_internal",
        "//tensorflow/core:framework",
        "//tensorflow/core:protos_all_cc",
        "//tensorflow/core:test",
        "//tensorflow/core:test_main",
        "//tensorflow/core/common_runtime/eager:context",
    ],
)

cc_library(
    name = "parallel_device_testlib",
    testonly = 1,

TFCI_MACOS_CROSS_COMPILE_ENABLE=1
TFCI_MACOS_CROSS_COMPILE_SDK_DEST="tensorflow/tools/toolchains/cross_compile/cc/MacOSX.sdk"
TFCI_MACOS_CROSS_COMPILE_SDK_SOURCE="/Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX.sdk"

        ":checkpoint_reader",
        ":tf_buffer",
        ":tf_buffer_internal",
        "//tensorflow/c/eager:c_api",
        "//tensorflow/c/eager:c_api_internal",
        "//tensorflow/c/eager:tfe_context_internal",
        "//tensorflow/c/eager:tfe_op_internal",
        "//tensorflow/c/eager:tfe_tensorhandle_internal",
        "//tensorflow/compiler/jit:flags",
        "//tensorflow/compiler/jit:get_compiler_ir",

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

        "//tensorflow/core:protos_all_cc",
    ],
)

cc_library(
    name = "immediate_execution_context",
    hdrs = ["immediate_execution_context.h"],
    visibility = [
        "//tensorflow:internal",
    ],
    deps = [
        ":abstract_context",
        ":immediate_execution_distributed_manager",
        ":immediate_execution_operation",
        ":immediate_execution_tensor_handle",

    *   It is available for immediate use.
        *   See the `TF_RUN_EAGER_OP_AS_FUNCTION` environment variable in
            [eager context](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/eager/context.py).
        *   Eager performance should be similar with this feature enabled.
            *   A roughly 5us per-op overhead may be observed when running many

        "//tensorflow/c/eager:c_api_experimental",
        "//tensorflow/c/eager:c_api_internal",
        "//tensorflow/c/eager:dlpack",
        "//tensorflow/c/eager:tape",
        "//tensorflow/c/eager:tfe_context_internal",
        "//tensorflow/c/eager:tfe_op_internal",
        "//tensorflow/c/eager:tfe_tensorhandle_internal",
        "//tensorflow/c/experimental/gradients",
        "//tensorflow/c/experimental/gradients/tape",

    name = "array_grad",
    srcs = ["array_grad.cc"],
    hdrs = [
        "array_grad.h",
    ],
    visibility = [
        "//tensorflow:internal",
    ],
    deps = [
        "//tensorflow/c/eager:abstract_context",
        "//tensorflow/c/eager:gradients_internal",
    ],
)

cc_library(
    name = "math_grad",
    srcs = ["math_grad.cc"],
    hdrs = [
        "math_grad.h",
    ],
    visibility = [

build:release_cpu_macos --config=avx_linux

# Base build configs for macOS
build:release_macos_base --action_env  DEVELOPER_DIR=/Applications/Xcode.app/Contents/Developer
build:release_macos_base --define=no_nccl_support=true --output_filter=^$

# Ensure release_base is set on mac
build:release_macos_base --config=release_base

# Build configs for macOS x86