"@llvm-project//mlir:FuncDialect",
        "@llvm-project//mlir:IR",
        "@llvm-project//mlir:Pass",
    ],
)

cc_library(
    name = "embedding_pipelining",
    srcs = ["embedding_pipelining.cc"],
    hdrs = [
        "sparsecore_passes.h",
    ],
    deps = [
        ":sparsecore_passes_inc_gen",
        "//tensorflow/compiler/jit:flags_headers",

        # Restricting visibility for now
        "//tensorflow/c/experimental/saved_model/core:__subpackages__",
    ],
    licenses = ["notice"],
)

cc_library(
    name = "restore_ops",
    srcs = [
        "restore_ops.cc",
    ],
    hdrs = [
        "restore_ops.h",
    ],
    deps = [
        "//tensorflow/c:tensor_interface",
        "//tensorflow/c/eager:abstract_tensor_handle",

)

package(
    # copybara:uncomment default_applicable_licenses = ["//tensorflow:license"],
    default_visibility = ["//visibility:private"],
    licenses = ["notice"],
)

cc_library(
    name = "cpp",
    srcs = glob(
        ["*.cc"],
        exclude = ["*_test.cc"],
    ),
    hdrs = glob(["*.h"]),
    visibility = ["//tensorflow/c/experimental/ops/gen:__pkg__"],
    deps = [

)

package(
    # copybara:uncomment default_applicable_licenses = ["//tensorflow:license"],
    default_visibility = ["//visibility:private"],
    licenses = ["notice"],
)

cc_library(
    name = "renderers",
    srcs = glob(
        ["*.cc"],
        exclude = ["*_test.cc"],
    ),
    hdrs = glob(["*.h"]),
    visibility = ["//tensorflow/c/experimental/ops/gen/cpp:__pkg__"],
    deps = [

        "//tensorflow/python:__pkg__",
    ],
    licenses = ["notice"],
)

# copybara:uncomment_begin(google-only)
# tf_py_strict_test(
#     name = "tensorflow_to_stablehlo_test",
#     testonly = 1,
#     srcs = ["integration_test/tensorflow_to_stablehlo_test.py"],
#     deps = [
#         ":pywrap_tensorflow_to_stablehlo",
#         "//testing/pymocks:matchers",
#         "//third_party/py/mlir",

	dst0 := image.NewRGBA(image.Rect(0, 0, 100, 100))
	src0 := image.NewRGBA(image.Rect(0, 0, 100, 100))
	mask0 := image.NewRGBA(image.Rect(0, 0, 100, 100))
	for _, c := range clipTests {
		dst := dst0.SubImage(c.dr).(*image.RGBA)
		src := src0.SubImage(c.sr).(*image.RGBA)
		r, sp, mp := c.r, c.sp, c.mp
		if c.nilMask {
			clip(dst, &r, src, &sp, nil, nil)
		} else {
			clip(dst, &r, src, &sp, mask0.SubImage(c.mr), &mp)
		}

tf_cc_binary(
    name = "tfl_quantizer",
    srcs = [
        "tfl_quantizer.cc",
    ],
    deps = [
        ":quantize_model",
        "//tensorflow/compiler/mlir/lite/schema:schema_fbs",
        "//tensorflow/lite:framework",
        "//tensorflow/lite/c:c_api_types",
        "@llvm-project//llvm:Support",
    ],
)

tf_cc_test(
    name = "quantize_model_test",
    srcs = ["quantize_model_test.cc"],
    args = [

filegroup(
    name = "extra_files",
    srcs = glob(
        [
            "**/importer_test_min_max.cc.mlir",
            "**/reshape.mlir",
        ],
    ),
)

# A binary to inject min/max to a tflite model.
# A file check command is used to verify the imported result from this
# binary format.
tf_native_cc_binary(
    name = "importer_test_min_max",
    srcs = [
        "importer_test_min_max.cc",
    ],

package(
    # copybara:uncomment default_applicable_licenses = ["//tensorflow:license"],
    default_visibility = ["//visibility:public"],
    licenses = ["notice"],
)

cc_library(
    name = "freeze_saved_model",
    srcs = ["freeze_saved_model.cc"],
    hdrs = ["freeze_saved_model.h"],
    deps = [
        "//tensorflow/cc/saved_model:loader",
        "//tensorflow/core:core_cpu",
        "//tensorflow/core:lib",

package(
    # copybara:uncomment default_applicable_licenses = ["//tensorflow:license"],
    licenses = ["notice"],
)

tf_python_pybind_extension(
    name = "mlir_wrapper",
    srcs = [
        "attrs.cc",
        "basic_classes.cc",
        "builders.cc",
        "mlir_wrapper.cc",
        "mlir_wrapper.h",
        "ops.cc",
        "types.cc",
    ],
    enable_stub_generation = True,