)

# Add Keras module aliases
_losses = _KerasLazyLoader(globals(), submodule="losses", name="losses")
_metrics = _KerasLazyLoader(globals(), submodule="metrics", name="metrics")
_optimizers = _KerasLazyLoader(
    globals(), submodule="optimizers", name="optimizers")
_initializers = _KerasLazyLoader(
    globals(), submodule="initializers", name="initializers")
setattr(_current_module, "losses", _losses)

# Lazy-load Keras v1.
_tf_uses_legacy_keras = (
    _os.environ.get("TF_USE_LEGACY_KERAS", None) in ("true", "True", "1"))
setattr(_current_module, "keras", _KerasLazyLoader(globals(), mode="v1"))
_module_dir = _module_util.get_parent_dir_for_name("keras._tf_keras.keras")
_current_module.__path__ = [_module_dir] + _current_module.__path__
if _tf_uses_legacy_keras:

//
// WARNING: This is very subtle to use correctly. The caller must
// ensure that it's truly safe for p to not escape to the heap by
// maintaining runtime pointer invariants (for example, that globals
// and the heap may not generally point into a stack).
//
//go:nosplit
//go:nocheckptr
func NoEscape(p unsafe.Pointer) unsafe.Pointer {
	x := uintptr(p)
	return unsafe.Pointer(x ^ 0)
}

{
    "backend.maxHeapSizeMb": 2602,

    // https://youtrack.jetbrains.com/issue/FL-22276
    // Fleet cannot handle nested maven projects until FL-22276
    "ignored.project.globs": [
        "**/pom.xml"
    ]

# Prepare copy of libcrypto.a with only the checked functions renamed and exported.
# All other symbols are left alone and hidden.
echo BORINGSSL_bcm_power_on_self_test >>syms.txt
awk '{print "_goboringcrypto_" $0 }' syms.txt >globals.txt
awk '{print $0 " _goboringcrypto_" $0 }' syms.txt >renames.txt
objcopy --globalize-symbol=BORINGSSL_bcm_power_on_self_test \
	../boringssl/build/crypto/libcrypto.a libcrypto.a

// RUN: tf-opt %s --allow-unregistered-dialect --tf-saved-model-lower-globals-to-mlprogram --split-input-file --verify-diagnostics

module attributes {tf_saved_model.semantics} {
  "tf_saved_model.global_tensor"() { is_mutable, sym_name = "v", type = tensor<?xf32>, value = dense<1.> : tensor<1xf32> } : () -> ()
  "tf_saved_model.global_tensor"() { is_mutable, sym_name = "v1", type = tensor<?xf32>, value = dense<1.> : tensor<1xf32> } : () -> ()

	_, err := Glob(os.DirFS("."), "/*"+strings.Repeat("/", 10001))
	if err != path.ErrBadPattern {
		t.Fatalf("Glob returned err=%v, want %v", err, path.ErrBadPattern)
	}
}

type globOnly struct{ GlobFS }

func (globOnly) Open(name string) (File, error) { return nil, ErrNotExist }

func TestGlobMethod(t *testing.T) {
	check := func(desc string, names []string, err error) {
		t.Helper()

// RUN: tf-opt %s --allow-unregistered-dialect --tf-saved-model-lower-globals-to-mlprogram --split-input-file | FileCheck %s

// CHECK-LABEL: module
module attributes {tf_saved_model.semantics} {
  // CHECK: ml_program.global private mutable [[V:@.+]](dense<1.000000e+00> : tensor<1xf32>) : tensor<?xf32>
  // CHECK: func.func @f
  // CHECK: [[T:%.+]] = ml_program.global_load [[V]]

		accum = f(accum)
	}
	*y = accum
}

var (
	salt1 = 0
)

// The actual CPU hogging function.
// Must not call other functions nor access heap/globals in the loop,
// otherwise under race detector the samples will be in the race runtime.
func cpuHog1(x int) int {
	return cpuHog0(x, 1e5)
}

func cpuHog0(x, n int) int {
	foo := x
	for i := 0; i < n; i++ {

	ACALLNORESUME

	ARETUNWIND

	AMOVB
	AMOVH
	AMOVW
	AMOVD

	AWORD
	ALAST
)

const (
	REG_NONE = 0
)

const (
	// globals
	REG_SP = obj.RBaseWasm + iota // SP is currently 32-bit, until 64-bit memory operations are available
	REG_CTXT
	REG_g