ArrayRef<int64_t> bounds = hlo::encodingToBounds(input_ty.getEncoding());
    // The input type has bounded dynamic dimension.
    if (!bounds.empty()) {
      SmallVector<int64_t> new_bounds(bounds.begin(), bounds.end());
      SmallVector<int64_t> new_shape(shape.begin(), shape.end());
      // If dimension of the input type is dynamic. Update the
      // bounds of the dim with the new type if needed.

  return absl::InvalidArgumentError(
      absl::StrCat("found ", kDeviceTPUSystem, " devices with conflicting ",
                   attribute, "s '", a, "' and '", b, "'"));
}

// Find TPU_SYSTEM:0 devices in `devices`. If multiple TPU_SYSTEM devices are
// found, the first one lexicographically is returned. If no TPU_SYSTEM device
// is found or if there are multiple TPU_SYSTEM devices with different jobs or

		defer func() {
			cache.updatedAt = time.Now()
			store.unlock()
		}()

		_, found := cache.iamUsersMap[accessKey]

		// Check for regular user access key
		if !found {
			err = store.loadUser(ctx, accessKey, regUser, cache.iamUsersMap)
			if _, found = cache.iamUsersMap[accessKey]; found {
				// load mapped policies

build:linux --copt="-Wno-all"
build:linux --copt="-Wno-extra"
build:linux --copt="-Wno-deprecated"
build:linux --copt="-Wno-deprecated-declarations"
build:linux --copt="-Wno-ignored-attributes"
build:linux --copt="-Wno-array-bounds"

# Add unused-result as an error on Linux.
build:linux --copt="-Wunused-result"
build:linux --copt="-Werror=unused-result"
# Add switch as an error on Linux.
build:linux --copt="-Wswitch"

	for addr < lastAddr {
		// Find the last symbol we'd write.
		idx := -1
		for i, s := range syms {
			if ldr.AttrSubSymbol(s) {
				continue
			}

			// If the next symbol's size would put us out of bounds on the total length,
			// stop looking.
			end := ldr.SymValue(s) + ldr.SymSize(s)
			if end > lastAddr {
				break
			}

			// We're gonna write this symbol.
			idx = i

        quant_parameters) {
  auto type = mlir::cast<TensorType>(value.getType());

  // TFLite requires tensor shape only for the inputs and constants.
  // However, we output all known shapes for better round-tripping
  auto check_shape =
      [&](llvm::ArrayRef<int64_t> shape_ref) -> mlir::LogicalResult {
    auto is_out_of_range = [](int64_t dim) {
      return dim > std::numeric_limits<int32_t>::max();
    };