Export of internal Abseil changes.
-- ba4dd47492748bd630462eb68b7959037fc6a11a by Abseil Team <absl-team@google.com>: Work around nvcc 9.0 compiler bug for open-source Tensorflow build. With the current implementation, when I (unintentionally and transitively) include absl/types/optional.h in a CUDA compilation unit, I get the following nvcc error message: INFO: From Compiling tensorflow/core/kernels/crop_and_resize_op_gpu.cu.cc: external/com_google_absl/absl/types/optional.h: In member function 'void absl::optional_internal::optional_data_dtor_base<T, <anonymous> >::destruct()': external/com_google_absl/absl/types/optional.h:185:50: error: '__T0' was not declared in this scope data_.~T(); I've also seen similar compilation failures online, for flat_hash_map: https://devtalk.nvidia.com/default/topic/1042599/nvcc-preprocessor-bug-causes-compilation-failure/ The bug is always around unnamed template parameters. Therefore, the workaround is to make them named. PiperOrigin-RevId: 219208288 -- dad2f40cb2e8d5017660985ef6fb57f3c3cdcc80 by CJ Johnson <johnsoncj@google.com>: Adds internal macros for catching and throwing unknown exception types PiperOrigin-RevId: 219207362 -- 0a9840328d2d86e8420b853435fdbf1f7a19d931 by Abseil Team <absl-team@google.com>: Fix typo in mutex.h comments. PiperOrigin-RevId: 219199397 -- 0d576dc7597564210bfdf91518075064756f0bf4 by Matt Calabrese <calabrese@google.com>: Internal change. PiperOrigin-RevId: 219185475 -- 66be156095571959fb19a76da8ad0b53ec37658e by Abseil Team <absl-team@google.com>: Fix alignment conformance for VS 2017 >= 15.8 (fix #193) PiperOrigin-RevId: 219129894 -- a6e1825a12587945f8194677ccfdcaba6f7aad1d by Abseil Team <absl-team@google.com>: Reapply PR #173 PiperOrigin-RevId: 219129361 -- cf72ade4881b25acc6ccaea468f69793a0fdce32 by Abseil Team <absl-team@google.com>: Update .gitignore PiperOrigin-RevId: 219127495 -- 0537490c6348a2cb489abe15638928ac5aa6982a by Jon Cohen <cohenjon@google.com>: Small refactor and reformat of error messages from the exception safety test framework. PiperOrigin-RevId: 218927773 -- 4c556ca45fa25698ad12002a00c713aeceefab73 by CJ Johnson <johnsoncj@google.com>: Updates the inlined vector swap tests to check for number of moves that took place if available PiperOrigin-RevId: 218900777 -- dcbfda0021a1e6dfa9586986b1269c06ec394053 by Mark Barolak <mbar@google.com>: Add parens around calls to std::numeric_limits<>::min and std::numeric_limits<>::max to prevent compilation errors on Windows platforms where min and max are defined as macros. PiperOrigin-RevId: 218888700 GitOrigin-RevId: ba4dd47492748bd630462eb68b7959037fc6a11a Change-Id: I0e393958eb8cb501b85f6114979f6d4d86ed996c
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20 changed files with 147 additions and 110 deletions
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@ -48,14 +48,15 @@ list(APPEND CONTAINER_INTERNAL_HEADERS
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)
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absl_header_library(
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absl_library(
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TARGET
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absl_container
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SOURCES
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"internal/raw_hash_set.cc"
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EXPORT_NAME
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container
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)
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#
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## TESTS
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#
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@ -162,3 +163,15 @@ absl_test(
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PUBLIC_LIBRARIES
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${TEST_INSTANCE_TRACKER_TEST_PUBLIC_LIBRARIES}
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)
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absl_test(
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TARGET
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raw_hash_set_test
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SOURCES
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"internal/raw_hash_set_test.cc"
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PUBLIC_LIBRARIES
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absl::base
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absl::hash
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absl_internal_throw_delegate
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test_instance_tracker_lib
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)
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@ -188,7 +188,7 @@ class FixedArray {
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// `FixedArray<T>`. This is equivalent to the most possible addressable bytes
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// over the number of bytes taken by T.
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constexpr size_type max_size() const {
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return std::numeric_limits<difference_type>::max() / sizeof(value_type);
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return (std::numeric_limits<difference_type>::max)() / sizeof(value_type);
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}
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// FixedArray::empty()
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@ -264,7 +264,7 @@ class InlinedVector {
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// One bit of the size storage is used to indicate whether the inlined
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// vector is allocated; as a result, the maximum size of the container that
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// we can express is half of the max for our size type.
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return std::numeric_limits<size_type>::max() / 2;
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return (std::numeric_limits<size_type>::max)() / 2;
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}
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// InlinedVector::data()
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@ -906,6 +906,8 @@ TYPED_TEST_P(InstanceTest, Swap) {
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InstanceTracker tracker;
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InstanceVec a, b;
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const size_t inlined_capacity = a.capacity();
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auto min_len = std::min(l1, l2);
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auto max_len = std::max(l1, l2);
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for (int i = 0; i < l1; i++) a.push_back(Instance(i));
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for (int i = 0; i < l2; i++) b.push_back(Instance(100+i));
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EXPECT_EQ(tracker.instances(), l1 + l2);
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@ -919,15 +921,15 @@ TYPED_TEST_P(InstanceTest, Swap) {
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EXPECT_EQ(tracker.swaps(), 0); // Allocations are swapped.
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EXPECT_EQ(tracker.moves(), 0);
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} else if (a.size() <= inlined_capacity && b.size() <= inlined_capacity) {
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EXPECT_EQ(tracker.swaps(), std::min(l1, l2));
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// TODO(bsamwel): This should use moves when the type is movable.
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EXPECT_EQ(tracker.copies(), std::max(l1, l2) - std::min(l1, l2));
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EXPECT_EQ(tracker.swaps(), min_len);
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EXPECT_EQ((tracker.moves() ? tracker.moves() : tracker.copies()),
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max_len - min_len);
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} else {
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// One is allocated and the other isn't. The allocation is transferred
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// without copying elements, and the inlined instances are copied/moved.
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EXPECT_EQ(tracker.swaps(), 0);
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// TODO(bsamwel): This should use moves when the type is movable.
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EXPECT_EQ(tracker.copies(), std::min(l1, l2));
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EXPECT_EQ((tracker.moves() ? tracker.moves() : tracker.copies()),
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min_len);
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}
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EXPECT_EQ(l1, b.size());
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@ -139,7 +139,7 @@ struct Alloc : std::allocator<T> {
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friend bool operator!=(const Alloc& a, const Alloc& b) { return !(a == b); }
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private:
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size_t id_ = std::numeric_limits<size_t>::max();
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size_t id_ = (std::numeric_limits<size_t>::max)();
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};
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template <class Map>
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@ -477,7 +477,7 @@ inline size_t NormalizeCapacity(size_t n) {
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constexpr size_t kMinCapacity = Group::kWidth - 1;
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return n <= kMinCapacity
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? kMinCapacity
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: std::numeric_limits<size_t>::max() >> LeadingZeros(n);
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: (std::numeric_limits<size_t>::max)() >> LeadingZeros(n);
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}
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// The node_handle concept from C++17.
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@ -1022,7 +1022,7 @@ class raw_hash_set {
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bool empty() const { return !size(); }
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size_t size() const { return size_; }
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size_t capacity() const { return capacity_; }
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size_t max_size() const { return std::numeric_limits<size_t>::max(); }
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size_t max_size() const { return (std::numeric_limits<size_t>::max)(); }
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void clear() {
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// Iterating over this container is O(bucket_count()). When bucket_count()
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