Use OpStats combiner in profiler_wrapper.cc
PiperOrigin-RevId: 333350927 Change-Id: Idb7bb344253f32326dbddf290e68f23a41827d6c
This commit is contained in:
A. Unique TensorFlower
TensorFlower Gardener
parent
a57895321e
commit
8c30da064f
@ -232,6 +232,7 @@ cc_library(
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hdrs = ["xplane_to_op_stats.h"],
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deps = [
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":op_metrics_db_combiner",
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":op_stats_combiner",
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":step_events_to_steps_db",
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":xplane_to_kernel_stats_db",
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":xplane_to_op_metrics_db",
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@ -249,6 +250,7 @@ cc_library(
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"//tensorflow/core/profiler/utils:event_span",
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"//tensorflow/core/profiler/utils:hardware_type_utils",
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"//tensorflow/core/profiler/utils:kernel_stats_utils",
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"//tensorflow/core/profiler/utils:step_intersection",
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"//tensorflow/core/profiler/utils:tf_op_utils",
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"//tensorflow/core/profiler/utils:tf_xplane_visitor",
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"//tensorflow/core/profiler/utils:xplane_schema",
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@ -22,6 +22,7 @@ limitations under the License.
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#include "tensorflow/core/platform/env.h"
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#include "tensorflow/core/platform/types.h"
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#include "tensorflow/core/profiler/convert/op_metrics_db_combiner.h"
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#include "tensorflow/core/profiler/convert/op_stats_combiner.h"
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#include "tensorflow/core/profiler/convert/step_events_to_steps_db.h"
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#include "tensorflow/core/profiler/convert/xplane_to_kernel_stats_db.h"
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#include "tensorflow/core/profiler/convert/xplane_to_op_metrics_db.h"
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@ -38,6 +39,7 @@ limitations under the License.
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#include "tensorflow/core/profiler/utils/event_span.h"
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#include "tensorflow/core/profiler/utils/hardware_type_utils.h"
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#include "tensorflow/core/profiler/utils/kernel_stats_utils.h"
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#include "tensorflow/core/profiler/utils/step_intersection.h"
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#include "tensorflow/core/profiler/utils/tf_op_utils.h"
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#include "tensorflow/core/profiler/utils/tf_xplane_visitor.h"
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#include "tensorflow/core/profiler/utils/xplane_schema.h"
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@ -202,5 +204,44 @@ OpStats ConvertXSpaceToOpStats(const XSpace& space,
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return op_stats;
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}
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Status ConvertMultiXSpacesToCombinedOpStats(
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const std::vector<std::string>& xspace_paths, const OpStatsOptions& options,
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OpStats* combined_op_stats) {
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// A shortcut code path for a single XSpace. There is no need to merge OpStats
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// if there is only a single XSpace.
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if (xspace_paths.size() == 1) {
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XSpace xspace;
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Status status = ReadBinaryProto(Env::Default(), xspace_paths[0], &xspace);
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if (!status.ok()) return status;
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*combined_op_stats = ConvertXSpaceToOpStats(xspace, options);
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return Status::OK();
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}
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// Read multiple XSpaces and convert to multiple OpStats.
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std::vector<OpStats> all_op_stats;
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for (const std::string& xspace_path : xspace_paths) {
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XSpace xspace;
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Status status = ReadBinaryProto(Env::Default(), xspace_path, &xspace);
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if (!status.ok()) return status;
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all_op_stats.push_back(ConvertXSpaceToOpStats(xspace, options));
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}
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// Combine OpStats.
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std::vector<OpStatsInfo> all_op_stats_info;
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all_op_stats_info.reserve(all_op_stats.size());
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for (int i = 0; i < all_op_stats.size(); i++) {
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all_op_stats_info.emplace_back(
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&all_op_stats[i],
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ParseHardwareType(all_op_stats[i].run_environment().device_type()), i);
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}
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// Do not limit the maximum number of steps during the merge of OpStats.
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StepIntersection step_intersection =
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ComputeStepIntersectionToMergeOpStats(all_op_stats_info, kuint32max);
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CombineAllOpStats(all_op_stats_info, step_intersection, combined_op_stats);
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return Status::OK();
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}
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} // namespace profiler
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} // namespace tensorflow
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@ -17,6 +17,7 @@ limitations under the License.
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#define TENSORFLOW_CORE_PROFILER_CONVERT_XPLANE_TO_OP_STATS_H_
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#include "absl/container/flat_hash_set.h"
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#include "tensorflow/core/platform/status.h"
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#include "tensorflow/core/profiler/protobuf/op_stats.pb.h"
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#include "tensorflow/core/profiler/protobuf/xplane.pb.h"
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@ -45,6 +46,14 @@ PerfEnv MakePerfEnv(double peak_tera_flops_per_second,
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// Extracts PerfEnv from XPlane stats.
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PerfEnv GetPerfEnvFromXPlane(const XPlane& device_plane);
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// Reads multiple XSpaces from <xspace_paths>, convert them to OpStats, and
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// combine them to a single OpStats in <combined_op_stats>.
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// Return the first error status during conversion, or return Status::OK() if
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// there is no error.
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Status ConvertMultiXSpacesToCombinedOpStats(
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const std::vector<std::string>& xspace_paths, const OpStatsOptions& options,
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OpStats* combined_op_stats);
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} // namespace profiler
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} // namespace tensorflow
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@ -16,6 +16,9 @@ limitations under the License.
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#include "tensorflow/core/profiler/convert/xplane_to_op_stats.h"
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#include "absl/strings/str_cat.h"
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#include "tensorflow/core/platform/env.h"
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#include "tensorflow/core/platform/path.h"
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#include "tensorflow/core/platform/status.h"
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#include "tensorflow/core/platform/test.h"
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#include "tensorflow/core/platform/types.h"
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#include "tensorflow/core/profiler/protobuf/diagnostics.pb.h"
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@ -175,6 +178,86 @@ TEST(ConvertXPlaneToOpStats, PropagateAndDedupErrors) {
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EXPECT_EQ(kError, op_stats.diagnostics().errors(/*index=*/0));
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}
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// Helper function to build a XSpace and store it to test directory.
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void BuildAndStoreXSpaceForTest(Env* test_env, const std::string& test_dir,
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const std::string& xspace_name) {
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constexpr int64 kStepNum = 123;
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constexpr int64 kStepId = 456;
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// Create a host only XSpace for test.
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XSpace xspace;
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XPlaneBuilder host_plane_builder(GetOrCreateHostXPlane(&xspace));
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host_plane_builder.ReserveLines(2);
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auto main_thread = host_plane_builder.GetOrCreateLine(0);
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CreateXEvent(&host_plane_builder, &main_thread, HostEventType::kTraceContext,
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0, 100, {{StatType::kStepNum, kStepNum}});
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CreateXEvent(&host_plane_builder, &main_thread, HostEventType::kFunctionRun,
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10, 90, {{StatType::kStepId, kStepId}});
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auto executor_thread = host_plane_builder.GetOrCreateLine(1);
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CreateXEvent(&host_plane_builder, &executor_thread,
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HostEventType::kExecutorStateProcess, 20, 80,
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{{StatType::kStepId, kStepId}});
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// Create a TensorFlow op that runs for 70 ps.
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CreateXEvent(&host_plane_builder, &executor_thread, "aaa:bbb", 30, 70);
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GroupTfEvents(&xspace, /*group_metadata_map=*/nullptr);
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TF_CHECK_OK(
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WriteBinaryProto(test_env, io::JoinPath(test_dir, xspace_name), xspace))
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<< "Failed to write binary XSpace to file: " << xspace_name;
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}
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TEST(ConvertXPlaneToOpStats, TestConvertMultiXSpacesToCombinedOpStats) {
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// Initialize environment and directory for testing.
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Env* test_env = Env::Default();
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std::string test_dir = io::JoinPath(testing::TmpDir(), "test_dir");
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TF_CHECK_OK(test_env->CreateDir(test_dir))
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<< "Failed to create test directory: " << test_dir;
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const std::string xspace1 = "xspace1.pb";
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const std::string xspace2 = "xspace2.pb";
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BuildAndStoreXSpaceForTest(test_env, test_dir, xspace1);
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BuildAndStoreXSpaceForTest(test_env, test_dir, xspace2);
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std::vector<std::string> xspace_paths;
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xspace_paths.push_back(io::JoinPath(test_dir, xspace1));
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xspace_paths.push_back(io::JoinPath(test_dir, xspace2));
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OpStatsOptions options;
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options.generate_op_metrics_db = true;
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options.generate_step_db = true;
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OpStats combined_op_stats;
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TF_CHECK_OK(ConvertMultiXSpacesToCombinedOpStats(xspace_paths, options,
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&combined_op_stats))
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<< "Failed to convert multi XSpace to OpStats";
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// Result OpStats has 2 Host Ops, "IDLE" and "aaa:bbb".
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ASSERT_EQ(combined_op_stats.host_op_metrics_db().metrics_db_size(), 2);
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const auto& metric = combined_op_stats.host_op_metrics_db().metrics_db(1);
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EXPECT_EQ(metric.name(), "aaa");
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EXPECT_EQ(metric.category(), "bbb");
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// Each host has the HostOp "aaa:bbb" running for 70 ps, so the combined
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// OpStats has "aaa:bbb" running for 140 ps in total.
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EXPECT_EQ(metric.self_time_ps(), 140);
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// Result OpStats has 1 step, 2 cores.
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ASSERT_EQ(combined_op_stats.step_db().step_sequence_size(), 1);
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ASSERT_EQ(
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combined_op_stats.step_db().step_sequence(0).step_info_per_core_size(),
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2);
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const auto& step_info_per_core =
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combined_op_stats.step_db().step_sequence(0).step_info_per_core();
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// global_core_id is computed using: 1000 * host_id + local_core_id.
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EXPECT_TRUE(step_info_per_core.contains(1));
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EXPECT_TRUE(step_info_per_core.contains(1001));
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// Tear down environment and directory for testing.
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int64 undeleted_files, undeleted_dirs;
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TF_CHECK_OK(
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test_env->DeleteRecursively(test_dir, &undeleted_files, &undeleted_dirs))
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<< "Failed to delete test directory: " << test_dir;
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}
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} // namespace
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} // namespace profiler
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} // namespace tensorflow
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@ -127,6 +127,8 @@ tf_python_pybind_extension(
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"//tensorflow/core/profiler/convert:xplane_to_op_stats",
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"//tensorflow/core/profiler/convert:xplane_to_trace_events",
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"//tensorflow/core/profiler/lib:profiler_session_headers",
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"//tensorflow/core/profiler/protobuf:op_stats_proto_cc",
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"//tensorflow/core/profiler/protobuf:xplane_proto_cc",
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"//tensorflow/core/profiler/rpc:profiler_server_headers",
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"//tensorflow/core/profiler/rpc/client:capture_profile",
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"//tensorflow/core/profiler/rpc/client:save_profile",
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@ -18,8 +18,10 @@ limitations under the License.
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#include "absl/memory/memory.h"
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#include "absl/strings/match.h"
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#include "absl/strings/numbers.h"
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#include "pybind11/cast.h"
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#include "pybind11/pybind11.h"
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#include "pybind11/pytypes.h"
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#include "tensorflow/core/platform/env.h"
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#include "tensorflow/core/platform/errors.h"
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#include "tensorflow/core/platform/status.h"
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#include "tensorflow/core/platform/types.h"
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@ -32,6 +34,8 @@ limitations under the License.
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#include "tensorflow/core/profiler/lib/profiler_session.h"
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#include "tensorflow/core/profiler/protobuf/input_pipeline.pb.h"
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#include "tensorflow/core/profiler/protobuf/kernel_stats.pb.h"
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#include "tensorflow/core/profiler/protobuf/op_stats.pb.h"
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#include "tensorflow/core/profiler/protobuf/xplane.pb.h"
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#include "tensorflow/core/profiler/rpc/client/capture_profile.h"
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#include "tensorflow/core/profiler/rpc/client/save_profile.h"
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#include "tensorflow/core/profiler/rpc/profiler_server.h"
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@ -114,6 +118,15 @@ class ProfilerSessionWrapper {
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tensorflow::string logdir_;
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};
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// Converts a pybind list of XSpace paths to a cpp vector.
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std::vector<std::string> GetXSpacePaths(const py::list& python_paths) {
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std::vector<std::string> cpp_paths;
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for (py::handle obj : python_paths) {
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cpp_paths.push_back(std::string(py::cast<py::str>(obj)));
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}
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return cpp_paths;
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}
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} // namespace
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PYBIND11_MODULE(_pywrap_profiler, m) {
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@ -171,71 +184,121 @@ PYBIND11_MODULE(_pywrap_profiler, m) {
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return content;
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});
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m.def("xspace_to_trace_events", [](const py::bytes& serialized_xspace_proto) {
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tensorflow::string content;
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m.def("xspace_to_trace_events", [](const py::list& xspace_path_list) {
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std::vector<std::string> xspace_paths = GetXSpacePaths(xspace_path_list);
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if (xspace_paths.size() != 1) {
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LOG(WARNING) << "Trace events tool expects only 1 XSpace path but gets "
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<< xspace_paths.size();
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return py::make_tuple(py::bytes(), py::bool_(false));
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}
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tensorflow::profiler::XSpace xspace;
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xspace.ParseFromString(std::string(serialized_xspace_proto));
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tensorflow::Status status = tensorflow::ReadBinaryProto(
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tensorflow::Env::Default(), xspace_paths[0], &xspace);
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if (!status.ok()) {
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LOG(WARNING) << "Could not read XSpace for trace events: "
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<< xspace_paths[0];
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return py::make_tuple(py::bytes(), py::bool_(false));
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}
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tensorflow::string content;
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tensorflow::profiler::ConvertXSpaceToTraceEventsString(xspace, &content);
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return py::bytes(content);
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return py::make_tuple(py::bytes(content), py::bool_(true));
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});
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m.def("xspace_to_overview_page",
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[](const py::bytes& serialized_xspace_proto) {
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tensorflow::profiler::XSpace xspace;
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xspace.ParseFromString(std::string(serialized_xspace_proto));
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tensorflow::profiler::OpStatsOptions options;
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options.generate_kernel_stats_db = true;
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options.generate_op_metrics_db = true;
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options.generate_step_db = true;
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// TODO(profiler): xspace should tell whether this is sampling mode.
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tensorflow::profiler::OverviewPage overview_page =
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tensorflow::profiler::ConvertOpStatsToOverviewPage(
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ConvertXSpaceToOpStats(xspace, options));
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return py::bytes(overview_page.SerializeAsString());
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});
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m.def("xspace_to_overview_page", [](const py::list& xspace_path_list) {
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std::vector<std::string> xspace_paths = GetXSpacePaths(xspace_path_list);
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tensorflow::profiler::OpStatsOptions options;
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options.generate_kernel_stats_db = true;
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options.generate_op_metrics_db = true;
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options.generate_step_db = true;
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tensorflow::profiler::OpStats combined_op_stats;
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tensorflow::Status status = ConvertMultiXSpacesToCombinedOpStats(
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xspace_paths, options, &combined_op_stats);
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if (!status.ok()) {
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LOG(WARNING) << "Could not generate OpStats for overview page. Error: "
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<< status.error_message();
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return py::make_tuple(py::bytes(), py::bool_(false));
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}
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// TODO(profiler): xspace should tell whether this is sampling mode.
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tensorflow::profiler::OverviewPage overview_page =
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tensorflow::profiler::ConvertOpStatsToOverviewPage(combined_op_stats);
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return py::make_tuple(py::bytes(overview_page.SerializeAsString()),
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py::bool_(true));
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});
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m.def("xspace_to_input_pipeline",
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[](const py::bytes& serialized_xspace_proto) {
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tensorflow::profiler::XSpace xspace;
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xspace.ParseFromString(std::string(serialized_xspace_proto));
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tensorflow::profiler::OpStatsOptions options;
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options.generate_op_metrics_db = true;
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options.generate_step_db = true;
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tensorflow::profiler::InputPipelineAnalysisResult input_pipeline =
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tensorflow::profiler::ConvertOpStatsToInputPipelineAnalysis(
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ConvertXSpaceToOpStats(xspace, options));
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return py::bytes(input_pipeline.SerializeAsString());
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});
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m.def("xspace_to_input_pipeline", [](const py::list& xspace_path_list) {
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std::vector<std::string> xspace_paths = GetXSpacePaths(xspace_path_list);
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tensorflow::profiler::OpStatsOptions options;
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options.generate_op_metrics_db = true;
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options.generate_step_db = true;
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tensorflow::profiler::OpStats combined_op_stats;
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tensorflow::Status status = ConvertMultiXSpacesToCombinedOpStats(
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xspace_paths, options, &combined_op_stats);
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if (!status.ok()) {
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LOG(WARNING) << "Could not generate OpStats for input pipeline. Error: "
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<< status.error_message();
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return py::make_tuple(py::bytes(), py::bool_(false));
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}
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tensorflow::profiler::InputPipelineAnalysisResult input_pipeline =
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tensorflow::profiler::ConvertOpStatsToInputPipelineAnalysis(
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combined_op_stats);
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return py::make_tuple(py::bytes(input_pipeline.SerializeAsString()),
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py::bool_(true));
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});
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m.def("xspace_to_tf_stats", [](const py::bytes& serialized_xspace_proto) {
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tensorflow::profiler::XSpace xspace;
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xspace.ParseFromString(std::string(serialized_xspace_proto));
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m.def("xspace_to_tf_stats", [](const py::list& xspace_path_list) {
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std::vector<std::string> xspace_paths = GetXSpacePaths(xspace_path_list);
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tensorflow::profiler::OpStatsOptions options;
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options.generate_op_metrics_db = true;
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options.generate_kernel_stats_db = true;
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tensorflow::profiler::OpStats combined_op_stats;
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tensorflow::Status status = ConvertMultiXSpacesToCombinedOpStats(
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xspace_paths, options, &combined_op_stats);
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if (!status.ok()) {
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LOG(WARNING) << "Could not generate OpStats for tensorflow stats. Error: "
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<< status.error_message();
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return py::make_tuple(py::bytes(), py::bool_(false));
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}
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tensorflow::profiler::TfStatsDatabase tf_stats_db =
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tensorflow::profiler::ConvertOpStatsToTfStats(
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ConvertXSpaceToOpStats(xspace, options));
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return py::bytes(tf_stats_db.SerializeAsString());
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tensorflow::profiler::ConvertOpStatsToTfStats(combined_op_stats);
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return py::make_tuple(py::bytes(tf_stats_db.SerializeAsString()),
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py::bool_(true));
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});
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m.def("xspace_to_kernel_stats", [](const py::bytes& serialized_xspace_proto) {
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tensorflow::profiler::XSpace xspace;
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xspace.ParseFromString(std::string(serialized_xspace_proto));
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m.def("xspace_to_kernel_stats", [](const py::list& xspace_path_list) {
|
||||
std::vector<std::string> xspace_paths = GetXSpacePaths(xspace_path_list);
|
||||
tensorflow::profiler::OpStatsOptions options;
|
||||
options.generate_kernel_stats_db = true;
|
||||
tensorflow::profiler::OpStats op_stats =
|
||||
ConvertXSpaceToOpStats(xspace, options);
|
||||
return py::bytes(op_stats.kernel_stats_db().SerializeAsString());
|
||||
tensorflow::profiler::OpStats combined_op_stats;
|
||||
tensorflow::Status status = ConvertMultiXSpacesToCombinedOpStats(
|
||||
xspace_paths, options, &combined_op_stats);
|
||||
if (!status.ok()) {
|
||||
LOG(WARNING) << "Could not generate OpStats for kernel stats. Error: "
|
||||
<< status.error_message();
|
||||
return py::make_tuple(py::bytes(), py::bool_(false));
|
||||
}
|
||||
return py::make_tuple(
|
||||
py::bytes(combined_op_stats.kernel_stats_db().SerializeAsString()),
|
||||
py::bool_(true));
|
||||
});
|
||||
|
||||
m.def("xspace_to_memory_profile",
|
||||
[](const py::bytes& serialized_xspace_proto) {
|
||||
tensorflow::profiler::XSpace xspace;
|
||||
xspace.ParseFromString(std::string(serialized_xspace_proto));
|
||||
std::string json_output;
|
||||
tensorflow::profiler::ConvertXSpaceToMemoryProfileJson(xspace,
|
||||
&json_output);
|
||||
return py::bytes(json_output);
|
||||
});
|
||||
m.def("xspace_to_memory_profile", [](const py::list& xspace_path_list) {
|
||||
std::vector<std::string> xspace_paths = GetXSpacePaths(xspace_path_list);
|
||||
if (xspace_paths.size() != 1) {
|
||||
LOG(WARNING) << "Memory profile tool expects only 1 XSpace path but gets "
|
||||
<< xspace_paths.size();
|
||||
return py::make_tuple(py::bytes(), py::bool_(false));
|
||||
}
|
||||
tensorflow::profiler::XSpace xspace;
|
||||
tensorflow::Status status = tensorflow::ReadBinaryProto(
|
||||
tensorflow::Env::Default(), xspace_paths[0], &xspace);
|
||||
if (!status.ok()) {
|
||||
LOG(WARNING) << "Could not read XSpace for memory profile: "
|
||||
<< xspace_paths[0];
|
||||
return py::make_tuple(py::bytes(), py::bool_(false));
|
||||
}
|
||||
std::string json_output;
|
||||
tensorflow::profiler::ConvertXSpaceToMemoryProfileJson(xspace,
|
||||
&json_output);
|
||||
return py::make_tuple(py::bytes(json_output), py::bool_(true));
|
||||
});
|
||||
};
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user