Struct TraceSession 

pub struct TraceSession { /* private fields */ }

Streaming trace session writing TensorFlow-Profiler-style span JSONL.

Implementations

impl TraceSession

pub fn open(path: impl AsRef<Path>, run: ProfileRun) -> Result<Self>

Open a trace and own its single root span until Self::finish.

pub fn begin_span( &self, name: impl Into<String>, kind: SpanKind, ) -> SpanGuard<'_>

Begin a nested span; parent is the top of the session span stack (TF Profiler call tree).

pub fn begin_measurement(&self, name: impl Into<String>) -> SpanGuard<'_>

Begin the single caller-controlled region used for total-time comparisons.

pub fn begin_step_span( &self, name: impl Into<String>, step: ExecutionStep, kind: SpanKind, ) -> SpanGuard<'_>

Begin a span tagged with a PyTorch-style training step (forward / backward / optimizer).

pub fn elapsed_ns(&self) -> u64

pub fn record_op(&self, span_id: SpanId, op: OpRecord<'_>) -> Result<()>

Record a timed op observation attached to span_id.

pub fn record_tensor( &self, span_id: SpanId, tensor: TensorRecord<'_>, ) -> Result<()>

Record tensor metadata and an allocation event.

pub fn record_memory_alloc( &self, span_id: SpanId, mem: MemoryRecord<'_>, ) -> Result<()>

Record an explicit tensor allocation (TensorFlow memory timeline).

pub fn record_memory_free( &self, span_id: SpanId, mem: MemoryRecord<'_>, ) -> Result<()>

Record an explicit tensor deallocation.

pub fn record_device_memory( &self, device: impl Into<String>, used_bytes: u64, free_bytes: u64, timestamp_ns: Option<u64>, ) -> Result<()>

Record a device-level memory checkpoint (cudaMemGetInfo-style).

pub fn record_gradient( &self, root: impl Into<String>, key: impl Into<String>, state: GradientState, norm: Option<f64>, ) -> Result<()>

Record one parameter gradient fact from a probe run.

pub fn flush(&self) -> Result<()>

pub fn finish(self) -> Result<PathBuf>

Close the owned root span, flush, and return the trace path.