# profile

Source: https://www.tensorplay.cn/docs/generated/tensorplay.profiler.profile.html

```python
class tensorplay.profiler.profile(enabled=True, *, activities=None, schedule=None, on_trace_ready=None, record_shapes=False, profile_memory=False, with_stack=False, with_flops=False, with_modules=False, use_device=None, gpu_timing=None, gpu_trace=None, with_samples=False)
```

Context manager that records dispatched operations and annotations.

```python
device_kernels(sort_by=None)
```

What the device ran, by the name the device knows it by.

```python
property device_time_by_span
```

For each collected span, the device time of the work inside it.

The per-span answer, for a caller that has a span and wants what it cost
on the device rather than what it cost to ask for.

```python
kineto_results()
```

The device’s own record of what it did, in a form meant to be read.

Named for what it is rather than for how it was collected: a caller
wants the device’s work, wants to know which piece of it belongs to which
operation, and wants the two joined by something exact.  What the
collector gathered is exactly that, so it is handed over as records that
answer those questions, and the join is already made rather than left to
the caller to reconstruct.

```python
step()
```

Advance the configured step schedule.