polish the code

Author: zhangting2020

python/paddle/profiler/profiler.py

@@ -268,10 +268,10 @@ class Profiler:
  scheduler (Callable|tuple, optional): If it is a callable object, it takes a step number as parameter and return the corresponding :ref:`ProfilerState <api_paddle_profiler_ProfilerState>`. This callable object can be generated by :ref:`make_scheduler <api_paddle_profiler_make_scheduler>` function.
  If not provided (None), the default scheduler will keep tracing until the profiler exits. If it is a tuple, it has two values start_batch and end_batch,
  which means profiling range [start_batch, end_batch).
- on_trace_ready (callable): callable object, takes the Profiler object as parameter, which provides a way for users to do post-processing.
- This callable object will be called when ``scheduler`` returns ``ProfilerState.RECORD_AND_RETURN``.
- timer_only (bool): If it is True, the cost of Dataloader and every step of the model will be count without profiling. Otherwise, the model will
- be timed and profiled.
+ on_trace_ready (Callable, optional): Callable object, serves as callback function, and takes the Profiler object as parameter, which provides a way for users to do post-processing.
+ This callable object will be called when ``scheduler`` returns ``ProfilerState.RECORD_AND_RETURN``. The default value is :ref:`export_chrome_tracing <api_paddle_profiler_export_chrome_tracing>` (./profiler_log/).
+ timer_only (bool, optional): If it is True, the cost of Dataloader and every step of the model will be count without profiling. Otherwise, the model will
+ be timed and profiled. Default: False.
 
  Examples:
  1. profiling range [2, 5).
@@ -322,6 +322,7 @@ class Profiler:
  4. Use profiler to get throughput and cost of the model
 
  .. code-block:: python
+ :name: code-example-timer1
 
  import paddle
  import paddle.profiler as profiler
@@ -368,8 +369,19 @@ def forward(self, image, label=None):
  if i % 10 == 0:
  step_info = p.step_info(unit='images')
  print("Iter {}: {}".format(i, step_info))
+ # The average statistics for 10 steps between the last and this call will be
+ # printed when the "step_info" is called at 10 iteration intervals.
+ # The values you get may be different from the following.
+ # Iter 0: reader_cost: 0.51946 s batch_cost: 0.66077 s ips: 6.054 images/s
+ # Iter 10: reader_cost: 0.00014 s batch_cost: 0.00441 s ips: 907.009 images/s
  p.stop()
-
+ # The performance summary will be automatically printed when the "stop" is called.
+ # Reader Ratio: 2.658%
+ # Time Unit: s, IPS Unit: images/s
+ # | | avg | max | min |
+ # | reader_cost | 0.00011 | 0.00013 | 0.00007 |
+ # | batch_cost | 0.00405 | 0.00434 | 0.00326 |
+ # | ips | 1086.42904 | 1227.30604 | 959.92796 |
  """
 
  def __init__(
@@ -455,6 +467,7 @@ def start(self):
  #train()
  prof.step()
  prof.stop()
+
  '''
  # Timing only without profiling
  benchmark().begin()
@@ -519,7 +532,7 @@ def step(self, num_samples: Optional[int]=None):
  Signals the profiler that the next profiling step has started.
  Get the new ProfilerState and trigger corresponding action.
 
- Parameters:
+ Args:
  num_samples (int|None, optional): Specifies the batch size of every step of the model
  that is used to compute throughput when timer_only is True. Default: None.
 
@@ -569,7 +582,7 @@ def step_info(self, unit=None):
  or others depends on the `unit`. When `num_samples` of `step()` is None, it is
  measured in `steps/s`.
 
- Parameters:
+ Args:
  unit (string, optional): The unit of input data is only used When `num_samples`
  of `step()` is specified as a number. For example, when it is `images`, the unit
  of throughput is `images/s`. Default: None, the unit of throughput is `samples/s`.
@@ -578,6 +591,7 @@ def step_info(self, unit=None):
  string: A string representing the statistic.
  Examples:
  .. code-block:: python
+ :name: code-example-timer2
 
  import paddle.profiler as profiler
  prof = profiler.Profiler(timer_only=True)
@@ -586,8 +600,15 @@ def step_info(self, unit=None):
  #train()
  prof.step()
  if iter % 10 == 0:
- print(prof.step_info())
+ print("Iter {}: {}".format(iter, prof.step_info()))
+ # The example does not call the DataLoader, so there is no "reader_cost".
+ # Iter 0: batch_cost: 0.00001 s ips: 86216.623 steps/s
+ # Iter 10: batch_cost: 0.00001 s ips: 103645.034 steps/s
  prof.stop()
+ # Time Unit: s, IPS Unit: steps/s
+ # | | avg | max | min |
+ # | batch_cost | 0.00000 | 0.00002 | 0.00000 |
+ # | ips | 267846.19437 | 712030.38727 | 45134.16662 |
  """
  if unit is None:
  unit = 'samples'