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!13502 Modify Profiler API example to a executable scripts 

From: @gzhcv
Reviewed-by: @yelihua
Signed-off-by:
This commit is contained in:
mindspore-ci-bot 2021-03-19 11:27:18 +08:00 committed by Gitee
parent caaff9ab03 95b7a6bcfb
commit 6c096bff31
1 changed files with 40 additions and 18 deletions
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58
mindspore/profiler/profiling.py
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@ -65,14 +65,45 @@ class Profiler:
This parameter is used to support offline parsing. This parameter is used to support offline parsing.
Examples: Examples:
>>> import numpy as np
>>> from mindspore import nn, context
>>> from mindspore.train import Model
>>> import mindspore.dataset as ds
>>> from mindspore.profiler import Profiler >>> from mindspore.profiler import Profiler
>>> import mindspore.context >>>
>>> context.set_context(mode=context.GRAPH_MODE, device_target="Ascend", >>>
>>> device_id=int(os.environ["DEVICE_ID"])) >>> class Net(nn.Cell):
>>> profiler = Profiler() ... def __init__(self):
>>> model = Model() ... super(Net, self).__init__()
>>> model.train() ... self.fc = nn.Dense(2,2)
>>> profiler.analyse() ... def construct(self, x):
... return self.fc(x)
>>>
>>> def generator():
... for i in range(2):
... yield (np.ones([2, 2]).astype(np.float32), np.ones([2]).astype(np.int32))
>>>
>>> def train(net):
... optimizer = nn.Momentum(net.trainable_params(), 1, 0.9)
... loss = nn.SoftmaxCrossEntropyWithLogits(sparse=True)
... data = ds.GeneratorDataset(generator, ["data", "label"])
... model = Model(net, loss, optimizer)
... model.train(1, data)
>>>
>>> if __name__ == '__main__':
... # If the device_target is GPU, set the device_target to "GPU"
... context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
...
... # Init Profiler
... # Note that the Profiler should be initialized after context.set_context and before model.train
... profiler = Profiler()
...
... # Train Model
... net = Net()
... train(net)
...
... # Profiler end
... profiler.analyse()
""" """
_hwts_output_filename_target = "output_format_data_hwts_" _hwts_output_filename_target = "output_format_data_hwts_"
@ -83,6 +114,7 @@ class Profiler:
# get device_id and device_target # get device_id and device_target
self._get_devid_and_devtarget() self._get_devid_and_devtarget()
self._get_output_path(kwargs) self._get_output_path(kwargs)
os.environ['PROFILING_MODE'] = 'true' os.environ['PROFILING_MODE'] = 'true'
os.environ['MINDDATA_PROFILING_DIR'] = self._output_path os.environ['MINDDATA_PROFILING_DIR'] = self._output_path
@ -154,17 +186,7 @@ class Profiler:
def analyse(self): def analyse(self):
""" """
Collect and analyse performance data, called after training or during training. Collect and analyse performance data, called after training or during training. The example shows above.
Examples:
>>> from mindspore.profiler import Profiler
>>> import mindspore.context
>>> context.set_context(mode=context.GRAPH_MODE, device_target="Ascend",
>>> device_id=int(os.environ["DEVICE_ID"]))
>>> profiler = Profiler()
>>> model = Model()
>>> model.train()
>>> profiler.analyse()
""" """
self._cpu_profiler.stop() self._cpu_profiler.stop()
if self._device_target and self._device_target == "GPU": if self._device_target and self._device_target == "GPU":