alibaba--mnn
wehub-resource-sync
84 行
1.6 KiB
Markdown
可执行文件
84 行
1.6 KiB
Markdown
可执行文件
## MNN.OpInfo
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```python
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class OpInfo
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```
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OpInfo是用来描述推理过程中一个执行层的具体信息的数据类型，其中包含了该层的Op类型，名称，计算量（flops)
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用法参考[runSessionWithCallBackInfo](Interpreter.html#runsessionwithcallbackinfo-session-begin-callback-end-callback)
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---
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### `OpInfo()`
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创建一个空OpInfo
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*在实际使用中创建空OpInfo没有意义，仅在`runSessionWithCallBackInfo`函数中用作返回信息*
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参数：
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- `None`
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返回：OpInfo对象
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返回类型：`OpInfo`
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---
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### `getName()`
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获取该层的名称
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参数：
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- `None`
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返回：该层的名称
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返回类型：`str`
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---
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### `getType()`
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获取该层的算子类型
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参数：
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- `None`
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返回：该层的算子类型
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返回类型：`str`
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---
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### `getFlops()`
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获取该层的计算量
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参数：
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- `None`
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返回：该层的计算量
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返回类型：`float`
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---
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### `Example`
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```python
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import MNN
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interpreter = MNN.Interpreter("mobilenet_v1.mnn")
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session = interpreter.createSession()
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# set input
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# ...
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def begin_callback(tensors, opinfo):
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print('layer name = ', opinfo.getName())
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print('layer op = ', opinfo.getType())
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# print('layer flops = ', opinfo.getFlops())
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for tensor in tensors:
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print(tensor.getShape())
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return True
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def end_callback(tensors, opinfo):
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print('layer name = ', opinfo.getName())
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print('layer op = ', opinfo.getType())
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# print('layer flops = ', opinfo.getFlops())
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for tensor in tensors:
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print(tensor.getShape())
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return True
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interpreter.runSessionWithCallBackInfo(session, begin_callback, end_callback)
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``` |