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f2619b0546
* Refactor js submodule * Remove change-log * Update ocr module * Update ocr-detection module * Update ocr-detection module * Remove change-log
65 lines
1.6 KiB
Python
65 lines
1.6 KiB
Python
#!/usr/bin/env python
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# -*- coding: UTF-8 -*-
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# pruning op tensor and relatad op with no sense, like ShapeTensor and OutSize
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def pruningNoSenseTensor(model):
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global ops
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ops = model["ops"]
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global vars
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vars = model["vars"]
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for op in ops[:]:
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shapeTensor = op["inputs"].get("ShapeTensor")
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outSizeTensor = op["inputs"].get("OutSize")
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noSenseTensor = shapeTensor or outSizeTensor
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if not noSenseTensor:
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continue
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print(noSenseTensor)
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if shapeTensor:
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del op["inputs"]["ShapeTensor"]
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if outSizeTensor:
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del op["inputs"]["OutSize"]
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for tensorId in noSenseTensor:
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delLeafOpWithoutChildren(tensorId)
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# delete leaf op which has no child
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def delLeafOpWithoutChildren(tensorId):
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# judge if there is an op which used the tensor
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for op in ops[:]:
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inputsTensor = op["inputs"]
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input = inputsTensor.get("Input") or inputsTensor.get("X")
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if input and (tensorId in input):
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return
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op = getOpByOutputTensor(tensorId)
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if not op:
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return
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# del op
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ops.remove(op)
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# del vars
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del vars[tensorId]
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# upward recursion
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delOpinputsTensor = op["inputs"]
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input = delOpinputsTensor.get("Input") or delOpinputsTensor.get("X")
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if not input:
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return
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for inputTensorId in input:
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delLeafOpWithoutChildren(inputTensorId)
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# find op by output tensor id
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def getOpByOutputTensor(tensorId):
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for op in ops[:]:
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outputTensor = op["outputs"]
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out = outputTensor.get("Out") or outputTensor.get("Output") or outputTensor.get("Y")
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if out[0] == tensorId:
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return op
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