mirror of https://github.com/alibaba/MNN.git
83 lines
3.1 KiB
Python
83 lines
3.1 KiB
Python
# automatically generated by the FlatBuffers compiler, do not modify
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# namespace: MNN
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import flatbuffers
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class Convolution3D(object):
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__slots__ = ['_tab']
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@classmethod
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def GetRootAsConvolution3D(cls, buf, offset):
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n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
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x = Convolution3D()
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x.Init(buf, n + offset)
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return x
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# Convolution3D
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def Init(self, buf, pos):
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self._tab = flatbuffers.table.Table(buf, pos)
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# Convolution3D
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def Common(self):
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o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
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if o != 0:
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x = self._tab.Indirect(o + self._tab.Pos)
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from .Convolution3DCommon import Convolution3DCommon
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obj = Convolution3DCommon()
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obj.Init(self._tab.Bytes, x)
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return obj
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return None
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# Convolution3D
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def Weight(self, j):
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o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
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if o != 0:
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a = self._tab.Vector(o)
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return self._tab.Get(flatbuffers.number_types.Float32Flags, a + flatbuffers.number_types.UOffsetTFlags.py_type(j * 4))
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return 0
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# Convolution3D
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def WeightAsNumpy(self):
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o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
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if o != 0:
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return self._tab.GetVectorAsNumpy(flatbuffers.number_types.Float32Flags, o)
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return 0
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# Convolution3D
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def WeightLength(self):
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o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
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if o != 0:
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return self._tab.VectorLen(o)
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return 0
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# Convolution3D
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def Bias(self, j):
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o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8))
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if o != 0:
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a = self._tab.Vector(o)
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return self._tab.Get(flatbuffers.number_types.Float32Flags, a + flatbuffers.number_types.UOffsetTFlags.py_type(j * 4))
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return 0
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# Convolution3D
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def BiasAsNumpy(self):
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o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8))
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if o != 0:
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return self._tab.GetVectorAsNumpy(flatbuffers.number_types.Float32Flags, o)
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return 0
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# Convolution3D
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def BiasLength(self):
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o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8))
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if o != 0:
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return self._tab.VectorLen(o)
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return 0
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def Convolution3DStart(builder): builder.StartObject(3)
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def Convolution3DAddCommon(builder, common): builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(common), 0)
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def Convolution3DAddWeight(builder, weight): builder.PrependUOffsetTRelativeSlot(1, flatbuffers.number_types.UOffsetTFlags.py_type(weight), 0)
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def Convolution3DStartWeightVector(builder, numElems): return builder.StartVector(4, numElems, 4)
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def Convolution3DAddBias(builder, bias): builder.PrependUOffsetTRelativeSlot(2, flatbuffers.number_types.UOffsetTFlags.py_type(bias), 0)
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def Convolution3DStartBiasVector(builder, numElems): return builder.StartVector(4, numElems, 4)
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def Convolution3DEnd(builder): return builder.EndObject()
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