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import flatbuffers |
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from flatbuffers.compat import import_numpy |
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np = import_numpy() |
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class RuleClassificationResult(object): |
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__slots__ = ['_tab'] |
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@classmethod |
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def GetRootAsRuleClassificationResult(cls, buf, offset): |
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n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset) |
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x = RuleClassificationResult() |
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x.Init(buf, n + offset) |
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return x |
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@classmethod |
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def RuleClassificationResultBufferHasIdentifier(cls, buf, offset, size_prefixed=False): |
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return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x54\x43\x32\x20", size_prefixed=size_prefixed) |
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def Init(self, buf, pos): |
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self._tab = flatbuffers.table.Table(buf, pos) |
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def CollectionName(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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return self._tab.String(o + self._tab.Pos) |
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return None |
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def TargetClassificationScore(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.Get(flatbuffers.number_types.Float32Flags, o + self._tab.Pos) |
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return 1.0 |
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def PriorityScore(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.Get(flatbuffers.number_types.Float32Flags, o + self._tab.Pos) |
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return 0.0 |
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def CapturingGroup(self, j): |
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o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(10)) |
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if o != 0: |
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x = self._tab.Vector(o) |
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x += flatbuffers.number_types.UOffsetTFlags.py_type(j) * 4 |
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x = self._tab.Indirect(x) |
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from libtextclassifier3.CapturingGroup import CapturingGroup |
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obj = CapturingGroup() |
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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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def CapturingGroupLength(self): |
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o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(10)) |
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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 CapturingGroupIsNone(self): |
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o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(10)) |
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return o == 0 |
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def SerializedEntityData(self): |
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o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(12)) |
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if o != 0: |
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return self._tab.String(o + self._tab.Pos) |
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return None |
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def EnabledModes(self): |
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o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(14)) |
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if o != 0: |
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return self._tab.Get(flatbuffers.number_types.Int32Flags, o + self._tab.Pos) |
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return 7 |
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def EntityData(self): |
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o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(16)) |
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if o != 0: |
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x = self._tab.Indirect(o + self._tab.Pos) |
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from libtextclassifier3.EntityData import EntityData |
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obj = EntityData() |
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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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def RuleClassificationResultStart(builder): builder.StartObject(7) |
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def RuleClassificationResultAddCollectionName(builder, collectionName): builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(collectionName), 0) |
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def RuleClassificationResultAddTargetClassificationScore(builder, targetClassificationScore): builder.PrependFloat32Slot(1, targetClassificationScore, 1.0) |
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def RuleClassificationResultAddPriorityScore(builder, priorityScore): builder.PrependFloat32Slot(2, priorityScore, 0.0) |
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def RuleClassificationResultAddCapturingGroup(builder, capturingGroup): builder.PrependUOffsetTRelativeSlot(3, flatbuffers.number_types.UOffsetTFlags.py_type(capturingGroup), 0) |
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def RuleClassificationResultStartCapturingGroupVector(builder, numElems): return builder.StartVector(4, numElems, 4) |
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def RuleClassificationResultAddSerializedEntityData(builder, serializedEntityData): builder.PrependUOffsetTRelativeSlot(4, flatbuffers.number_types.UOffsetTFlags.py_type(serializedEntityData), 0) |
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def RuleClassificationResultAddEnabledModes(builder, enabledModes): builder.PrependInt32Slot(5, enabledModes, 7) |
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def RuleClassificationResultAddEntityData(builder, entityData): builder.PrependUOffsetTRelativeSlot(6, flatbuffers.number_types.UOffsetTFlags.py_type(entityData), 0) |
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def RuleClassificationResultEnd(builder): return builder.EndObject() |
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