# automatically generated by the FlatBuffers compiler, do not modify # namespace: RegexModel_ import flatbuffers from flatbuffers.compat import import_numpy np = import_numpy() class Pattern(object): __slots__ = ['_tab'] @classmethod def GetRootAsPattern(cls, buf, offset): n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset) x = Pattern() x.Init(buf, n + offset) return x @classmethod def PatternBufferHasIdentifier(cls, buf, offset, size_prefixed=False): return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x54\x43\x32\x20", size_prefixed=size_prefixed) # Pattern def Init(self, buf, pos): self._tab = flatbuffers.table.Table(buf, pos) # Pattern def CollectionName(self): o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4)) if o != 0: return self._tab.String(o + self._tab.Pos) return None # Pattern def Pattern(self): o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6)) if o != 0: return self._tab.String(o + self._tab.Pos) return None # Pattern def EnabledModes(self): o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8)) if o != 0: return self._tab.Get(flatbuffers.number_types.Int32Flags, o + self._tab.Pos) return 7 # Pattern def TargetClassificationScore(self): o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(10)) if o != 0: return self._tab.Get(flatbuffers.number_types.Float32Flags, o + self._tab.Pos) return 1.0 # Pattern def PriorityScore(self): o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(12)) if o != 0: return self._tab.Get(flatbuffers.number_types.Float32Flags, o + self._tab.Pos) return 0.0 # Pattern def UseApproximateMatching(self): o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(14)) if o != 0: return bool(self._tab.Get(flatbuffers.number_types.BoolFlags, o + self._tab.Pos)) return False # Pattern def CompressedPattern(self): o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(16)) if o != 0: x = self._tab.Indirect(o + self._tab.Pos) from libtextclassifier3.CompressedBuffer import CompressedBuffer obj = CompressedBuffer() obj.Init(self._tab.Bytes, x) return obj return None # Pattern def VerificationOptions(self): o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(18)) if o != 0: x = self._tab.Indirect(o + self._tab.Pos) from libtextclassifier3.VerificationOptions import VerificationOptions obj = VerificationOptions() obj.Init(self._tab.Bytes, x) return obj return None # Pattern def CapturingGroup(self, j): o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(20)) if o != 0: x = self._tab.Vector(o) x += flatbuffers.number_types.UOffsetTFlags.py_type(j) * 4 x = self._tab.Indirect(x) from libtextclassifier3.CapturingGroup import CapturingGroup obj = CapturingGroup() obj.Init(self._tab.Bytes, x) return obj return None # Pattern def CapturingGroupLength(self): o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(20)) if o != 0: return self._tab.VectorLen(o) return 0 # Pattern def CapturingGroupIsNone(self): o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(20)) return o == 0 # Pattern def SerializedEntityData(self): o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(22)) if o != 0: return self._tab.String(o + self._tab.Pos) return None # Pattern def EntityData(self): o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(24)) if o != 0: x = self._tab.Indirect(o + self._tab.Pos) from libtextclassifier3.EntityData import EntityData obj = EntityData() obj.Init(self._tab.Bytes, x) return obj return None def PatternStart(builder): builder.StartObject(11) def PatternAddCollectionName(builder, collectionName): builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(collectionName), 0) def PatternAddPattern(builder, pattern): builder.PrependUOffsetTRelativeSlot(1, flatbuffers.number_types.UOffsetTFlags.py_type(pattern), 0) def PatternAddEnabledModes(builder, enabledModes): builder.PrependInt32Slot(2, enabledModes, 7) def PatternAddTargetClassificationScore(builder, targetClassificationScore): builder.PrependFloat32Slot(3, targetClassificationScore, 1.0) def PatternAddPriorityScore(builder, priorityScore): builder.PrependFloat32Slot(4, priorityScore, 0.0) def PatternAddUseApproximateMatching(builder, useApproximateMatching): builder.PrependBoolSlot(5, useApproximateMatching, 0) def PatternAddCompressedPattern(builder, compressedPattern): builder.PrependUOffsetTRelativeSlot(6, flatbuffers.number_types.UOffsetTFlags.py_type(compressedPattern), 0) def PatternAddVerificationOptions(builder, verificationOptions): builder.PrependUOffsetTRelativeSlot(7, flatbuffers.number_types.UOffsetTFlags.py_type(verificationOptions), 0) def PatternAddCapturingGroup(builder, capturingGroup): builder.PrependUOffsetTRelativeSlot(8, flatbuffers.number_types.UOffsetTFlags.py_type(capturingGroup), 0) def PatternStartCapturingGroupVector(builder, numElems): return builder.StartVector(4, numElems, 4) def PatternAddSerializedEntityData(builder, serializedEntityData): builder.PrependUOffsetTRelativeSlot(9, flatbuffers.number_types.UOffsetTFlags.py_type(serializedEntityData), 0) def PatternAddEntityData(builder, entityData): builder.PrependUOffsetTRelativeSlot(10, flatbuffers.number_types.UOffsetTFlags.py_type(entityData), 0) def PatternEnd(builder): return builder.EndObject()