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# 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()