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Diffstat (limited to 'python/serializer/tosa_serializer.py')
| -rw-r--r-- | python/serializer/tosa_serializer.py | 802 |
1 files changed, 802 insertions, 0 deletions
diff --git a/python/serializer/tosa_serializer.py b/python/serializer/tosa_serializer.py new file mode 100644 index 0000000..b29f963 --- /dev/null +++ b/python/serializer/tosa_serializer.py @@ -0,0 +1,802 @@ +# Copyright (c) 2020-2022, ARM Limited. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import os +import json +import flatbuffers +import numpy as np +import struct +from enum import IntEnum, unique +from tosa import ( + TosaGraph, + TosaBasicBlock, + TosaTensor, + TosaOperator, + Version, +) +import tosa.DType as TosaDType +import tosa.Op as TosaOp + +# Keep version number in sync with the version default value with schema/tosa.fbs +TOSA_VERSION_MAJOR = 0 +TOSA_VERSION_MINOR = 24 +TOSA_VERSION_PATCH = 0 +TOSA_VERSION_DRAFT = True +TOSA_VERSION = [ + TOSA_VERSION_MAJOR, + TOSA_VERSION_MINOR, + TOSA_VERSION_PATCH, + TOSA_VERSION_DRAFT, +] +# With the way flatc generates its python types, there is no programatic way +# to get string names for the integer types. Manually maintain a string table +# here. +DType = TosaDType.DType() +DTypeNames = [ + "UNKNOWN", + "BOOL", + "UINT8", + "INT4", + "INT8", + "INT16", + "INT32", + "INT48", + "FLOAT", +] + +ByteMask = np.uint64(0xFF) + + +def dtype_str_to_val(name): + + for i in range(len(DTypeNames)): + if name.casefold() == DTypeNames[i].casefold(): + return i + raise Exception("Unable to parse DType name {}".format(name)) + + +class TosaSerializerUnion: + """This class handles encapsulating and serializing union types into flatbuffers""" + + def __init__(self): + + # A tuple of the start and end functions. + # Set by the options constructors below + self.optFcns = None + + # The type from the tosa.Options enumeration. + # Set by the options constructors below. + self.utype = None + + # Each of these lists is a tuple of the add function and the + # value being added. Set by the options constructors below. + self.ints = [] + self.bools = [] + self.floats = [] + self.strings = [] + self.intvecs = [] + self.fpvecs = [] + + def serialize(self, builder): + + # We have to build strings and vectors first + strList = [] + intVecList = [] + fpVecList = [] + + for fcn, val in self.strings: + strList.append((fcn, builder.CreateString(val))) + + for fcn, val in self.intvecs: + intVecList.append((fcn, TosaSerializer.serializeInt32Vec(builder, val))) + + for fcn, val in self.fpvecs: + fpVecList.append((fcn, TosaSerializer.serializeFpVec(builder, val))) + + startFcn, endFcn = self.optFcns + + # Then serialize the options object from the list of primitives and + # other serialized values + startFcn(builder) + for fcn, val in self.ints: + fcn(builder, val) + + for fcn, val in self.bools: + fcn(builder, val) + + for fcn, val in self.floats: + fcn(builder, val) + + for fcn, val in strList: + fcn(builder, val) + + for fcn, val in intVecList: + fcn(builder, val) + + for fcn, val in fpVecList: + fcn(builder, val) + + return endFcn(builder) + + +class TosaSerializerAttribute(TosaSerializerUnion): + """This class handles encapsulating all of the enumerated types for attributes""" + + def __init__(self): + super().__init__() + + def PoolAttribute(self, kernel, stride, padding): + from tosa import PoolAttribute as a, Attribute + + self.utype = Attribute.Attribute().PoolAttribute + + self.optFcns = (a.Start, a.End) + self.intvecs.append((a.AddPadding, padding)) + self.intvecs.append((a.AddKernel, kernel)) + self.intvecs.append((a.AddStride, stride)) + + def ConvAttribute(self, padding, stride, dilation): + from tosa import ConvAttribute as a, Attribute + + self.utype = Attribute.Attribute().ConvAttribute + self.optFcns = (a.Start, a.End) + + self.intvecs.append((a.AddPadding, padding)) + self.intvecs.append((a.AddStride, stride)) + self.intvecs.append((a.AddDilation, dilation)) + + def TransposeConvAttribute(self, outpad, stride, dilation, output_shape): + from tosa import TransposeConvAttribute as a, Attribute + + self.utype = Attribute.Attribute().TransposeConvAttribute + self.optFcns = (a.Start, a.End) + + self.intvecs.append((a.AddOutpad, outpad)) + self.intvecs.append((a.AddStride, stride)) + self.intvecs.append((a.AddDilation, dilation)) + self.intvecs.append((a.AddOutputShape, output_shape)) + + def PadAttribute(self, padding, pad_const_int, pad_const_fp): + from tosa import PadAttribute as a, Attribute + + self.utype = Attribute.Attribute().PadAttribute + self.optFcns = (a.Start, a.End) + + self.intvecs.append((a.AddPadding, padding)) + self.ints.append((a.AddPadConstInt, pad_const_int)) + self.floats.append((a.AddPadConstFp, pad_const_fp)) + + def AxisAttribute(self, axis): + from tosa import AxisAttribute as a, Attribute + + self.utype = Attribute.Attribute().AxisAttribute + self.optFcns = (a.Start, a.End) + + self.ints.append((a.AddAxis, axis)) + + def ReshapeAttribute(self, shape): + from tosa import ReshapeAttribute as a, Attribute + + self.utype = Attribute.Attribute().ReshapeAttribute + self.optFcns = (a.Start, a.End) + + self.intvecs.append((a.AddShape, shape)) + + def SliceAttribute(self, begin, size): + from tosa import SliceAttribute as a, Attribute + + self.utype = Attribute.Attribute().SliceAttribute + self.optFcns = (a.Start, a.End) + + self.intvecs.append((a.AddBegin, begin)) + self.intvecs.append((a.AddSize, size)) + + def TileAttribute(self, multiples): + from tosa import TileAttribute as a, Attribute + + self.utype = Attribute.Attribute().TileAttribute + self.optFcns = (a.Start, a.End) + + self.intvecs.append((a.AddMultiples, multiples)) + + def ResizeAttribute( + self, output_size, stride, offset, shift, stride_fp, offset_fp, mode + ): + from tosa import ResizeAttribute as a, Attribute + + self.utype = Attribute.Attribute().ResizeAttribute + self.optFcns = (a.Start, a.End) + + self.intvecs.append((a.AddOutputSize, output_size)) + self.intvecs.append((a.AddStride, stride)) + self.intvecs.append((a.AddOffset, offset)) + self.ints.append((a.AddShift, shift)) + self.fpvecs.append((a.AddStrideFp, stride_fp)) + self.fpvecs.append((a.AddOffsetFp, offset_fp)) + self.ints.append((a.AddMode, mode)) + + def ClampAttribute(self, minint, maxint, minfp, maxfp): + from tosa import ClampAttribute as a, Attribute + + self.utype = Attribute.Attribute().ClampAttribute + self.optFcns = (a.Start, a.End) + + self.ints.append((a.AddMinInt, minint)) + self.ints.append((a.AddMaxInt, maxint)) + + self.ints.append((a.AddMinFp, minfp)) + self.ints.append((a.AddMaxFp, maxfp)) + + def RescaleAttribute( + self, input_zp, output_zp, multiplier, shift, scale32, double_round, per_channel + ): + from tosa import RescaleAttribute as a, Attribute + + self.utype = Attribute.Attribute().RescaleAttribute + self.optFcns = (a.Start, a.End) + + self.ints.append((a.AddInputZp, input_zp)) + self.ints.append((a.AddOutputZp, output_zp)) + self.intvecs.append((a.AddMultiplier, multiplier)) + self.intvecs.append((a.AddShift, shift)) + self.bools.append((a.AddScale32, scale32)) + self.bools.append((a.AddDoubleRound, double_round)) + self.bools.append((a.AddPerChannel, per_channel)) + + def MulAttribute(self, shift): + from tosa import MulAttribute as a, Attribute + + self.utype = Attribute.Attribute().MulAttribute + self.optFcns = (a.Start, a.End) + + self.ints.append((a.AddShift, shift)) + + def ArithmeticRightShiftAttribute(self, round): + from tosa import ArithmeticRightShiftAttribute as a, Attribute + + self.utype = Attribute.Attribute().ArithmeticRightShiftAttribute + self.optFcns = ( + a.Start, + a.End, + ) + + self.bools.append((a.AddRound, round)) + + def CondIfAttribute(self, then_branch, else_branch): + from tosa import CondIfAttribute as a, Attribute + + self.utype = Attribute.Attribute().CondIfAttribute + self.optFcns = (a.Start, a.End) + + self.strings.append((a.AddThenBranch, then_branch)) + self.strings.append((a.AddElseBranch, else_branch)) + + def WhileLoopAttribute(self, cond_branch, body_branch): + from tosa import WhileLoopAttribute as a, Attribute + + self.utype = Attribute.Attribute().WhileLoopAttribute + self.optFcns = (a.Start, a.End) + + self.strings.append((a.AddCondBranch, cond_branch)) + self.strings.append((a.AddBodyBranch, body_branch)) + + def TransposeAttribute(self, perm): + from tosa import TransposeAttribute as a, Attribute + + self.utype = Attribute.Attribute().TransposeAttribute + self.optFcns = (a.Start, a.End) + + self.intvecs.append((a.AddPerm, perm)) + + def TableAttribute(self, table): + from tosa import TableAttribute as a, Attribute + + self.utype = Attribute.Attribute().TableAttribute + self.optFcns = (a.Start, a.End) + + self.intvecs.append((a.AddTable, table)) + + +class TosaSerializerQuantInfo(TosaSerializerUnion): + """This class handles encapsulating all of the enumerated types for quantinfo""" + + def __init__(self): + super().__init__() + + def ConvQuantInfo(self, input_zp, weight_zp): + from tosa import ConvQuantInfo as q, QuantInfo + + self.utype = QuantInfo.QuantInfo().ConvQuantInfo + self.optFcns = (q.Start, q.End) + self.ints.append((q.AddInputZp, input_zp)) + self.ints.append((q.AddWeightZp, weight_zp)) + + def UnaryQuantInfo(self, input_zp, output_zp): + from tosa import UnaryQuantInfo as q, QuantInfo + + self.utype = QuantInfo.QuantInfo().UnaryQuantInfo + self.optFcns = (q.Start, q.End) + self.ints.append((q.AddInputZp, input_zp)) + self.ints.append((q.AddOutputZp, output_zp)) + + def MatMulQuantInfo(self, a_zp, b_zp): + from tosa import MatMulQuantInfo as q, QuantInfo + + self.utype = QuantInfo.QuantInfo().MatMulQuantInfo + self.optFcns = (q.Start, q.End) + self.ints.append((q.AddAZp, a_zp)) + self.ints.append((q.AddBZp, b_zp)) + + def PadQuantInfo(self, input_zp): + from tosa import PadQuantInfo as q, QuantInfo + + self.utype = QuantInfo.QuantInfo().PadQuantInfo + self.optFcns = (q.Start, q.End) + self.ints.append((q.AddInputZp, input_zp)) + + +class TosaSerializerTensor: + def __init__( + self, + name, + shape, + dtype, + data=None, + placeholderFilename=None, + ): + self.name = name + + if isinstance(shape, np.ndarray): + shape = shape.astype(int).tolist() + shape = list(map(int, shape)) + + self.shape = shape + self.dtype = dtype + + if isinstance(data, np.ndarray): + data = data.flatten().astype(int).tolist() + data = list(map(int, data)) + self.data = data + elif isinstance(data, list): + data = list(map(int, data)) + self.data = data + else: + self.data = None + + # Filename for placeholder tensors. These get generated by the test generation + # process and are written to disk, but are considered input tensors by the + # network so they do not appear in the TOSA serialiazation. However, if we + # want to form a unit test around these input tensors, we can get the filename + # from here. + self.placeholderFilename = placeholderFilename + + def __str__(self): + str = "TosaSerializerTensor name: {} shape: {} dtype: {}".format( + self.name, + self.shape, + DTypeNames[self.dtype], + ) + return str + + def setDtype(self, dtype): + self.dtype = dtype + + def serialize(self, builder): + fb_name = builder.CreateString(self.name) + fb_shapes = TosaSerializer.serializeInt32Vec(builder, self.shape) + if self.data: + u8_data = list() + # little endianess + if self.dtype == DType.BOOL: + for val in self.data: + val_u8 = np.uint8(val) + u8_data.append(val_u8) + elif self.dtype == DType.INT4: + in_size = len(self.data) + out_size = (in_size + 1) // 2 + for i in range(out_size): + val_0 = self.data[2 * i] + if (2 * i + 1) < in_size: + val_1 = self.data[2 * i + 1] + else: + val_1 = 0 + val_i8 = (val_0 & 0xF) | ((val_1 & 0xF) << 4) + val_u8 = np.uint8(val_i8) + u8_data.append(val_u8) + elif self.dtype == DType.INT8: + for val in self.data: + val_u8 = np.uint8(val) + u8_data.append(val_u8) + elif self.dtype == DType.INT16: + for val in self.data: + val_u16 = np.uint16(val) + b0 = val_u16 & ByteMask + b1 = (val_u16 >> np.uint16(8)) & ByteMask + u8_data.extend([b0, b1]) + elif self.dtype == DType.INT32: + for val in self.data: + val_u32 = np.uint32(val) + b0 = val_u32 & ByteMask + b1 = (val_u32 >> np.uint32(8)) & ByteMask + b2 = (val_u32 >> np.uint32(16)) & ByteMask + b3 = (val_u32 >> np.uint32(24)) & ByteMask + u8_data.extend([b0, b1, b2, b3]) + elif self.dtype == DType.INT48: + for val in self.data: + val_u64 = np.uint64(val) + b0 = val_u64 & ByteMask + b1 = (val_u64 >> np.uint64(8)) & ByteMask + b2 = (val_u64 >> np.uint64(16)) & ByteMask + b3 = (val_u64 >> np.uint64(24)) & ByteMask + b4 = (val_u64 >> np.uint64(32)) & ByteMask + b5 = (val_u64 >> np.uint64(40)) & ByteMask + u8_data.extend([b0, b1, b2, b3, b4, b5]) + elif self.dtype == DType.FLOAT: + for val in self.data: + b = struct.pack("!f", val) + u8_data.extend([b[3], b[2], b[1], b[0]]) + else: + raise Exception( + "unsupported data type {}".format(DTypeNames[self.dtype]) + ) + fb_data = TosaSerializer.serializeUint8Vec(builder, u8_data) + + TosaTensor.Start(builder) + TosaTensor.AddName(builder, fb_name) + TosaTensor.AddShape(builder, fb_shapes) + TosaTensor.AddType(builder, self.dtype) + if self.data: + TosaTensor.AddData(builder, fb_data) + + return TosaTensor.End(builder) + + +class TosaSerializerOperator: + def __init__(self, op, inputs, outputs, attributes=None, quantInfo=None): + self.op = op + self.attributes = attributes + self.inputs = TosaSerializer.toList(inputs) + self.outputs = TosaSerializer.toList(outputs) + self.quantInfo = quantInfo + + def __str__(self): + str = "Op {}\n----\n".format(self.op) + + for i in self.inputs: + str = str + " Input: {}\n".format(i) + for o in self.outputs: + str = str + " Output: {}\n".format(o) + + return str + + def serialize(self, builder): + fb_inputs = TosaSerializer.serializeStrVec( + builder, self.inputs, TosaOperator.StartInputsVector + ) + fb_outputs = TosaSerializer.serializeStrVec( + builder, self.outputs, TosaOperator.StartOutputsVector + ) + # Need to serialize quant_info and attributes enums still + if self.attributes is not None: + fb_attributes = self.attributes.serialize(builder) + + if self.quantInfo is not None: + fb_qinfo = self.quantInfo.serialize(builder) + + TosaOperator.Start(builder) + TosaOperator.AddOp(builder, self.op) + TosaOperator.AddInputs(builder, fb_inputs) + TosaOperator.AddOutputs(builder, fb_outputs) + if self.attributes is not None: + TosaOperator.AddAttributeType(builder, self.attributes.utype) + TosaOperator.AddAttribute(builder, fb_attributes) + if self.quantInfo is not None: + TosaOperator.AddQuantInfoType(builder, self.quantInfo.utype) + TosaOperator.AddQuantInfo(builder, fb_qinfo) + + return TosaOperator.End(builder) + + +class TosaSerializerBasicBlock: + def __init__(self, name): + self.name = name + self.operators = [] + + # Dict assures uniqueness, but allows us to look up by name + self.tensors = dict() + + self.inputs = [] + self.outputs = [] + + def addTensor( + self, + name, + shape, + dtype, + data=None, + placeholderFilename=None, + ): + if name not in self.tensors: + self.tensors[name] = TosaSerializerTensor( + name, shape, dtype, data, placeholderFilename + ) + + return self.tensors[name] + + def addInput(self, name): + self.inputs.append(name) + + def addOutput(self, name): + self.outputs.append(name) + + def addOperator(self, op, inputs, outputs, attributes=None, quant_info=None): + self.operators.append( + TosaSerializerOperator(op, inputs, outputs, attributes, quant_info) + ) + + def serialize(self, builder): + fb_name = builder.CreateString(self.name) + fbv_inputs = TosaSerializer.serializeStrVec( + builder, list(self.inputs), TosaBasicBlock.StartInputsVector + ) + fbv_outputs = TosaSerializer.serializeStrVec( + builder, list(self.outputs), TosaBasicBlock.StartOutputsVector + ) + fbv_tensors = TosaSerializer.serializeObjVec( + builder, + list(self.tensors.values()), + TosaBasicBlock.StartTensorsVector, + ) + fbv_operators = TosaSerializer.serializeObjVec( + builder, self.operators, TosaBasicBlock.StartOperatorsVector + ) + + TosaBasicBlock.Start(builder) + TosaBasicBlock.AddName(builder, fb_name) + TosaBasicBlock.AddInputs(builder, fbv_inputs) + TosaBasicBlock.AddOutputs(builder, fbv_outputs) + TosaBasicBlock.AddTensors(builder, fbv_tensors) + TosaBasicBlock.AddOperators(builder, fbv_operators) + return TosaBasicBlock.End(builder) + + +@unique +class TensorDir(IntEnum): + PLACEHOLDER = 0 + CONST = 1 + INTERMEDIATE = 2 + RESULT = 3 + + +class TosaSerializer: + def __init__(self, pathPrefix): + + # Get the global TOSA version if not already defined + + self.builder = flatbuffers.Builder(0) + + self.basicBlocks = [] + self.startBasicBlock("main") + self.pathPrefix = pathPrefix + + # Indicies used for adding/naming tensors + self.currInputIdx = 0 + self.currConstIdx = 0 + self.currLayerIdx = 1 + self.currResultIdx = 0 + + # Is this an illegal test that is expected to fail? + self.expectedReturnCode = 0 + self.expectedFailure = False + self.expectedFailureDesc = "" + + def __str__(self): + str = "" + for bb in self.basicBlocks: + str = str + bb.__str__() + return str + + def addPlaceholder(self, shape, dtype, vals): + if not self.currBasicBlock: + raise Exception("addTensor called without valid basic block") + + name = "input-{}".format(self.currInputIdx) + filename = "{}.npy".format(name) + self.currInputIdx = self.currInputIdx + 1 + + tens = self.currBasicBlock.addTensor(name, shape, dtype, None, filename) + # This is always an input to the block + self.currBasicBlock.addInput(name) + + if vals is not None: + np.save(os.path.join(self.pathPrefix, filename), vals, False) + + return tens + + def addConst(self, shape, dtype, vals): + if not self.currBasicBlock: + raise Exception("addTensor called without valid basic block") + + name = "const-{}".format(self.currInputIdx) + self.currInputIdx = self.currInputIdx + 1 + + tens = self.currBasicBlock.addTensor(name, shape, dtype, vals) + # Add the operator now + self.currBasicBlock.addOperator(TosaOp.Op().CONST, [], name) + + return tens + + def addIntermediate(self, shape, dtype): + + if not self.currBasicBlock: + raise Exception("addTensor called without valid basic block") + + name = "layer-{}".format(self.currLayerIdx) + self.currLayerIdx = self.currLayerIdx + 1 + + tens = self.currBasicBlock.addTensor(name, shape, dtype, None) + + return tens + + def addInputTensor(self, tensor): + self.currBasicBlock.addTensor(tensor.name, tensor.shape, tensor.dtype) + self.currBasicBlock.addInput(tensor.name) + + def addOutputTensor(self, tensor): + self.currBasicBlock.addOutput(tensor.name) + + def addOutput(self, shape, dtype): + if not self.currBasicBlock: + raise Exception("addTensor called without valid basic block") + + name = "result-{}".format(self.currResultIdx) + self.currResultIdx = self.currResultIdx + 1 + + tens = self.currBasicBlock.addTensor(name, shape, dtype, None) + self.currBasicBlock.addOutput(name) + return tens + + def addOperator(self, op, inputs, outputs, attributes=None, quant_info=None): + + if op == TosaOp.Op().CONST: + raise Exception("Use addConstTensor() to add CONST ops") + + return self.currBasicBlock.addOperator( + op, inputs, outputs, attributes, quant_info + ) + + def setExpectedReturnCode(self, val, fail, desc=""): + + self.expectedReturnCode = val + self.expectedFailureDesc = desc + self.expectedFailure = fail + + def serialize(self): + + builder = self.builder + + Version.Start(builder) + Version.Add_major(builder, TOSA_VERSION[0]) + Version.Add_minor(builder, TOSA_VERSION[1]) + Version.Add_patch(builder, TOSA_VERSION[2]) + Version.Add_draft(builder, TOSA_VERSION[3]) + version = Version.End(builder) + + fbv_bb = TosaSerializer.serializeObjVec( + builder, self.basicBlocks, TosaGraph.StartBlocksVector + ) + + TosaGraph.Start(builder) + TosaGraph.AddVersion(builder, version) + TosaGraph.AddBlocks(builder, fbv_bb) + graph = TosaGraph.End(builder) + + self.builder.Finish(graph) + return self.builder.Output() + + def writeJson(self, tosa_filename): + """Write a json test file so that it is fairly easy to pick up the test + and generate commands for third party tool""" + test_desc = dict() + + test_desc["tosa_file"] = tosa_filename + ifm_name = [] + ifm_file = [] + ofm_name = [] + ofm_file = [] + + for b in self.basicBlocks: + if b.name == "main": + for i in b.inputs: + ifm_name.append(i) + ifm_file.append(b.tensors[i].placeholderFilename) + for o in b.outputs: + ofm_name.append(o) + # Make up an OFM filename here. One isn't generated until the + # reference tool is run, so any name is a good name + ofm_file.append("ref-{}.npy".format(o)) + + test_desc["ifm_name"] = ifm_name + test_desc["ifm_file"] = ifm_file + test_desc["ofm_name"] = ofm_name + test_desc["ofm_file"] = ofm_file + test_desc["expected_return_code"] = self.expectedReturnCode + test_desc["expected_failure"] = self.expectedFailure + if self.expectedFailureDesc: + test_desc["expected_failure_desc"] = self.expectedFailureDesc + + return json.dumps(test_desc, indent=" ") + + def startBasicBlock(self, name): + self.currBasicBlock = TosaSerializerBasicBlock(name) + self.basicBlocks.append(self.currBasicBlock) + + @staticmethod + def serializeStrVec(builder, vec, start_fcn): + fb_strs = [builder.CreateString(i) for i in vec] + start_fcn(builder, len(fb_strs)) + for s in fb_strs[::-1]: + builder.PrependUOffsetTRelative(s) + return builder.EndVector() + + @staticmethod + def serializeUint8Vec(builder, vec): + builder.StartVector(1, len(vec), 8) + for v in vec[::-1]: + builder.PrependUint8(v) + try: + return builder.EndVector() + except TypeError: + return builder.EndVector(len(vec)) + + @staticmethod + def serializeInt32Vec(builder, vec): + builder.StartVector(4, len(vec), 4) + for v in vec[::-1]: + builder.PrependInt32(v) + try: + return builder.EndVector() + except TypeError: + return builder.EndVector(len(vec)) + + @staticmethod + def serializeFpVec(builder, vec): + builder.StartVector(4, len(vec), 4) + for v in vec[::-1]: + builder.PrependFloat32(v) + try: + return builder.EndVector() + except TypeError: + return builder.EndVector(len(vec)) + + @staticmethod + def serializeObjVec(builder, vec, start_fcn): + serialized_vec = [] + for v in vec[::-1]: + serialized_vec.append(v.serialize(builder)) + + start_fcn(builder, len(vec)) + for v in serialized_vec: + builder.PrependUOffsetTRelative(v) + try: + return builder.EndVector() + except TypeError: + return builder.EndVector(len(vec)) + + @staticmethod + def toList(val): + if isinstance(val, list): + return val + else: + return [val] |