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Diffstat (limited to 'verif/tosa_serializer.py')
| -rw-r--r-- | verif/tosa_serializer.py | 718 |
1 files changed, 718 insertions, 0 deletions
diff --git a/verif/tosa_serializer.py b/verif/tosa_serializer.py new file mode 100644 index 0000000..7ba68c3 --- /dev/null +++ b/verif/tosa_serializer.py @@ -0,0 +1,718 @@ + + +# Copyright (c) 2020, 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. + +#!/usr/bin/env python3 + +import flatbuffers +import numpy as np +from enum import Enum, IntEnum, unique +from tosa import TosaGraph, TosaBasicBlock, TosaTensor, TosaOperator, DType, Format, Usage, Op, ResizeMode, Version +import tosa +import os +import json + +# 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. +DTypeNames = [ 'UNKNOWN', + 'BOOL', + 'AINT8', + 'UINT8', + 'INT4', + 'INT8', + 'INT16', + 'INT32', + 'INT48', + 'FLOAT' ] + +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 = [] + + def serialize(self, builder): + + # We have to build strings and vectors first + strList = [] + intVecList = [] + + 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))) + + 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) + + return endFcn(builder) + +class TosaSerializerAttribute(TosaSerializerUnion): + '''This class handles encapsulating all of the enumerated types for attributes''' + + def __init__(self): + super().__init__() + + def Pool2dAttribute(self, kernel, stride, padding): + from tosa import Pool2dAttribute as a, Attribute + + self.utype = Attribute.Attribute().Pool2dAttribute + + self.optFcns = (a.Pool2dAttributeStart, a.Pool2dAttributeEnd) + self.intvecs.append((a.Pool2dAttributeAddPadding, + padding)) + self.intvecs.append((a.Pool2dAttributeAddKernel, + kernel)) + self.intvecs.append((a.Pool2dAttributeAddStride, + stride)) + + def Conv2dAttribute(self, padding, stride, dilation): + from tosa import Conv2dAttribute as a, Attribute + + self.utype = Attribute.Attribute().Conv2dAttribute + self.optFcns = (a.Conv2dAttributeStart, a.Conv2dAttributeEnd) + + self.intvecs.append((a.Conv2dAttributeAddPadding, + padding)) + self.intvecs.append((a.Conv2dAttributeAddStride, + stride)) + self.intvecs.append((a.Conv2dAttributeAddDilation, + dilation)) + + def TransposeConv2DAttribute(self, outpad, stride, dilation, output_shape): + from tosa import TransposeConv2dAttribute as a, Attribute + + self.utype = Attribute.Attribute().TransposeConv2dAttribute + self.optFcns = (a.TransposeConv2dAttributeStart, a.TransposeConv2dAttributeEnd) + + self.intvecs.append((a.TransposeConv2dAttributeAddOutpad, + outpad)) + self.intvecs.append((a.TransposeConv2dAttributeAddStride, + stride)) + self.intvecs.append((a.TransposeConv2dAttributeAddDilation, + dilation)) + self.intvecs.append((a.TransposeConv2dAttributeAddOutputShape, + output_shape)) + + def ReluNAttribute(self, maxint, maxfp): + from tosa import ReluNAttribute as a, Attribute + + self.utype = Attribute.Attribute().ReluNAttribute + self.optFcns = (a.ReluNAttributeStart, a.ReluNAttributeEnd) + + self.ints.append((a.ReluNAttributeAddMaxInt, maxint)) + self.ints.append((a.ReluNAttributeAddMaxFp, maxfp)) + + + def AxisAttribute(self, axis): + from tosa import AxisAttribute as a, Attribute + + self.utype = Attribute.Attribute().AxisAttribute + self.optFcns = (a.AxisAttributeStart, a.AxisAttributeEnd) + + self.ints.append((a.AxisAttributeAddAxis, + axis)) + + def ReshapeAttribute(self, shape): + from tosa import ReshapeAttribute as a, Attribute + + self.utype = Attribute.Attribute().ReshapeAttribute + self.optFcns = (a.ReshapeAttributeStart, a.ReshapeAttributeEnd) + + self.intvecs.append((a.ReshapeAttributeAddShape, + shape)) + + def SliceAttribute(self, begin, size): + from tosa import SliceAttribute as a, Attribute + + self.utype = Attribute.Attribute().SliceAttribute + self.optFcns = (a.SliceAttributeStart, a.SliceAttributeEnd) + + self.intvecs.append((a.SliceAttributeAddBegin, + begin)) + self.intvecs.append((a.SliceAttributeAddSize, + size)) + + def TileAttribute(self, multiples): + from tosa import TileAttribute as a, Attribute + + self.utype = Attribute.Attribute().TileAttribute + self.optFcns = (a.TileAttributeStart, a.TileAttributeEnd) + + self.intvecs.append((a.TileAttributeAddMultiples, + multiples)) + + def ResizeAttribute(self, output_size, stride, offset, shift, mode): + from tosa import ResizeAttribute as a, Attribute + + self.utype = Attribute.Attribute().ResizeAttribute + self.optFcns = (a.ResizeAttributeStart, a.ResizeAttributeEnd) + + self.intvecs.append((a.ResizeAttributeAddOutputSize, + output_size)) + self.intvecs.append((a.ResizeAttributeAddStride, + stride)) + self.intvecs.append((a.ResizeAttributeAddOffset, + offset)) + self.ints.append((a.ResizeAttributeAddShift, + shift)) + self.ints.append((a.ResizeAttributeAddMode, + mode)) + + def ClampAttribute(self, minint, maxint, minfp, maxfp): + from tosa import ClampAttribute as a, Attribute + + self.utype = Attribute.Attribute().ClampAttribute + self.optFcns = (a.ClampAttributeStart, a.ClampAttributeEnd) + + self.ints.append((a.ClampAttributeAddMinInt, + minint)) + self.ints.append((a.ClampAttributeAddMaxInt, + maxint)) + + self.ints.append((a.ClampAttributeAddMinFp, + minfp)) + self.ints.append((a.ClampAttributeAddMaxFp, + 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.RescaleAttributeStart, a.RescaleAttributeEnd) + + self.ints.append((a.RescaleAttributeAddInputZp, + input_zp)) + self.ints.append((a.RescaleAttributeAddOutputZp, + output_zp)) + self.intvecs.append((a.RescaleAttributeAddMultiplier, + multiplier)) + self.intvecs.append((a.RescaleAttributeAddShift, + shift)) + self.bools.append((a.RescaleAttributeAddScale32, + scale32)) + self.bools.append((a.RescaleAttributeAddDoubleRound, + double_round)) + self.bools.append((a.RescaleAttributeAddPerChannel, + per_channel)) + + def CustomAttribute(self, identifier): + from tosa import CustomAttribute as a, Attribute + + self.utype = Attribute.Attribute().CustomAttribute + self.optFcns = (a.CustomAttributeStart, a.CustomAttributeEnd) + + self.strings.append((a.CustomAttributeAddIdentifier, + identifier)) + + def CondIfAttribute(self, then_branch, else_branch): + from tosa import CondIfAttribute as a, Attribute + + self.utype = Attribute.Attribute().CondIfAttribute + self.optFcns = (a.CondIfAttributeStart, a.CondIfAttributeEnd) + + self.strings.append((a.CondIfAttributeAddThenBranch, + then_branch)) + self.strings.append((a.CondIfAttributeAddElseBranch, + else_branch)) + + def WhileLoopAttribute(self, cond_branch, body_branch): + from tosa import WhileLoopAttribute as a, Attribute + + self.utype = Attribute.Attribute().WhileLoopAttribute + self.optFcns = (a.WhileLoopAttributeStart, a.WhileLoopAttributeEnd) + + self.strings.append((a.WhileLoopAttributeAddCondBranch, + cond_branch)) + self.strings.append((a.WhileLoopAttributeAddBodyBranch, + body_branch)) + +class TosaSerializerQuantInfo(TosaSerializerUnion): + '''This class handles encapsulating all of the enumerated types for quantinfo types''' + 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.ConvQuantInfoStart, q.ConvQuantInfoEnd) + self.ints.append((q.ConvQuantInfoAddInputZp, input_zp)) + self.ints.append((q.ConvQuantInfoAddWeightZp, weight_zp)) + + def UnaryQuantInfo(self, input_zp, output_zp): + from tosa import UnaryQuantInfo as q, QuantInfo + + self.utype = QuantInfo.QuantInfo().UnaryQuantInfo + self.optFcns = (q.UnaryQuantInfoStart, q.UnaryQuantInfoEnd) + self.ints.append((q.UnaryQuantInfoAddInputZp, input_zp)) + self.ints.append((q.UnaryQuantInfoAddOutputZp, output_zp)) + + def MatMulQuantInfo(self, a_zp, b_zp): + from tosa import MatMulQuantInfo as q, QuantInfo + + self.utype = QuantInfo.QuantInfo().MatMulQuantInfo + self.optFcns = (q.MatMulQuantInfoStart, q.MatMulQuantInfoEnd) + self.ints.append((q.MatMulQuantInfoAddAZp, a_zp)) + self.ints.append((q.MatMulQuantInfoAddBZp, b_zp)) + + def PadQuantInfo(self, input_zp): + from tosa import PadQuantInfo as q, QuantInfo + + self.utype = QuantInfo.QuantInfo().PadQuantInfo + self.optFcns = (q.PadQuantInfoStart, q.PadQuantInfoEnd) + self.ints.append((q.PadQuantInfoAddInputZp, input_zp)) + +class TosaSerializerTensor: + def __init__(self, name, shape, dtype, usage, dformat, filename = 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 + self.usage = TosaSerializer.toList(usage) + self.dformat = TosaSerializer.toList(dformat) + + # Filename for const tensors. This gets written to the .tosa serialization + self.filename = filename + + # 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: {} Usage: {} format {} filename: {}'.format( + self.name, self.shape, DTypeNames[self.dtype], self.usage, self.dformat, self.filename) + return str + + def addUsage(self, usage): + self.usage.append(usage) + + def addFormat(self, format): + self.dformat.append(format) + + def setDtype(self, dtype): + self.dtype = dtype + + def merge(self, name, shape, dtype, usage, dformat, filename = None): + # Merge in additional usage/formats to the list + found = 0 + for i in self.usage: + if i == usage: + found = 1 + break + if not found: + self.usage.append(usage) + + found = 0 + for i in self.dformat: + if i == dformat: + found = 1 + break + if not found: + self.dformat.append(dformat) + + def serialize(self, builder): + fb_name = builder.CreateString(self.name) + if self.filename: + fb_filename = builder.CreateString(self.filename) + fb_shapes = TosaSerializer.serializeInt32Vec(builder, self.shape) + fb_usage = TosaSerializer.serializeInt32Vec(builder, self.usage) + fb_dformat = TosaSerializer.serializeInt32Vec(builder, self.dformat) + + TosaTensor.TosaTensorStart(builder) + TosaTensor.TosaTensorAddName(builder, fb_name) + TosaTensor.TosaTensorAddShape(builder, fb_shapes) + TosaTensor.TosaTensorAddType(builder, self.dtype) + TosaTensor.TosaTensorAddUsage(builder, fb_usage) + TosaTensor.TosaTensorAddFormat(builder, fb_dformat) + if self.filename: + TosaTensor.TosaTensorAddNpyFilename(builder, fb_filename) + + return TosaTensor.TosaTensorEnd(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.TosaOperatorStartInputsVector) + fb_outputs = TosaSerializer.serializeStrVec(builder, self.outputs, TosaOperator.TosaOperatorStartOutputsVector) + # 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.TosaOperatorStart(builder) + TosaOperator.TosaOperatorAddOp(builder, self.op) + TosaOperator.TosaOperatorAddInputs(builder, fb_inputs) + TosaOperator.TosaOperatorAddOutputs(builder, fb_outputs) + if self.attributes is not None: + TosaOperator.TosaOperatorAddAttributeType(builder, self.attributes.utype) + TosaOperator.TosaOperatorAddAttribute(builder, fb_attributes) + if self.quantInfo is not None: + TosaOperator.TosaOperatorAddQuantInfoType(builder, self.quantInfo.utype) + TosaOperator.TosaOperatorAddQuantInfo(builder, fb_qinfo) + + return TosaOperator.TosaOperatorEnd(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, usage, dformat, filename = None, placeholderFilename = None): + try: + # Someone already added this tensor. + # We may have to add more usages and formats + tens = self.tensors[name] + filename = tens.merge(name, shape, dtype, usage, dformat, filename) + except KeyError: + self.tensors[name] = TosaSerializerTensor(name, shape, dtype, usage, dformat, filename, 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.TosaBasicBlockStartInputsVector) + fbv_outputs = TosaSerializer.serializeStrVec(builder, list(self.outputs), TosaBasicBlock.TosaBasicBlockStartOutputsVector) + fbv_tensors = TosaSerializer.serializeObjVec(builder, list(self.tensors.values()), TosaBasicBlock.TosaBasicBlockStartTensorsVector) + fbv_operators = TosaSerializer.serializeObjVec(builder, self.operators, TosaBasicBlock.TosaBasicBlockStartOperatorsVector) + + TosaBasicBlock.TosaBasicBlockStart(builder) + TosaBasicBlock.TosaBasicBlockAddName(builder, fb_name) + TosaBasicBlock.TosaBasicBlockAddInputs(builder, fbv_inputs) + TosaBasicBlock.TosaBasicBlockAddOutputs(builder, fbv_outputs) + TosaBasicBlock.TosaBasicBlockAddTensors(builder, fbv_tensors) + TosaBasicBlock.TosaBasicBlockAddOperators(builder, fbv_operators) + return TosaBasicBlock.TosaBasicBlockEnd(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 + try: + TOSA_VERSION + except NameError: + TosaSerializer.setTosaVersion() + + 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.expectedFailure = False + self.expectedFailureDesc = '' + + def __str__(self): + str = '' + for bb in self.basicBlocks: + str = str + bb.__str__() + return str + + def addPlaceholder(self, shape, dtype, usage, dformat, 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, usage, dformat, None, filename) + # This is always an input to the block + self.currBasicBlock.addInput(name) + # Add the operator now + self.currBasicBlock.addOperator(tosa.Op.Op().PLACEHOLDER, [], name) + + if vals is not None: + np.save(os.path.join(self.pathPrefix, filename), vals, False) + + return tens + + def addConst(self, shape, dtype, usage, dformat, vals): + if not self.currBasicBlock: + raise Exception('addTensor called without valid basic block') + + name = 'const-{}'.format(self.currInputIdx) + filename = '{}.npy'.format(name) + self.currInputIdx = self.currInputIdx + 1 + + tens = self.currBasicBlock.addTensor(name, shape, dtype, usage, dformat, filename) + # Add the operator now + self.currBasicBlock.addOperator(tosa.Op.Op().CONST, [], name) + + if vals is not None: + np.save(os.path.join(self.pathPrefix, filename), vals, False) + return tens + + def addIntermediate(self, shape, dtype, usage, dformat): + + if not self.currBasicBlock: + raise Exception('addTensor called without valid basic block') + + name = 'layer-{}'.format(self.currLayerIdx) + filename = None # No file, so no filename + self.currLayerIdx = self.currLayerIdx + 1 + + tens = self.currBasicBlock.addTensor(name, shape, dtype, usage, dformat, filename) + + return tens + + def addInputTensor(self, tensor): + self.currBasicBlock.addOperator(tosa.Op.Op().PLACEHOLDER, [], tensor.name) + self.currBasicBlock.addTensor(tensor.name, tensor.shape, tensor.dtype, tensor.usage, tensor.dformat) + self.currBasicBlock.addInput(tensor.name) + + def addOutputTensor(self, tensor): + self.currBasicBlock.addOutput(tensor.name) + + def addOutput(self, shape, dtype, usage, dformat): + 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, usage, dformat, None) + self.currBasicBlock.addOutput(name) + return tens + + def addOperator(self, op, inputs, outputs, attributes = None, quant_info = None): + + if op == tosa.Op.Op().PLACEHOLDER or \ + op == tosa.Op.Op().CONST: + raise Exception('Use addPlaceholderTensor() or addConstTensor() to add PLACEHOLDER and CONST ops') + + return self.currBasicBlock.addOperator(op, inputs, outputs, attributes, quant_info) + + def setExpectedFailure(self, desc='', val=True): + self.expectedFailure = val + self.expectedFailureDesc = desc + + def setExpectedFailure(self, desc='', val=True): + self.expectedFailure = val + self.expectedFailureDesc = desc + + def serialize(self): + + builder = self.builder + + Version.VersionStart(builder) + Version.VersionAdd_major(builder, TOSA_VERSION[0]) + Version.VersionAdd_minor(builder, TOSA_VERSION[1]) + Version.VersionAdd_patch(builder, TOSA_VERSION[2]) + Version.VersionAdd_experimental(builder, TOSA_VERSION[3]) + version = Version.VersionEnd(builder) + + fbv_bb = TosaSerializer.serializeObjVec(builder, self.basicBlocks, TosaGraph.TosaGraphStartBlocksVector) + + TosaGraph.TosaGraphStart(builder) + TosaGraph.TosaGraphAddVersion(builder, version) + TosaGraph.TosaGraphAddBlocks(builder, fbv_bb) + graph = TosaGraph.TosaGraphEnd(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_shape = [] + ifm_file = [] + ofm_name = [] + ofm_file = [] + ofm_shape = [] + + for b in self.basicBlocks: + if b.name == 'main': + for i in b.inputs: + ifm_name.append(i) + ifm_shape.append(b.tensors[i].shape) + ifm_file.append(b.tensors[i].placeholderFilename) + for o in b.outputs: + ofm_name.append(o) + ofm_shape.append(b.tensors[o].shape) + # 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_placeholder'] = ifm_name + test_desc['ifm_file'] = ifm_file + test_desc['ifm_shape'] = ifm_shape + test_desc['ofm_name'] = ofm_name + test_desc['ofm_shape'] = ofm_shape + test_desc['ofm_file'] = ofm_file + 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(len(fb_strs)) + + @staticmethod + def serializeInt32Vec(builder, vec): + builder.StartVector(4, len(vec), 4) + for v in vec[::-1]: + builder.PrependInt32(v) + 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) + return builder.EndVector(len(vec)) + + @staticmethod + def toList(val): + if isinstance(val, list): + return val + else: + return [val] + + @staticmethod + def setTosaVersion(): + # Create a dummy flatbuffers file with the default version information + # There does not appear to be a better way to get a constant from a + # flatbuffer schema file + builder = flatbuffers.Builder(0) + Version.VersionStart(builder) + ver = Version.VersionEnd(builder) + TosaGraph.TosaGraphStart(builder) + TosaGraph.TosaGraphAddVersion(builder, ver) + gr = TosaGraph.TosaGraphEnd(builder) + builder.Finish(gr) + + out = builder.Output() + + gr = TosaGraph.TosaGraph() + root = gr.GetRootAsTosaGraph(out, 0) + + # Store the version as a global variable so that it only needs to be + # generated once per process. + global TOSA_VERSION + TOSA_VERSION = [root.Version()._major(), + root.Version()._minor(), + root.Version()._patch(), + root.Version()._experimental() ] |