# Copyright (c) 2020-2021, 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 os
import sys
import json
import flatbuffers
import numpy as np
import struct
from enum import Enum, IntEnum, unique
from tosa import (
    TosaGraph,
    TosaBasicBlock,
    TosaTensor,
    TosaOperator,
    DType,
    Op,
    ResizeMode,
    Version,
)
from tosa_ref_run import TosaReturnCode

# Include the ../thirdparty/serialization_lib/python directory in PYTHONPATH
parent_dir = os.path.dirname(os.path.realpath(__file__))
sys.path.append(
    os.path.join(parent_dir, "..", "thirdparty", "serialization_lib", "python")
)
import tosa

# 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 = tosa.DType.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 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, stride_fp, offset_fp, 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.fpvecs.append((a.ResizeAttributeAddStrideFp, stride_fp))
        self.fpvecs.append((a.ResizeAttributeAddOffsetFp, offset_fp))
        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 MulAttribute(self, shift):
        from tosa import MulAttribute as a, Attribute

        self.utype = Attribute.Attribute().MulAttribute
        self.optFcns = (a.MulAttributeStart, a.MulAttributeEnd)

        self.ints.append((a.MulAttributeAddShift, shift))

    def ArithmeticRightShiftAttribute(self, round):
        from tosa import ArithmeticRightShiftAttribute as a, Attribute

        self.utype = Attribute.Attribute().ArithmeticRightShiftAttribute
        self.optFcns = (
            a.ArithmeticRightShiftAttributeStart,
            a.ArithmeticRightShiftAttributeEnd,
        )

        self.bools.append((a.ArithmeticRightShiftAttributeAddRound, round))

    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,
        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(32)) & 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.TosaTensorStart(builder)
        TosaTensor.TosaTensorAddName(builder, fb_name)
        TosaTensor.TosaTensorAddShape(builder, fb_shapes)
        TosaTensor.TosaTensorAddType(builder, self.dtype)
        if self.data:
            TosaTensor.TosaTensorAddData(builder, fb_data)

        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,
        data=None,
        placeholderFilename=None,
    ):
        try:
            # Someone already added this tensor.
            tens = self.tensors[name]
        except KeyError:
            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.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.expectedReturnCode = TosaReturnCode.VALID
        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)
        filename = "{}.npy".format(name)
        self.currInputIdx = self.currInputIdx + 1

        tens = self.currBasicBlock.addTensor(name, shape, dtype, vals)
        # Add the operator now
        self.currBasicBlock.addOperator(tosa.Op.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 == tosa.Op.Op().CONST:
            raise Exception("Use addConstTensor() to add CONST ops")

        return self.currBasicBlock.addOperator(
            op, inputs, outputs, attributes, quant_info
        )

    def setExpectedReturnCode(self, val, desc=""):

        self.expectedReturnCode = val
        self.expectedFailureDesc = desc

        if val == TosaReturnCode.VALID:
            self.expectedFailure = False
        else:
            # Unpredictable or error results are considered expected failures
            # for conformance
            self.expectedFailure = True

    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_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(len(fb_strs))

    @staticmethod
    def serializeUint8Vec(builder, vec):
        builder.StartVector(1, len(vec), 8)
        for v in vec[::-1]:
            builder.PrependUint8(v)
        return builder.EndVector(len(vec))

    @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 serializeFpVec(builder, vec):
        builder.StartVector(4, len(vec), 4)
        for v in vec[::-1]:
            builder.PrependFloat32(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(),
        ]