Move python-based serializer from reference_model.

Signed-off-by: Kevin Cheng <kevin.cheng@arm.com>
Change-Id: I5369f1543b8980ad690073102f4557e215269d3b

1 files changed, 834 insertions, 0 deletions

diff --git a/python/tosa_serializer.py b/python/tosa_serializer.py
new file mode 100644
index 0000000..b1c5dae
--- /dev/null
+++ b/python/tosa_serializer.py
@@ -0,0 +1,834 @@
+# 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
+
+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 PoolAttribute(self, kernel, stride, padding):
+        from tosa import PoolAttribute as a, Attribute
+
+        self.utype = Attribute.Attribute().PoolAttribute
+
+        self.optFcns = (a.PoolAttributeStart, a.PoolAttributeEnd)
+        self.intvecs.append((a.PoolAttributeAddPadding, padding))
+        self.intvecs.append((a.PoolAttributeAddKernel, kernel))
+        self.intvecs.append((a.PoolAttributeAddStride, stride))
+
+    def ConvAttribute(self, padding, stride, dilation):
+        from tosa import ConvAttribute as a, Attribute
+
+        self.utype = Attribute.Attribute().ConvAttribute
+        self.optFcns = (a.ConvAttributeStart, a.ConvAttributeEnd)
+
+        self.intvecs.append((a.ConvAttributeAddPadding, padding))
+        self.intvecs.append((a.ConvAttributeAddStride, stride))
+        self.intvecs.append((a.ConvAttributeAddDilation, dilation))
+
+    def TransposeConvAttribute(self, outpad, stride, dilation, output_shape):
+        from tosa import TransposeConvAttribute as a, Attribute
+
+        self.utype = Attribute.Attribute().TransposeConvAttribute
+        self.optFcns = (a.TransposeConvAttributeStart, a.TransposeConvAttributeEnd)
+
+        self.intvecs.append((a.TransposeConvAttributeAddOutpad, outpad))
+        self.intvecs.append((a.TransposeConvAttributeAddStride, stride))
+        self.intvecs.append((a.TransposeConvAttributeAddDilation, dilation))
+        self.intvecs.append((a.TransposeConvAttributeAddOutputShape, 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)
+        # This try/except block supports both the Flatbuffers 2.x and 1.x APIs,
+        # defaulting to 2.x.  If/when Flatbuffers 1.x support is deprecated, the
+        # try block and builder.EndVector(len) function calls can be removed.
+        try:
+            return builder.EndVector()
+        except TypeError:
+            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)
+        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]
+
+    @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(),
+        ]