| # Copyright (c) 2020-2023, 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 struct |
| import serializer.tosa_serializer as ts |
| import json |
| import flatbuffers |
| import numpy as np |
| from enum import IntEnum, unique |
| from tosa import ( |
| TosaGraph, |
| TosaRegion, |
| 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 = 70 |
| TOSA_VERSION_PATCH = 0 |
| TOSA_VERSION_DRAFT = False |
| TOSA_VERSION = [ |
| TOSA_VERSION_MAJOR, |
| TOSA_VERSION_MINOR, |
| TOSA_VERSION_PATCH, |
| TOSA_VERSION_DRAFT, |
| ] |
| |
| # File identifier needs to be kept in sync with schema/tosa.fbs |
| TOSA_GRAPH_IDENTIFIER = b"\x54\x4F\x53\x41" |
| |
| # 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", |
| "FP32", |
| "UINT16", |
| "FP16", |
| "BF16", |
| ] |
| |
| 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.int16vecs = [] |
| 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.int16vecs: |
| intVecList.append((fcn, TosaSerializer.serializeInt16Vec(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, |
| pad, |
| input_zp, |
| output_zp, |
| accum_dtype, |
| ): |
| from tosa import PoolAttribute as a, Attribute |
| |
| self.utype = Attribute.Attribute().PoolAttribute |
| |
| self.optFcns = (a.Start, a.End) |
| self.intvecs.append((a.AddPad, pad)) |
| self.intvecs.append((a.AddKernel, kernel)) |
| self.intvecs.append((a.AddStride, stride)) |
| self.ints.append((a.AddInputZp, input_zp)) |
| self.ints.append((a.AddOutputZp, output_zp)) |
| self.ints.append((a.AddAccumDtype, accum_dtype)) |
| |
| def ConvAttribute(self, pad, stride, dilation, input_zp, weight_zp): |
| from tosa import ConvAttribute as a, Attribute |
| |
| self.utype = Attribute.Attribute().ConvAttribute |
| self.optFcns = (a.Start, a.End) |
| |
| self.intvecs.append((a.AddPad, pad)) |
| self.intvecs.append((a.AddStride, stride)) |
| self.intvecs.append((a.AddDilation, dilation)) |
| self.ints.append((a.AddInputZp, input_zp)) |
| self.ints.append((a.AddWeightZp, weight_zp)) |
| |
| def TransposeConvAttribute(self, outpad, stride, output_shape, input_zp, weight_zp): |
| 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.AddOutputShape, output_shape)) |
| self.ints.append((a.AddInputZp, input_zp)) |
| self.ints.append((a.AddWeightZp, weight_zp)) |
| |
| def PadAttribute(self, serializer_builder, 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)) |
| |
| # pad_const_fp attribute serialized as uint8 vector |
| pad_const_float_as_bytes = struct.pack("<f", pad_const_fp) |
| serialized_pad_const_fp = ts.TosaSerializer.serializeUint8Vec( |
| serializer_builder, pad_const_float_as_bytes |
| ) |
| |
| self.floats.append((a.AddPadConstFp, serialized_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, new_shape): |
| from tosa import ReshapeAttribute as a, Attribute |
| |
| self.utype = Attribute.Attribute().ReshapeAttribute |
| self.optFcns = (a.Start, a.End) |
| |
| self.intvecs.append((a.AddNewShape, new_shape)) |
| |
| def SliceAttribute(self, start, size): |
| from tosa import SliceAttribute as a, Attribute |
| |
| self.utype = Attribute.Attribute().SliceAttribute |
| self.optFcns = (a.Start, a.End) |
| |
| self.intvecs.append((a.AddStart, start)) |
| 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, scale, offset, border, mode): |
| from tosa import ResizeAttribute as a, Attribute |
| |
| self.utype = Attribute.Attribute().ResizeAttribute |
| self.optFcns = (a.Start, a.End) |
| |
| self.int16vecs.append((a.AddScale, scale)) |
| self.int16vecs.append((a.AddOffset, offset)) |
| self.int16vecs.append((a.AddBorder, border)) |
| self.ints.append((a.AddMode, mode)) |
| |
| def ClampAttribute(self, serializer_builder, 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)) |
| |
| # min/max float attributes serialized as uint8 vectors |
| minfp_bytes = struct.pack("<f", minfp) |
| maxfp_bytes = struct.pack("<f", maxfp) |
| serialized_minfp_bytes = ts.TosaSerializer.serializeUint8Vec( |
| serializer_builder, minfp_bytes |
| ) |
| serialized_maxfp_bytes = ts.TosaSerializer.serializeUint8Vec( |
| serializer_builder, maxfp_bytes |
| ) |
| |
| self.floats.append((a.AddMinFp, serialized_minfp_bytes)) |
| self.floats.append((a.AddMaxFp, serialized_maxfp_bytes)) |
| |
| 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, perms): |
| from tosa import TransposeAttribute as a, Attribute |
| |
| self.utype = Attribute.Attribute().TransposeAttribute |
| self.optFcns = (a.Start, a.End) |
| |
| self.intvecs.append((a.AddPerms, perms)) |
| |
| 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)) |
| |
| def MatMulAttribute(self, A_zp, B_zp): |
| from tosa import MatMulAttribute as a, Attribute |
| |
| self.utype = Attribute.Attribute().MatMulAttribute |
| self.optFcns = (a.Start, a.End) |
| |
| self.ints.append((a.AddAZp, A_zp)) |
| self.ints.append((a.AddBZp, B_zp)) |
| |
| def FullyConnectedAttribute(self, input_zp, weight_zp): |
| from tosa import FullyConnectedAttribute as a, Attribute |
| |
| self.utype = Attribute.Attribute().FullyConnectedAttribute |
| self.optFcns = (a.Start, a.End) |
| |
| self.ints.append((a.AddInputZp, input_zp)) |
| self.ints.append((a.AddWeightZp, weight_zp)) |
| |
| def NegateAttribute(self, input1_zp, output_zp): |
| from tosa import NegateAttribute as a, Attribute |
| |
| self.utype = Attribute.Attribute().NegateAttribute |
| self.optFcns = (a.Start, a.End) |
| |
| self.ints.append((a.AddInput1Zp, input1_zp)) |
| self.ints.append((a.AddOutputZp, output_zp)) |
| |
| def FFTAttribute(self, inverse): |
| from tosa import FFTAttribute as a, Attribute |
| |
| self.utype = Attribute.Attribute().FFTAttribute |
| self.optFcns = (a.Start, a.End) |
| |
| self.bools.append((a.AddInverse, inverse)) |
| |
| |
| 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 dtype == DType.FP32 or dtype == DType.BF16: |
| fntype = np.float32 |
| elif dtype == DType.FP16: |
| fntype = np.float16 |
| else: |
| fntype = int |
| |
| if isinstance(data, np.ndarray): |
| data = data.flatten().astype(fntype).tolist() |
| data = list(map(fntype, data)) |
| self.data = data |
| elif isinstance(data, list): |
| data = list(map(fntype, 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): |
| concatString = "TosaSerializerTensor name: {} shape: {} dtype: {}".format( |
| self.name, |
| self.shape, |
| DTypeNames[self.dtype], |
| ) |
| return concatString |
| |
| 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.FP16: |
| np_arr = np.array(self.data, dtype=np.float16) |
| u8_data.extend(np_arr.view(np.uint8)) |
| elif self.dtype == DType.FP32 or self.dtype == DType.BF16: |
| # for val in self.data: |
| # b = struct.pack("!f", val) |
| # u8_data.extend([b[3], b[2], b[1], b[0]]) |
| np_arr = np.array(self.data, dtype=np.float32) |
| u8_data.extend(np_arr.view(np.uint8)) |
| elif self.dtype == TosaDType.DType: |
| # Serialize DType enum data as uint8 bytes |
| for val in self.data: |
| np_arr = np.array(self.data, dtype=np.uint32) |
| u8_data.extend(np_arr.view(np.uint8)) |
| 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): |
| self.op = op |
| self.attributes = attributes |
| self.inputs = TosaSerializer.toList(inputs) |
| self.outputs = TosaSerializer.toList(outputs) |
| |
| def __str__(self): |
| concatString = "Op {}\n----\n".format(self.op) |
| |
| for i in self.inputs: |
| concatString = concatString + " Input: {}\n".format(i) |
| for o in self.outputs: |
| concatString = concatString + " Output: {}\n".format(o) |
| |
| return concatString |
| |
| 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 attributes enums still |
| if self.attributes is not None: |
| fb_attributes = self.attributes.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) |
| |
| 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): |
| self.operators.append(TosaSerializerOperator(op, inputs, outputs, attributes)) |
| |
| 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) |
| |
| |
| class TosaSerializerRegion: |
| def __init__(self, name, pathPrefix, saveConstsToFile=False): |
| self.name = name |
| self.basicBlocks = [] |
| self.currInputIdx = 0 |
| self.currConstIdx = 0 |
| self.currLayerIdx = 1 |
| self.currResultIdx = 0 |
| self.pathPrefix = pathPrefix |
| self.saveConstsToFile = saveConstsToFile |
| |
| def addBasicBlock(self, name): |
| self.currBasicBlock = TosaSerializerBasicBlock(name) |
| self.basicBlocks.append(self.currBasicBlock) |
| |
| def serialize(self, builder): |
| fb_name = builder.CreateString(self.name) |
| fbv_basicBlocks = TosaSerializer.serializeObjVec( |
| builder, self.basicBlocks, TosaRegion.StartBlocksVector |
| ) |
| |
| TosaRegion.Start(builder) |
| TosaRegion.AddName(builder, fb_name) |
| TosaRegion.AddBlocks(builder, fbv_basicBlocks) |
| return TosaRegion.End(builder) |
| |
| 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) |
| |
| if self.saveConstsToFile: |
| filename = "{}.npy".format(name) |
| np.save(os.path.join(self.pathPrefix, filename), vals, False) |
| |
| 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): |
| if op == TosaOp.Op().CONST: |
| raise Exception("Use addConstTensor() to add CONST ops") |
| |
| return self.currBasicBlock.addOperator( |
| op, |
| inputs, |
| outputs, |
| attributes, |
| ) |
| |
| |
| @unique |
| class TensorDir(IntEnum): |
| PLACEHOLDER = 0 |
| CONST = 1 |
| INTERMEDIATE = 2 |
| RESULT = 3 |
| |
| |
| class TosaSerializer: |
| def __init__(self, pathPrefix, saveConstsToFile=False): |
| self.builder = flatbuffers.Builder(0) |
| |
| self.regions = [] |
| self.startRegion("main", pathPrefix, saveConstsToFile) |
| |
| # Enables inspection of constant data outside of graph |
| self.saveConstsToFile = saveConstsToFile |
| |
| self.currRegion.addBasicBlock("main") |
| |
| # Is this an illegal test that is expected to fail? |
| self.expectedReturnCode = 0 |
| self.expectedFailure = False |
| self.expectedFailureDesc = "" |
| |
| def __str__(self): |
| concatString = "" |
| for region in self.regions: |
| concatString = concatString + str(region) |
| return concatString |
| |
| def addPlaceholder(self, shape, dtype, vals): |
| return self.currRegion.addPlaceholder(shape, dtype, vals) |
| |
| def addConst(self, shape, dtype, vals): |
| return self.currRegion.addConst(shape, dtype, vals) |
| |
| def addIntermediate(self, shape, dtype): |
| return self.currRegion.addIntermediate(shape, dtype) |
| |
| def addInputTensor(self, tensor): |
| self.currRegion.addInputTensor(tensor) |
| |
| def addOutputTensor(self, tensor): |
| self.currRegion.addOutputTensor(tensor) |
| |
| def addOutput(self, shape, dtype): |
| return self.currRegion.addOutput(shape, dtype) |
| |
| def addOperator(self, op, inputs, outputs, attributes=None): |
| return self.currRegion.addOperator(op, inputs, outputs, attributes) |
| |
| def addBasicBlock(self, name): |
| self.currRegion.addBasicBlock(name) |
| |
| 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_region = TosaSerializer.serializeObjVec( |
| builder, self.regions, TosaGraph.StartRegionsVector |
| ) |
| |
| TosaGraph.Start(builder) |
| TosaGraph.AddVersion(builder, version) |
| TosaGraph.AddRegions(builder, fbv_region) |
| graph = TosaGraph.End(builder) |
| |
| self.builder.Finish(graph, TOSA_GRAPH_IDENTIFIER) |
| 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 region in self.regions: |
| for block in region.basicBlocks: |
| if block and block.name == "main": |
| for i in block.inputs: |
| ifm_name.append(i) |
| ifm_file.append(block.tensors[i].placeholderFilename) |
| for o in block.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 startRegion(self, name, pathPrefix, saveConstsToFile): |
| self.currRegion = TosaSerializerRegion(name, pathPrefix, saveConstsToFile) |
| self.regions.append(self.currRegion) |
| |
| @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) |
| try: |
| return builder.EndVector() |
| except TypeError: |
| return builder.EndVector(len(vec)) |
| |
| @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 serializeInt16Vec(builder, vec): |
| builder.StartVector(2, len(vec), 4) |
| for v in vec[::-1]: |
| builder.PrependInt16(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] |