| # 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 |
| |
| # Keep version number in sync with the version default value with schema/tosa.fbs |
| TOSA_VERSION_MAJOR = 0 |
| TOSA_VERSION_MINOR = 24 |
| TOSA_VERSION_PATCH = 0 |
| TOSA_VERSION_DRAFT = True |
| TOSA_VERSION = [TOSA_VERSION_MAJOR, |
| TOSA_VERSION_MINOR, |
| TOSA_VERSION_PATCH, |
| TOSA_VERSION_DRAFT] |
| # With the way flatc generates its python types, there is no programatic way |
| # to get string names for the integer types. Manually maintain a string table |
| # here. |
| DType = tosa.DType.DType() |
| DTypeNames = [ |
| "UNKNOWN", |
| "BOOL", |
| "UINT8", |
| "INT4", |
| "INT8", |
| "INT16", |
| "INT32", |
| "INT48", |
| "FLOAT", |
| ] |
| |
| # File identifier needs to be kept in sync with schema/tosa.fbs |
| TOSA_GRAPH_IDENTIFIER = b"\x54\x4F\x53\x41" |
| |
| 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 PadAttribute(self, padding, pad_const_int, pad_const_fp): |
| from tosa import PadAttribute as a, Attribute |
| |
| self.utype = Attribute.Attribute().PadAttribute |
| self.optFcns = (a.PadAttributeStart, a.PadAttributeEnd) |
| |
| self.intvecs.append((a.PadAttributeAddPadding, padding)) |
| self.ints.append((a.PadAttributeAddPadConstInt, pad_const_int)) |
| self.floats.append((a.PadAttributeAddPadConstFp, pad_const_fp)) |
| |
| 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 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)) |
| |
| def TransposeAttribute(self, perm): |
| from tosa import TransposeAttribute as a, Attribute |
| |
| self.utype = Attribute.Attribute().TransposeAttribute |
| self.optFcns = (a.TransposeAttributeStart, a.TransposeAttributeEnd) |
| |
| self.intvecs.append((a.TransposeAttributeAddPerm, perm)) |
| |
| def TableAttribute(self, table): |
| from tosa import TableAttribute as a, Attribute |
| |
| self.utype = Attribute.Attribute().TableAttribute |
| self.optFcns = (a.TableAttributeStart, a.TableAttributeEnd) |
| |
| self.intvecs.append((a.TableAttributeAddTable, table)) |
| |
| 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(24)) & ByteMask |
| u8_data.extend([b0, b1, b2, b3]) |
| elif self.dtype == DType.INT48: |
| for val in self.data: |
| val_u64 = np.uint64(val) |
| b0 = val_u64 & ByteMask |
| b1 = (val_u64 >> np.uint64(8)) & ByteMask |
| b2 = (val_u64 >> np.uint64(16)) & ByteMask |
| b3 = (val_u64 >> np.uint64(24)) & ByteMask |
| b4 = (val_u64 >> np.uint64(32)) & ByteMask |
| b5 = (val_u64 >> np.uint64(40)) & ByteMask |
| u8_data.extend([b0, b1, b2, b3, b4, b5]) |
| elif self.dtype == DType.FLOAT: |
| for val in self.data: |
| b = struct.pack("!f", val) |
| u8_data.extend([b[3], b[2], b[1], b[0]]) |
| else: |
| raise Exception( |
| "unsupported data type {}".format(DTypeNames[self.dtype]) |
| ) |
| fb_data = TosaSerializer.serializeUint8Vec(builder, u8_data) |
| |
| TosaTensor.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 |
| |
| 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_draft(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, 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 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] |
| |