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Diffstat (limited to 'ethosu/vela/architecture_features.py')
| -rw-r--r-- | ethosu/vela/architecture_features.py | 618 |
1 files changed, 618 insertions, 0 deletions
diff --git a/ethosu/vela/architecture_features.py b/ethosu/vela/architecture_features.py new file mode 100644 index 00000000..4a03d0ef --- /dev/null +++ b/ethosu/vela/architecture_features.py @@ -0,0 +1,618 @@ +# Copyright (C) 2020 Arm Limited or its affiliates. All rights reserved. +# +# SPDX-License-Identifier: Apache-2.0 +# +# 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 +# +# 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. + + +# Description: +# Holds a container for Ethos-U55/System architecture parameters. + +from .nn_graph import MemArea, TensorPurpose, NpuBlockType, TensorFormat +from .numeric_util import round_up, round_up_divide +from collections import namedtuple +from configparser import ConfigParser +from .supported_operators import SupportedOperators +import numpy as np +import enum + +PointXY = namedtuple("PointXY", "x y") +PointXYZ = namedtuple("PointXYZ", "x y z") + + +class Block: + def __init__(self, w, h, d): + self.width = w + self.height = h + self.depth = d + + def __eq__(self, other): + if self.width == other.width and self.height == other.height and self.depth == other.depth: + return True + else: + return False + + def __repr__(self): + return "<Block: {0},{1},{2}>".format(self.width, self.height, self.depth) + + @classmethod + def from_string(cls, s): + w, h, c = (int(v) for v in s.split("x")) + return cls(w, h, c) + + +class Rect: + def __init__(self, x, y, z, x2, y2, z2): + self.x = x + self.y = y + self.z = z + self.x2 = x2 + self.y2 = y2 + self.z2 = z2 + + def start(self): + return PointXYZ(self.x, self.y, self.z) + + def end(self): + return PointXYZ(self.x2, self.y2, self.z2) + + def size(self): + return Block(self.x2 - self.x + 1, self.y2 - self.y + 1, self.z2 - self.z + 1) + + def __repr__(self): + return "<Rect: ({0},{1},{2}) ({3},{4},{5})>".format(self.x, self.y, self.z, self.x2, self.y2, self.z2) + + +class Kernel: + def __init__(self, w, h, sx=1, sy=1, dx=1, dy=1): + assert sx > 0 and sy > 0 + assert dx > 0 and dy > 0 + self.width = w + self.height = h + self.stride = PointXY(sx, sy) + self.dilation = PointXY(dx, dy) + + +class SHRAMElements: + IFM8 = 0 + IFM16 = 1 + IFM8_Elementwise = 2 + IFM16_Elementwise = 3 + Acc16 = 4 + Acc32 = 5 + Acc40 = 6 + Last = Acc40 + BitSizes = np.array([8, 16, 8, 16, 16, 32, 40], np.int32) + + +class SHRAMBlockConfig: + def __init__(self, sizes, banks): + assert len(banks) == SHRAMElements.Last + 1 + self.sizes = sizes + self.banks = banks + + +# Area indices must match Ethos-U55 SHRAM layout spec +class SharedBufferArea(enum.IntEnum): + OFM = 0 + Weights = 1 + IFM = 2 + Accumulators = 3 + Size = Accumulators + 1 + + +class ArchitectureFeatures: + """This class is a container for various parameters of the Ethos-U55 core +and system configuration that can be tuned, either by command line +parameters or by the Ethos-U55 architects. The class is often passed +around to passes that need to do architecture-dependent actions. + +Note the difference between ArchitectureFeatures and CompilerOptions +- ArchitectureFeatures is for changing the Ethos-U55 and system architecture +- CompilerOptions is for changing the behaviour of the compiler + +""" + + ArchitectureConfig = namedtuple( + "ArchitectureConfig", "macs cores ofm_ublock ifm_ublock shram_banks shram_granules elem_units" + ) + accelerator_configs = { + "ethos-u55-256": ArchitectureConfig(256, 1, Block(2, 2, 8), Block(2, 2, 8), 48, [8, 8, 8, 8, 8, 16, 20], 8), + "ethos-u55-128": ArchitectureConfig(128, 1, Block(2, 1, 8), Block(2, 2, 8), 24, [4, 4, 4, 4, 4, 8, 12], 4), + "ethos-u55-64": ArchitectureConfig(64, 1, Block(1, 1, 8), Block(1, 1, 8), 16, [2, 2, 2, 2, 4, 4, 8], 2), + "ethos-u55-32": ArchitectureConfig(32, 1, Block(1, 1, 4), Block(1, 1, 8), 16, [2, 2, 2, 2, 4, 4, 4], 1), + } + + OFMSplitDepth = 16 + + def __init__( + self, + vela_config: ConfigParser, + accelerator_config, + system_config, + permanent_storage, + inter_pass_cycle_delay, + dram_bandwidth, + override_block_config, + block_config_limit, + global_memory_clock_scale, + max_blockdep, + ): + accelerator_config = accelerator_config.lower() + self.vela_config = vela_config + self.accelerator_config = accelerator_config + if not self.accelerator_config in ArchitectureFeatures.accelerator_configs: + raise Exception("Unknown accelerator configuration " + self.accelerator_config) + accel_config = ArchitectureFeatures.accelerator_configs[self.accelerator_config] + self.config = accel_config + + self.system_config = system_config + + is_yoda_system = "yoda-" in self.accelerator_config + + if is_yoda_system: + self.sram_size = 256 * 1024 + else: + self.sram_size = 200 * 1024 * 1024 + + self.ncores = accel_config.cores + self.ofm_ublock = accel_config.ofm_ublock + self.ifm_ublock = accel_config.ifm_ublock + self.subkernel_max = Block(8, 8, 65536) + self.ofm_block_max = Block(64, 32, 128) + self.override_block_config = override_block_config + self.block_config_limit = block_config_limit + + self.global_memory_clock_scale = global_memory_clock_scale + if self.global_memory_clock_scale <= 0.0 or self.global_memory_clock_scale > 1.0: + raise Exception( + "Invalid global_memory_clock_scale = " + + str(self.global_memory_clock_scale) + + " (must be > 0.0 and <= 1.0)" + ) + + self.max_blockdep = max_blockdep + + dpu_min_height = accel_config.ofm_ublock.height + dpu_min_width = accel_config.ofm_ublock.width + dpu_dot_product_width = 8 + dpu_min_ofm_channels = accel_config.ofm_ublock.depth + + self.num_elem_wise_units = accel_config.elem_units + self.num_macs_per_cycle = dpu_min_height * dpu_min_width * dpu_dot_product_width * dpu_min_ofm_channels + + self.memory_clock_scales = np.zeros(MemArea.Size) + self.memory_port_widths = np.zeros(MemArea.Size) + + # Get system configuration + self.__read_sys_config() + + # apply the global memory clock scales to the individual ones from the system config + for mem in MemArea.all(): + self.memory_clock_scales[mem] *= self.global_memory_clock_scale + + self.memory_clocks = self.memory_clock_scales * self.npu_clock + self.memory_bandwidths_per_cycle = self.memory_port_widths * self.memory_clock_scales / 8 + + if dram_bandwidth != 0: + self.memory_bandwidths_per_cycle[MemArea.Dram] = dram_bandwidth * 1e9 / self.npu_clock + + self.memory_bandwidths_per_second = self.memory_bandwidths_per_cycle * self.npu_clock + + # sizes as N x H x W x C. we need to round up to these when allocating storage + self.storage_rounding_quantums = { + TensorFormat.Unknown: (1, 1, 1, 1), + TensorFormat.WeightsCompressed: (1, 1, 1, 1), + TensorFormat.NHWC: (1, 1, 1, 1), + TensorFormat.NHCWB16: (1, 1, 1, 16), + } + + # brick sizes as N x H x W x C. We have to fetch whole bricks at a time + self.brick_sizes = { + TensorFormat.Unknown: (1, 1, 1, 1), + TensorFormat.WeightsCompressed: (1, 1, 1, 1), + TensorFormat.NHWC: (1, 1, 1, 1), + TensorFormat.NHCWB16: (1, 1, 1, 16), + } + + self.inter_pass_cycle_delay = inter_pass_cycle_delay + + self.default_weight_format = TensorFormat.WeightsCompressed + self.default_feature_map_format = TensorFormat.NHWC + + if permanent_storage != MemArea.OffChipFlash: + self.permanent_storage_mem_area = permanent_storage + + self.tensor_storage_mem_area = { + # permanent mem_area + TensorPurpose.Weights: self.permanent_storage_mem_area, + TensorPurpose.FeatureMap: self.feature_map_storage_mem_area, + } + + self.tensor_load_mem_area = dict(self.tensor_storage_mem_area) + + if self.tensor_storage_mem_area[TensorPurpose.Weights] in (MemArea.OffChipFlash,): + self.tensor_load_mem_area[TensorPurpose.Weights] = MemArea.Sram + + self.min_block_sizes = { + NpuBlockType.Default: (dpu_min_height, dpu_min_width), + NpuBlockType.VectorProduct: (1, 1), + NpuBlockType.ConvolutionMxN: (dpu_min_height, dpu_min_width), + NpuBlockType.Pooling: (dpu_min_height, dpu_min_width), + NpuBlockType.ConvolutionDepthWise: (dpu_min_height, dpu_min_width), + NpuBlockType.ElementWise: (1, 1), + } + + self.sub_kernel_limits = { + NpuBlockType.Default: (8, 8), + NpuBlockType.VectorProduct: (1, 1), + NpuBlockType.ConvolutionMxN: (8, 8), + NpuBlockType.Pooling: (8, 8), + NpuBlockType.ConvolutionDepthWise: (8, 8), + NpuBlockType.ElementWise: (1, 1), + } + + # weights for scheduler search + from .npu_performance import make_bandwidth_array + + self.bandwidth_weights = make_bandwidth_array() + self.bandwidth_weights[MemArea.Sram] = 1.0 + self.bandwidth_weights[MemArea.Dram] = 10.0 + self.bandwidth_weights[MemArea.OnChipFlash] = 2.0 + self.bandwidth_weights[MemArea.OffChipFlash] = 20.0 + self.cycles_weight = 40 + self.max_sram_used_weight = 1000 + + if is_yoda_system: + self.max_sram_used_weight = 0 + + # Shared Buffer Block allocations + self.shram_bank_size = 1024 # bytes + self.shram_size_bytes = accel_config.shram_banks * self.shram_bank_size + self.shram_reserved_output_banks = 2 + self.shram_reserved_weight_banks = 0 + self.shram_reserved_unused_banks = 2 if accel_config.shram_banks > 16 else 0 + self.shram_total_banks = accel_config.shram_banks - self.shram_reserved_unused_banks + self.shram_bank_granules = np.array(accel_config.shram_granules, np.int32) + + # Build a map of acceptable IFM/OFM block configurations up to the maximum + # IFM/OFM block size. + ifm_block_max = self.get_ifm_block_size(32, self.ofm_block_max, Kernel(8, 8)) + self.block_config_map = dict() + self.generate_block_config_map(Block(ifm_block_max.width, ifm_block_max.height, 128)) + + # Setup supported operators and restriction checkers class + self.supported_operators = SupportedOperators() + + # Calculate block configuration for ALL known IFM operations and + # accumulator sizes. Consumers will need to select their preferred + # operation and bit-width at read-time. + def generate_block_config(self, width, height, depth): + # Number of bytes required for any SRAM element for a FM of given dimensions + size_bytes = (SHRAMElements.BitSizes * (height * width * depth)) // 8 + # Convert byte size (rounded) to size in banks + size_banks = round_up_divide(size_bytes, self.shram_bank_size) + size_banks *= 2 # Double buffer the IFM/Acc (need twice as many banks) + # Round bank requirement to bank granularity + required_banks = round_up(size_banks, self.shram_bank_granules) + return SHRAMBlockConfig(size_bytes, required_banks) + + @staticmethod + def make_block_config_key(width, height, depth): + return (int(height), int(width), int(depth)) + + def get_block_config(self, width, height, depth): + assert depth <= self.ofm_block_max.depth + key = ArchitectureFeatures.make_block_config_key(width, height, depth) + config = self.block_config_map.get(key, None) + return config + + # Generate a key:value map of possible block configurations, where the + # key is compounded from the block dimensions: 0x00HHWWCC + def generate_block_config_map(self, block: Block): + for h in range(1, block.height + 1): + for w in range(1, block.width + 1): + # All possible IFM/OFM depth values + for c in [4, 8, 12, 16, 24, 32, 40, 48, 56, 64, 72, 80, 88, 96, 104, 112, 120, 128]: + key = ArchitectureFeatures.make_block_config_key(w, h, c) + self.block_config_map[key] = self.generate_block_config(w, h, c) + + def calc_ifm_block_depth(self, ifm_depth, ifm_bits): + assert ifm_bits == 8 or ifm_bits == 16 + assert ifm_depth > 0 + ifm_depth = round_up(ifm_depth, self.ifm_ublock.depth) + max_block_depth = 32 if ifm_bits == 8 else 16 + return min(max_block_depth, ifm_depth) + + # Calculate the size of the IFM block given a depth, target OFM block and a kernel + def get_ifm_block_size( + self, ifm_block_depth, ofm_block: Block, kernel: Kernel, subkernel: Block = Block(8, 8, 65536) + ): + upscaling = 1 + # Height + ifm_odd_2x_height_enable = 0 + dilated_kernel_height = ((kernel.height - 1) * kernel.dilation.y) + 1 + ifm_block_height = ( + (ofm_block.height - 1) * kernel.stride.y + + min(subkernel.height, dilated_kernel_height) + + ifm_odd_2x_height_enable + ) // upscaling + + if kernel.stride.y == 1: + ifm_block_height = round_up(ifm_block_height, self.ofm_ublock.height) + elif kernel.stride.y == 2: + if (self.ofm_ublock.height == 2) and (ifm_block_height % 4 == 2): + ifm_block_height = ifm_block_height + 2 + else: + ifm_block_height = round_up(ifm_block_height, self.ofm_ublock.height) + else: + assert False + + # Width + ifm_odd_2x_width_enable = 0 + dilated_kernel_width = ((kernel.width - 1) * kernel.dilation.x) + 1 + ifm_block_width = ( + (ofm_block.width - 1) * kernel.stride.x + + min(subkernel.width, dilated_kernel_width) + + ifm_odd_2x_width_enable + ) // upscaling + + if kernel.stride.x == 1: + ifm_block_width = round_up(ifm_block_width, self.ofm_ublock.width) + elif kernel.stride.x == 2: + if (self.ofm_ublock.width == 2) and (ifm_block_width % 4 == 2): + ifm_block_width = ifm_block_width + 2 + else: + ifm_block_width = round_up(ifm_block_width, self.ofm_ublock.width) + else: + assert False + + return Block(ifm_block_width, ifm_block_height, ifm_block_depth) + + @staticmethod + def intersects(start_a, end_a, start_b, end_b): + start_x = max(start_a[0], start_b[0]) + end_x = min(end_a[0], end_b[0]) + start_y = max(start_a[1], start_b[1]) + end_y = min(end_a[1], end_b[1]) + start_z = max(start_a[2], start_b[2]) + end_z = min(end_a[2], end_b[2]) + return ((end_x - start_x) > 0) and ((end_y - start_y) > 0) and ((end_z - start_z) > 0) + + # Block job dependency: + # Does the VOLUME of IFMs for block job B(0) overlap with VOLUME of OFMs block jobs A(8,9,10) + # + # A | B + # ----------------------+------------------ + # .... 3,4,5,6,7,8,9,10 | 0,1,2,3,4,5,6,8 10 < JOB NUMBER + # |<------->| dependency offset + # + MAX_BLOCKDEP = 3 + + # Get the coordinates of a block offset from either the end (negative) + # or the start (zero or positive) of the given 3d area + def get_offset_block_coords(self, area: Rect, block: Block, offset): + size = area.size() + # Dimensions of the region, in blocks + width_blocks = round_up_divide(size.width, block.width) + height_blocks = round_up_divide(size.height, block.height) + depth_blocks = round_up_divide(size.depth, block.depth) + total_blocks = width_blocks * height_blocks * depth_blocks + if offset < 0: + index = total_blocks + offset + else: + index = offset + + if index >= total_blocks: + return None + + # Coordinates of the indexed block + coord_z = block.depth * (index % depth_blocks) + coord_y = block.height * (index // (depth_blocks * width_blocks)) + coord_x = block.width * ((index // depth_blocks) % width_blocks) + + return (coord_x + area.x, coord_y + area.y, coord_z + area.z) + + def get_first_job_input_volume( + self, ifm: Rect, ofm: Rect, ifm_block_depth, ofm_block: Block, kernel: Kernel, padLT, block_offset + ): + # Get ifm block size (jobs are invisibly decomposed into subkernels) + ifm_block = self.get_ifm_block_size(ifm_block_depth, ofm_block, kernel, self.ofm_block_max) + ifm_depth_blocks = round_up_divide(ifm.size().depth, ifm_block_depth) + + # Which OFM block are we calculating + ofm_coord = self.get_offset_block_coords(ofm, ofm_block, block_offset // ifm_depth_blocks) + if ofm_coord is None: + return None + + # Coordinate of the source IFM block + ifm_coord_x = max(0, ofm_coord[0] * kernel.stride.x - padLT[0]) + ifm_coord_y = max(0, ofm_coord[1] * kernel.stride.y - padLT[1]) + ifm_coord_z = ifm.z + (block_offset % ifm_depth_blocks) * ifm_block.depth + + # IFM block that will be sampled for the FIRST+block_offset job in the next operator's OFM + start_coord = (ifm_coord_x, ifm_coord_y, ifm_coord_z) + end_coord = ( + start_coord[0] + ifm_block.width, + start_coord[1] + ifm_block.height, + start_coord[2] + ifm_block.depth, + ) + + return (start_coord, end_coord, 1) # start, end, total jobs + + def get_prev_job_output_volume( + self, ifm: Block, ofm: Rect, ifm_block_depth, ofm_block: Block, kernel: Kernel, block_offset + ): + assert block_offset >= 0 + + # Get OFM block's volume coordinates + start_coord = self.get_offset_block_coords(ofm, ofm_block, -1 - block_offset) + if start_coord is None: + return None + end_coord = ( + start_coord[0] + ofm_block.width, + start_coord[1] + ofm_block.height, + start_coord[2] + ofm_block.depth, + ) + + # Calculate how many IFM blocks this OFM block requires (i.e how many jobs) + ifm_block = self.get_ifm_block_size(ifm_block_depth, ofm_block, kernel, self.ofm_block_max) + ifm_depth_blocks = round_up_divide(ifm.size().depth, ifm_block_depth) + ifm_depth_blocks = 1 # Overwrite with 1 to force OFM block dependency, not IFM + + return (start_coord, end_coord, ifm_depth_blocks) # start, end, total jobs for this OFM block + + def calc_block_dep( + self, + prev_ifm: Block, + prev_ofm: Block, + prev_ifm_block_depth, + prev_ofm_block: Block, + prev_kernel: Kernel, + ifm: Block, + ofm: Block, + ifm_block_depth, + ofm_block: Block, + kernel: Kernel, + padLT, + ): + + blockdep = ArchitectureFeatures.MAX_BLOCKDEP + + # Iterate over the next BLOCKDEP inputs, checking to see if a sliding window + # of IFM area overlaps with any previous OFM block generation. + elapsed_jobs = 0 + ifm_depth = ifm.size().depth + for forward_offset in range(ArchitectureFeatures.MAX_BLOCKDEP): + # This is the IFM block we want to sample from + in_area = self.get_first_job_input_volume( + ifm, ofm, ifm_block_depth, ofm_block, kernel, padLT, forward_offset + ) + if in_area is None: + break + + # Try several previous-OFM blocks in the past (they still might comprise multiple IFM jobs) + outstanding_jobs = 0 + for block_offset in range(ArchitectureFeatures.MAX_BLOCKDEP): + # This is the OFM block being generated by the previous op + out_area = self.get_prev_job_output_volume( + prev_ifm, prev_ofm, prev_ifm_block_depth, prev_ofm_block, prev_kernel, block_offset + ) + if out_area is None: + break + + # Block dependency is the max number of allowed outstanding jobs + # in the pipeline. Selected by determining how many jobs occur + # in between two operators' overlapping OFM->IFM block volumes + if ArchitectureFeatures.intersects(in_area[0], in_area[1], out_area[0], out_area[1]): + break + # Early exit if no intersections and we've seen enough jobs in the pipeline + elif outstanding_jobs > ArchitectureFeatures.MAX_BLOCKDEP: + break + + # This OFM had this many jobs (accumulate over multiple OFM blocks) + outstanding_jobs += out_area[2] + + blockdep = min(blockdep, elapsed_jobs + outstanding_jobs) + elapsed_jobs += in_area[2] + # Early exit if no intersections and we've seen enough jobs in the pipeline + if elapsed_jobs > ArchitectureFeatures.MAX_BLOCKDEP: + break + + return blockdep + + def cpu_cycle_estimate(self, op): + """ + Gets estimated performance of a CPU operation, based on a linear model of intercept, slope, + specified in the vela config file, in ConfigParser file format (.ini file). + Example configuration snippet: + [CpuPerformance.MyOperationType] + Cortex-Mx.intercept=<some float value> + Cortex-Mx.slope=<some float value> + """ + section = "CpuPerformance." + op.type + if self.vela_config is not None and section in self.vela_config: + op_config = self.vela_config[section] + try: + intercept = float(op_config.get(self.cpu_config + ".intercept", op_config["default.intercept"])) + slope = float(op_config.get(self.cpu_config + ".slope", op_config["default.slope"])) + n_elements = op.inputs[0].elements() + cycles = intercept + n_elements * slope + return cycles + except: + print("Error: Reading CPU cycle estimate in vela configuration file, section {}".format(section)) + raise + + print("Warning: No configured CPU performance estimate for", op.type) + return 0 + + def __read_sys_config(self): + """ + Gets the system configuration with the given name from the vela configuration file + Example configuration snippet: + [SysConfig.MyConfigName] + npu_freq=<some float value> + cpu=Cortex-Mx + ... + """ + # Get system configuration from the vela configuration file + if self.vela_config is None: + print("Warning: Using default values for system configuration") + else: + section_key = "SysConfig." + self.system_config + if not section_key in self.vela_config: + raise Exception("Unknown system configuration " + self.system_config) + + try: + self.npu_clock = float(self.__sys_config("npu_freq", "500e6")) + self.cpu_config = self.__sys_config("cpu", "Cortex-M7") + + self.memory_clock_scales[MemArea.Sram] = float(self.__sys_config("Sram_clock_scale", "1")) + self.memory_port_widths[MemArea.Sram] = int(self.__sys_config("Sram_port_width", "64")) + + self.memory_clock_scales[MemArea.OnChipFlash] = float(self.__sys_config("OnChipFlash_clock_scale", "1")) + self.memory_port_widths[MemArea.OnChipFlash] = int(self.__sys_config("OnChipFlash_port_width", "64")) + + self.memory_clock_scales[MemArea.OffChipFlash] = float( + self.__sys_config("OffChipFlash_clock_scale", "0.25") + ) + self.memory_port_widths[MemArea.OffChipFlash] = int(self.__sys_config("OffChipFlash_port_width", "32")) + + self.memory_clock_scales[MemArea.Dram] = float(self.__sys_config("Dram_clock_scale", "1")) + self.memory_port_widths[MemArea.Dram] = int(self.__sys_config("Dram_port_width", "32")) + + self.fast_storage_mem_area = MemArea[self.__sys_config("fast_storage_mem_area", "Sram")] + self.feature_map_storage_mem_area = MemArea[self.__sys_config("feature_map_storage_mem_area", "Sram")] + self.permanent_storage_mem_area = MemArea[self.__sys_config("permanent_storage_mem_area", "OffChipFlash")] + if self.permanent_storage_mem_area not in set((MemArea.OnChipFlash, MemArea.OffChipFlash)): + raise Exception( + "Invalid permanent_storage_mem_area = " + + str(self.permanent_storage_mem_area) + + " (must be 'OnChipFlash' or 'OffChipFlash'). To store the weights and other constant data in SRAM" + " select 'OnChipFlash'" + ) + except: + print("Error: Reading System Configuration in vela configuration file, section {}".format(section_key)) + raise + + def __sys_config(self, key, default_value): + """ + Gets the system configuration value with the given key from the vela config file. + """ + if self.vela_config is None: + return default_value + section = "SysConfig." + self.system_config + result = self.vela_config[section].get(key, None) + if result is None: + raise Exception("Error: System Configuration Missing key {} in section [{}] ".format(key, section)) + return result |