def setUp(self):
self.alex_net = import_network('alex_net')
self.vgg_net = import_network('vgg_net')
self.map_strategy = MapStrategyEyeriss
self.resource = Resource(
proc_region=NodeRegion(origin=PhyDim2(0, 0),
dim=PhyDim2(1, 1),
type=NodeRegion.PROC),
data_regions=(NodeRegion(origin=PhyDim2(0, 0),
dim=PhyDim2(1, 1),
type=NodeRegion.DATA), ),
dim_array=PhyDim2(16, 16),
size_gbuf=128 * 1024 // 2, # 128 kB
size_regf=512 // 2, # 512 B
)
self.cost = Cost(mac_op=1,
mem_hier=(200, 6, 2, 1),
noc_hop=0,
unit_static=0)
self.options = Option()
def setUp(self):
self.alex_net = import_network('alex_net')
self.vgg_net = import_network('vgg_net')
net = Network('simple')
net.set_input_layer(InputLayer(4, 2))
net.add('1', ConvLayer(4, 4, 2, 1))
net.add('2', ConvLayer(4, 4, 2, 1))
# Two more layers to avoid single-segment case.
net.add('a1', ConvLayer(4, 1, 1, 1, strd=2))
net.add('a2', ConvLayer(1, 1, 1, 1))
self.simple_net = net
net = Network('complex')
net.set_input_layer(InputLayer(8, 8))
net.add('1', ConvLayer(8, 8, 8, 1))
net.add('2a', ConvLayer(8, 8, 8, 1), prevs=('1', ))
net.add('3a', ConvLayer(8, 8, 8, 1))
net.add('2b', ConvLayer(8, 8, 8, 1), prevs=('1', ))
net.add('3b', ConvLayer(8, 8, 8, 1))
net.add('4', ConvLayer(16, 8, 8, 1), prevs=('3a', '3b'))
self.complex_net = net
self.map_strategy = MapStrategyEyeriss
self.resource = Resource(
proc_region=NodeRegion(origin=PhyDim2(0, 0),
dim=PhyDim2(1, 1),
type=NodeRegion.PROC),
dram_region=NodeRegion(origin=PhyDim2(0, 0),
dim=PhyDim2(1, 1),
type=NodeRegion.DRAM),
src_data_region=NodeRegion(origin=PhyDim2(0, 0),
dim=PhyDim2(1, 1),
type=NodeRegion.DRAM),
dst_data_region=NodeRegion(origin=PhyDim2(0, 0),
dim=PhyDim2(1, 1),
type=NodeRegion.DRAM),
dim_array=PhyDim2(16, 16),
size_gbuf=128 * 1024 // 2, # 128 kB
size_regf=512 // 2, # 512 B
array_bus_width=float('inf'),
dram_bandwidth=float('inf'),
no_time_mux=False,
)
self.cost = Cost(mac_op=1,
mem_hier=(200, 6, 2, 1),
noc_hop=0,
idl_unit=0)
self.options = Option()
def __init__(self):
self.alex_net = import_network('alex_net')
self.mock_net = import_network('mock_net')
self.map_strategy = MapStrategyEyeriss
value_mult = {}
value_control = 1
my_weights = {}
self.cost = Cost(value_control=value_control,
value_mult=value_mult,
adder_cost=1,
mac_op=1,
mem_hier=(200, 6, 2, 1),
noc_hop=0,
idl_unit=0,
my_weights=my_weights,
mem_cycles=(200, 6, 2, 1))
self.options = Option()
def __init__(self):
self.alex_net = import_network('alex_net')
self.map_strategy = MapStrategyEyeriss
value_mult = {}
value_control = {}
my_weights = {}
self.cost = Cost(value_control=value_control,
value_mult=value_mult,
mac_op=1,
mem_hier=(200, 6, 2, 1),
noc_hop=0,
idl_unit=0,
my_weights=my_weights)
self.options = Option()
print('mapping is : {}'.format(self.map_strategy))
print('cost is: {}'.format(self.cost))
print('options are: {}'.format(self.options))
def do_scheduling(args):
'''
Get optimal scheduling for given problem. Return a result schedule.
'''
## Network.
network = import_network(args.net)
batch_size = args.batch
## Resource.
dim_nodes = PhyDim2(*args.nodes)
dim_array = PhyDim2(*args.array)
# Sizes of gbuf and regf are in words.
word = (args.word + 7) / 8
size_gbuf = args.gbuf / word
size_regf = args.regf / word
array_bus_width = args.bus_width // args.word
if not array_bus_width:
array_bus_width = float('inf')
dram_bandwidth = args.dram_bw / word
proc_region = NodeRegion(dim=dim_nodes,
origin=PhyDim2(0, 0),
type=NodeRegion.PROC)
if args.mem_type == '2D':
# Memory nodes are on two sides.
data_region = NodeRegion(dim=PhyDim2(2, 2),
origin=PhyDim2(0, 0),
dist=dim_nodes - PhyDim2(1, 1),
type=NodeRegion.DRAM)
assert data_region.rel2abs(PhyDim2(1, 1)) + PhyDim2(1, 1) \
== proc_region.dim
elif args.mem_type == '3D':
# Memory nodes are on the top.
data_region = NodeRegion(dim=dim_nodes,
origin=PhyDim2(0, 0),
type=NodeRegion.DRAM)
resource = Resource(proc_region=proc_region,
dram_region=data_region,
src_data_region=data_region,
dst_data_region=data_region,
dim_array=dim_array,
size_gbuf=size_gbuf,
size_regf=size_regf,
array_bus_width=array_bus_width,
dram_bandwidth=dram_bandwidth,
no_time_mux=False)
## Cost.
hier_cost = [0] * me.NUM
hier_cost[me.DRAM] = args.hier_cost[0]
hier_cost[me.GBUF] = args.hier_cost[1]
hier_cost[me.ITCN] = args.hier_cost[2]
hier_cost[me.REGF] = args.hier_cost[3]
cost = Cost(mac_op=args.op_cost,
mem_hier=tuple(hier_cost),
noc_hop=args.hop_cost,
idl_unit=args.unit_idle_cost)
## Options.
bypass = [True] * de.NUM
bypass[de.IFM] = 'i' not in args.disable_bypass
bypass[de.OFM] = 'o' not in args.disable_bypass
bypass[de.FIL] = 'f' not in args.disable_bypass
options = Option(
sw_gbuf_bypass=tuple(bypass),
sw_solve_loopblocking=args.solve_loopblocking,
hw_access_forwarding=args.enable_access_forwarding,
hw_gbuf_sharing=args.enable_gbuf_sharing,
hw_gbuf_save_writeback=args.enable_save_writeback,
partition_hybrid=args.hybrid_partition,
partition_batch=args.batch_partition,
partition_ifmaps=args.ifmaps_partition,
partition_interlayer=args.interlayer_partition,
layer_pipeline_time_ovhd=args.layer_pipeline_time_overhead,
layer_pipeline_max_degree=args.layer_pipeline_max_degree,
layer_pipeline_opt=not args.disable_interlayer_opt,
opt_goal=args.goal.lower(),
ntops=args.top,
nprocesses=args.processes,
verbose=args.verbose)
## Search schedules.
nnd = NNDataflow(network, batch_size, resource, cost, MapStrategyEyeriss)
tbeg = time.time()
tops, cache_stats = nnd.schedule_search(options)
tend = time.time()
telapsed = tend - tbeg
if not tops:
sys.stderr.write('No valid dataflow found.\n')
return None
top = tops[0]
## Write results.
res_map = OrderedDict()
res_map['version'] = get_version(with_local=True)
res_map['net'] = args.net
res_map['batch'] = args.batch
res_map['resource'] = resource._asdict()
res_map['cost'] = cost._asdict()
res_map['options'] = options._asdict()
res_map['cache_stats'] = cache_stats
res_map['elapsed'] = telapsed
stats = stats_dict(top, cost)
for key, val in stats.items():
res_map[key] = val
return res_map
def do_scheduling(args):
'''
Get optimal scheduling for given problem. Return a result schedule.
'''
## Network.
network = import_network(args.net)
batch_size = args.batch
## Resource.
dim_nodes = PhyDim2(*args.nodes)
dim_array = PhyDim2(*args.array)
# Sizes of gbuf and regf are in words.
word = (args.word + 7) / 8
size_gbuf = args.gbuf / word
size_regf = args.regf / word
proc_region = NodeRegion(dim=dim_nodes,
origin=PhyDim2(0, 0),
type=NodeRegion.PROC)
if args.mem_type == '2D':
# Memory nodes are on two sides.
data_regions = (NodeRegion(dim=PhyDim2(h=dim_nodes.h, w=1),
origin=PhyDim2(h=0, w=0),
type=NodeRegion.DATA),
NodeRegion(dim=PhyDim2(h=dim_nodes.h, w=1),
origin=PhyDim2(h=0, w=dim_nodes.w - 1),
type=NodeRegion.DATA))
elif args.mem_type == '3D':
# All nodes have memory.
data_regions = (NodeRegion(dim=dim_nodes,
origin=PhyDim2(0, 0),
type=NodeRegion.DATA), )
resource = Resource(proc_region=proc_region,
data_regions=data_regions,
dim_array=dim_array,
size_gbuf=size_gbuf,
size_regf=size_regf)
## Cost.
hier_cost = [0] * me.NUM
hier_cost[me.DRAM] = args.hier_cost[0]
hier_cost[me.GBUF] = args.hier_cost[1]
hier_cost[me.ITCN] = args.hier_cost[2]
hier_cost[me.REGF] = args.hier_cost[3]
cost = Cost(mac_op=args.op_cost,
mem_hier=tuple(hier_cost),
noc_hop=args.hop_cost,
unit_static=args.unit_static_cost)
## Options.
bypass = [True] * de.NUM
bypass[de.IFM] = 'i' not in args.disable_bypass
bypass[de.OFM] = 'o' not in args.disable_bypass
bypass[de.FIL] = 'f' not in args.disable_bypass
options = Option(sw_gbuf_bypass=tuple(bypass),
sw_solve_loopblocking=args.solve_loopblocking,
partition_hybrid=args.hybrid_partition,
partition_batch=args.batch_partition,
partition_ifmaps=args.ifmaps_partition,
ntops=args.top,
nprocesses=args.processes,
verbose=args.verbose)
## Search schedules.
nnd = NNDataflow(network, batch_size, resource, cost, MapStrategyEyeriss)
tops, cache_stats = nnd.schedule_search(options)
if not tops:
sys.stderr.write('No valid dataflow found.\n')
return None
top = tops[0]
## Write results.
res_map = OrderedDict()
res_map['version'] = get_version(with_local=True)
res_map['net'] = args.net
res_map['batch'] = args.batch
res_map['resource'] = resource._asdict()
res_map['cost'] = cost._asdict()
res_map['options'] = options._asdict()
res_map['cache_stats'] = cache_stats
stats = stats_dict(top, cost)
for key, val in stats.items():
res_map[key] = val
return res_map
def setUp(self):
self.net = {}
net = Network('net1')
# Linear.
net.set_input_layer(InputLayer(10, 1))
net.add('0', FCLayer(10, 20))
net.add('1', FCLayer(20, 30))
net.add('1p', PoolingLayer(30, 1, 1))
net.add('2', FCLayer(30, 40))
net.add('3', FCLayer(40, 50))
self.net[net.net_name] = net
net = Network('net2')
# Long linear.
net.set_input_layer(InputLayer(1, 1))
for idx in range(16):
net.add(str(idx), FCLayer(1, 1))
self.net[net.net_name] = net
net = Network('net3')
# Fork.
# /0-2\ /6- 7- 8\
# x 4-5 12
# \1-3/ \9-10-11/
net.set_input_layer(InputLayer(1, 1))
net.add('0', FCLayer(1, 1), prevs=net.INPUT_LAYER_KEY)
net.add('1', FCLayer(1, 1), prevs=net.INPUT_LAYER_KEY)
net.add('2', FCLayer(2, 1), prevs=('0', '1'))
net.add('2p', PoolingLayer(1, 1, 1))
net.add('3', FCLayer(2, 1), prevs=('0', '1'))
net.add('4', FCLayer(2, 1), prevs=('2p', '3'))
net.add('5', FCLayer(1, 1))
net.add('5p', PoolingLayer(1, 1, 1))
net.add('6', FCLayer(1, 1), prevs='5p')
net.add('7', FCLayer(1, 1))
net.add('8', FCLayer(1, 1))
net.add('9', FCLayer(1, 1), prevs='5p')
net.add('10', FCLayer(1, 1))
net.add('11', FCLayer(1, 1))
net.add('12', FCLayer(2, 1), prevs=('8', '11'))
self.net[net.net_name] = net
net = Network('net4')
# Complex fork.
# /5 \
# 0-1-2-3-4-6-7-8-10-14
# \9/
# \11-12 /
# \13 /
net.set_input_layer(InputLayer(1, 1))
net.add('0', FCLayer(1, 1))
net.add('1', FCLayer(1, 1))
net.add('2', FCLayer(1, 1))
net.add('3', FCLayer(1, 1))
net.add('4', FCLayer(1, 1))
net.add('5', FCLayer(1, 1), prevs='4')
net.add('6', FCLayer(1, 1), prevs='4')
net.add('7', FCLayer(1, 1))
net.add('8', FCLayer(1, 1), prevs='7')
net.add('9', FCLayer(1, 1), prevs='7')
net.add('10', FCLayer(1, 1))
net.add('10p', PoolingLayer(2, 1, 1), prevs=('8', '10'))
net.add('11', PoolingLayer(1, 1, 1), prevs='4')
net.add('12', FCLayer(1, 1))
net.add('13', PoolingLayer(1, 1, 1), prevs='4')
net.add('14', FCLayer(5, 1), prevs=('5', '10p', '12', '13'))
self.net[net.net_name] = net
net = Network('net5')
# Corner cases.
# ----\
# //1-2\ 7-8\
# 0-3-4-x 10-11-12
# \ \5/ 9 / \__/
# 6--/
net.set_input_layer(InputLayer(1, 1))
net.add('0', FCLayer(1, 1))
net.add('1', FCLayer(1, 1), prevs='0')
net.add('2', FCLayer(1, 1))
net.add('3', FCLayer(1, 1), prevs='0')
net.add('4', FCLayer(1, 1), prevs='3')
net.add('5', FCLayer(1, 1), prevs='3')
net.add('6', FCLayer(1, 1), prevs='0')
net.add('7', FCLayer(5, 1), prevs=('0', '2', '4', '5', '6'))
net.add('8', FCLayer(1, 1))
net.add('9', FCLayer(5, 1), prevs=('0', '2', '4', '5', '6'))
net.add('10', FCLayer(2, 1), prevs=('8', '9'))
net.add('11', FCLayer(1, 1))
net.add('12', FCLayer(2, 1), prevs=('10', '11'))
self.net[net.net_name] = net
net = Network('net6')
# Fmap sizes.
net.set_input_layer(InputLayer(1, 24))
net.add('0', ConvLayer(1, 1, 24, 3))
net.add('1', ConvLayer(1, 1, 12, 3, strd=2))
net.add('1p', PoolingLayer(1, 6, 2))
net.add('2', ConvLayer(1, 1, 6, 3))
net.add('3', ConvLayer(1, 1, 6, 3, strd=4), prevs=('0'))
self.net[net.net_name] = net
net = Network('net7')
# Topological order: see a visited vertex again.
# /---
# 0-1-\\
# \2--2p
net.set_input_layer(InputLayer(1, 1))
net.add('0', FCLayer(1, 1))
net.add('1', FCLayer(1, 1), prevs='0')
net.add('2', FCLayer(1, 1), prevs='0')
net.add('2p', PoolingLayer(3, 1, 1), prevs=('0', '1', '2'))
self.net[net.net_name] = net
net = Network('net8')
# Forward to the middle.
# /-\
# 0-1-2-2p-4-4p
# \-3------/
net.set_input_layer(InputLayer(1, 1))
net.add('0', FCLayer(1, 1))
net.add('1', FCLayer(1, 1), prevs='0')
net.add('2', FCLayer(1, 1), prevs='1')
net.add('2p', PoolingLayer(2, 1, 1), prevs=('1', '2'))
net.add('3', FCLayer(1, 1), prevs='0')
net.add('4', FCLayer(2, 1), prevs='2p')
net.add('4p', PoolingLayer(2, 1, 1), prevs=('3', '4'))
self.net[net.net_name] = net
net = Network('net9')
# Previous layers include input and others.
net.set_input_layer(InputLayer(1, 1))
net.add('0', FCLayer(1, 1))
net.add('1', FCLayer(2, 1), prevs=(net.INPUT_LAYER_KEY, '0'))
self.net[net.net_name] = net
# Real networks.
for net_name in all_networks():
self.net[net_name] = import_network(net_name)
self.batch_size = 16
self.resource = Resource(
proc_region=NodeRegion(origin=PhyDim2(0, 0),
dim=PhyDim2(8, 8),
type=NodeRegion.PROC),
dram_region=NodeRegion(origin=PhyDim2(0, 0),
dim=PhyDim2(8, 8),
type=NodeRegion.DRAM),
src_data_region=NodeRegion(origin=PhyDim2(0, 0),
dim=PhyDim2(8, 4),
type=NodeRegion.DRAM),
dst_data_region=NodeRegion(origin=PhyDim2(0, 4),
dim=PhyDim2(8, 4),
type=NodeRegion.DRAM),
dim_array=PhyDim2(16, 16),
size_gbuf=65536,
size_regf=64,
array_bus_width=float('inf'),
dram_bandwidth=float('inf'),
no_time_mux=False)
part = PartitionScheme(order=range(pe.NUM), pdims=[(1, 1)] * pe.NUM)
self.ofmap_layout = DataLayout(
frngs=(FmapRange((0, 0, 0, 0), (2, 4, 16, 16)), ),
regions=(NodeRegion(origin=PhyDim2(0, 0),
dim=PhyDim2(1, 1),
type=NodeRegion.DRAM), ),
parts=(part, ))
def layer_stats(args):
''' Print stats of layers in the network. '''
network = import_network(args.net)
word_bytes = (args.word + 7) // 8
batch = args.batch
hder_fmt = ','.join([STR_FMT_NAME] + [STR_FMT_NUMB_HDER] * 5) + '\n'
line_fmt = ','.join([STR_FMT_NAME] + [STR_FMT_NUMB] * 5) + '\n'
line_sep = '-' * int(STR_FMT_NAME_LEN) + '\n'
# Header.
sys.stdout.write(hder_fmt
.format('Layer',
'Ifmap/kB', 'Ofmap/kB', 'Weight/kB',
'MACs/M', 'MinOptBuf/kB'))
# Aggregate stats.
max_fmaps = 0
max_filters = 0
max_ops = 0
sum_fmaps = 0
sum_filters = 0
sum_ops = 0
convs = 0
fcs = 0
for name in network:
layer = network[name]
if isinstance(layer, FCLayer):
fcs += 1
elif isinstance(layer, ConvLayer):
convs += 1
ifmap_size = layer.total_ifmap_size(word_bytes) * batch / KILO
ofmap_size = layer.total_ofmap_size(word_bytes) * batch / KILO
try:
filter_size = layer.total_filter_size(word_bytes) / KILO
except AttributeError:
filter_size = 0
ops = layer.total_ops(batch) / MILLION
# The minimum optimal buffer size is the sum of the full size (two
# dimensions) for one data category, the size of one dimension for the
# second, and the size of one point for the third.
min_opt_buf_size = min(
filter_size + (ifmap_size + ofmap_size / layer.nofm) / batch,
filter_size + (ifmap_size / layer.nifm + ofmap_size) / batch,
ifmap_size + (ofmap_size + filter_size / layer.nifm) / layer.nofm,
ifmap_size + (ofmap_size / batch + filter_size) / layer.nofm,
ofmap_size + (ifmap_size + filter_size / layer.nofm) / layer.nifm,
ofmap_size + (ifmap_size / batch + filter_size) / layer.nifm)
sys.stdout.write(line_fmt
.format(name,
ifmap_size, ofmap_size, filter_size,
ops, min_opt_buf_size))
max_fmaps = max(max_fmaps, ofmap_size)
max_filters = max(max_filters, filter_size)
max_ops = max(max_ops, ops)
sum_fmaps += ofmap_size
sum_filters += filter_size
sum_ops += ops
sys.stdout.write(line_sep)
sys.stdout.write(line_fmt
.format('MAX',
float('nan'), max_fmaps, max_filters,
max_ops, float('nan')))
sys.stdout.write(line_fmt
.format('SUM',
float('nan'), sum_fmaps, sum_filters,
sum_ops, float('nan')))
sys.stdout.write(line_sep)
sys.stdout.write('# CONV layers = {}, # FC layers = {}\n'
.format(convs, fcs))
def test_import_network_invalid(self):
''' Get import_network invalid. '''
with self.assertRaisesRegexp(ImportError, 'nns: .*defined.*'):
_ = nns.import_network('aaa')
def test_import_network(self):
''' Get import_network. '''
for name in nns.all_networks():
network = nns.import_network(name)
self.assertIsInstance(network, Network)