def test_graph_kws_auto_quant(kws_graph, kws_sounds):
G = create_graph(kws_graph, opts={"load_tensors": True})
G.add_dimensions()
G.adjust_order()
get_std_match_group().match(G)
G.add_dimensions()
stats_collector = ActivationStatsCollector()
for input_file in kws_sounds:
data = import_data(input_file, offset=0, divisor=256, nptype='int16')
stats_collector.collect_stats(G, [data])
astats = stats_collector.reduce_stats()
stats_collector = FilterStatsCollector()
fstats = stats_collector.collect_stats(G)
quantizer = SimpleQuantizer(astats, fstats, force_width=16)
qrecs = quantizer.quantize(G)
G.quantization = qrecs
def test_simple_quantization(mnist_graph, mnist_images):
G = create_graph(mnist_graph, opts={"load_tensors": True})
G.add_dimensions()
input_tensor = import_data(mnist_images[0],
height=28,
width=28,
offset=0,
divisor=255)
input_tensor = input_tensor.reshape((28, 28, 1))
stats_collector = ActivationStatsCollector()
stats_collector.collect_stats(G, [input_tensor])
astats = stats_collector.reduce_stats()
stats_collector = FilterStatsCollector()
fstats = stats_collector.collect_stats(G)
quantizer = SymmetricQuantizer(astats, fstats, force_width=8)
qrecs = quantizer.quantize(G)
assert len(qrecs) == 11 # One more for saved quantizer
report = QuantizationReporter().report(G, qrecs)
renderer = TextTableRenderer(maxwidth=200)
print(report.render(renderer))
def do_aquant(self, args: argparse.Namespace):
"""
Attempt to calculate quantization for graph using one or more sample imput files."""
self._check_graph()
input_args = self._get_input_args(args)
processed_input = False
stats_collector = ActivationStatsCollector()
for file_per_input in glob_input_files(args.input_files,
self.G.num_inputs):
LOG.info("input file %s", file_per_input)
processed_input = True
data = [
import_data(input_file, **input_args)
for input_file in file_per_input
]
stats_collector.collect_stats(self.G, data)
if not processed_input:
self.perror("No imput files found")
return
astats = stats_collector.reduce_stats()
if args.scheme == 'SQ8':
quantizer = MultQuantizer(
astats,
8,
quantized_dimension=args.quant_dimension,
narrow_weights=not args.no_narrow_weights)
else:
stats_collector = FilterStatsCollector()
fstats = stats_collector.collect_stats(self.G)
quantizer = SymmetricQuantizer(astats,
fstats,
force_width=args.force_width,
min_qsnr=args.qsnr)
qrecs = quantizer.quantize(self.G)
self.G.quantization = qrecs
if args.scheme == 'SQ8':
concats_matcher = EqualizeSymmetricMultiplicativeQuantivedConcats()
concats_matcher.match(self.G, set_identity=False)
softmax_qrec_matcher = PropagateSoftmaxSymQrec()
softmax_qrec_matcher.match(self.G, set_identity=False)
LOG.info("Quantization set. Use qshow command to see it.")
def do_stats(self, args: argparse.Namespace):
"""
Display statistics on weights and biases"""
self._check_graph()
fmt = ('tab' if args.output is None else args.output['fmt'])
if args.detailed:
stats_collector = FilterDetailedStatsCollector()
stats = stats_collector.collect_stats(self.G)
tab = FilterDetailedStatsReporter().report(self.G, stats)
else:
step_idx = args.step
if step_idx is not None:
if len(step_idx) == 1:
step_idx = step_idx[0]
else:
step_idx = tuple(step_idx)
stats_collector = FilterStatsCollector()
stats = stats_collector.collect_stats(self.G, step_idx=step_idx)
tab = FilterStatsReporter(do_totals=(fmt != "csv"), threshold=args.qsnr, step_idx=step_idx)\
.report(self.G, stats)
output_table(tab, args)
def save_state(temp_dir, width, fusions=False, adjust=False):
file_name = os.path.join(temp_dir, "state_file")
G = create_graph(MNIST_GRAPH, opts={"load_tensors":True})
G.add_dimensions()
if adjust:
G.adjust_order()
if fusions:
get_std_match_group().match(G)
G.add_dimensions()
stats_collector = ActivationStatsCollector()
for input_file in MNIST_IMAGES:
data = import_data(input_file, offset=0, divisor=255)
if not adjust:
data = data.reshape((28, 28, 1))
stats_collector.collect_stats(G, [data])
astats = stats_collector.reduce_stats()
stats_collector = FilterStatsCollector()
fstats = stats_collector.collect_stats(G)
quantizer = SimpleQuantizer(astats, fstats, force_width=width)
qrecs = quantizer.quantize(G)
G.quantization = qrecs
dump_state(G, include_parameters=True, state_path=file_name)
return file_name