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[Python Tools] Replace use of layers in cross-check-tools (#1803)

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Anastasia Kuporosova 2020-09-03 15:40:32 +03:00 committed by GitHub
parent 5a376477a9
commit d9e9abcf50
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2 changed files with 23 additions and 13 deletions
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32
inference-engine/tools/cross_check_tool/cross_check_tool.py
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@ -17,6 +17,13 @@ except Exception as e:
print("The following error happened while importing Python API module:\n[ {} ] {}".format(exception_type, e))
sys.exit(1)
try:
import ngraph as ng
except Exception as e:
exception_type = type(e).name
print("The following error happened while importing nGraph module:\n[ {} ] {}".format(exception_type, e))
sys.exit(1)
from utils import get_config_dictionary, get_layers_list, print_output_layers, input_processing, \
accuracy_metrics, validate_args, build_parser, set_logger, find_out_cct_mode, print_all_over_the_net_metrics, \
update_global_accuracy_matrics, blob_counters, performance_metrics, manage_user_outputs_with_mapping, \
@ -75,9 +82,9 @@ def get_net_copy_with_output(model: str, output: str, core: IECore):
@error_handling('getting model layers info')
def get_model_info(net: IENetwork):
layers = net.layers
precision = layers[list(layers.keys())[0]].out_data[0].precision
return layers, net.input_info, net.outputs, precision
func = ng.function_from_cnn(net)
ops = func.get_ops()
return ops, net.input_info, net.outputs
###
@ -135,8 +142,8 @@ def overall_accuracy_check(model: str, ref_model: str, out_layers: list, ref_out
def one_ir_mode(args):
core = get_plugin(args.device, args.l, args.config)
net = get_net(model=args.model, core=core)
net_layers, net_inputs, net_outputs, precision = get_model_info(net)
log.info('{}:{} vs {}:{}'.format(args.device, precision, args.reference_device, precision))
net_layers, net_inputs, net_outputs = get_model_info(net)
log.info('{} vs {}'.format(args.device, args.reference_device))
log.info('The same IR on both devices: {}'.format(args.model))
out_layers = get_layers_list(net_layers, net_inputs, net_outputs, args.layers)
print_input_layers(net_inputs)
@ -173,10 +180,10 @@ def two_ir_mode(args):
core = get_plugin(args.device, args.l, args.config)
ref_core = get_plugin(args.reference_device, args.l, args.reference_config)
net = get_net(model=args.model, core=core)
net_layers, net_inputs, net_outputs, precision = get_model_info(net)
net_layers, net_inputs, net_outputs = get_model_info(net)
ref_net = get_net(model=args.reference_model, core=ref_core)
ref_net_layers, ref_net_inputs, ref_net_outputs, ref_precision = get_model_info(ref_net)
log.info('{}:{} vs {}:{}'.format(args.device, precision, args.reference_device, ref_precision))
ref_net_layers, ref_net_inputs, ref_net_outputs = get_model_info(ref_net)
log.info('{} vs {}'.format(args.device, args.reference_device))
log.info('IR for {} : {}'.format(args.device, args.model))
log.info('IR for {} : {}'.format(args.reference_device, args.reference_model))
out_layers = get_layers_list(net_layers, net_inputs, net_outputs, args.layers)
@ -207,7 +214,8 @@ def two_ir_mode(args):
if out_layer not in results:
continue
out_blob, pc = results[out_layer]
ref_results = infer(net=ref_net_copy, core=ref_core, device=args.reference_device, inputs=ref_inputs, output=[ref_out_layer])
ref_results = infer(net=ref_net_copy, core=ref_core, device=args.reference_device,
inputs=ref_inputs, output=[ref_out_layer])
ref_out_blob, ref_pc = ref_results[ref_out_layer]
if ref_out_layer not in ref_results:
continue
@ -222,7 +230,9 @@ def two_ir_mode(args):
def dump_mode(args):
core = get_plugin(args.device, args.l, args.config)
net = get_net(model=args.model, core=core)
out_layers = get_layers_list(net.layers, net.input_info, net.outputs, args.layers)
func = ng.function_from_cnn(net)
ops = func.get_ops()
out_layers = get_layers_list(ops, net.input_info, net.outputs, args.layers)
inputs = input_processing(args.model, net.input_info, args.input)
dump_dict = {}
for out_layer in out_layers:
@ -241,7 +251,7 @@ def load_mode(args):
log.info('IR for {} : {}'.format(args.device, args.model))
log.info('Loading blob from {}'.format(args.load))
net = get_net(model=args.model, core=core)
net_layers, net_inputs, net_outputs, precision = get_model_info(net)
net_layers, net_inputs, net_outputs = get_model_info(net)
out_layers = get_layers_list(net_layers, net_inputs, net_outputs, args.layers)
print_input_layers(net_inputs)
print_output_layers(out_layers)

4
inference-engine/tools/cross_check_tool/utils.py
View File

@ -503,10 +503,10 @@ def manage_user_outputs_with_mapping(mapping, reference_mapping, user_layers):
return layers_map
def get_layers_list(all_layers: dict, inputs: dict, outputs: list, layers: str):
def get_layers_list(all_layers: list, inputs: dict, outputs: list, layers: str):
if layers is not None and layers != 'None':
if layers == 'all':
return {name: layer for name, layer in all_layers.items() if layer.type not in ['Const']}
return {layer.get_friendly_name(): layer for layer in all_layers if layer.get_type_name() not in ['Const']}
else:
user_layers = [layer.strip() for layer in layers.split(',')]
layers_to_check = []