Allow python benchmark_app load onnx model (#1283)

inference-engine/ie_bridges/python/src/openvino/inference_engine/ie_api.pyx

@@ -245,7 +245,7 @@ cdef class IECore:
         return versions
 
     ## Reads a network from the Intermediate Representation (IR) and creates an `IENetwork`.
-    #  @param model: A `.xml` file of the IR or string with IR.
+    #  @param model: A `.xml`, `.onnx`or `.prototxt` model file or string with IR.
     #  @param weights: A `.bin` file of the IR. Depending on `init_from_buffer` value, can be a string path or
     #                  bytes with file content.
     #  @param init_from_buffer: Defines the way of how `model` and `weights` attributes are interpreted.
@@ -274,10 +274,10 @@ cdef class IECore:
             free(xml_buffer)
         else:
             weights_ = "".encode()
-            if isinstance(model, Path) and isinstance(weights, Path):
+            if isinstance(model, Path) and (isinstance(weights, Path) or not weights):
                 if not model.is_file():
                     raise Exception("Path to the model {} doesn't exist or it's a directory".format(model))
-                if model.suffix != ".onnx":
+                if model.suffix not in [ ".onnx", ".prototxt"]:
                     if not weights.is_file():
                         raise Exception("Path to the weights {} doesn't exist or it's a directory".format(weights))
                     weights_ = bytes(weights)
@@ -285,7 +285,7 @@ cdef class IECore:
             else:
                 if not os.path.isfile(model):
                     raise Exception("Path to the model {} doesn't exist or it's a directory".format(model))
-                if not fnmatch(model, "*.onnx"):
+                if not (fnmatch(model, "*.onnx") or fnmatch(model, "*.prototxt")):
                     if not os.path.isfile(weights):
                         raise Exception("Path to the weights {} doesn't exist or it's a directory".format(weights))
                     weights_ = weights.encode()

inference-engine/ie_bridges/python/tests/conftest.py

@@ -18,6 +18,10 @@ def model_onnx_path():
     test_onnx = os.path.join(path_to_repo, "models", "test_model", 'test_model.onnx')
     return test_onnx
 
+def model_prototxt_path():
+    path_to_repo = os.environ["MODELS_PATH"]
+    test_prototxt = os.path.join(path_to_repo, "models", "test_model", 'test_model.prototxt')
+    return test_prototxt
 
 def image_path():
     path_to_repo = os.environ["DATA_PATH"]

inference-engine/ie_bridges/python/tests/test_IECore.py

@@ -5,10 +5,12 @@ import numpy as np
 from pathlib import Path
 
 from openvino.inference_engine import IENetwork, IECore, ExecutableNetwork
-from conftest import model_path, plugins_path, model_onnx_path
+from conftest import model_path, plugins_path, model_onnx_path, model_prototxt_path
 
 
 test_net_xml, test_net_bin = model_path()
+test_net_onnx = model_onnx_path()
+test_net_prototxt = model_prototxt_path()
 plugins_xml, plugins_win_xml, plugins_osx_xml = plugins_path()
 
 
@@ -159,9 +161,23 @@ def test_read_network_as_path():
 
 def test_read_network_from_onnx():
     ie = IECore()
-    net = ie.read_network(model=model_onnx_path())
+    net = ie.read_network(model=test_net_onnx)
     assert isinstance(net, IENetwork)
 
+def test_read_network_from_onnx_as_path():
+    ie = IECore()
+    net = ie.read_network(model=Path(test_net_onnx))
+    assert isinstance(net, IENetwork)
+
+def test_read_network_from_prototxt():
+    ie = IECore()
+    net = ie.read_network(model=test_net_prototxt)
+    assert isinstance(net, IENetwork)
+
+def test_read_network_from_prototxt_as_path():
+    ie = IECore()
+    net = ie.read_network(model=Path(test_net_prototxt))
+    assert isinstance(net, IENetwork)
 
 def test_incorrect_xml():
     ie = IECore()

inference-engine/samples/benchmark_app/README.md

@@ -69,7 +69,7 @@ Options:
 
     -h, --help                Print a usage message
     -i "<path>"               Optional. Path to a folder with images and/or binaries or to specific image or binary file.
-    -m "<path>"               Required. Path to an .xml file with a trained model.
+    -m "<path>"               Required. Path to an .xml/.onnx/.prototxt file with a trained model or to a .blob files with a trained compiled model.
     -d "<device>"             Optional. Specify a target device to infer on (the list of available devices is shown below). Default value is CPU.
                               Use "-d HETERO:<comma-separated_devices_list>" format to specify HETERO plugin.
                               Use "-d MULTI:<comma-separated_devices_list>" format to specify MULTI plugin. 

inference-engine/samples/benchmark_app/benchmark_app.hpp

@@ -16,7 +16,7 @@ static const char help_message[] = "Print a usage message";
 static const char input_message[] = "Optional. Path to a folder with images and/or binaries or to specific image or binary file.";
 
 /// @brief message for model argument
-static const char model_message[] = "Required. Path to an .xml file with a trained model or to a .blob files with a trained compiled model";
+static const char model_message[] = "Required. Path to an .xml/.onnx/.prototxt file with a trained model or to a .blob files with a trained compiled model.";
 
 /// @brief message for execution mode
 static const char api_message[] = "Optional. Enable Sync/Async API. Default value is \"async\".";

inference-engine/samples/benchmark_app/main.cpp

@@ -75,7 +75,7 @@ static void next_step(const std::string additional_info = "") {
             { 1, "Parsing and validating input arguments" },
             { 2, "Loading Inference Engine" },
             { 3, "Setting device configuration" },
-            { 4, "Reading the Intermediate Representation network" },
+            { 4, "Reading network files" },
             { 5, "Resizing network to match image sizes and given batch" },
             { 6, "Configuring input of the model" },
             { 7, "Loading the model to the device" },

inference-engine/tools/benchmark_tool/README.md

@@ -69,7 +69,9 @@ Options:
                         Optional. Path to a folder with images and/or binaries
                         or to specific image or binary file.
   -m PATH_TO_MODEL, --path_to_model PATH_TO_MODEL
-                        Required. Path to an .xml file with a trained model.
+                        Required. Path to an .xml/.onnx/.prototxt file with a
+                        trained model or to a .blob file with a trained
+                        compiled model.
   -d TARGET_DEVICE, --target_device TARGET_DEVICE
                         Optional. Specify a target device to infer on: CPU,
                         GPU, FPGA, HDDL or MYRIAD.

tools/benchmark/benchmark.py

@@ -18,7 +18,7 @@ from datetime import datetime
 from statistics import median
 from openvino.inference_engine import IENetwork, IECore, get_version, StatusCode
 
-from .utils.constants import MULTI_DEVICE_NAME, HETERO_DEVICE_NAME, CPU_DEVICE_NAME, GPU_DEVICE_NAME, BIN_EXTENSION
+from .utils.constants import MULTI_DEVICE_NAME, HETERO_DEVICE_NAME, CPU_DEVICE_NAME, GPU_DEVICE_NAME, XML_EXTENSION, BIN_EXTENSION
 from .utils.logging import logger
 from .utils.utils import get_duration_seconds
 from .utils.statistics_report import StatisticsReport
@@ -60,17 +60,10 @@ class Benchmark:
             self.ie.set_config(config[device], device)
 
     def read_network(self, path_to_model: str):
-        xml_filename = os.path.abspath(path_to_model)
-        head, _ = os.path.splitext(xml_filename)
-        bin_filename = os.path.abspath(head + BIN_EXTENSION)
-
-        ie_network = self.ie.read_network(xml_filename, bin_filename)
-
-        input_info = ie_network.input_info
-
-        if not input_info:
-            raise AttributeError('No inputs info is provided')
-
+        model_filename = os.path.abspath(path_to_model)
+        head, ext = os.path.splitext(model_filename)
+        weights_filename = os.path.abspath(head + BIN_EXTENSION) if ext == XML_EXTENSION else ""
+        ie_network = self.ie.read_network(model_filename, weights_filename)
         return ie_network
 
     def load_network(self, ie_network: IENetwork, config = {}):

tools/benchmark/main.py

@@ -5,7 +5,7 @@ from datetime import datetime
 from openvino.tools.benchmark.benchmark import Benchmark
 from openvino.tools.benchmark.parameters import parse_args
 from openvino.tools.benchmark.utils.constants import MULTI_DEVICE_NAME, HETERO_DEVICE_NAME, CPU_DEVICE_NAME, \
-    GPU_DEVICE_NAME, MYRIAD_DEVICE_NAME, GNA_DEVICE_NAME, BIN_EXTENSION, BLOB_EXTENSION
+    GPU_DEVICE_NAME, MYRIAD_DEVICE_NAME, GNA_DEVICE_NAME, BLOB_EXTENSION
 from openvino.tools.benchmark.utils.inputs_filling import set_inputs
 from openvino.tools.benchmark.utils.logging import logger
 from openvino.tools.benchmark.utils.progress_bar import ProgressBar

tools/benchmark/parameters.py

@@ -1,7 +1,6 @@
 import sys,argparse
 from fnmatch import fnmatch
 
-from openvino.tools.benchmark.utils.constants import XML_EXTENSION_PATTERN, BLOB_EXTENSION_PATTERN
 from openvino.tools.benchmark.utils.utils import show_available_devices
 
 def str2bool(v):
@@ -12,15 +11,11 @@ def str2bool(v):
     else:
         raise argparse.ArgumentTypeError('Boolean value expected.')
 
-
-def validate_args(args):
-    if args.number_iterations is not None and args.number_iterations < 0:
-        raise Exception("Number of iterations should be positive (invalid -niter option value)")
-    if args.number_infer_requests and args.number_infer_requests < 0:
-        raise Exception("Number of inference requests should be positive (invalid -nireq option value)")
-    if not (fnmatch(args.path_to_model, XML_EXTENSION_PATTERN) or fnmatch(args.path_to_model, BLOB_EXTENSION_PATTERN)):
-        raise Exception('Path {} is not xml or blob file.')
-
+def check_positive(value):
+    ivalue = int(value)
+    if ivalue <= 0:
+        raise argparse.ArgumentTypeError("%s is an invalid positive int value" % value)
+    return ivalue
 
 class print_help(argparse.Action):
     def __call__(self, parser, namespace, values, option_string=None):
@@ -37,7 +32,7 @@ def parse_args():
                       help='Optional. '
                            'Path to a folder with images and/or binaries or to specific image or binary file.')
     args.add_argument('-m', '--path_to_model', type=str, required=True,
-                      help='Required. Path to an .xml file with a trained model or '
+                      help='Required. Path to an .xml/.onnx/.prototxt file with a trained model or '
                            'to a .blob file with a trained compiled model.')
     args.add_argument('-d', '--target_device', type=str, required=False, default='CPU',
                       help='Optional. Specify a target device to infer on (the list of available devices is shown below). '
@@ -52,10 +47,10 @@ def parse_args():
                            'kernels description.')
     args.add_argument('-api', '--api_type', type=str, required=False, default='async', choices=['sync', 'async'],
                       help='Optional. Enable using sync/async API. Default value is async.')
-    args.add_argument('-niter', '--number_iterations', type=int, required=False, default=None,
+    args.add_argument('-niter', '--number_iterations', type=check_positive, required=False, default=None,
                       help='Optional. Number of iterations. '
                            'If not specified, the number of iterations is calculated depending on a device.')
-    args.add_argument('-nireq', '--number_infer_requests', type=int, required=False, default=None,
+    args.add_argument('-nireq', '--number_infer_requests', type=check_positive, required=False, default=None,
                       help='Optional. Number of infer requests. Default value is determined automatically for device.')
     args.add_argument('-b', '--batch_size', type=int, required=False, default=0,
                       help='Optional. ' +
@@ -111,6 +106,4 @@ def parse_args():
                       help="Optional. Weight bits for quantization:  8 (I8) or 16 (I16) ")
     parsed_args = parser.parse_args()
 
-    validate_args(parsed_args)
-
     return parsed_args

tools/benchmark/utils/constants.py

@@ -29,9 +29,6 @@ XML_EXTENSION = '.xml'
 BIN_EXTENSION = '.bin'
 BLOB_EXTENSION = '.blob'
 
-XML_EXTENSION_PATTERN = '*' + XML_EXTENSION
-BLOB_EXTENSION_PATTERN = '*' + BLOB_EXTENSION
-
 IMAGE_EXTENSIONS = ['JPEG', 'JPG', 'PNG', 'BMP']
 BINARY_EXTENSIONS = ['BIN']
 
@@ -45,14 +42,3 @@ DEVICE_DURATION_IN_SECS = {
     GNA_DEVICE_NAME: 60,
     UNKNOWN_DEVICE_TYPE: 120
 }
-
-DEVICE_NIREQ_ASYNC = {
-    CPU_DEVICE_NAME: 2,
-    GPU_DEVICE_NAME: 2,
-    VPU_DEVICE_NAME: 4,
-    MYRIAD_DEVICE_NAME: 4,
-    HDDL_DEVICE_NAME: 100,
-    FPGA_DEVICE_NAME: 3,
-    GNA_DEVICE_NAME: 1,
-    UNKNOWN_DEVICE_TYPE: 1
-}

tools/benchmark/utils/utils.py

@@ -15,7 +15,7 @@
 """
 from openvino.inference_engine import IENetwork,IECore
 
-from .constants import DEVICE_DURATION_IN_SECS, UNKNOWN_DEVICE_TYPE, DEVICE_NIREQ_ASYNC, \
+from .constants import DEVICE_DURATION_IN_SECS, UNKNOWN_DEVICE_TYPE, \
     CPU_DEVICE_NAME, GPU_DEVICE_NAME
 from .inputs_filling import is_image
 from .logging import logger
@@ -38,7 +38,7 @@ def next_step(additional_info='', step_id=0):
         1: "Parsing and validating input arguments",
         2: "Loading Inference Engine",
         3: "Setting device configuration",
-        4: "Reading the Intermediate Representation network",
+        4: "Reading network files",
         5: "Resizing network to match image sizes and given batch",
         6: "Configuring input of the model",
         7: "Loading the model to the device",
@@ -110,19 +110,6 @@ def get_duration_in_secs(target_device):
     return duration
 
 
-def get_nireq(target_device):
-    nireq = 0
-    for device in DEVICE_NIREQ_ASYNC:
-        if device in target_device:
-            nireq = max(nireq, DEVICE_NIREQ_ASYNC[device])
-
-    if nireq == 0:
-        nireq = DEVICE_NIREQ_ASYNC[UNKNOWN_DEVICE_TYPE]
-        logger.warn('Default number of requests {} is used for unknown device {}'.format(nireq, target_device))
-
-    return nireq
-
-
 def parse_devices(device_string):
     if device_string in ['MULTI', 'HETERO']:
         return list()