Merge branch 'master' into python_demos/remove_extensions

Author: anzhella-pankratova

ci/dependencies.yml

@@ -1,6 +1,6 @@
 opencv_linux: '20220210_0636-4.5.5_043'
 opencv_windows: '20220210_0636-4.5.5_043'
-openvino_linux: '2022.1.0.577'
-openvino_windows: '2022.1.0.577'
-wheel_linux: '2022.1.0.dev20220209-6562'
-wheel_windows: '2022.1.0.dev20220209-6562'
+openvino_linux: '2022.1.0.582'
+openvino_windows: '2022.1.0.582'
+wheel_linux: '2022.1.0.dev20220211-6610'
+wheel_windows: '2022.1.0.dev20220211-6610'

demos/3d_segmentation_demo/python/3d_segmentation_demo.py

@@ -267,6 +267,7 @@ def main():
     n, c, d, h, w = model.inputs[0].shape
 
     compiled_model = core.compile_model(model, args.target_device)
+    output_tensor = compiled_model.outputs[0]
     infer_request = compiled_model.create_infer_request()
     log.info('The model {} is loaded to {}'.format(args.path_to_model, args.target_device))
 
@@ -297,8 +298,8 @@ def main():
         original_data = data_crop
         original_size = original_data.shape[-3:]
 
-    result = infer_request.infer({input_tensor_name: data_crop})
-    result = next(iter(result.values()))
+    input_data = {input_tensor_name: data_crop}
+    result = infer_request.infer(input_data)[output_tensor]
     batch, channels, out_d, out_h, out_w = result.shape
 
     list_img = []

demos/action_recognition_demo/python/action_recognition_demo/models.py

@@ -93,12 +93,13 @@ def __init__(self, model_path, core, target_device, num_requests, model_type):
             log.error("Demo supports only models with 1 output")
             sys.exit(1)
 
-        self.compiled_model = core.compile_model(self.model, target_device)
+        compiled_model = core.compile_model(self.model, target_device)
+        self.output_tensor = compiled_model.outputs[0]
         self.input_name = self.model.inputs[0].get_any_name()
         self.input_shape = self.model.inputs[0].shape
 
         self.num_requests = num_requests
-        self.infer_requests = [self.compiled_model.create_infer_request() for _ in range(self.num_requests)]
+        self.infer_requests = [compiled_model.create_infer_request() for _ in range(self.num_requests)]
         log.info('The {} model {} is loaded to {}'.format(model_type, model_path, target_device))
 
     def async_infer(self, frame, req_id):
@@ -107,7 +108,7 @@ def async_infer(self, frame, req_id):
 
     def wait_request(self, req_id):
         self.infer_requests[req_id].wait()
-        return next(iter(self.infer_requests[req_id].results.values()))
+        return self.infer_requests[req_id].results[self.output_tensor]
 
 
 class DummyDecoder:

demos/background_subtraction_demo/python/background_subtraction_demo.py

@@ -1,6 +1,6 @@
 #!/usr/bin/env python3
 """
- Copyright (C) 2021 Intel Corporation
+ Copyright (C) 2021-2022 Intel Corporation
 
  Licensed under the Apache License, Version 2.0 (the "License");
  you may not use this file except in compliance with the License.
@@ -68,6 +68,10 @@ def build_argparser():
                            'same shape as an input image.')
     args.add_argument('--blur_bgr', default=0, type=int,
                       help='Optional. Background blur strength (by default with value 0 is not applied).')
+    args.add_argument('--layout', type=str, default=None,
+                      help='Optional. Model inputs layouts. '
+                           'Format "[<layout>]" or "<input1>[<layout1>],<input2>[<layout2>]" in case of more than one input.'
+                           'To define layout you should use only capital letters')
 
     infer_args = parser.add_argument_group('Inference options')
     infer_args.add_argument('-nireq', '--num_infer_requests', help='Optional. Number of infer requests.',
@@ -211,7 +215,7 @@ def main():
     if args.adapter == 'openvino':
         plugin_config = get_user_config(args.device, args.num_streams, args.num_threads)
         model_adapter = OpenvinoAdapter(create_core(), args.model, device=args.device, plugin_config=plugin_config,
-                                        max_num_requests=args.num_infer_requests)
+                                        max_num_requests=args.num_infer_requests, model_parameters = {'input_layouts': args.layout})
     elif args.adapter == 'ovms':
         model_adapter = OVMSAdapter(args.model)
 

demos/bert_named_entity_recognition_demo/python/bert_named_entity_recognition_demo.py

@@ -1,7 +1,7 @@
 #!/usr/bin/env python3
 
 """
- Copyright (c) 2021 Intel Corporation
+ Copyright (c) 2021-2022 Intel Corporation
 
  Licensed under the Apache License, Version 2.0 (the "License");
  you may not use this file except in compliance with the License.
@@ -56,6 +56,11 @@ def build_argparser():
                       help="Optional. Inputs names for the network. "
                            "Default values are \"input_ids,attention_mask,token_type_ids\" ",
                       required=False, type=str, default="input_ids,attention_mask,token_type_ids")
+    args.add_argument('--layout',
+                      help='Optional. Model inputs layouts. '
+                           'Format "[<layout>]" or "<input1>[<layout1>],<input2>[<layout2>]" in case of more than one input.'
+                           'To define layout you should use only capital letters',
+                      type=str, default=None)
     args.add_argument("-d", "--device",
                       help="Optional. Target device to perform inference on."
                            "Default value is CPU", default="CPU", type=str)
@@ -108,7 +113,7 @@ def main():
     if args.adapter == 'openvino':
         plugin_config = get_user_config(args.device, args.num_streams, args.num_threads)
         model_adapter = OpenvinoAdapter(create_core(), args.model, device=args.device, plugin_config=plugin_config,
-                                        max_num_requests=args.num_infer_requests)
+                                        max_num_requests=args.num_infer_requests, model_parameters = {'input_layouts': args.layout})
     elif args.adapter == 'ovms':
         model_adapter = OVMSAdapter(args.model)
 

demos/bert_question_answering_demo/python/bert_question_answering_demo.py

@@ -1,7 +1,7 @@
 #!/usr/bin/env python3
 
 """
- Copyright (c) 2020-2021 Intel Corporation
+ Copyright (c) 2020-2022 Intel Corporation
 
  Licensed under the Apache License, Version 2.0 (the "License");
  you may not use this file except in compliance with the License.
@@ -55,6 +55,10 @@ def build_argparser():
                       help="Optional. Inputs names for the network. "
                            "Default values are \"input_ids,attention_mask,token_type_ids\" ",
                       required=False, type=str, default="input_ids,attention_mask,token_type_ids")
+    args.add_argument('--layout', type=str, default=None,
+                      help='Optional. Model inputs layouts. '
+                           'Format "[<layout>]" or "<input1>[<layout1>],<input2>[<layout2>]" in case of more than one input.'
+                           'To define layout you should use only capital letters')
     args.add_argument("--output_names",
                       help="Optional. Outputs names for the network. "
                            "Default values are \"output_s,output_e\" ",
@@ -166,7 +170,7 @@ def main():
     if args.adapter == 'openvino':
         plugin_config = get_user_config(args.device, args.num_streams, args.num_threads)
         model_adapter = OpenvinoAdapter(create_core(), args.model, device=args.device, plugin_config=plugin_config,
-                                        max_num_requests=args.num_infer_requests)
+                                        max_num_requests=args.num_infer_requests, model_parameters = {'input_layouts': args.layout})
     elif args.adapter == 'ovms':
         model_adapter = OVMSAdapter(args.model)
 
@@ -227,7 +231,7 @@ def questions():
             if pipeline.is_ready():
                 if source.is_over():
                     break
-                pipeline.submit_data(source.get_data(), next_window_id, None)
+                pipeline.submit_data(source.get_data(), next_window_id)
                 next_window_id += 1
             else:
                 pipeline.await_any()

demos/bert_question_answering_embedding_demo/python/bert_question_answering_embedding_demo.py

@@ -1,7 +1,7 @@
 #!/usr/bin/env python3
 
 """
- Copyright (c) 2020-2021 Intel Corporation
+ Copyright (c) 2020-2022 Intel Corporation
 
  Licensed under the Apache License, Version 2.0 (the "License");
  you may not use this file except in compliance with the License.
@@ -60,6 +60,10 @@ def build_argparser():
                            "For example 'input_ids,attention_mask,token_type_ids','position_ids'",
                       default='input_ids,attention_mask,token_type_ids,position_ids',
                       required=False, type=str)
+    args.add_argument('--layout_emb', type=str, default=None,
+                      help='Optional. MODEL_EMB inputs layouts. '
+                           'Format "[<layout>]" or "<input1>[<layout1>],<input2>[<layout2>]" in case of more than one input.'
+                           'To define layout you should use only capital letters')
     args.add_argument("-m_qa", "--model_qa",
                       help="Optional. Path to an .xml file with a trained model to give exact answer",
                       default = None,
@@ -75,6 +79,10 @@ def build_argparser():
                       required=False, type=str)
     args.add_argument("--model_qa_squad_ver", help="Optional. SQUAD version used for QuestionAnswering model fine tuning",
                       default="1.2", required=False, type=str)
+    args.add_argument('--layout_qa', type=str, default=None,
+                      help='Optional. MODEL_QA inputs layouts. '
+                           'Format "[<layout>]" or "<input1>[<layout1>],<input2>[<layout2>]" in case of more than one input.'
+                           'To define layout you should use only capital letters')
     args.add_argument("-a", "--max_answer_token_num",
                       help="Optional. Maximum number of tokens in exact answer",
                       default=15,
@@ -167,10 +175,10 @@ def main():
     visualizer = Visualizer(args.colors)
     total_latency = (perf_counter() - vocab_start_time) * 1e3
 
-    ie = create_core()
+    core = create_core()
     plugin_config = get_user_config(args.device, args.num_streams, args.num_threads)
-    model_emb_adapter = OpenvinoAdapter(ie, args.model_emb, device=args.device, plugin_config=plugin_config,
-                                        max_num_requests=args.num_infer_requests)
+    model_emb_adapter = OpenvinoAdapter(core, args.model_emb, device=args.device, plugin_config=plugin_config,
+                                        max_num_requests=args.num_infer_requests, model_parameters = {'input_layouts': args.layout_emb})
     model_emb = BertEmbedding(model_emb_adapter, {'vocab': vocab, 'input_names': args.input_names_emb})
     model_emb.log_layers_info()
 
@@ -181,13 +189,13 @@ def main():
     for new_length in [max_len_question, max_len_context]:
         model_emb.reshape(new_length)
         if new_length == max_len_question:
-            emb_exec_net = ie.load_network(model_emb_adapter.net, args.device)
+            emb_request = core.compile_model(model_emb_adapter.model, args.device).create_infer_request()
         else:
             emb_pipeline = AsyncPipeline(model_emb)
 
     if args.model_qa:
-        model_qa_adapter = OpenvinoAdapter(ie, args.model_qa, device=args.device, plugin_config=plugin_config,
-                                           max_num_requests=args.num_infer_requests)
+        model_qa_adapter = OpenvinoAdapter(core, args.model_qa, device=args.device, plugin_config=plugin_config,
+                                           max_num_requests=args.num_infer_requests, model_parameters = {'input_layouts': args.layout_qa})
         config = {
             'vocab': vocab,
             'input_names': args.input_names_qa,
@@ -216,7 +224,8 @@ def main():
     def calc_question_embedding(tokens_id):
         num = min(max_len_question - 2, len(tokens_id))
         inputs, _ = model_emb.preprocess((tokens_id[:num], max_len_question))
-        raw_result = emb_exec_net.infer(inputs)
+        emb_request.infer(inputs)
+        raw_result = model_emb_adapter.get_raw_result(emb_request)
         return model_emb.postprocess(raw_result, None)
 
     source = ContextSource(paragraphs, vocab, c_window_len)

demos/classification_demo/python/classification_demo.py

@@ -1,6 +1,6 @@
 #!/usr/bin/env python3
 """
- Copyright (C) 2018-2021 Intel Corporation
+ Copyright (C) 2018-2022 Intel Corporation
 
  Licensed under the Apache License, Version 2.0 (the "License");
  you may not use this file except in compliance with the License.
@@ -58,6 +58,10 @@ def build_argparser():
     common_model_args.add_argument('--labels', help='Optional. Labels mapping file.', default=None, type=str)
     common_model_args.add_argument('-topk', help='Optional. Number of top results. Default value is 5. Must be from 1 to 10.', default=5,
                                    type=int, choices=range(1, 11))
+    common_model_args.add_argument('--layout', type=str, default=None,
+                                   help='Optional. Model inputs layouts. '
+                                        'Format "[<layout>]" or "<input1>[<layout1>],<input2>[<layout2>]" in case of more than one input.'
+                                        'To define layout you should use only capital letters')
 
     infer_args = parser.add_argument_group('Inference options')
     infer_args.add_argument('-nireq', '--num_infer_requests', help='Optional. Number of infer requests',
@@ -106,11 +110,11 @@ def build_argparser():
 
 def draw_labels(frame, classifications, output_transform):
     frame = output_transform.resize(frame)
-    сlass_label = ""
+    class_label = ""
     if classifications:
-        сlass_label = classifications[0][1]
+        class_label = classifications[0][1]
     font_scale = 0.7
-    label_height = cv2.getTextSize(сlass_label, cv2.FONT_HERSHEY_COMPLEX, font_scale, 2)[0][1]
+    label_height = cv2.getTextSize(class_label, cv2.FONT_HERSHEY_COMPLEX, font_scale, 2)[0][1]
     initial_labels_pos =  frame.shape[0] - label_height * (int(1.5 * len(classifications)) + 1)
 
     if (initial_labels_pos < 0):
@@ -123,8 +127,8 @@ def draw_labels(frame, classifications, output_transform):
     put_highlighted_text(frame, header, (frame.shape[1] - label_width, offset_y),
         cv2.FONT_HERSHEY_COMPLEX, font_scale, (255, 0, 0), 2)
 
-    for idx, сlass_label, score in classifications:
-        label = '{}. {}    {:.2f}'.format(idx, сlass_label, score)
+    for idx, class_label, score in classifications:
+        label = '{}. {}    {:.2f}'.format(idx, class_label, score)
         label_width = cv2.getTextSize(label, cv2.FONT_HERSHEY_COMPLEX, font_scale, 2)[0][0]
         offset_y += int(label_height * 1.5)
         put_highlighted_text(frame, label, (frame.shape[1] - label_width, offset_y),
@@ -160,7 +164,7 @@ def main():
     if args.adapter == 'openvino':
         plugin_config = get_user_config(args.device, args.num_streams, args.num_threads)
         model_adapter = OpenvinoAdapter(create_core(), args.model, device=args.device, plugin_config=plugin_config,
-                                        max_num_requests=args.num_infer_requests)
+                                        max_num_requests=args.num_infer_requests, model_parameters = {'input_layouts': args.layout})
     elif args.adapter == 'ovms':
         model_adapter = OVMSAdapter(args.model)
 

demos/colorization_demo/python/colorization_demo.py

@@ -80,6 +80,7 @@ def main(args):
     assert len(model.outputs) == 1, "Expected number of outputs is equal 1"
 
     compiled_model = core.compile_model(model, device_name=args.device)
+    output_tensor = compiled_model.outputs[0]
     infer_request = compiled_model.create_infer_request()
     log.info('The model {} is loaded to {}'.format(args.model, args.device))
 
@@ -115,7 +116,7 @@ def main(args):
 
         inputs[input_tensor_name] = np.expand_dims(img_l_rs, axis=[0, 1])
 
-        res = next(iter(infer_request.infer(inputs).values()))
+        res = infer_request.infer(inputs)[output_tensor]
 
         update_res = np.squeeze(res)
 

demos/common/cpp/utils/include/utils/common.hpp

@@ -296,7 +296,7 @@ void logCompiledModelInfo(
         for (const auto& device : devices) {
             try {
                 slog::info << "\tDevice: " << device << slog::endl;
-                int32_t nstreams = compiledModel.get_property(ov::streams::num);
+                int32_t nstreams = compiledModel.get_property(ov::num_streams);
                 slog::info << "\t\tNumber of streams: " << nstreams << slog::endl;
                 if (device == "CPU") {
                     int32_t nthreads = compiledModel.get_property(ov::inference_num_threads);