Revert "[MO] remove deprecated: data_type, disable_nhwc_to_nchw, tensorflow_use_custom_operations_config (#16394)" (#16555)

This reverts commit 43ef89e625.

tests/layer_tests/common/layer_test_class.py

@@ -40,11 +40,10 @@ class CommonLayerTest:
         os.environ['MO_ENABLED_TRANSFORMS'] = enabled_transforms
         os.environ['MO_DISABLED_TRANSFORMS'] = disabled_transforms
 
-        compress_to_fp16 = False if precision == 'FP32' else True
         mo_params = {self.input_model_key: model_path,
                      "output_dir": temp_dir,
-                     "compress_to_fp16": compress_to_fp16,
+                     "data_type": precision, "model_name": 'model'
-                     "model_name": 'model'}
+                     }
 
         if 'input_shapes' in kwargs and len(kwargs['input_shapes']):
             input_shapes_str = []

tests/layer_tests/common/utils/common_utils.py

@@ -26,10 +26,6 @@ def generate_ir(coverage=False, **kwargs):
             params.extend(("-b", str(value)))
         elif key == "k":
             params.extend(("-k", str(value)))
-        # for FP32 set explicitly compress_to_fp16=False,
-        # if we omit this argument for FP32, it will be set implicitly to True as the default
-        elif key == 'compress_to_fp16':
-            params.append("--{}={}".format(key, value))
         elif isinstance(value, bool) and value:
             params.append("--{}".format(key))
         elif isinstance(value, bool) and not value:

tools/mo/openvino/tools/mo/analysis/tf_od_api.py

@@ -70,7 +70,7 @@ class TensorFlowObjectDetectionAPIAnalysis(AnalyzeAction):
                 if all([graph_contains_scope(graph, scope) for scope in scopes]):
                     result = dict()
                     result['flavor'] = flavor
-                    result['mandatory_parameters'] = {'transformations_config':
+                    result['mandatory_parameters'] = {'tensorflow_use_custom_operations_config':
                                                           files_by_pattern(get_mo_root_dir() + '/openvino/tools/mo/front/tf',
                                                                            __class__.file_patterns[flavor],
                                                                            add_prefix=True),

tools/mo/openvino/tools/mo/analysis/tf_retinanet.py

@@ -52,14 +52,14 @@ class TensorFlowRetinaNet(AnalyzeAction):
 
         if pattern_instance_counter.counter > 0:
             result = dict()
-            result['mandatory_parameters'] = {'transformations_config':
+            result['mandatory_parameters'] = {'tensorflow_use_custom_operations_config':
                                                   'openvino/tools/mo/front/tf/retinanet.json'}
 
             message = "Your model looks like TensorFlow RetinaNet Model.\n" \
                       "To generate the IR, provide model to the Model Optimizer with the following parameters:\n" \
                       "\t--input_model <path_to_model>/<model>.pb\n" \
                       "\t--input_shape [1,600,600,3]\n" \
-                      "\t--transformations_config <OPENVINO_INSTALL_DIR>/tools/model_optimizer/openvino/tools/mo/front/tf/retinanet.json\n" \
+                      "\t--tensorflow_use_custom_operations_config <OPENVINO_INSTALL_DIR>/tools/model_optimizer/openvino/tools/mo/front/tf/retinanet.json\n" \
                       "\t--reverse_input_channels"
 
             return {'model_type': {'TF_RetinaNet': result}}, message

tools/mo/openvino/tools/mo/analysis/tf_yolo.py

@@ -47,7 +47,7 @@ YOLO_CONFIGS = {'YOLOV2Full': ['openvino/tools/mo/front/tf/yolo_v2.json', 'openv
 def get_YOLO_params_by_flavor(flavor: str):
     result = dict()
     result['flavor'] = flavor
-    result['mandatory_parameters'] = {'transformations_config': YOLO_CONFIGS[flavor]}
+    result['mandatory_parameters'] = {'tensorflow_use_custom_operations_config': YOLO_CONFIGS[flavor]}
     return result
 
 
@@ -72,7 +72,7 @@ class TensorFlowYOLOV1V2Analysis(AnalyzeAction):
                       "To generate the IR, provide TensorFlow YOLOv1 or YOLOv2 Model to the Model Optimizer with the following parameters:\n" \
                       "\t--input_model <path_to_model>/<model_name>.pb\n" \
                       "\t--batch 1\n" \
-                      "\t--transformations_config <PYTHON_SITE_PACKAGES>/openvino/tools/mo/front/tf/<yolo_config>.json\n" \
+                      "\t--tensorflow_use_custom_operations_config <PYTHON_SITE_PACKAGES>/openvino/tools/mo/front/tf/<yolo_config>.json\n" \
                       "All detailed information about conversion of this model can be found at\n" \
                       "https://docs.openvino.ai/latest/_docs_MO_DG_prepare_model_convert_model_tf_specific_Convert_YOLO_From_Tensorflow.html"
             return {'model_type': {'YOLO': get_YOLO_params_by_flavor(flavor)}}, message
@@ -99,7 +99,7 @@ class TensorFlowYOLOV3Analysis(AnalyzeAction):
                       "To generate the IR, provide TensorFlow YOLOv3 Model to the Model Optimizer with the following parameters:\n" \
                       "\t--input_model <path_to_model>/yolo_v3.pb\n" \
                       "\t--batch 1\n" \
-                      "\t--transformations_config <PYTHON_SITE_PACKAGES>/openvino/tools/mo/front/tf/yolo_v3.json\n" \
+                      "\t--tensorflow_use_custom_operations_config <PYTHON_SITE_PACKAGES>/openvino/tools/mo/front/tf/yolo_v3.json\n" \
                       "Detailed information about conversion of this model can be found at\n" \
                       "https://docs.openvino.ai/latest/_docs_MO_DG_prepare_model_convert_model_tf_specific_Convert_YOLO_From_Tensorflow.html"
             return {'model_type': {'YOLO': get_YOLO_params_by_flavor(flavor)}}, message

tools/mo/openvino/tools/mo/back/offline_transformations.py

@@ -65,7 +65,7 @@ def apply_offline_transformations(func: Model, argv: argparse.Namespace):
     apply_moc_legacy_transformations(func, params_with_custom_types)
     apply_user_transformations(func, parse_transform(argv.transform))
 
-    if "compress_to_fp16" in argv and argv.compress_to_fp16:
+    if "compress_fp16" in argv and argv.compress_fp16:
         compress_model(func)
 
     apply_fused_names_cleanup(func)

tools/mo/openvino/tools/mo/convert_impl.py

@@ -214,6 +214,13 @@ def arguments_post_parsing(argv: argparse.Namespace):
         log.error(e)
         raise_ie_not_found()
 
+    # Turn off compression only if it's disabled explicitly by --compress_to_fp16=False or --data_type=FP32.
+    # By default, in all other cases compression is enabled
+    if ('data_type' in argv and argv.data_type in ['FP32', 'float']) or \
+            ('compress_to_fp16' in argv and argv.compress_to_fp16 is False):
+        argv.compress_fp16 = False
+    else:
+        argv.compress_fp16 = True
     argv.data_type = 'FP32'  # if compression was enabled will be restored back to 'FP16' after apply_offline_transformations
 
     # This is just to check that transform key is valid and transformations are available
@@ -227,6 +234,12 @@ def arguments_post_parsing(argv: argparse.Namespace):
     if ret_code:
         raise Error('check_requirements exited with return code {}'.format(ret_code))
 
+    if hasattr(argv, 'tensorflow_use_custom_operations_config') and \
+            argv.tensorflow_use_custom_operations_config is not None:
+        # update command-line arguments even for new TensorFlow Frontend
+        # because it should fallback to the Legacy Frontend in this case
+        argv.transformations_config = argv.tensorflow_use_custom_operations_config
+
     if argv.scale and argv.scale_values:
         raise Error(
             'Both --scale and --scale_values are defined. Specify either scale factor or scale values per input ' +
@@ -496,7 +509,7 @@ def emit_ir(graph: Graph, argv: argparse.Namespace, non_default_params: dict):
         try:
             from openvino.tools.mo.back.offline_transformations import apply_offline_transformations
             func = apply_offline_transformations(func, argv)
-            if "compress_to_fp16" in argv and argv.compress_to_fp16:
+            if "compress_fp16" in argv and argv.compress_fp16:
                 # restore data_type cmd parameter
                 argv.data_type = 'FP16'
             return_code = 0

tools/mo/openvino/tools/mo/front/tf/ObjectDetectionAPI.py

@@ -98,7 +98,7 @@ def _value_or_raise(match: SubgraphMatch, pipeline_config: PipelineConfig, key:
         raise Error('The sub-graph replacer "[REPLACEMENT_ID]" was not able to find the value for key "{}" in the '
                     'pipeline configuration file specified with the --tensorflow_object_detection_api_pipeline_config '
                     'command line parameter. Update the sub-graph replacement configuration file specified with the '
-                    '--transformations_config command line parameter by adding key "{}" with required '
+                    '--tensorflow_use_custom_operations_config command line parameter by adding key "{}" with required '
                     'value to the "custom_attributes" dictionary of the "[REPLACEMENT_ID]" replacer.'.format(key, key))
     return value
 

tools/mo/openvino/tools/mo/load/tf/loader.py

@@ -91,7 +91,7 @@ class TFLoader(Loader):
         graph.__setattr__('name', argv.model_name)
         # 'layout' parameter change may cause an issue in EltwiseInputReshape replacer
         # and convert_nhwc_to_nchw(graph)
-        graph.graph['layout'] = 'NHWC'
+        graph.graph['layout'] = 'NCHW' if argv.disable_nhwc_to_nchw else 'NHWC'
         graph.graph['fw'] = 'tf'
 
         graph.graph['variables_values'] = variables_values
@@ -114,7 +114,7 @@ class TFLoader(Loader):
 
         # try to detect layout from the nodes of the graph. If there are no convolution nodes in N(D)HWC layout then we
         # consider that the graph is in NCHW layout and no layout conversion should be performed
-        if not graph_or_sub_graph_has_nhwc_ops(graph):
+        if not argv.disable_nhwc_to_nchw and not graph_or_sub_graph_has_nhwc_ops(graph):
             if not argv.silent:
                 log.debug('disable_nhwc_to_nchw" was automatically enabled.')
             for_graph_and_each_sub_graph_recursively(graph, update_cmd_params_and_layout)

tools/mo/openvino/tools/mo/main.py

@@ -37,7 +37,8 @@ def main(cli_parser: argparse.ArgumentParser, framework=None):
     try:
         ngraph_function, argv = _convert(cli_parser, framework, {})
         is_tf, _, _, _, _ = deduce_legacy_frontend_by_namespace(argv)
-        if 'compress_to_fp16' in argv and argv.compress_to_fp16:
+        if ('compress_to_fp16' in argv and argv.compress_to_fp16) \
+                or ('data_type' in argv and argv.data_type in ['half', 'FP16']):
             print(get_compression_message())
 
         ov_update_message = get_ov_update_message()

tools/mo/openvino/tools/mo/moc_frontend/serialize.py

@@ -32,7 +32,7 @@ def moc_emit_ir(ngraph_function: Model, argv: argparse.Namespace):
 
     apply_user_transformations(ngraph_function, parse_transform(argv.transform))
 
-    if argv.compress_to_fp16:
+    if argv.compress_fp16:
         from openvino.tools.mo.back.offline_transformations import compress_model
         compress_model(ngraph_function)
 

tools/mo/openvino/tools/mo/utils/cli_parser.py

@@ -836,6 +836,8 @@ class DeprecatedCanonicalizePathCheckExistenceAction(CanonicalizePathCheckExiste
     def __call__(self, parser, namespace, values, option_string=None):
         dep_msg = "Use of deprecated cli option {} detected. Option use in the following releases will be fatal. ".format(
             option_string)
+        if 'tensorflow_use_custom_operations_config' in option_string:
+            dep_msg += 'Please use --transformations_config cli option instead'
         log.error(dep_msg, extra={'is_warning': True})
         super().__call__(parser, namespace, values, option_string)
 
@@ -1019,6 +1021,15 @@ def get_common_cli_parser(parser: argparse.ArgumentParser = None):
                               help=mo_convert_params_common['layout'].description.format(
                                   mo_convert_params_common['layout'].possible_types_command_line),
                               default=())
+    # TODO: isn't it a weights precision type
+    common_group.add_argument('--data_type',
+                              help='[DEPRECATED] Data type for model weights and biases. '
+                                   'If original model has FP32 weights or biases and --data_type=FP16 is specified, '
+                                   'FP32 model weights and biases are compressed to FP16. '
+                                   'All intermediate data is kept in original precision.',
+                              choices=["FP16", "FP32", "half", "float"],
+                              default='FP16',
+                              action=DeprecatedOptionCommon)
     common_group.add_argument('--compress_to_fp16',
                               help=mo_convert_params_common['compress_to_fp16'].description,
                               type=check_bool,
@@ -1093,6 +1104,7 @@ def get_common_cli_options(model_name):
     d['mean_values'] = ['- Mean values', lambda x: x if x else 'Not specified']
     d['scale_values'] = ['- Scale values', lambda x: x if x else 'Not specified']
     d['scale'] = ['- Scale factor', lambda x: x if x else 'Not specified']
+    d['data_type'] = ['- Precision of IR', lambda x: 'FP32' if x == 'float' else 'FP16' if x == 'half' else x]
     d['transform'] = ['- User transformations', lambda x: x if x else 'Not specified']
     d['reverse_input_channels'] = '- Reverse input channels'
     d['static_shape'] = '- Enable IR generation for fixed input shape'
@@ -1121,6 +1133,7 @@ def get_tf_cli_options():
     d = {
         'input_model_is_text': '- Input model in text protobuf format',
         'tensorflow_custom_operations_config_update': '- Update the configuration file with input/output node names',
+        'tensorflow_use_custom_operations_config': '- Use the config file',
         'tensorflow_object_detection_api_pipeline_config': '- Use configuration file used to generate the model with '
                                                            'Object Detection API',
         'tensorflow_custom_layer_libraries': '- List of shared libraries with TensorFlow custom layers implementation',
@@ -1164,7 +1177,7 @@ def get_params_with_paths_list():
             'input_checkpoint', 'input_meta_graph', 'input_proto', 'input_symbol',
             'pretrained_model_name', 'saved_model_dir', 'tensorboard_logdir',
             'tensorflow_custom_layer_libraries', 'tensorflow_custom_operations_config_update',
-            'tensorflow_object_detection_api_pipeline_config',
+            'tensorflow_object_detection_api_pipeline_config', 'tensorflow_use_custom_operations_config',
             'transformations_config']
 
 
@@ -1243,6 +1256,9 @@ def get_tf_cli_parser(parser: argparse.ArgumentParser = None):
     tf_group.add_argument('--tensorflow_custom_operations_config_update',
                           help=mo_convert_params_tf['tensorflow_custom_operations_config_update'].description,
                           action=CanonicalizePathCheckExistenceAction)
+    tf_group.add_argument('--tensorflow_use_custom_operations_config',
+                          help='Use the configuration file with custom operation description.',
+                          action=DeprecatedCanonicalizePathCheckExistenceAction)
     tf_group.add_argument('--tensorflow_object_detection_api_pipeline_config',
                           help=mo_convert_params_tf['tensorflow_object_detection_api_pipeline_config'].description,
                           action=CanonicalizePathCheckExistenceAction)
@@ -1254,6 +1270,10 @@ def get_tf_cli_parser(parser: argparse.ArgumentParser = None):
                           help=mo_convert_params_tf['tensorflow_custom_layer_libraries'].description,
                           default=None,
                           action=CanonicalizePathCheckExistenceAction)
+    tf_group.add_argument('--disable_nhwc_to_nchw',
+                          help='[DEPRECATED] Disables the default translation from NHWC to NCHW. Since 2022.1 this option '
+                               'is deprecated and used only to maintain backward compatibility with previous releases.',
+                          action=DeprecatedStoreTrue, default=False)
     return parser