remove deprecated cli arguments from MO (#14937)

* removed deprecated cli arguments from MO

* removed deprecated options from docs

* Update tools/legacy/benchmark_app/README.md

* removed ConcatOptimization.py, removed deprecated args from unit-tests, renamed tensorflow_use_custom_operations_config -> transformations_config; replaced using or cmd_params.data_type -> cmd_params.compress_to_fp16

* added comment why we set internal 'data_type' always to 'FP32' after introducing 'compress_to_fp16'

* removed openvino_docs_MO_DG_prepare_model_Model_Optimization_Techniques from MO_DevGuide

* returned back --data_type argument

* leftovers from recovering

* returned back to package_BOM.txt; fixed NHWC by default for TF

* recovered --disable_nhwc_to_nchw to MO args

* reverted removing --tensorflow_use_custom_operations_config

Co-authored-by: Roman Kazantsev <roman.kazantsev@intel.com>

tools/legacy/benchmark_app/README.md

@@ -142,7 +142,7 @@ This section provides step-by-step instructions on how to run the Benchmark Tool
    omz_downloader --name googlenet-v1 -o <models_dir>
 2. Convert the model to the Inference Engine IR format. Run the Model Optimizer using the `mo` command with the path to the model, model format (which must be FP32 for CPU and FPG) and output directory to generate the IR files:
    ```sh
-   mo --input_model <models_dir>/public/googlenet-v1/googlenet-v1.caffemodel --data_type FP32 --output_dir <ir_dir>
+   mo --input_model <models_dir>/public/googlenet-v1/googlenet-v1.caffemodel
    ```
 3. Run the tool with specifying the `<INSTALL_DIR>/samples/scripts/car.png` file as an input image, the IR of the `googlenet-v1` model and a device to perform inference on. The following commands demonstrate running the Benchmark Tool in the asynchronous mode on CPU and GPU devices:
 

tools/mo/openvino/tools/mo/back/TransposeDFT.py

@@ -14,7 +14,7 @@ class TransposeDFT(BackReplacementPattern):
     for operation DFT or IDFT.
 
     If the input rank in the TF model was greater than 2, we have [N_0, 2, N_1, ..., N_{r - 1}] as the input shape of
-    (I)DFT after the layout conversion, if the option '--disable_nhwc_to_nchw' is not specified.
+    (I)DFT after the layout conversion.
 
     But, generally speaking, according to DFT and IDFT specifications, the input shape [N_0, 2, N_1, ..., N_{r - 1}]
     is not correct input shape for DFT and IDFT. Hence, we need to insert Transpose operations before and after (I)DFT

tools/mo/openvino/tools/mo/back/compress_quantized_weights.py

@@ -82,7 +82,6 @@ class CompressQuantizeWeights(BackReplacementPattern):
     """
 
     enabled = True
-    graph_condition = [lambda graph: not graph.graph['cmd_params'].disable_weights_compression]
 
     force_clean_up = True
 

tools/mo/openvino/tools/mo/middle/ConcatOptimization.py

@@ -1,86 +1,10 @@
 # Copyright (C) 2018-2022 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
-import logging as log
-
-from openvino.tools.mo.middle.fusings import Fusing
-from openvino.tools.mo.middle.pass_separator import PostMiddleStart
-from openvino.tools.mo.graph.graph import Node, Graph
+from openvino.tools.mo.graph.graph import Graph
 from openvino.tools.mo.middle.replacement import MiddleReplacementPattern
 
 
-class ConcatOptimization(MiddleReplacementPattern):
-    # This optimization reduces number of edges between Concat operations
-    # that significantly reduce memory consumption
-
-    enabled = True
-    graph_condition = [lambda graph: graph.graph['cmd_params'].enable_concat_optimization]
-
-    def run_after(self):
-        return [Fusing]
-
-    def run_before(self):
-        return [PostMiddleStart]
-
-    def find_and_replace_pattern(self, graph: Graph):
-        mp = {}
-        used = {}
-        for node in graph.get_op_nodes(type='Concat'):
-            in_nodes = tuple([node.in_node(idx).id for idx in range(len(node.in_nodes()))])
-            out_node = (node.id, node.out_node().id)
-            if in_nodes in mp:
-                log.warning("Something is weird! {} and {}".format(node.id, mp[in_nodes]))
-            else:
-                mp.update({in_nodes: out_node})
-                used.update({node.id: {x: False for x in in_nodes}})
-
-        for key in mp.keys():
-            replacers = []
-            for i in range(len(key)):
-                for j in range(i + 1, len(key)):
-                    arr = tuple(key[i:j + 1])
-                    if arr in mp.keys() and arr != key:
-                        replacers.append((len(arr), arr))
-
-            replacers.sort(reverse=True)
-
-            concat_id = mp[key][0]
-            for ln, arr in replacers:
-                # Check that we can do it!!!
-                we_can = True
-                for x in arr:
-                    if used[concat_id][x]:
-                        we_can = False
-                        break
-
-                if not we_can:
-                    continue
-
-                for x in arr:
-                    used[concat_id][x] = True
-
-                edge_attrs = graph.get_edge_data(arr[0], concat_id)[0]
-                for in_node in arr:
-                    graph.remove_edge(in_node, concat_id)
-
-                new_input = mp[arr][1]
-                out_port = len(Node(graph, new_input).out_nodes()) + 1
-                edge_attrs['out'] = out_port
-                graph.add_edge(new_input, concat_id, **edge_attrs)
-
-                # Renumber 'in' attrs
-                concat_node = Node(graph, concat_id)
-                ln = len(concat_node.in_nodes())
-                ports = [x for x in concat_node.in_nodes().keys()]
-                ports.sort()
-
-                p_id = 0
-                for p in ports:
-                    in_node = concat_node.in_nodes()[p]
-                    graph[in_node.id][concat_id][0]['in'] = p_id
-                    p_id += 1
-
-
 class ConcatOdInputEraserAndPortsReconnect(MiddleReplacementPattern):
     """
     The transformation performs two actions with Concat operations:

tools/mo/openvino/tools/mo/middle/ReluQuantizeFuse.py

@@ -21,7 +21,6 @@ class ReluFakeQuantizeMark(MiddleReplacementPattern):
 
     """
     enabled = True
-    graph_condition = [lambda graph: not graph.graph['cmd_params'].disable_fusing]
 
     def run_after(self):
         return [BinarizeWeightsM1P1]

tools/mo/openvino/tools/mo/middle/fusings.py

@@ -46,9 +46,6 @@ class Fusing(MiddleReplacementPattern):
         for_graph_and_each_sub_graph_recursively(graph, fuse_pad)
         for_graph_and_each_sub_graph_recursively(graph, lambda G: G.clean_up())
 
-        # Mark nodes with attr 'can_be_fused': False to disable fusing for specified nodes
-        for_graph_and_each_sub_graph_recursively(graph, lambda graph: mark_unfused_nodes(graph, argv.finegrain_fusing))
-
         # Converting FusedBatchNorm layer to Mul->Add->Mul->Add sequence
         # IE doesn't support batchNormInference with 4 inputs, so we have to split it to two ScaleShift
         for_graph_and_each_sub_graph_recursively(graph, convert_batch_norm)
@@ -61,42 +58,40 @@ class Fusing(MiddleReplacementPattern):
         for_graph_and_each_sub_graph_recursively(graph, Sub().find_and_replace_pattern)
         for_graph_and_each_sub_graph_recursively(graph, lambda G: G.clean_up())
 
-        if not argv.disable_fusing:
-            if fw != 'caffe':
-                # Converting ScaleShift layer to Mul->Add
-                for_graph_and_each_sub_graph_recursively(graph, convert_scale_shift_to_mul_add)
-                for_graph_and_each_sub_graph_recursively(graph, lambda G: G.clean_up())
-
-            # Fusing the sequences of Mul/Add operations
-            for_graph_and_each_sub_graph_recursively(graph, fuse_mul_add_sequence)
+        if fw != 'caffe':
+            # Converting ScaleShift layer to Mul->Add
+            for_graph_and_each_sub_graph_recursively(graph, convert_scale_shift_to_mul_add)
             for_graph_and_each_sub_graph_recursively(graph, lambda G: G.clean_up())
 
-            normalize_eltwise_inputs(graph)
-            for_graph_and_each_sub_graph_recursively(graph, lambda G: G.clean_up())
+        # Fusing the sequences of Mul/Add operations
+        for_graph_and_each_sub_graph_recursively(graph, fuse_mul_add_sequence)
+        for_graph_and_each_sub_graph_recursively(graph, lambda G: G.clean_up())
 
-            # Fusing linear operation to Convolution
-            for_graph_and_each_sub_graph_recursively(graph, fuse_linear_ops)
-            for_graph_and_each_sub_graph_recursively(graph, lambda G: G.clean_up())
+        normalize_eltwise_inputs(graph)
+        for_graph_and_each_sub_graph_recursively(graph, lambda G: G.clean_up())
+
+        # Fusing linear operation to Convolution
+        for_graph_and_each_sub_graph_recursively(graph, fuse_linear_ops)
+        for_graph_and_each_sub_graph_recursively(graph, lambda G: G.clean_up())
 
         for_graph_and_each_sub_graph_recursively(graph, grouped_convolutions_fusing)
         for_graph_and_each_sub_graph_recursively(graph, lambda G: G.clean_up())
-        if not argv.disable_fusing:
-            for_graph_and_each_sub_graph_recursively(graph, fuse_linear_ops)
-            for_graph_and_each_sub_graph_recursively(graph, lambda G: G.clean_up())
+
+        for_graph_and_each_sub_graph_recursively(graph, fuse_linear_ops)
+        for_graph_and_each_sub_graph_recursively(graph, lambda G: G.clean_up())
 
         for_graph_and_each_sub_graph_recursively(graph, normalize_eltwise_inputs)
         for_graph_and_each_sub_graph_recursively(graph, lambda G: G.clean_up())
 
-        if not argv.disable_fusing:
-            MarkNodesToFuseUpToFakeQuantize().find_and_replace_pattern(graph)
-            FakeQuantizeFuse().find_and_replace_pattern(graph)
-            AddFakeQuantizeFuse().find_and_replace_pattern(graph)
-            MulFakeQuantizeFuse().find_and_replace_pattern(graph)
-            for_graph_and_each_sub_graph_recursively(graph, lambda G: G.clean_up())
+        MarkNodesToFuseUpToFakeQuantize().find_and_replace_pattern(graph)
+        FakeQuantizeFuse().find_and_replace_pattern(graph)
+        AddFakeQuantizeFuse().find_and_replace_pattern(graph)
+        MulFakeQuantizeFuse().find_and_replace_pattern(graph)
+        for_graph_and_each_sub_graph_recursively(graph, lambda G: G.clean_up())
 
         mark_shape_of_sugraph_as_unfusable(graph)
         for_graph_and_each_sub_graph_recursively(graph, fuse_pad)
         for_graph_and_each_sub_graph_recursively(graph, lambda G: G.clean_up())
 
-        if layout != 'NHWC' and not argv.disable_resnet_optimization:
+        if layout != 'NHWC':
             stride_optimization(graph)

tools/mo/openvino/tools/mo/middle/quantize_fuses.py

@@ -20,7 +20,6 @@ class MarkNodesToFuseUpToFakeQuantize(MiddleReplacementPattern):
 
     """
     enabled = True
-    graph_condition = [lambda graph: not graph.graph['cmd_params'].disable_fusing]
 
     def run_after(self):
         return [DeleteControlFlowEdges]
@@ -73,7 +72,6 @@ class FakeQuantizeFuse(MiddleReplacementPattern):
             replacer duplicates node to fuse (duplicate connections of inputs of node to fuse to duplicates of it)
     """
     enabled = True
-    graph_condition = [lambda graph: not graph.graph['cmd_params'].disable_fusing]
 
     def run_after(self):
         return [QuantizeLinearResolver]

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

@@ -723,9 +723,9 @@ class DeprecatedStoreTrue(argparse.Action):
 
 class DeprecatedOptionCommon(argparse.Action):
     def __call__(self, parser, args, values, option_string):
-       dep_msg = "Use of deprecated cli option {} detected. Option use in the following releases will be fatal. ".format(option_string)
-       log.error(dep_msg, extra={'is_warning': True})
-       setattr(args, self.dest, values)
+        dep_msg = "Use of deprecated cli option {} detected. Option use in the following releases will be fatal. ".format(option_string)
+        log.error(dep_msg, extra={'is_warning': True})
+        setattr(args, self.dest, values)
 
 
 class IgnoredAction(argparse.Action):
@@ -1025,19 +1025,6 @@ def get_common_cli_parser(parser: argparse.ArgumentParser = None):
                               help=mo_convert_params_common['transform'].description.format(
                                   mo_convert_params_common['transform'].possible_types_command_line),
                               default="")
-    common_group.add_argument('--disable_fusing',
-                              help='[DEPRECATED] Turn off fusing of linear operations to Convolution.',
-                              action=DeprecatedStoreTrue)
-    common_group.add_argument('--disable_resnet_optimization',
-                              help='[DEPRECATED] Turn off ResNet optimization.',
-                              action=DeprecatedStoreTrue, default=False)
-    common_group.add_argument('--finegrain_fusing',
-                              help='[DEPRECATED] Regex for layers/operations that won\'t be fused. ' +
-                                   'Example: --finegrain_fusing Convolution1,.*Scale.*',
-                              action=DeprecatedOptionCommon)
-    common_group.add_argument('--enable_concat_optimization',
-                              help='[DEPRECATED] Turn on Concat optimization.',
-                              action=DeprecatedStoreTrue, default=False)
     # we use CanonicalizeDirCheckExistenceAction instead of readable_dirs to handle empty strings
     common_group.add_argument("--extensions",
                               help=mo_convert_params_common['extensions'].description.format(
@@ -1067,9 +1054,6 @@ def get_common_cli_parser(parser: argparse.ArgumentParser = None):
     common_group.add_argument('--static_shape',
                               help=mo_convert_params_common['static_shape'].description,
                               action='store_true', default=False)
-    common_group.add_argument('--disable_weights_compression',
-                              help='[DEPRECATED] Disable compression and store weights with original precision.',
-                              action=DeprecatedStoreTrue, default=False)
     common_group.add_argument('--progress',
                               help=mo_convert_params_common['progress'].description,
                               action='store_true', default=False)
@@ -1106,7 +1090,6 @@ def get_common_cli_options(model_name):
     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['disable_fusing'] = ['- Enable fusing', lambda x: not 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'
@@ -1126,7 +1109,6 @@ def get_caffe_cli_options():
         'input_proto': ['- Path to the Input prototxt', lambda x: x],
         'caffe_parser_path': ['- Path to Python Caffe* parser generated from caffe.proto', lambda x: x],
         'k': '- Path to CustomLayersMapping.xml',
-        'disable_resnet_optimization': ['- Enable resnet optimization', lambda x: not x],
     }
 
     return OrderedDict(sorted(d.items(), key=lambda t: t[0]))

tools/mo/unit_tests/mo/extensions_test_actual.py

@@ -45,13 +45,8 @@ def base_args_config():
     args.output_dir = os.getcwd()
     args.freeze_placeholder_with_value = None
     args.transformations_config = None
-    args.disable_fusing = None
-    args.finegrain_fusing = None
     args.disable_gfusing = None
-    args.disable_resnet_optimization = None
-    args.enable_concat_optimization = None
     args.static_shape = None
-    args.disable_weights_compression = None
     args.reverse_input_channels = None
     args.data_type = None
     args.layout = None

tools/mo/unit_tests/mo/front/tf/TFFFTToDFT_test.py

@@ -104,7 +104,6 @@ class TFFFTToDFTTest(unittest.TestCase):
                                 'fft': {'num_of_dimensions': num_of_dimensions, 'fft_kind': dft_type},
                             })
         graph.stage = 'front'
-        setattr(graph.graph['cmd_params'], 'disable_nhwc_to_nchw', False)
         graph.graph['layout'] = 'NHWC'
         TFFFTToDFT().find_and_replace_pattern(graph)
         ref_graph = build_graph(nodes_attrs=ref_dft_graph_node_attrs,
@@ -147,7 +146,6 @@ class TFFFTToDFTTest(unittest.TestCase):
                                 'fft': {'num_of_dimensions': num_of_dims, 'fft_kind': fft_kind},
                             })
         graph.stage = 'front'
-        setattr(graph.graph['cmd_params'], 'disable_nhwc_to_nchw', False)
         graph.graph['layout'] = 'NHWC'
         TFFFTToDFT().find_and_replace_pattern(graph)
         ref_graph = build_graph(nodes_attrs=ref_dft_graph_with_signal_size_node_attrs,

tools/mo/unit_tests/mo/utils/freeze_placeholder_test.py

@@ -40,12 +40,7 @@ def base_args_config(use_legacy_fe: bool = None, use_new_fe: bool = None):
     args.output_dir = os.getcwd()
     args.freeze_placeholder_with_value = None
     args.transformations_config = None
-    args.disable_fusing = None
-    args.finegrain_fusing = None
-    args.disable_resnet_optimization = None
-    args.enable_concat_optimization = None
     args.static_shape = None
-    args.disable_weights_compression = None
     args.reverse_input_channels = None
     args.data_type = None
     args.layout = None

tools/mo/unit_tests/mo/utils/mo_fallback_test_actual.py

@@ -44,12 +44,7 @@ def base_args_config(use_legacy_fe:bool=None, use_new_fe:bool=None):
     args.output_dir=os.getcwd()
     args.freeze_placeholder_with_value = None
     args.transformations_config = None
-    args.disable_fusing = None
-    args.finegrain_fusing = None
-    args.disable_resnet_optimization = None
-    args.enable_concat_optimization = None
     args.static_shape = None
-    args.disable_weights_compression = None
     args.reverse_input_channels = None
     args.data_type = None
     args.layout = None

tools/mo/unit_tests/mo/utils/mo_fallback_test_tf_fe.py

@@ -39,12 +39,7 @@ def base_args_config(use_legacy_fe: bool = None, use_new_fe: bool = None):
     args.output_dir = os.getcwd()
     args.freeze_placeholder_with_value = None
     args.transformations_config = None
-    args.disable_fusing = None
-    args.finegrain_fusing = None
-    args.disable_resnet_optimization = None
-    args.enable_concat_optimization = None
     args.static_shape = None
-    args.disable_weights_compression = None
     args.reverse_input_channels = None
     args.data_type = None
     args.layout = None
@@ -55,7 +50,6 @@ def base_args_config(use_legacy_fe: bool = None, use_new_fe: bool = None):
     args.saved_model_dir = None
     args.input_meta_graph = None
     args.saved_model_tags = None
-    args.tensorflow_use_custom_operations_config = None
     return args
 
 

tools/mo/unit_tests/mo/utils/test_mo_model_analysis_actual.py

@@ -39,12 +39,7 @@ def base_args_config():
     args.output_dir=os.getcwd()
     args.freeze_placeholder_with_value = None
     args.transformations_config = None
-    args.disable_fusing = None
-    args.finegrain_fusing = None
-    args.disable_resnet_optimization = None
-    args.enable_concat_optimization = None
     args.static_shape = None
-    args.disable_weights_compression = None
     args.reverse_input_channels = None
     args.data_type = None
     args.layout = None

tools/mo/unit_tests/moc_tf_fe/check_info_messages.py

@@ -46,7 +46,6 @@ def arg_parse_helper(input_model,
         source_layout={},
         target_layout={},
         freeze_placeholder_with_value=None,
-        tensorflow_use_custom_operations_config=None,
         data_type=None,
         tensorflow_custom_operations_config_update=None,
     )

tools/mo/unit_tests/moc_tf_fe/conversion_basic_models.py

@@ -43,14 +43,8 @@ def base_args_config():
     args.scale_values = None
     args.output_dir = os.getcwd()
     args.freeze_placeholder_with_value = None
-    args.tensorflow_use_custom_operations_config = None
     args.transformations_config = None
-    args.disable_fusing = None
-    args.finegrain_fusing = None
-    args.disable_resnet_optimization = None
-    args.enable_concat_optimization = None
     args.static_shape = None
-    args.disable_weights_compression = None
     args.reverse_input_channels = None
     args.data_type = None
     args.layout = None