Automatically detect --disable_nhwc_to_nchw option in MO (#8450)

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Co-authored-by: Tatiana Savina <tatiana.savina@intel.com>

Update docs/MO_DG/prepare_model/customize_model_optimizer/Customize_Model_Optimizer.md

Co-authored-by: Tatiana Savina <tatiana.savina@intel.com>

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docs/MO_DG/prepare_model/convert_model/Convert_Model_From_TensorFlow.md

@@ -299,7 +299,9 @@ TensorFlow*-specific parameters:
                         TensorFlow*: comma separated list of shared libraries
                         with TensorFlow* custom operations implementation.
   --disable_nhwc_to_nchw
-                        Disables default translation from NHWC to NCHW
+                        [DEPRECATED] Disables default translation from NHWC to NCHW. Since 2022.1
+                        this option is deprecated and used only to maintain backward compatibility
+                        with previous releases.
 ```
 
 > **NOTE:** Models produces with TensorFlow\* usually have not fully defined shapes (contain `-1` in some dimensions). It is necessary to pass explicit shape for the input using command line parameter `--input_shape` or `-b` to override just batch dimension. If the shape is fully defined, then there is no need to specify either `-b` or `--input_shape` options.

docs/MO_DG/prepare_model/convert_model/tf_specific/Convert_BERT_From_Tensorflow.md

@@ -35,7 +35,6 @@ To generate the BERT Intermediate Representation (IR) of the model, run the Mode
 python3 ./mo_tf.py
 --input_meta_graph uncased_L-12_H-768_A-12/bert_model.ckpt.meta \
 --output bert/pooler/dense/Tanh                                 \
---disable_nhwc_to_nchw                                          \
 --input Placeholder{i32},Placeholder_1{i32},Placeholder_2{i32}
 ```
 
@@ -110,10 +109,9 @@ python3 run_classifier.py \
 
 Run the Model Optimizer with the following command line parameters to generate reshape-able BERT Intermediate Representation (IR):
 ```sh
-python3 ./mo_tf.py
+python3 ./mo_tf.py \
---input_model inference_graph.pb 
+    --input_model inference_graph.pb  \
---input "IteratorGetNext:0{i32}[1 128],IteratorGetNext:1{i32}[1 128],IteratorGetNext:4{i32}[1 128]" 
+    --input "IteratorGetNext:0{i32}[1 128],IteratorGetNext:1{i32}[1 128],IteratorGetNext:4{i32}[1 128]" 
---disable_nhwc_to_nchw 
 ```
 For other applicable parameters, refer to [Convert Model from TensorFlow](../Convert_Model_From_TensorFlow.md).
 

docs/MO_DG/prepare_model/convert_model/tf_specific/Convert_DeepSpeech_From_Tensorflow.md

@@ -71,8 +71,7 @@ To generate the IR, run the Model Optimizer with the following parameters:
 python3 {path_to_mo}/mo_tf.py                            \
 --input_model output_graph.pb                            \
 --input "input_lengths->[16],input_node[1 16 19 26],previous_state_h[1 2048],previous_state_c[1 2048]"   \
---output "cudnn_lstm/rnn/multi_rnn_cell/cell_0/cudnn_compatible_lstm_cell/GatherNd_1,cudnn_lstm/rnn/multi_rnn_cell/cell_0/cudnn_compatible_lstm_cell/GatherNd,logits" \
+--output "cudnn_lstm/rnn/multi_rnn_cell/cell_0/cudnn_compatible_lstm_cell/GatherNd_1,cudnn_lstm/rnn/multi_rnn_cell/cell_0/cudnn_compatible_lstm_cell/GatherNd,logits"
---disable_nhwc_to_nchw
 ```
 
 Where:

docs/MO_DG/prepare_model/convert_model/tf_specific/Convert_XLNet_From_Tensorflow.md

@@ -186,6 +186,7 @@ The script should save into `~/XLNet-Large/xlnet`.
 
 To generate the XLNet Intermediate Representation (IR) of the model, run the Model Optimizer with the following parameters:
 ```sh
-python3 mo.py --input_model path-to-model/model_frozen.pb  --input "input_mask[50 1],input_ids[50 1],seg_ids[50 1]" --log_level DEBUG --disable_nhwc_to_nchw --output_dir <OUTPUT_MODEL_DIR>
+python3 mo.py --input_model path-to-model/model_frozen.pb \
+    --input "input_mask[50 1],input_ids[50 1],seg_ids[50 1]"
 ```
 

docs/MO_DG/prepare_model/customize_model_optimizer/Customize_Model_Optimizer.md

@@ -285,10 +285,9 @@ More information on how to develop middle transformations and dedicated API desc
 ### NHWC to NCHW Layout Change <a name="layout-change"></a>
 There are several middle transformations responsible for changing model layout from NHWC to NCHW. These transformations
 are triggered by default for TensorFlow\* models only because it is the only framework with Convolution operations in
-NHWC layout.
+NHWC layout. This layout change is disabled if the model does not have operations that OpenVINO&trade needs to execute in
-
+NCHW layout, for example, Convolutions in NHWC layout. It is still possible to force Model Optimizer to do layout change
-> **NOTE**: If a TensorFlow\* model is in NCHW layout, you should specify the `--disable_nhwc_to_nchw` command line
+using `--disable_nhwc_to_nchw` command-line parameter.
-> parameter to disable these transformations.
 
 The layout change is a complex problem and detailed explanation of it is out of this document scope. A very brief
 explanation of this process is provided below:

model-optimizer/extensions/load/tf/loader.py

@@ -23,6 +23,7 @@ from mo.front.extractor import restore_edges, extract_node_attrs, remove_control
 from mo.front.tf.extractor import get_tf_edges, create_tf_edge, tf_op_extractor, tf_op_extractors
 from mo.front.tf.loader import load_tf_graph_def, protobuf2nx
 from mo.graph.graph import Graph, Node
+from mo.middle.pattern_match import for_graph_and_each_sub_graph_recursively
 from mo.utils import tensorboard_util
 from mo.utils.error import Error
 from mo.utils.telemetry_utils import send_op_names_info, send_shapes_info, send_framework_info
@@ -103,10 +104,10 @@ 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 argv.disable_nhwc_to_nchw and not argv.silent and 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):
-            log.error('The TensorFlow model does not contain Convolution operations with N(D)HWC layout. Most likely '
+            if not argv.silent:
-                      'the model should be converted using additional "--disable_nhwc_to_nchw" command line parameter '
+                log.debug('disable_nhwc_to_nchw" was automatically enabled.')
-                      'which disables model layout conversion inside the Model Optimizer.', extra={'is_warning': True})
+            for_graph_and_each_sub_graph_recursively(graph, update_cmd_params_and_layout)
 
         send_op_names_info(framework, graph)
         send_shapes_info(framework, graph)
@@ -143,3 +144,15 @@ def graph_or_sub_graph_has_nhwc_ops(graph: Graph):
                 NHWC_conv_detected |= graph_or_sub_graph_has_nhwc_ops(node.soft_get(sub_graph_name))
 
     return NHWC_conv_detected
+
+
+def update_cmd_params_and_layout(graph: Graph):
+    """
+    Updates "cmd_params" and "layout" attribute as the model has only NCHW layout operations.
+    :param graph: graph to update attributes
+    :return: Nones
+    """
+    if 'cmd_params' in graph.graph:
+        graph.graph['cmd_params'].auto_disable_nhwc_to_nchw = True
+    if 'layout' in graph.graph:
+        graph.graph['layout'] = 'NCHW'

model-optimizer/extensions/middle/PreserveRuntimeInfo.py

@@ -5,8 +5,9 @@ import numpy as np
 
 from extensions.middle.MergeNodesPermutations import MergeNodesPermutations
 from extensions.ops.transpose import Transpose
+from mo.front.common.partial_infer.utils import int64_array
 from mo.front.tf.graph_utils import create_op_node_with_second_input
-from mo.graph.graph import Graph
+from mo.graph.graph import Graph, Node
 from mo.middle.replacement import MiddleReplacementPattern
 from mo.utils.runtime_info import OldAPIMapOrder
 
@@ -39,30 +40,41 @@ class PreserveRuntimeInfo(MiddleReplacementPattern):
     def find_and_replace_pattern(self, graph: Graph):
         self.preserve_rt_info(graph)
 
+    @staticmethod
+    def add_old_api_map_order_into_rt_info(op: Node):
+        # rt info update
+        assert op.has('rt_info'), 'Unable to preserve runtime information for node with name={}'.format(op)
+
+        old_api_map = OldAPIMapOrder(version=0)
+        attr_name = old_api_map.get_name()
+        if (attr_name, old_api_map.get_version()) not in op.rt_info.info:
+            op.rt_info.info[(attr_name, old_api_map.get_version())] = old_api_map
+        return attr_name, old_api_map.get_version()
+
     @staticmethod
     def preserve_rt_info(graph: Graph):
-        for op in graph.get_op_nodes():
+        for op in graph.get_op_nodes(type='Parameter'):
             op_name = op.soft_get('name', op.id)
-            op_type = op.soft_get('type')
+            if 'auto_disable_nhwc_to_nchw' in graph.graph['cmd_params'] and \
-            if op_type == 'Parameter' and op.has_valid('permute_attrs') and not op.has_and_set('nchw_layout'):
+                    graph.graph['cmd_params'].auto_disable_nhwc_to_nchw:
-                if not op.out_node(0).has_valid('permutation'):
+                rank = op.out_port(0).data.get_shape().size
+                if rank < 4:
                     continue
+                order = list(range(rank))
+                order.remove(1)
+                order.append(1)
+                order = int64_array(order)
+            elif op.has_valid('permute_attrs') and not op.has_and_set('nchw_layout') and \
+                    op.out_node(0).has_valid('permutation'):
                 permutation = op.out_node(0).permutation
-                if np.array_equal(permutation.inv, range(len(permutation.inv))):
+                order = permutation.inv
+                if np.array_equal(order, range(len(permutation.inv))):
                     continue
 
-                # rt info update
-                assert op.has('rt_info'), 'Unable to preserve runtime information for node with name={}'.format(op_name)
-
-                old_api_map = OldAPIMapOrder(version=0)
-                attr_name = old_api_map.get_name()
-                if (attr_name, old_api_map.get_version()) not in op.rt_info.info:
-                    op.rt_info.info[(attr_name, old_api_map.get_version())] = old_api_map
-                op.rt_info.info[(attr_name, old_api_map.get_version())].old_api_transpose_parameter(permutation.inv)
-
                 # keep input in the framework format
                 transpose = create_op_node_with_second_input(
-                    graph, Transpose, permutation.perm, {'name': op_name + '/Transpose({})'.format(permutation.perm)})
+                    graph, Transpose, permutation.perm,
+                    {'name': op_name + '/Transpose({})'.format(permutation.perm)})
 
                 # source mode is used to keep tensor names at Parameter node
                 op.out_port(0).get_connection().insert_node(transpose, "source")
@@ -71,25 +83,34 @@ class PreserveRuntimeInfo(MiddleReplacementPattern):
                     del op['permute_attrs']
                 if op.out_node(0).has_valid('permutation'):
                     del op.out_node(0)['permutation']
+            else:
+                continue
 
-            elif op_type == 'Result' and op.in_ports():
+            rt_info_key = PreserveRuntimeInfo.add_old_api_map_order_into_rt_info(op)
+            op.rt_info.info[rt_info_key].old_api_transpose_parameter(order)
+
+        for op in graph.get_op_nodes(type='Result'):
+            if op.in_ports():
                 prev_node_out_port = op.in_port(0).get_connection().get_source()
                 if prev_node_out_port is None:
                     continue
                 in_node = prev_node_out_port.node
                 in_data_node = in_node.out_node(prev_node_out_port.idx)
-                if in_data_node.has_and_set('permutation'):
-                    permutation = in_data_node['permutation']
-                    if np.array_equal(permutation.perm, range(len(permutation.perm))):
-                        continue
 
-                    # rt info update
+                if 'auto_disable_nhwc_to_nchw' in graph.graph['cmd_params'] and \
-                    assert op.has('rt_info'), 'Unable to preserve runtime information for node with name={}'.format(op)
+                        graph.graph['cmd_params'].auto_disable_nhwc_to_nchw:
-                    old_api_map = OldAPIMapOrder(version=0)
+                    rank = prev_node_out_port.data.get_shape().size
-                    attr_name = old_api_map.get_name()
+                    if rank < 4:
-                    if (attr_name, old_api_map.get_version()) not in op.rt_info.info:
+                        continue
-                        op.rt_info.info[(attr_name, old_api_map.get_version())] = old_api_map
+                    order = list(range(rank - 1))
-                    op.rt_info.info[(attr_name, old_api_map.get_version())].old_api_transpose_result(permutation.perm)
+                    order.insert(1, rank - 1)
+                    order = int64_array(order)
+                elif in_data_node.has_and_set('permutation'):
+                    permutation = in_data_node['permutation']
+                    order = permutation.perm
+
+                    if np.array_equal(order, range(len(permutation.perm))):
+                        continue
 
                     # keep result in the framework format
                     transpose = create_op_node_with_second_input(graph, Transpose, permutation.inv)
@@ -98,3 +119,8 @@ class PreserveRuntimeInfo(MiddleReplacementPattern):
                     in_node.name += "/prev"
 
                     prev_node_out_port.get_connection().insert_node(transpose)
+                else:
+                    continue
+
+                rt_info_key = PreserveRuntimeInfo.add_old_api_map_order_into_rt_info(op)
+                op.rt_info.info[rt_info_key].old_api_transpose_result(order)

model-optimizer/mo/utils/cli_parser.py

@@ -564,7 +564,8 @@ def get_tf_cli_parser(parser: argparse.ArgumentParser = None):
                           default=None,
                           action=CanonicalizePathCheckExistenceAction)
     tf_group.add_argument('--disable_nhwc_to_nchw',
-                          help='Disables default translation from 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='store_true')
     return parser
 

model-optimizer/unit_tests/extensions/middle/PreserveRuntimeInfo_test.py

@@ -88,3 +88,37 @@ class PreserveRuntimeInfoTest(unittest.TestCase):
             rt_info = result_node.rt_info.info
             old_api_map = rt_info[('old_api_map_order', 0)].info
             self.assertTrue(np.array_equal(old_api_map['order'], nhwc_to_nchw_order))
+
+    def test_auto_disable_nhwc_to_nchw(self):
+        shape_len = 4
+        shape = np.array(range(shape_len))
+        add_shape = shape
+        graph_nodes = {
+            **regular_op_with_shaped_data('placeholder1', shape,
+                                          {'type': 'Parameter', 'rt_info': RTInfo(), 'shape': shape}),
+            **regular_op_with_shaped_data('placeholder2', shape,
+                                          {'type': 'Parameter', 'rt_info': RTInfo(), 'shape': shape}),
+            **regular_op_with_shaped_data('result', shape, {'type': 'Result', 'rt_info': RTInfo(), 'shape': shape}),
+            **regular_op_with_shaped_data('add', add_shape,
+                                          {'type': 'Add', 'op': 'Add', 'infer': copy_shape_infer}),
+        }
+
+        graph = build_graph(graph_nodes, edges)
+        graph.graph['cmd_params'].auto_disable_nhwc_to_nchw = True
+        graph_ref = build_graph(graph_nodes, edges)
+
+        param_node = Node(graph, 'placeholder1')
+        result_node = Node(graph, 'result')
+
+        PreserveRuntimeInfo().find_and_replace_pattern(graph)
+
+        (flag, resp) = compare_graphs(graph, graph_ref, 'result')
+        self.assertTrue(flag, resp)
+
+        rt_info = param_node.rt_info.info
+        old_api_map = rt_info[('old_api_map_order', 0)].info
+        self.assertTrue(np.array_equal(old_api_map['inverse_order'], [0, 2, 3, 1]))
+
+        rt_info = result_node.rt_info.info
+        old_api_map = rt_info[('old_api_map_order', 0)].info
+        self.assertTrue(np.array_equal(old_api_map['order'], [0, 3, 1, 2]))