Actualize operations attributes (#3613)

* Fix missed/redundant attrs for some operations

* Align auto_pad attr values in spec

* Update MO IR Reader extenders for appropriate operations

* Allign auto_pad attr values for appropriate operations

* Remove changes in extenders

* Update backend_attrs for some operations

* Changes in shape_infer functions to correct work with explicit mode

* Apply offline comments

docs/ops/convolution/ConvolutionBackpropData_1.md

@@ -75,7 +75,7 @@ else:
 * *auto_pad*
 
   * **Description**: *auto_pad* has the same definition as *auto_pad* for a regular Convolution but applied in the backward way, for the output tensor. 
-    * None (not specified): use explicit padding values from `pads_begin` and `pads_end`.
+    * *explicit*: use explicit padding values from `pads_begin` and `pads_end`.
     * *same_upper (same_lower)* the input is padded to match the output size. In case of odd padding value an extra padding is added at the end (at the beginning).
     * *valid* - do not use padding.
   * **Type**: string

docs/ops/convolution/Convolution_1.md

@@ -70,7 +70,7 @@ n_{out} = \left ( \frac{n_{in} + 2p - k}{s} \right ) + 1
 * *auto_pad*
 
   * **Description**: *auto_pad* how the padding is calculated. Possible values:
-    * None (not specified): use explicit padding values.
+    * *explicit*: use explicit padding values from `pads_begin` and `pads_end`.
     * *same_upper (same_lower)* the input is padded to match the output size. In case of odd padding value an extra padding is added at the end (at the beginning).
     * *valid* - do not use padding.
   * **Type**: string

docs/ops/convolution/DeformableConvolution_1.md

@@ -45,7 +45,7 @@
 * *auto_pad*
 
   * **Description**: *auto_pad* how the padding is calculated. Possible values:
-    * None (not specified): use explicit padding values.
+    * *explicit*: use explicit padding values from `pads_begin` and `pads_end`.
     * *same_upper (same_lower)* the input is padded to match the output size. In case of odd padding value an extra padding is added at the end (at the beginning).
     * *valid* - do not use padding.
   * **Type**: string

docs/ops/convolution/GroupConvolutionBackpropData_1.md

@@ -77,7 +77,7 @@ else:
 * *auto_pad*
 
   * **Description**: *auto_pad* has the same definition as *auto_pad* for a regular Convolution but applied in the backward way, for the output tensor. 
-    * None (not specified): use explicit padding values from `pads_begin` and `pads_end`.
+    * *explicit*: use explicit padding values from `pads_begin` and `pads_end`.
     * *same_upper (same_lower)* the input is padded to match the output size. In case of odd padding value an extra padding is added at the end (at the beginning).
     * *valid* - do not use padding.
   * **Type**: string

docs/ops/convolution/GroupConvolution_1.md

@@ -47,7 +47,7 @@
 * *auto_pad*
 
   * **Description**: *auto_pad* how the padding is calculated. Possible values:
-    * None (not specified): use explicit padding values.
+    * *explicit*: use explicit padding values from `pads_begin` and `pads_end`.
     * *same_upper (same_lower)* the input is padded to match the output size. In case of odd padding value an extra padding is added at the end (at the beginning).
     * *valid* - do not use padding.
   * **Type**: string

docs/ops/pooling/AvgPool_1.md

@@ -64,7 +64,7 @@
 * *auto_pad*
 
   * **Description**: *auto_pad* how the padding is calculated. Possible values:
-    * None (not specified): use explicit padding values.
+    * *explicit*: use explicit padding values from `pads_begin` and `pads_end`.
     * *same_upper (same_lower)* the input is padded to match the output size. In case of odd padding value an extra padding is added at the end (at the beginning).
     * *valid* - do not use padding.
   * **Type**: string

docs/ops/pooling/MaxPool_1.md

@@ -57,7 +57,7 @@
 * *auto_pad*
 
   * **Description**: *auto_pad* how the padding is calculated. Possible values:
-    * *explicit*: use explicit padding values.
+    * *explicit*: use explicit padding values from `pads_begin` and `pads_end`.
     * *same_upper (same_lower)* the input is padded to match the output size. In case of odd padding value an extra padding is added at the end (at the beginning).
     * *valid* - do not use padding.
   * **Type**: string

model-optimizer/extensions/ops/elementwise.py

@@ -63,7 +63,8 @@ class Elementwise(Op):
             'in_ports_count': 2,
             'out_ports_count': 1,
             'is_eltwise': True,
-            'stop_value_propagation': False
+            'stop_value_propagation': False,
+            'auto_broadcast': 'numpy'
         }, attrs)
 
     @staticmethod
@@ -71,6 +72,9 @@ class Elementwise(Op):
         override_data_type_of_constant(node)
         node.out_port(0).set_data_type(node.in_port(0).get_data_type())
 
+    def backend_attrs(self):
+        return ['auto_broadcast']
+
 
 class UnaryElementwise(Elementwise):
     def __init__(self, graph: Graph, attrs: dict):
@@ -82,6 +86,9 @@ class UnaryElementwise(Elementwise):
     def type_infer(node):
         copy_type_infer(node)
 
+    def backend_attrs(self):
+        return []
+
 
 class Add(Elementwise):
     op = 'Add'

model-optimizer/extensions/ops/fakequantize.py

@@ -49,6 +49,7 @@ class FakeQuantize(Op):
             'infer': self.infer,
             'in_ports_count': 5,
             'out_ports_count': 1,
+            'auto_broadcast': 'numpy'
         }
         super().__init__(graph, mandatory_props, attrs)
         if self.attrs['levels'] is None:
@@ -57,6 +58,7 @@ class FakeQuantize(Op):
     def supported_attrs(self):
         return [
             'levels',
+            'auto_broadcast'
         ]
 
     @staticmethod

model-optimizer/extensions/ops/select.py

@@ -33,9 +33,13 @@ class Select(Op):
             'out_ports_count': 1,
             'infer': __class__.infer,
             'type_infer': __class__.type_infer,
+            'auto_broadcast': 'numpy'
         }
         super().__init__(graph, mandatory_props, attrs)
 
+    def backend_attrs(self):
+        return ['auto_broadcast']
+
     @staticmethod
     def infer(node: Node):
         assert len([port for port in node.in_ports().values() if not port.disconnected()]) == 3, "Select operation must have 3 inputs:" \

model-optimizer/mo/ops/convolution.py

@@ -48,18 +48,21 @@ class Convolution(Op):
             if not node.has_valid('pad'):
                 return None
             pad = get_backend_pad(node.pad, node.spatial_dims, 0 if pad_type == 'begin' else 1)
-            if node.has_valid('auto_pad'):
+            if node.has_valid('auto_pad') and node.auto_pad != 'explicit':
                 pad = [0 for _ in pad]
             return ','.join(map(str, pad))
 
         return [
-            'auto_pad',
+            ('auto_pad', lambda node: node.auto_pad if node.has_valid('auto_pad') else 'explicit'),
             ('strides', lambda node: ','.join(map(str, node['stride'][node.spatial_dims]))),
             ('dilations', lambda node: ','.join(map(str, node['dilation'][node.spatial_dims]))),
             ('pads_begin', lambda node: pad_attribute_helper(node, 'begin')),
             ('pads_end', lambda node: pad_attribute_helper(node, 'end')),
+
+            # for Backpropdata operations only - according to spec
             ('output_padding', lambda node: ','.join(map(str, node.output_padding[node.spatial_dims])) \
-                if node.has_valid('output_padding') else None),
+                if node.has_valid('output_padding') and node.type in
+                    ('GroupConvolutionBackpropData', 'ConvolutionBackpropData') else None),
 
             # for BinaryConvolution only
             'pad_value',
@@ -187,7 +190,7 @@ class Convolution(Op):
         # TensorFlow always has auto_pad attribute that can be either valid or same_upper
         # In ONNX auto_pad attribute is deprecated but appears in some models (could be valid, same_upper or same_lower)
         # Caffe do not use auto_pad attribute
-        if node.has_valid('auto_pad') and not node.has_valid('output_spatial_shape'):
+        if node.has_valid('auto_pad') and node.auto_pad != 'explicit' and not node.has_valid('output_spatial_shape'):
             node['pad_spatial_shape'], node['output_spatial_shape'] = tf_window_op_pad_infer(input_spatial_shape,
                                                                                              kernel_extent,
                                                                                              stride_spatial_shape,

model-optimizer/mo/ops/pooling.py

@@ -48,7 +48,7 @@ class Pooling(Op):
             ('exclude-pad', 'exclude_pad'),
 
             'rounding_type',
-            'auto_pad',
+            ('auto_pad', lambda node: node.auto_pad if node.has_valid('auto_pad') else 'explicit'),
         ]
 
     @staticmethod
@@ -80,7 +80,7 @@ class Pooling(Op):
         stride_spatial = node.stride[node.spatial_dims]
         assert any(stride_spatial), 'Stride can not be zero in node {}'.format(node.id)
 
-        if node.has_valid('auto_pad'):
+        if node.has_valid('auto_pad') and node.auto_pad != 'explicit':
             node.pad_spatial_shape, node.output_spatial_shape = tf_window_op_pad_infer(input_spatial_shape,
                                                                                        window_spatial_shape,
                                                                                        stride_spatial, node.auto_pad)