Merge branch 'master' into fix_instance_norm

Author: masakistan

doc/support_status.md

@@ -35,9 +35,9 @@ Notes:
 |Celu|-|-|-|-|-|-|-|-|-|-|-|**12**|12|Celu|
 |Clip|**1**|1|1|1|1|**6**|6|6|6|6|**11**|**12**|**13**|Clip|
 |Compress|-|-|-|-|-|-|-|-|**9**|9|**11**|11|11|Compress|
-|Concat|**1**|1|1|**4**|4|4|4|4|4|4|**11**|11|**13**:small_red_triangle:|Concat|
+|Concat|**1**|1|1|**4**|4|4|4|4|4|4|**11**|11|**13**|Concat|
 |ConcatFromSequence|-|-|-|-|-|-|-|-|-|-|**11**:small_orange_diamond:|11:small_orange_diamond:|11:small_orange_diamond:|ConcatFromSequence|
-|Constant|**1**|1|1|1|1|1|1|1|**9**|9|**11**|**12**|**13**:small_red_triangle:|Constant|
+|Constant|**1**|1|1|1|1|1|1|1|**9**|9|**11**|**12**|**13**|Constant|
 |ConstantOfShape|-|-|-|-|-|-|-|-|**9**|9|9|9|9|ConstantOfShape|
 |Conv|**1**|1|1|1|1|1|1|1|1|1|**11**|11|11|Conv|
 |ConvInteger|-|-|-|-|-|-|-|-|-|**10**|10|10|10|ConvInteger|
@@ -68,26 +68,26 @@ Notes:
 |GlobalAveragePool|**1**|1|1|1|1|1|1|1|1|1|1|1|1|GlobalAveragePool|
 |GlobalLpPool|**1**|**2**|2|2|2|2|2|2|2|2|2|2|2|GlobalLpPool|
 |GlobalMaxPool|**1**|1|1|1|1|1|1|1|1|1|1|1|1|GlobalMaxPool|
-|Greater|**1**|1|1|1|1|1|**7**|7|**9**|9|9|9|**13**:small_red_triangle:|Greater|
+|Greater|**1**|1|1|1|1|1|**7**|7|**9**|9|9|9|**13**|Greater|
 |GreaterOrEqual|-|-|-|-|-|-|-|-|-|-|-|**12**|12|GreaterOrEqual|
 |HardSigmoid|**1**|1|1|1|1|**6**|6|6|6|6|6|6|6|HardSigmoid|
 |Hardmax|**1**|1|1|1|1|1|1|1|1|1|**11**|11|**13**:small_red_triangle:|Hardmax|
 |Identity|**1**|1|1|1|1|1|1|1|1|1|1|1|**13**:small_red_triangle:|Identity|
-|If|**1**|1|1|1|1|1|1|1|1|1|**11**|11|**13**:small_red_triangle:|If|
+|If|**1**|1|1|1|1|1|1|1|1|1|**11**|11|**13**|If|
 |InstanceNormalization|**1**|1|1|1|1|**6**|6|6|6|6|6|6|6|InstanceNormalization|
 |IsInf|-|-|-|-|-|-|-|-|-|**10**|10|10|10|IsInf|
 |IsNaN|-|-|-|-|-|-|-|-|**9**|9|9|9|**13**:small_red_triangle:|IsNaN|
 |LRN|**1**|1|1|1|1|1|1|1|1|1|1|1|**13**|LRN|
 |LSTM|**1**:small_orange_diamond:|1:small_orange_diamond:|1:small_orange_diamond:|1:small_orange_diamond:|1:small_orange_diamond:|1:small_orange_diamond:|**7**:small_orange_diamond:|7:small_orange_diamond:|7:small_orange_diamond:|7:small_orange_diamond:|7:small_orange_diamond:|7:small_orange_diamond:|7:small_orange_diamond:|LSTM|
 |LeakyRelu|**1**|1|1|1|1|**6**|6|6|6|6|6|6|6|LeakyRelu|
-|Less|**1**|1|1|1|1|1|**7**|7|**9**|9|9|9|**13**:small_red_triangle:|Less|
+|Less|**1**|1|1|1|1|1|**7**|7|**9**|9|9|9|**13**|Less|
 |LessOrEqual|-|-|-|-|-|-|-|-|-|-|-|**12**|12|LessOrEqual|
 |Log|**1**|1|1|1|1|**6**|6|6|6|6|6|6|**13**|Log|
 |LogSoftmax|**1**|1|1|1|1|1|1|1|1|1|**11**|11|**13**:small_red_triangle:|LogSoftmax|
-|Loop|**1**|1|1|1|1|1|1|1|1|1|**11**|11|**13**:small_red_triangle:|Loop|
+|Loop|**1**|1|1|1|1|1|1|1|1|1|**11**|11|**13**|Loop|
 |LpNormalization|**1**|1|1|1|1|1|1|1|1|1|1|1|1|LpNormalization|
 |LpPool|**1**|**2**|2|2|2|2|2|2|2|2|**11**|11|11|LpPool|
-|MatMul|**1**|1|1|1|1|1|1|1|**9**|9|9|9|**13**:small_red_triangle:|MatMul|
+|MatMul|**1**|1|1|1|1|1|1|1|**9**|9|9|9|**13**|MatMul|
 |MatMulInteger|-|-|-|-|-|-|-|-|-|**10**|10|10|10|MatMulInteger|
 |Max|**1**|1|1|1|1|**6**|6|**8**|8|8|8|**12**|**13**|Max|
 |MaxPool|**1**:small_orange_diamond:|1:small_orange_diamond:|1:small_orange_diamond:|1:small_orange_diamond:|1:small_orange_diamond:|1:small_orange_diamond:|1:small_orange_diamond:|**8**:small_orange_diamond:|8:small_orange_diamond:|**10**:small_orange_diamond:|**11**:small_orange_diamond:|**12**:small_orange_diamond:|12:small_orange_diamond:|MaxPool|
@@ -164,7 +164,7 @@ Notes:
 |Sqrt|**1**|1|1|1|1|**6**|6|6|6|6|6|6|**13**|Sqrt|
 |Squeeze|**1**|1|1|1|1|1|1|1|1|1|**11**|11|**13**:small_red_triangle:|Squeeze|
 |StringNormalizer|-|-|-|-|-|-|-|-|-|**10**:small_red_triangle:|10:small_red_triangle:|10:small_red_triangle:|10:small_red_triangle:|StringNormalizer|
-|Sub|**1**|1|1|1|1|**6**|**7**|7|7|7|7|7|**13**:small_red_triangle:|Sub|
+|Sub|**1**|1|1|1|1|**6**|**7**|7|7|7|7|7|**13**|Sub|
 |Sum|**1**|1|1|1|1|**6**|6|**8**|8|8|8|8|**13**:small_red_triangle:|Sum|
 |Tan|-|-|-|-|-|-|**7**|7|7|7|7|7|7|Tan|
 |Tanh|**1**|1|1|1|1|**6**|6|6|6|6|6|6|**13**|Tanh|
@@ -179,7 +179,7 @@ Notes:
 |Where|-|-|-|-|-|-|-|-|**9**|9|9|9|9|Where|
 |Xor|**1**|1|1|1|1|1|**7**|7|7|7|7|7|7|Xor|
 
-ONNX-TF Supported Operators / ONNX Operators: 103 / 162
+ONNX-TF Supported Operators / ONNX Operators: 105 / 162
 
 Notes:
 1. Cast: Cast string to data types other than float32/float64/int32/int64 is not supported in Tensorflow

onnx_tf/backend.py

@@ -114,13 +114,12 @@ def _onnx_graph_to_tensorflow_rep(cls, graph_def, opset, strict, **kwargs):
     # initialized: A list of names of the initialized tensors.
 
     if graph_def.initializer:
-      input_dict_items = cls._onnx_initializer_to_input_dict_items(
-          graph_def.initializer)
       initialized = {init.name for init in graph_def.initializer}
     else:
-      input_dict_items = []
       initialized = set()
 
+    input_dict = dict()
+
     module = BackendTFModule(handlers, opset, strict, graph_def, cls)
     signatures = dict()
     for value_info in graph_def.input:
@@ -146,7 +145,7 @@ def _onnx_graph_to_tensorflow_rep(cls, graph_def, opset, strict, **kwargs):
             shape=shape
         ) if value_info.name not in input_tensor_dict else input_tensor_dict[
             value_info.name]
-        input_dict_items.append((value_info_name, x))
+        input_dict[value_info.name] = x
 
     tf_rep = TensorflowRep()
     tf_rep.inputs = [
@@ -159,8 +158,7 @@ def _onnx_graph_to_tensorflow_rep(cls, graph_def, opset, strict, **kwargs):
     tf_rep.tf_module = module
     tf_rep.signatures = signatures
     tf_rep.tensor_dict = module.gen_tensor_dict(
-        input_dict_items) if gen_tensor_dict else None
-
+        input_dict) if gen_tensor_dict else None
     return tf_rep
 
   @classmethod
@@ -288,55 +286,30 @@ def supports_device(cls, device):
   @classmethod
   def onnx_graph_to_tensorflow_ops(cls,
                                    subgraph,
-                                   input_values,
                                    tensor_dict,
                                    opset=None,
                                    strict=True):
     """
     Converts ONNX graph to Tensorflow operations
     Args:
-      subgraph:         the ONNX graph to be converted
-      input_values:     dictionary with values/tensors to initialize
-                        the subgraph inputs. if the subgraph.input
-                        are send in as parameters then it is required,
-                        otherwise this can be empty dictionary
-      tensor_dict:      the dictionary that contain values for all the
-                        node.inputs in the subgraph that are not defined
-                        in the subgraph or input_values.
+      subgraph:         the ONNX graph to be converted.
+      tensor_dict:      tensor dict of the subgraph.
       opset:            opset version of the operator set.
       strict:           whether to enforce semantic equivalence between the
                         original model and the converted tensorflow model,
                         defaults to True (yes, enforce semantic equivalence).
     Returns:
       array of Tensorflow Tensors
     """
-    # get the subgraph.input from input_values
-    subgraph_tensor_dict = input_values.copy()
-    # get the rest of the subgraph input from tensor_dict
-    for i in subgraph.input:
-      if i.name not in subgraph_tensor_dict.keys():
-        subgraph_tensor_dict[i.name] = tensor_dict[i.name]
-    # get the required initializer constant node(s) for the subgraph
-    # Need to get the initializer constant nodes from tensor_dict here
-    # because input from initializer will not be send in as inputs
-    # to the subgraph and those nodes are not in the subgraph
-    nodes_outputs = []
-    for node in subgraph.node:
-      for o_name in node.output:
-        nodes_outputs.append(o_name)
     for node in subgraph.node:
-      for i_name in node.input:
-        if i_name not in nodes_outputs and i_name not in subgraph_tensor_dict.keys(
-        ):
-          subgraph_tensor_dict[i_name] = tensor_dict[i_name]
       onnx_node = OnnxNode(node)
       output_ops = cls._onnx_node_to_tensorflow_op(onnx_node,
-                                                   subgraph_tensor_dict,
+                                                   tensor_dict,
                                                    opset=opset,
                                                    strict=strict)
       curr_node_output_map = dict(zip(onnx_node.outputs, output_ops))
-      subgraph_tensor_dict.update(curr_node_output_map)
-    return subgraph_tensor_dict
+      tensor_dict.update(curr_node_output_map)
+    return tensor_dict
 
   @classmethod
   def onnx_graph_to_tensorflow_rep(cls, graph_def, strict=True, **kwargs):

onnx_tf/backend_tf_module.py

@@ -13,9 +13,32 @@ def __init__(self, handlers, opset, strict, graph_def, backend):
     self.backend = backend
     self.outputs = []
 
+  # get initializer from the main graph and all subgraphs in loop or if or scan
+  # into tensor_dict
+  def _get_initializer_from_graph_and_subgraphs(self, graph, graph_tensor_dict):
+    if graph.initializer:
+      graph_tensor_dict.update(
+          self.backend._onnx_initializer_to_input_dict_items(graph.initializer))
+    for node in graph.node:
+      if node.op_type in ['Loop', 'Scan']:
+        onnx_node = OnnxNode(node)
+        body = onnx_node.attrs["body"]
+        graph_tensor_dict = self._get_initializer_from_graph_and_subgraphs(
+            body, graph_tensor_dict)
+      elif node.op_type == 'If':
+        onnx_node = OnnxNode(node)
+        then_branch = onnx_node.attrs['then_branch']
+        graph_tensor_dict = self._get_initializer_from_graph_and_subgraphs(
+            then_branch, graph_tensor_dict)
+        else_branch = onnx_node.attrs['else_branch']
+        graph_tensor_dict = self._get_initializer_from_graph_and_subgraphs(
+            else_branch, graph_tensor_dict)
+    return graph_tensor_dict
+
   @tf.function
-  def gen_tensor_dict(self, input_dict_items):
-    tensor_dict = dict(input_dict_items)
+  def gen_tensor_dict(self, input_dict):
+    tensor_dict = self._get_initializer_from_graph_and_subgraphs(
+        self.graph_def, dict(input_dict))
 
     for node in self.graph_def.node:
       onnx_node = OnnxNode(node)
@@ -31,15 +54,8 @@ def gen_tensor_dict(self, input_dict_items):
 
   @tf.function
   def __call__(self, **kwargs):
-    tensor_dict = kwargs
-
-    if self.graph_def.initializer:
-      input_dict_items = self.backend._onnx_initializer_to_input_dict_items(
-          self.graph_def.initializer)
-    else:
-      input_dict_items = []
-
-    tensor_dict.update(input_dict_items)
+    tensor_dict = self._get_initializer_from_graph_and_subgraphs(
+        self.graph_def, kwargs)
 
     for node in self.graph_def.node:
       onnx_node = OnnxNode(node)

onnx_tf/handlers/backend/concat.py

@@ -25,3 +25,7 @@ def version_4(cls, node, **kwargs):
   @classmethod
   def version_11(cls, node, **kwargs):
     return cls._common(node, **kwargs)
+
+  @classmethod
+  def version_13(cls, node, **kwargs):
+    return cls._common(node, **kwargs)

onnx_tf/handlers/backend/constant.py

@@ -71,3 +71,7 @@ def version_12(cls, node, **kwargs):
                                        inputs=[value],
                                        attrs={"dtype": dtype})
     ]
+
+  @classmethod
+  def version_13(cls, node, **kwargs):
+    return cls.version_12(node, **kwargs)

onnx_tf/handlers/backend/greater.py

@@ -21,3 +21,7 @@ def version_7(cls, node, **kwargs):
   @classmethod
   def version_9(cls, node, **kwargs):
     return [cls.make_tensor_from_onnx_node(node, **kwargs)]
+
+  @classmethod
+  def version_13(cls, node, **kwargs):
+    return [cls.make_tensor_from_onnx_node(node, **kwargs)]

onnx_tf/handlers/backend/if.py

@@ -21,22 +21,19 @@ def _common(cls, node, **kwargs):
     def true_fn():
       subgraph_tensor_dict = onnx_tf.backend.onnx_graph_to_tensorflow_ops(
           subgraph=then_branch,
-          input_values={}, # all inputs of then_branch are in tensor_dict
-          tensor_dict=kwargs["tensor_dict"],
+          tensor_dict=dict(kwargs["tensor_dict"]),
           opset=current_opset)
       return [subgraph_tensor_dict[o.name] for o in then_branch.output]
 
     def false_fn():
       subgraph_tensor_dict = onnx_tf.backend.onnx_graph_to_tensorflow_ops(
           subgraph=else_branch,
-          input_values={}, # all inputs of else_branch are in tensor_dict
-          tensor_dict=kwargs["tensor_dict"],
+          tensor_dict=dict(kwargs["tensor_dict"]),
           opset=current_opset)
       return [subgraph_tensor_dict[o.name] for o in else_branch.output]
 
-    return [
-        cls.make_tensor_from_onnx_node(node, inputs=[cond, true_fn, false_fn])
-    ]
+    return cls.make_tensor_from_onnx_node(node,
+                                          inputs=[cond, true_fn, false_fn])
 
   @classmethod
   def version_1(cls, node, **kwargs):
@@ -45,3 +42,7 @@ def version_1(cls, node, **kwargs):
   @classmethod
   def version_11(cls, node, **kwargs):
     return cls._common(node, **kwargs)
+
+  @classmethod
+  def version_13(cls, node, **kwargs):
+    return cls._common(node, **kwargs)

onnx_tf/handlers/backend/less.py

@@ -21,3 +21,7 @@ def version_7(cls, node, **kwargs):
   @classmethod
   def version_9(cls, node, **kwargs):
     return [cls.make_tensor_from_onnx_node(node, **kwargs)]
+
+  @classmethod
+  def version_13(cls, node, **kwargs):
+    return [cls.make_tensor_from_onnx_node(node, **kwargs)]