Tf2mx/yolov3

mmdnn/conversion/mxnet/mxnet_emitter.py

@@ -133,17 +133,27 @@ def gen_code(self, phase):
                 np.save(outfile, self.output_weights)
 
         comment = "\n    # if a GPU is available, change mx.cpu() to mx.gpu()"
+        self.add_body(1, comment)
         # We use the real_name for specifying the input layer in data_names
         # since MXNet API wants the actual name of the layer. On the other
         # hand, the module API wants the last symbol in the symbol chain, so
         # for the output node we need to use the actual python variable name
-        # of the last layer (real_variable_name).
-        last_line = "{:<15} = mx.mod.Module(symbol = {}, context = mx.cpu(), data_names = ['{}'])".format(
+        # of the last layer (real_variable_name)
+        if len(self.IR_graph.output_layers) == 1:
+            last_line = "{:<15} = mx.mod.Module(symbol = {}, context = mx.cpu(), data_names = ['{}'])".format(
             "model",
             ', '.join([self.IR_graph.get_node(name).real_variable_name for name in self.IR_graph.output_layers if self.IR_graph.get_node(name).type !='Pack' and self.IR_graph.get_node(name).type != 'Shape']),
             ', '.join([self.IR_graph.get_node(name).real_name for name in self.IR_graph.input_layers if self.IR_graph.get_node(name).type != 'Const']))
+        else:
+            group_line = "{:<15} = mx.sym.Group([{}])".format(
+            "group",
+            ', '.join([self.IR_graph.get_node(name).real_variable_name for name in self.IR_graph.output_layers if self.IR_graph.get_node(name).type !='Pack' and self.IR_graph.get_node(name).type != 'Shape']))
+            last_line = "{:<15} = mx.mod.Module(symbol = {}, context = mx.cpu(), data_names = ['{}'])".format(
+            "model",
+            "group",
+            ', '.join([self.IR_graph.get_node(name).real_name for name in self.IR_graph.input_layers if self.IR_graph.get_node(name).type != 'Const']))
+            self.add_body(1, group_line)
 
-        self.add_body(1, comment)
         self.add_body(1, last_line)
         self.add_body(1, "return model")
 
@@ -946,7 +956,13 @@ def emit_Mul(self, IR_node):
                 self.parent_variable_name(IR_node, [1]))
 
         return code
-
+
+    def emit_RealDiv(self, IR_node):           
+        code = "{:<15} = mx.sym.broadcast_div({}, {})".format(
+                IR_node.variable_name,
+                self.parent_variable_name(IR_node),
+                self.parent_variable_name(IR_node, [1]))
+        return code
 
     def emit_ReduceMean(self, IR_node):
         axes = IR_node.layer.attr['axes'].list.i[:]
@@ -1109,7 +1125,16 @@ def emit_Split(self, IR_node):
             axis)
 
         return code
-
+
+    def emit_SplitV(self, IR_node):  
+        axis = IR_node.get_attr('axis')
+        indices_or_sections = tuple(IR_node.get_attr('indices_or_sections'))
+        code = "{:<15} = mx.sym.split_v2({}, {}, axis={})".format(
+            IR_node.variable_name,
+            self.parent_variable_name(IR_node),
+            indices_or_sections,
+            axis)
+        return code
 
     def emit_Sigmoid(self, IR_node):
         code = "{:<15} = mx.sym.sigmoid(data={}, name='{}')".format(
@@ -1118,7 +1143,15 @@ def emit_Sigmoid(self, IR_node):
             IR_node.name
         )
         return code
+
+    def emit_ResizeNearestNeighbor(self, IR_node): 
+        scale = int(IR_node.get_attr('upSample_scale'))
+        code = "{:<15} = mx.sym.UpSampling({}, scale={}, sample_type='nearest')".format(
+            IR_node.variable_name,
+            self.parent_variable_name(IR_node),
+            scale)
 
+        return code
 
     def emit_Tanh(self, IR_node):
         code = "{:<15} = mx.sym.tanh(data={}, name='{}')".format(
@@ -1128,7 +1161,14 @@ def emit_Tanh(self, IR_node):
         )
         return code
 
-
+    def emit_Exp(self, IR_node):                 
+        code = "{:<15} = mx.sym.exp(data={}, name='{}')".format(
+            IR_node.variable_name,
+            self.parent_variable_name(IR_node),
+            IR_node.name
+        )
+        return code
+
     def emit_Maxmum(self, IR_node):
         code = "{:<15} = mx.sym.maxmum({}, {}, name='{}')".format(
             IR_node.variable_name,
@@ -1137,7 +1177,15 @@ def emit_Maxmum(self, IR_node):
             IR_node.name
         )
         return code
-
+
+    def emit_Maximum(self, IR_node):         
+        code = "{:<15} = mx.sym.broadcast_maximum({}, {}, name='{}')".format(
+            IR_node.variable_name,
+            self.parent_variable_name(IR_node),
+            self.parent_variable_name(IR_node, [1]),
+            IR_node.name
+        )
+        return code
 
     def emit_Minimum(self, IR_node):
         code = "{:<15} = mx.sym.minimum({}, {}, name='{}')".format(

mmdnn/conversion/tensorflow/tensorflow_graph.py

@@ -59,7 +59,8 @@ class TensorflowGraph(Graph):
     multi_tensor_type = [
         "Slice",
         "Split",
-        "Unpack"
+        "Unpack",
+        "SplitV"
     ]
 
 

mmdnn/conversion/tensorflow/tensorflow_parser.py

@@ -514,6 +514,14 @@ def rename_UNKNOWN(self, source_node):
               % (source_node.type, source_node.name))
         return
 
+    def rename_ResizeNearestNeighbor(self, source_node):               
+        IR_node = self._convert_identity_operation(source_node)
+        input_shape = self.get_parent(source_node.name,[0]).layer.attr['_output_shapes'].list.shape[0].dim[1].size
+        output_shape = source_node.layer.attr['_output_shapes'].list.shape[0].dim[1].size
+        upSample_scale = output_shape/input_shape
+        kwargs = {}
+        kwargs['upSample_scale'] = upSample_scale
+        assign_IRnode_values(IR_node, kwargs)
 
     def rename_Placeholder(self, source_node):
         IR_node = self._convert_identity_operation(source_node, new_op='DataInput')
@@ -565,7 +573,12 @@ def _convert_identity_operation(self, source_node, start_edge_id = 0, in_edge_co
 
     def rename_Relu(self, source_node):
         self._convert_identity_operation(source_node)
-
+
+    def rename_LeakyRelu(self, source_node):            # 191011 sfj add
+        IR_node = self._convert_identity_operation(source_node)
+        kwargs = {}
+        kwargs['alpha'] = source_node.get_attr('alpha')  # 191014 sfj add
+        assign_IRnode_values(IR_node, kwargs)
 
     def rename_Softmax(self, source_node):
         self._convert_identity_operation(source_node)
@@ -612,7 +625,9 @@ def rename_Abs(self, source_node):
 
     def rename_Square(self, source_node):
         IR_node = self._convert_identity_operation(source_node, in_edge_count = 1, new_op = 'Square')
-
+
+    def rename_Exp(self, source_node):        # 191013 sfj add
+        IR_node = self._convert_identity_operation(source_node, in_edge_count = 1, new_op = 'Exp')
 
     def rename_MatMul(self, source_node):
 
@@ -685,7 +700,10 @@ def rename_RealDiv(self, source_node):
             # print (source_node)
             # print (source_node.layer)
             # assert False
-            self._convert_identity_operation(source_node, new_op='Div')
+            #self._convert_identity_operation(source_node, new_op='Div')
+            self._convert_identity_operation(source_node, new_op='RealDiv') 
+            self._add_constant_node(source_node)
+
 
 
     def rename_Floor(self, source_node):
@@ -928,7 +946,21 @@ def rename_Split(self, source_node):
                 'split' : source_node.get_attr('num_split')
             }
             assign_IRnode_values(IR_node, kwargs)
+
+    def rename_SplitV(self, source_node):          # 191013 sfj add, const is [2,2,1,0]
+        IR_node = self._convert_identity_operation(source_node)
+        sizes = tensor_util.MakeNdarray(self.get_parent(source_node.name, [1]).layer.attr['value'].tensor)
+        indices_or_sections = []
+        target = 0
+        for size in sizes:
+            target += size
+            indices_or_sections.append(target)
 
+        kwargs = {
+                'indices_or_sections' : indices_or_sections,
+                'axis' : self.get_parent(source_node.name, [2]).layer.attr['value'].tensor.int_val[0]
+            }
+        assign_IRnode_values(IR_node, kwargs)
 
     def rename_StridedSlice(self, source_node):
         # TODO: Current it is only for slice
@@ -1054,6 +1086,10 @@ def rename_Minimum(self, source_node):
     def rename_Maxmum(self, source_node):
         self._add_constant_node(source_node)
         self._convert_identity_operation(source_node)
+
+    def rename_Maximum(self, source_node):    # 191016 sfj add
+        self._add_constant_node(source_node)
+        IR_node = self._convert_identity_operation(source_node)
 
     def rename_Cast(self, source_node):
         IR_node = self._convert_identity_operation(source_node)