libavfilter/dnn: add layer maximum for native mode.

The reason to add this layer is that it is used by srcnn in vf_sr.
This layer is currently ignored in native mode. After this patch,
we can add multiple outputs support for native mode.

Signed-off-by: Guo, Yejun <yejun.guo@intel.com>
Signed-off-by: Pedro Arthur <bygrandao@gmail.com>

2 files changed, 17 insertions, 2 deletions

diff --git a/tools/python/convert_from_tensorflow.py b/tools/python/convert_from_tensorflow.py
index 1437ad358d..a663b34004 100644
--- a/tools/python/convert_from_tensorflow.py
+++ b/tools/python/convert_from_tensorflow.py
@@ -70,7 +70,7 @@ class TFConverter:
         self.converted_nodes = set()
         self.conv2d_scope_names = set()
         self.conv2d_scopename_inputname_dict = {}
-        self.op2code = {'Conv2D':1, 'DepthToSpace':2, 'MirrorPad':3}
+        self.op2code = {'Conv2D':1, 'DepthToSpace':2, 'MirrorPad':3, 'Maximum':4}
         self.mirrorpad_mode = {'CONSTANT':0, 'REFLECT':1, 'SYMMETRIC':2}
         self.name_operand_dict = {}
 
@@ -200,6 +200,19 @@ class TFConverter:
         np.array([input_operand_index, output_operand_index], dtype=np.uint32).tofile(f)
 
 
+    def dump_maximum_to_file(self, node, f):
+        assert(node.op == 'Maximum')
+        self.layer_number = self.layer_number + 1
+        ynode = self.name_node_dict[node.input[1]]
+        y = ynode.attr['value'].tensor.float_val[0]
+        np.array([self.op2code[node.op]], dtype=np.uint32).tofile(f)
+        np.array([y], dtype=np.float32).tofile(f)
+        self.converted_nodes.add(node.name)
+        input_operand_index = self.add_operand(node.input[0], Operand.IOTYPE_INPUT)
+        output_operand_index = self.add_operand(node.name, Operand.IOTYPE_OUTPUT)
+        np.array([input_operand_index, output_operand_index], dtype=np.uint32).tofile(f)
+
+
     def dump_layers_to_file(self, f):
         for node in self.nodes:
             if node.name in self.converted_nodes:
@@ -216,6 +229,8 @@ class TFConverter:
                 self.dump_depth2space_to_file(node, f)
             elif node.op == 'MirrorPad':
                 self.dump_mirrorpad_to_file(node, f)
+            elif node.op == 'Maximum':
+                self.dump_maximum_to_file(node, f)
 
 
     def dump_operands_to_file(self, f):
diff --git a/tools/python/convert_header.py b/tools/python/convert_header.py
index 6a7e4af0c9..3c2acd5b15 100644
--- a/tools/python/convert_header.py
+++ b/tools/python/convert_header.py
@@ -23,4 +23,4 @@ str = 'FFMPEGDNNNATIVE'
 major = 0
 
 # increase minor when we don't have to re-convert the model file
-minor = 1
+minor = 2