fix identity problem

tensorflow2fluid/tf2fluid/paddle_emitter.py

@@ -31,12 +31,22 @@ class PaddleEmitter(object):
         self.weights = parser.weights
         self.infer = parser.infer
         self.inputs_sample_data = dict()
-        self.outputs = parser.outputs
-        self.inputs = parser.inputs
         self.save_dir = save_dir
         self.body_code = ""
         self.tab = " " * 4
 
+        self.outputs = parser.outputs
+        self.inputs = parser.inputs
+        outputs = list()
+        for output in self.outputs:
+            while True:
+                if output in self.graph.identity_relation:
+                    output = self.graph.identity_relation[output]
+                else:
+                    break
+            outputs.append(output)
+        self.outputs = outputs
+
     @staticmethod
     def compute_padding_size(in_size, filter_size, stride):
         new_size = int(math.ceil(in_size * 1.0 / stride))
@@ -306,10 +316,10 @@ class PaddleEmitter(object):
 
         node.code.add_str("#{} {} {}".format(node.layer_name, node.ref_name,
                                              value.shape))
-        if len(shape) == 0 or (len(shape) == 1 and shape[0] < 2):
+        if value.size == 1:
             param_attr = {
                 "shape": [1],
-                "value": value,
+                "value": value.flatten()[0],
                 "dtype": "\'{}\'".format(dtype),
             }
             node.code.add_layer("fill_constant", None, node.output_name,
@@ -343,9 +353,6 @@ class PaddleEmitter(object):
         if node.data_format == NHWC:
             input_h, input_w = input_shape[1:3]
             strides = node.get_attr("strides")[1:3]
-        if k_h < strides[0] or k_w < strides[1]:
-            raise Exception("Unexpected situation with kernel's height/width " \
-                "less than the corresponding stride")
 
         if kernel.layer_name in self.weights:
             weight = self.weights[kernel.layer_name]
@@ -1035,3 +1042,11 @@ class PaddleEmitter(object):
                 num_sections) + num_sections[index[0]]
         param = {"num_or_sections": list(num_sections), "dim": split_dim}
         node.code.add_layer("split", data.ref_name, node.output_name, param)
+
+    def emit_expanddims(self, node):
+        data = node.inputs[0]
+        dim = node.inputs[1]
+        dim.code.clear()
+        dim = self.infer.get_const_tensor_value(dim.layer)
+        param = {"axes":[dim]}
+        node.code.add_layer("unsqueeze", data.ref_name, node.output_name, param)

tensorflow2fluid/tf2fluid/tensorflow_graph.py

@@ -76,6 +76,7 @@ class TensorflowGraph(Graph):
     def __init__(self, tf_graph):
         super(TensorflowGraph, self).__init__(tf_graph)
         self.tf_graph = tf_graph
+        self.identity_relation = dict()
 
     def build(self, input_format):
         skip_node = set(['const'])
@@ -131,6 +132,7 @@ class TensorflowGraph(Graph):
             current_node = self.node_map[name]
             if current_node.layer_type in self.useless_type:
                 input = current_node.inputs[0]
+                self.identity_relation[current_node.layer.name] = input.layer.name
                 for node in current_node.outputs:
                     for k in range(0, len(node.inputs)):
                         if node.inputs[k] == current_node: