Merge pull request #92 from SunAhong1993/develop

fix the slice

x2paddle/core/op_mapper.py

@@ -97,6 +97,11 @@ class OpMapper(object):
         import model
         try:
             inputs, outputs = model.x2paddle_net()
+            for i, out in enumerate(outputs):
+                if isinstance(out, list):
+                    for out_part in out:
+                        outputs.append(out_part)
+                    del outputs[i]
             input_names = [input.name for input in inputs]
             exe = fluid.Executor(fluid.CPUPlace())
             exe.run(fluid.default_startup_program())

x2paddle/core/util.py

@@ -26,6 +26,11 @@ def string(param):
 def run_net(param_dir="./"):
     import os
     inputs, outputs = x2paddle_net()
+    for i, out in enumerate(outputs):
+        if isinstance(out, list):
+            for out_part in out:
+                outputs.append(out_part)
+            del outputs[i]
     exe = fluid.Executor(fluid.CPUPlace())
     exe.run(fluid.default_startup_program())
 

x2paddle/op_mapper/caffe_op_mapper.py

@@ -399,9 +399,22 @@ class CaffeOpMapper(OpMapper):
         assert len(
             node.inputs) == 1, 'The count of Slice node\'s input is not 1.'
         input = self.graph.get_bottom_node(node, idx=0, copy=True)
+        top_len = len(node.layer.top)
         params = node.layer.slice_param
         axis = params.axis
+        slice_dim = params.slice_dim
+        if slice_dim != 1 and axis == 1:
+            axis = slice_dim
         points = list(params.slice_point)
+
+        if len(points) == 0:
+            dims = node.input_shape[0][axis]
+            assert dims % top_len == 0, "the parameter of Slice is wrong"
+            part = dims / top_len
+            t = part
+            while t < dims:
+                points.append(int(t))
+                t += part
         maxint32 = 2147483647
         points = [0] + points
         points.append(maxint32)
@@ -570,9 +583,7 @@ class CaffeOpMapper(OpMapper):
                                       param_attr=attr)
 
     def BatchNorm(self, node):
-        assert len(node.inputs) == 1 and len(
-            node.outputs
-        ) == 1, 'The count of BatchNorm node\'s input and output is not 1.'
+        assert len(node.inputs) == 1, 'The count of BatchNorm node\'s input is not 1.'
         input = self.graph.get_bottom_node(node, idx=0, copy=True)
         params = node.layer.batch_norm_param
         if hasattr(params, 'eps'):

x2paddle/op_mapper/caffe_shape.py

@@ -151,10 +151,22 @@ def shape_concat(layer, input_shape):
 
 def shape_slice(layer, input_shape):
     inshape = input_shape[0]
+
+    top_len = len(layer.top)
     params = layer.slice_param
     axis = params.axis
-    count = inshape[axis]
+    slice_dim = params.slice_dim
+    if slice_dim != 1 and axis == 1:
+        axis = slice_dim
     points = list(params.slice_point)
+    count = inshape[axis]
+    if len(points) == 0:
+        assert count % top_len == 0, "the parameter of Slice is wrong"
+        part = count / top_len
+        t = part
+        while t < count:
+            points.append(int(t))
+            t += part
     points = [0] + points + [count]
     output_shape = []
     for i in range(len(points)):