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X2Paddle
未验证 提交 57786e37 编写于 作者: Y yeliang2258 提交者： GitHub
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add 5 operators and fix 2 operators (#682) 

* support movenet

* update

* update

* update reducesum

* update max and min
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Showing with 148 addition and 16 deletion
x2paddle/op_mapper/onnx2paddle/opset9/opset.py
浏览文件 @ 57786e37
......@@ -124,27 +124,22 @@ class OpSet9():
'ReduceMean': [
'paddle.mean', dict(
axes='axis', keepdims='keepdim'), dict(
axes=None, keepdims=1)
],
'ReduceSum': [
'paddle.sum', dict(
axes='axis', keepdims='keepdim'), dict(
axes=None, keepdims=1)
axes=None, keepdims=True)
],
'ReduceMin': [
'paddle.min', dict(
axes='axis', keepdims='keepdim'), dict(
axes=None, keepdim=1)
axes=None, keepdim=True)
],
'ReduceMax': [
'paddle.max', dict(
axes='axis', keepdims='keepdim'), dict(
axes=None, keepdim=1)
axes=None, keepdim=True)
],
'ReduceProd': [
'paddle.prod', dict(
axes='axis', keepdims='keepdim'), dict(
axes=None, keepdim=1)
axes=None, keepdim=True)
],
# active function
'Relu': ['paddle.nn.ReLU'],
......@@ -663,7 +658,9 @@ class OpSet9():
def Unsqueeze(self, node):
val_x = self.graph.get_input_node(node, idx=0, copy=True)
axes = node.get_attr('axes')
layer_attrs = {'axis': axes}
if axes is None:
axes = self.graph.get_input_node(node, idx=1, copy=True)
if len(val_x.out_shapes[0]) == 0:
if node.name:
self.paddle_graph.add_layer(
......@@ -672,11 +669,18 @@ class OpSet9():
outputs=[node.name],
shape=[1])
else:
if isinstance(axes, list) or isinstance(axes, tuple):
self.paddle_graph.add_layer(
'paddle.unsqueeze',
inputs={"x": val_x.name},
outputs=[node.name],
**layer_attrs)
axis=axes,
outputs=[node.name])
else:
self.paddle_graph.add_layer(
'paddle.unsqueeze',
inputs={"x": val_x.name,
"axis": axes.name},
outputs=[node.name])
@print_mapping_info
def Shrink(self, node):
......@@ -1183,11 +1187,135 @@ class OpSet9():
else:
raise Exception("max_value or min_value can't be None")
@print_mapping_info
def ReduceSum(self, node):
val_x = self.graph.get_input_node(node, idx=0, copy=True)
if len(node.inputs) == 1:
keepdims = node.get_attr('keepdims')
if keepdims is None:
keepdims = True
axes_value = node.get_attr('axes')
layer_attrs = {'axis': axes_value, 'keepdim': keepdims}
self.paddle_graph.add_layer(
'paddle.sum',
inputs={"x": val_x.name},
outputs=[node.name],
**layer_attrs)
else:
axes = self.graph.get_input_node(node, idx=1, copy=True)
axes_value = _const_weight_or_none(axes)
if axes_value.shape == (1, ):
axes_value = axes_value[0]
keepdims = node.get_attr('keepdims')
if keepdims is None:
layer_attrs = {'axis': axes_value}
else:
layer_attrs = {'axis': axes_value, 'keepdim': keepdims}
self.paddle_graph.add_layer(
'paddle.sum',
inputs={"x": val_x.name},
outputs=[node.name],
**layer_attrs)
@print_mapping_info
def Max(self, node):
if len(node.inputs) == 2:
val_x = self.graph.get_input_node(node, idx=0, copy=True)
val_y = self.graph.get_input_node(node, idx=1, copy=True)
self.paddle_graph.add_layer(
"paddle.maximum",
inputs={"x": val_x.name,
"y": val_y.name},
outputs=[node.name])
else:
val_x = self.graph.get_input_node(node, idx=0, copy=True)
temp_name = "max_"
for i in range(1, len(node.inputs)):
val_y = self.graph.get_input_node(node, idx=i, copy=True)
temp_name = temp_name + str(i)
if i == len(node.inputs) - 1:
self.paddle_graph.add_layer(
"paddle.maximum",
inputs={"x": val_x.name,
"y": val_y.name},
outputs=[node.name])
else:
self.paddle_graph.add_layer(
"paddle.maximum",
inputs={"x": val_x.name,
"y": val_y.name},
outputs=[temp_name])
val_x.name = temp_name
@print_mapping_info
def Min(self, node):
if len(node.inputs) == 2:
val_x = self.graph.get_input_node(node, idx=0, copy=True)
val_y = self.graph.get_input_node(node, idx=1, copy=True)
self.paddle_graph.add_layer(
"paddle.minimum",
inputs={"x": val_x.name,
"y": val_y.name},
outputs=[node.name])
else:
val_x = self.graph.get_input_node(node, idx=0, copy=True)
temp_name = "min_"
for i in range(1, len(node.inputs)):
val_y = self.graph.get_input_node(node, idx=i, copy=True)
temp_name = temp_name + str(i)
if i == len(node.inputs) - 1:
self.paddle_graph.add_layer(
"paddle.minimum",
inputs={"x": val_x.name,
"y": val_y.name},
outputs=[node.name])
else:
self.paddle_graph.add_layer(
"paddle.minimum",
inputs={"x": val_x.name,
"y": val_y.name},
outputs=[temp_name])
val_x.name = temp_name
@print_mapping_info
def GreaterOrEqual(self, node):
val_x = self.graph.get_input_node(node, idx=0, copy=True)
val_y = self.graph.get_input_node(node, idx=1, copy=True)
self.paddle_graph.add_layer(
"paddle.greater_equal",
inputs={"x": val_x.name,
"y": val_y.name},
outputs=[node.name])
@print_mapping_info
def GatherND(self, node):
print(len(node.inputs), node.inputs)
val_x = self.graph.get_input_node(node, idx=0, copy=True)
val_y = self.graph.get_input_node(node, idx=1, copy=True)
self.paddle_graph.add_layer(
"paddle.gather_nd",
inputs={"x": val_x.name,
"index": val_y.name},
outputs=[node.name])
@print_mapping_info
def And(self, node):
val_x = self.graph.get_input_node(node, idx=0, copy=True)
val_y = self.graph.get_input_node(node, idx=1, copy=True)
self.paddle_graph.add_layer(
"paddle.logical_and",
inputs={"x": val_x.name,
"y": val_y.name},
outputs=[node.name])
@print_mapping_info
def Split(self, node):
val_x = self.graph.get_input_node(node, idx=0, copy=True)
paddle_op = 'split'
split = node.get_attr('split')
if split is None:
split = len(node.outputs)
axis = node.get_attr('axis', 0)
layer_attrs = {
'num_or_sections': split,
......@@ -1201,7 +1329,11 @@ class OpSet9():
for i in range(len(split)):
outputs_list.append("{}_p{}".format(node.layer_name, i))
else:
if len(node.outputs) == 1:
outputs_list.append(node.name)
else:
for i in range(len(node.outputs)):
outputs_list.append("{}_p{}".format(node.layer_name, i))
self.paddle_graph.add_layer(
'paddle.split',
inputs={"x": val_x.name},
......
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