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未验证 提交 78c614b7 编写于 作者: J Jason 提交者： GitHub
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Merge pull request #359 from Channingss/scatter_nd 

add OP:scatter_nd, fix bug of elementwise_map
上级 42d917e6 0fe0fc12
隐藏空白更改
内联 并排
Showing with 162 addition and 44 deletion
x2paddle/op_mapper/onnx2paddle/opset9/opset.py
浏览文件 @ 78c614b7
...@@ -43,6 +43,21 @@ def _const_weight_or_none(node, necessary=False): ...@@ -43,6 +43,21 @@ def _const_weight_or_none(node, necessary=False):
return None return None
def _is_static_shape(shape):
negtive_dims = 0
error_dims = 0
for dim in shape:
if dim < 0:
negtive_dims += 1
if dim < -1:
error_dims += 1
if negtive_dims > 1:
return False
if error_dims > 0:
return False
return True
def _get_same_padding(in_size, kernel_size, stride): def _get_same_padding(in_size, kernel_size, stride):
new_size = int(math.ceil(in_size * 1.0 / stride)) new_size = int(math.ceil(in_size * 1.0 / stride))
pad_size = (new_size - 1) * stride + kernel_size - in_size pad_size = (new_size - 1) * stride + kernel_size - in_size
...@@ -231,42 +246,9 @@ class OpSet9(): ...@@ -231,42 +246,9 @@ class OpSet9():
val_x = self.graph.get_input_node(node, idx=0, copy=True) val_x = self.graph.get_input_node(node, idx=0, copy=True)
val_y = self.graph.get_input_node(node, idx=1, copy=True) val_y = self.graph.get_input_node(node, idx=1, copy=True)
val_y_shape = val_y.out_shapes[0] inputs = {'x': val_x, 'y': val_y}
val_x_shape = val_x.out_shapes[0] node.fluid_code.add_layer(
op_type, inputs=inputs, output=node, param_attr=None)
if len(val_x_shape) < len(val_y_shape):
val_x, val_y = val_y, val_x
val_y_shape, val_x_shape = val_x_shape, val_y_shape
str_y_shape = ','.join(str(e) for e in val_y_shape)
str_x_shape = ','.join(str(e) for e in val_x_shape)
slice_idx = 0
if str_y_shape not in str_x_shape:
for dim in val_y_shape:
if dim == 1:
slice_idx += 1
else:
break
attr = {"name": string(node.layer_name)}
if slice_idx < len(val_y_shape) and slice_idx > 0:
val_y_reshaped = val_y_shape[slice_idx:]
var_y_reshaped = val_y.layer_name + '_reshaped'
attr_reshaped = {
'shape': val_y_reshaped,
'name': string(var_y_reshaped)
}
node.fluid_code.add_layer(
'reshape',
inputs=val_y,
output=var_y_reshaped,
param_attr=attr_reshaped)
inputs = {'x': val_x, 'y': var_y_reshaped}
node.fluid_code.add_layer(
op_type, inputs=inputs, output=node, param_attr=attr)
else:
inputs = {'x': val_x, 'y': val_y}
node.fluid_code.add_layer(
op_type, inputs=inputs, output=node, param_attr=attr)
@print_mapping_info @print_mapping_info
def place_holder(self, node): def place_holder(self, node):
...@@ -479,8 +461,21 @@ class OpSet9(): ...@@ -479,8 +461,21 @@ class OpSet9():
output=node, output=node,
param_attr={'shape': [1]}) param_attr={'shape': [1]})
else: else:
node.fluid_code.add_layer( if str(val_x.dtype) == 'bool':
'unsqueeze', inputs=val_x, output=node, param_attr=attr) val_x_cast = val_x.layer_name + '_cast'
node.fluid_code.add_layer(
'cast',
inputs=val_x,
output=val_x_cast,
param_attr={'dtype': string('int64')})
node.fluid_code.add_layer(
'unsqueeze',
inputs=val_x_cast,
output=node,
param_attr=attr)
else:
node.fluid_code.add_layer(
'unsqueeze', inputs=val_x, output=node, param_attr=attr)
@print_mapping_info @print_mapping_info
def Shrink(self, node): def Shrink(self, node):
...@@ -600,12 +595,35 @@ class OpSet9(): ...@@ -600,12 +595,35 @@ class OpSet9():
#assert len( #assert len(
# indices_shape) <= 2, "Gather op don't support dim of indice >2 " # indices_shape) <= 2, "Gather op don't support dim of indice >2 "
if axis == 0 and len(indices_shape) <= 1: if axis == 0 and len(indices_shape) <= 1:
node.fluid_code.add_layer( if len(val_x.out_shapes[0]) <= 1:
'gather', node.fluid_code.add_layer(
inputs={'input': val_x, 'gather',
'index': indices}, inputs={'input': val_x,
output=node, 'index': indices},
param_attr=None) output=node,
param_attr=None)
elif len(val_x.out_shapes[0]) > 1:
if len(indices_shape) == 0:
gather_ = node.layer_name + '_1'
node.fluid_code.add_layer(
'gather',
inputs={'input': val_x,
'index': indices},
output=gather_,
param_attr=None)
node.fluid_code.add_layer(
'squeeze',
inputs={'input': gather_,
'axes': [0]},
output=node,
param_attr=None)
else:
node.fluid_code.add_layer(
'gather',
inputs={'input': val_x,
'index': indices},
output=node,
param_attr=None)
elif axis > 0 and len(indices_shape) <= 1: elif axis > 0 and len(indices_shape) <= 1:
perm = list(range(len(val_x.out_shapes[0]))) perm = list(range(len(val_x.out_shapes[0])))
perm = [axis] + perm[:axis] + perm[axis + 1:] perm = [axis] + perm[:axis] + perm[axis + 1:]
...@@ -624,6 +642,13 @@ class OpSet9(): ...@@ -624,6 +642,13 @@ class OpSet9():
param_attr=None) param_attr=None)
node.fluid_code.add_layer( node.fluid_code.add_layer(
'transpose', inputs=node, output=node, param_attr=attr_trans) 'transpose', inputs=node, output=node, param_attr=attr_trans)
if len(indices_shape) < 1:
node.fluid_code.add_layer(
'squeeze',
inputs={'input': node,
'axes': [0]},
output=node,
param_attr=None)
elif axis == 0 and len(indices_shape) > 1: elif axis == 0 and len(indices_shape) > 1:
if val_x.out_shapes[0] is not None and isinstance( if val_x.out_shapes[0] is not None and isinstance(
val_x, ONNXGraphDataNode): val_x, ONNXGraphDataNode):
...@@ -704,6 +729,86 @@ class OpSet9(): ...@@ -704,6 +729,86 @@ class OpSet9():
output=node, output=node,
param_attr={'shape': reshaped_shape}) param_attr={'shape': reshaped_shape})
@print_mapping_info
def ScatterND(self, node):
val_x = self.graph.get_input_node(node, idx=0, copy=True)
indices = self.graph.get_input_node(node, idx=1, copy=True)
updates = self.graph.get_input_node(node, idx=2, copy=True)
if len(indices.out_shapes[0]) == 1:
node.fluid_code.add_layer(
'scatter',
inputs={'input': val_x,
'index': indices,
'updates': updates},
output=node,
param_attr=None)
else:
input_inner_indices = node.layer_name + '_input_inner_indices'
node.fluid_code.add_layer(
'scatter_nd',
inputs={
'shape': val_x.out_shapes[0],
'index': indices,
'updates': updates
},
output=input_inner_indices,
param_attr=None)
constant_minus_one = node.layer_name + '_constant_minus_one'
node.fluid_code.add_layer(
'fill_constant',
inputs=None,
output=constant_minus_one,
param_attr={
'shape': updates.out_shapes[0],
'dtype': string(updates.dtype),
'value': -1
})
indices_mask = node.layer_name + '_indices_mask'
node.fluid_code.add_layer(
'scatter_nd',
inputs={
'shape': val_x.out_shapes[0],
'index': indices,
'updates': constant_minus_one
},
output=indices_mask,
param_attr=None)
constant_1 = node.layer_name + '_constant_1'
node.fluid_code.add_layer(
'fill_constant',
inputs=None,
output=constant_1,
param_attr={
'shape': val_x.out_shapes[0],
'dtype': string(val_x.dtype),
'value': 1
})
input_out_indices_mask = node.layer_name + '_input_out_indices_mask'
node.fluid_code.add_layer(
"elementwise_add",
inputs={"x": indices_mask,
"y": constant_1},
output=input_out_indices_mask,
param_attr=None)
input_out_indices = node.layer_name + '_input_out_indices'
node.fluid_code.add_layer(
"elementwise_mul",
inputs={"x": val_x,
"y": input_out_indices_mask},
output=input_out_indices,
param_attr=None)
node.fluid_code.add_layer(
"elementwise_add",
inputs={"x": input_inner_indices,
"y": input_out_indices},
output=node,
param_attr=None)
@print_mapping_info @print_mapping_info
def Range(self, node): def Range(self, node):
val_start = self.graph.get_input_node(node, idx=0, copy=True) val_start = self.graph.get_input_node(node, idx=0, copy=True)
...@@ -831,6 +936,14 @@ class OpSet9(): ...@@ -831,6 +936,14 @@ class OpSet9():
inputs={'x': val_x}, inputs={'x': val_x},
output=node, output=node,
param_attr={'shape': shape_value.tolist()}) param_attr={'shape': shape_value.tolist()})
elif len(node.out_shapes[0]) > 0 and _is_static_shape(node.out_shapes[
0]):
node.fluid_code.add_layer(
'reshape',
inputs={'x': val_x,
'shape': node.out_shapes[0]},
output=node,
param_attr=attr)
elif val_shape.dtype == 'int64': elif val_shape.dtype == 'int64':
val_shape_cast = val_shape.layer_name + '_cast' val_shape_cast = val_shape.layer_name + '_cast'
node.fluid_code.add_layer( node.fluid_code.add_layer(
...@@ -882,6 +995,11 @@ class OpSet9(): ...@@ -882,6 +995,11 @@ class OpSet9():
node.fluid_code.add_layer( node.fluid_code.add_layer(
'cast', inputs=val_input, output=node, param_attr=attr) 'cast', inputs=val_input, output=node, param_attr=attr)
@print_mapping_info
def Not(self, node):
val_input = self.graph.get_input_node(node, idx=0, copy=True)
node.fluid_code.add_layer('logical_not', inputs=val_input, output=node)
@print_mapping_info @print_mapping_info
def AveragePool(self, node): def AveragePool(self, node):
val_x = self.graph.get_input_node(node, idx=0, copy=True) val_x = self.graph.get_input_node(node, idx=0, copy=True)
......
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