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提交 de295641 编写于 作者: J jiangjiajun
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fix shufflenet xception and hrnet

上级 d7ab3a27
隐藏空白更改
内联 并排
Showing with 64 addition and 31 deletion
x2paddle/op_mapper/paddle_op_mapper.py
浏览文件 @ de295641
......@@ -13,6 +13,7 @@
# limitations under the License.
import math
import sys
import x2paddle
import os
import numpy as np
......@@ -261,21 +262,22 @@ class PaddleOpMapper(object):
inputs=op.input('X'),
outputs=op.output('Out'),
axis=op.attr('axis'))
return node
def slice(self, op, block):
axes = op.attr('axes')
starts = op.attr('starts')
ends = op.attr('ends')
axes_name = get_name(op.type, 'axes')
starts_name = get_name(op.type, 'starts')
ends_name = get_name(op.type, 'ends')
axes_node = make_constant_node(axes_name, onnx_pb.TensorProto.INT64,
axes)
starts_node = make_constant_node(starts_name, onnx_pb.TensorProto.INT64,
starts)
ends_node = make_constant_node(ends_name, onnx_pb.TensorProto.INT64,
ends)
axes_name = self.get_name(op.type, 'axes')
starts_name = self.get_name(op.type, 'starts')
ends_name = self.get_name(op.type, 'ends')
axes_node = self.make_constant_node(axes_name,
onnx_pb.TensorProto.INT64, axes)
starts_node = self.make_constant_node(starts_name,
onnx_pb.TensorProto.INT64, starts)
ends_node = self.make_constant_node(ends_name,
onnx_pb.TensorProto.INT64, ends)
node = helper.make_node(
"Slice",
inputs=[op.input('Input')[0], starts_name, ends_name, axes_name],
......@@ -288,12 +290,14 @@ class PaddleOpMapper(object):
dtype = op.attr('dtype')
shape = op.attr('shape')
value = np.ones(shape) * value
if dtype == 2:
value = value.astype('int32')
node = helper.make_node(
'Constant',
inputs=[],
outputs=op.attr('Out'),
outputs=op.output('Out'),
value=helper.make_tensor(
name=op.attr('Out'),
name=op.output('Out')[0],
data_type=self.paddle_onnx_dtype_map[dtype],
dims=shape,
vals=value.tolist()))
......@@ -304,28 +308,45 @@ class PaddleOpMapper(object):
'Transpose',
inputs=op.input('X'),
outputs=op.output('Out'),
perm=op.attr('perm'))
perm=op.attr('axis'))
return node
def reshape2(self, op, block):
input_names = op.input_names
if 'Shape' in input_names and len(op.input('Shape')) > 0:
if len(op.input('ShapeTensor')) > 1:
cast_shape_nodes = list()
cast_shape_names = list()
for i in range(len(op.input('ShapeTensor'))):
dim = op.input('ShapeTensor')[i]
temp_name = self.get_name(op.type, 'shape.cast')
node = helper.make_node(
'Cast',
inputs=[dim],
outputs=[temp_name],
to=onnx_pb.TensorProto.INT64)
cast_shape_nodes.append(node)
cast_shape_names.append(temp_name)
temp_name = self.get_name(op.type, 'shape.concat')
shape_node = helper.make_node(
'Concat', inputs=cast_shape_names, outputs=[temp_name], axis=-1)
node = helper.make_node(
'Reshape',
inputs=[op.input('X')[0],
op.input('Shape')[0]],
inputs=[op.input('X')[0], temp_name],
outputs=op.output('Out'))
return cast_shape_nodes + [shape_node, node]
else:
shape = op.attr('shape')
shape_name = get_name(op.type, 'shape')
shape_node = make_constant_node(shape_name,
onnxpb.TensorProto.INT64, shape)
temp_name = self.get_name(op.type, 'shape.cast')
cast_shape_node = helper.make_node(
'Cast',
inputs=op.input('ShapeTensor'),
outputs=[temp_name],
to=onnx_pb.TensorProto.INT64)
node = helper.make_node(
'Reshape',
inputs=[op.input('X')[0], shape_name],
inputs=[op.input('X')[0], temp_name],
outputs=op.output('Out'))
return [shape_node, node]
return node
return [cast_shape_node, node]
def dropout(self, op, block):
dropout_mode = op.attr('dropout_implementation')
......@@ -351,24 +372,31 @@ class PaddleOpMapper(object):
'ReduceMean',
inputs=op.input('X'),
outputs=op.output('Out'),
axes=op.attr('axes'),
axes=op.attr('dim'),
keepdims=op.attr('keep_dim'))
return node
def nearest_interp(self, op, block):
input_names = op.input_names
coordinate_transformation_mode = 'half_pixel'
if op.attr('align_corners'):
coordinate_transformation_mode = 'align_corners'
if 'OutSize' in input_names and len(op.input('OutSize')) > 0:
node = helper.make_node(
'Resize',
inputs=[op.input('X')[0], '',
op.input('OutSize')[0]],
outputs=op.output('Out'))
outputs=op.output('Out'),
mode='nearest',
coordinate_transformation_mode=coordinate_transformation_mode)
elif 'Scale' in input_names and len(op.input('Scale')) > 0:
node = helper.make_node(
'Resize',
inputs=[op.input('X')[0],
op.input('Scale')[0]],
outputs=op.output('Out'))
outputs=op.output('Out'),
mode='nearest',
coordinate_transformation_mode=coordinate_transformation_mode)
else:
out_shape = [op.attr('out_h'), op.attr('out_w')]
scale = op.attr('scale')
......@@ -384,7 +412,9 @@ class PaddleOpMapper(object):
'Resize',
inputs=[op.input('X')[0], roi_name, scale_name],
outputs=op.output('Out'),
mode='nearest')
mode='nearest',
coordinate_transformation_mode=coordinate_transformation_mode
)
return [scale_node, roi_node, node]
else:
raise Exception("Unexpected situation happend")
......@@ -477,9 +507,12 @@ class PaddleOpMapper(object):
unsupported_ops = set()
print("Translating PaddlePaddle to ONNX...\n")
for block in program.blocks:
for op in block.ops:
print('Translating op: {}'.format(op.type))
for i, op in enumerate(block.ops):
sys.stdout.write(
"\rTotal:{}, Current:{} : {} ".format(
len(block.ops), i + 1, op.type))
if not hasattr(self, op.type):
unsupported_ops.add(op.type)
continue
......@@ -497,7 +530,7 @@ class PaddleOpMapper(object):
op_nodes.append(node)
if len(unsupported_ops) > 0:
print("There's {} ops are not supported yet".format(
print("\nThere's {} ops are not supported yet".format(
len(unsupported_ops)))
for op in unsupported_ops:
print("=========== {} ===========".format(op))
......@@ -516,5 +549,5 @@ class PaddleOpMapper(object):
os.makedirs(save_dir)
with open(os.path.join(save_dir, 'x2paddle_model.onnx'), 'wb') as f:
f.write(model.SerializeToString())
print("Translated model saved in {}".format(
print("\nTranslated model saved in {}".format(
os.path.join(save_dir, 'x2paddle_model.onnx')))
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