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Support T5 Model #794

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merged 19 commits into from
May 25, 2022
Merged

Support T5 Model #794

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817dfcb
add replication pad
wjj19950828 Apr 28, 2022
6656224
update op_list.md
wjj19950828 Apr 28, 2022
789d07b
resolve conflict
wjj19950828 May 5, 2022
583bfd8
re-lint
wjj19950828 May 5, 2022
f5f9799
Merge remote-tracking branch 'upstream/develop' into fixed_aten_index
wjj19950828 May 7, 2022
902bdef
fixed aten::index
wjj19950828 May 7, 2022
48a3e3b
rm useless code
wjj19950828 May 7, 2022
620666e
Merge remote-tracking branch 'upstream/develop' into Supoort_wav2vec2
wjj19950828 May 9, 2022
be22eaa
Support Wav2vec2
wjj19950828 May 9, 2022
448fb19
Merge remote-tracking branch 'upstream/develop' into ONNX_for_HF
wjj19950828 May 10, 2022
4309c31
Support onnx roberta
wjj19950828 May 10, 2022
1761e71
update op_list.md
wjj19950828 May 10, 2022
16d15aa
deal with comments
wjj19950828 May 11, 2022
942de10
deal with comments
wjj19950828 May 11, 2022
5f0b141
Merge remote-tracking branch 'upstream/develop' into ONNX_for_HF
wjj19950828 May 11, 2022
a229bff
Support T5
wjj19950828 May 11, 2022
a6c820c
fixed for ci
wjj19950828 May 12, 2022
422a6b5
deal with comments
wjj19950828 May 12, 2022
feb0f15
deal with scalar tensor
wjj19950828 May 12, 2022
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248 changes: 86 additions & 162 deletions x2paddle/op_mapper/onnx2paddle/opset9/opset.py
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Original file line number Diff line number Diff line change
Expand Up @@ -122,6 +122,7 @@ class OpSet9():
'Mul': 'paddle.multiply',
'Pow': 'paddle.pow',
'Less': 'paddle.less_than',
'LessOrEqual': 'paddle.less_equal',
}

directly_map_ops = {
Expand Down Expand Up @@ -740,27 +741,21 @@ def Unsqueeze(self, node):
val_x = self.graph.get_input_node(node, idx=0, copy=True)
axes = node.get_attr('axes')
if axes is None:
axes = self.graph.get_input_node(node, idx=1, copy=True)
axes_node = self.graph.get_input_node(node, idx=1, copy=True)
axes = _const_weight_or_none(axes_node, necessary=True)
# deal with scalar(0D) tensor
if len(val_x.out_shapes[0]) == 0 and len(axes) == 1 and axes[0] == 0:
if node.name:
self.paddle_graph.add_layer(
'paddle.reshape',
inputs={"x": val_x.name},
outputs=[node.name],
shape=[1])
self.paddle_graph.add_layer(
'paddle.reshape',
inputs={"x": val_x.name},
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},
axis=axes,
outputs=[node.name])
else:
self.paddle_graph.add_layer(
'paddle.unsqueeze',
inputs={"x": val_x.name,
"axis": axes.name},
outputs=[node.name])
self.paddle_graph.add_layer(
'paddle.unsqueeze',
inputs={"x": val_x.name},
axis=axes,
outputs=[node.name])

@print_mapping_info
def Shrink(self, node):
Expand Down Expand Up @@ -893,72 +888,31 @@ def GatherND(self, node):
def Gather(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)
indices_values = _const_weight_or_none(indices, necessary=True)
if isinstance(indices_values, np.ndarray):
indices_values = indices_values.tolist()
indices_shape = indices.out_shapes[0]
val_x_shape = val_x.out_shapes[0]
axis = node.get_attr('axis', 0)
#assert len(
# indices_shape) <= 2, "Gather op don't support dim of indice >2 "
if axis == 0 and len(indices_shape) <= 1:
if len(val_x.out_shapes[0]) <= 1:
self.paddle_graph.add_layer(
'paddle.gather',
inputs={'x': val_x.name,
'index': indices.name},
outputs=[node.name])
elif len(val_x.out_shapes[0]) > 1:
if len(indices_shape) == 0:
self.paddle_graph.add_layer(
'paddle.reshape',
inputs={"x": indices.name},
outputs=[indices.name],
shape=[-1, ])
gather_ = node.name + '_1'
self.paddle_graph.add_layer(
'paddle.gather',
inputs={'x': val_x.name,
'index': indices.name},
outputs=[gather_])
self.paddle_graph.add_layer(
'paddle.squeeze',
inputs={'x': gather_},
outputs=[node.name],
axis=[0])
else:
self.paddle_graph.add_layer(
'paddle.gather',
inputs={'x': val_x.name,
'index': indices.name},
outputs=[node.name])
elif axis > 0 and len(indices_shape) <= 1:
perm = list(range(len(val_x.out_shapes[0])))
perm = [axis] + perm[:axis] + perm[axis + 1:]
name_trans = val_x.name + '_trans'
self.paddle_graph.add_layer(
'paddle.transpose',
inputs={"x": val_x.name},
outputs=[name_trans],
perm=perm)
if len(indices_shape) == 1 or \
(indices_values is not None and isinstance(indices_values, int)) or \
(indices_values is not None and len(indices_values) == 1):
self.paddle_graph.add_layer(
'paddle.gather',
inputs={'x': name_trans,
inputs={'x': val_x.name,
'index': indices.name},
outputs=[node.name])
new_perm = [0] * len(perm)
for i in range(len(perm)):
new_perm[perm[i]] = i
self.paddle_graph.add_layer(
'paddle.transpose',
inputs={"x": node.name},
outputs=[node.name],
perm=new_perm)
if len(indices_shape) < 1:
axis=axis)
# deal with indice is scalar(0D) Tensor
if isinstance(indices_values, int) and len(val_x_shape) > 1:
self.paddle_graph.add_layer(
'paddle.squeeze',
inputs={'x': node.name},
outputs=[node.name],
axis=[axis])
elif axis == 0 and len(indices_shape) > 1:
if val_x.out_shapes[0] is not None and isinstance(
val_x, ONNXGraphDataNode):
else:
# if val_x is DataNode, convert gather to embedding
if axis == 0 and isinstance(val_x, ONNXGraphDataNode):
indices_cast = indices.name + '_cast'
self.paddle_graph.add_layer(
'paddle.cast',
Expand All @@ -973,79 +927,68 @@ def Gather(self, node):
'paddle.nn.Embedding',
inputs={"x": indices_cast},
outputs=layer_outputs,
num_embeddings=val_x.out_shapes[0][0],
embedding_dim=val_x.out_shapes[0][1])
num_embeddings=val_x_shape[0],
embedding_dim=val_x_shape[1])
else:
from functools import reduce
reshape_shape = reduce(lambda x, y: x * y, indices_shape)
indices_reshape = indices.name + '_shape'
self.paddle_graph.add_layer(
'paddle.reshape',
inputs={"x": indices.name},
outputs=[indices_reshape],
shape=[reshape_shape, ])

perm = list(range(len(val_x.out_shapes[0])))
outputs=[indices.name + "_reshape"],
shape=[-1])
gather_1d = node.name + '_1D'
self.paddle_graph.add_layer(
'paddle.gather',
inputs={'x': val_x.name,
'index': indices_reshape},
outputs=[node.name])
val_x_shape = val_x.out_shapes[0]
reshaped_shape = []
for i in perm:
reshaped_shape.append(indices_shape[i])
for i in val_x_shape[:axis] + val_x_shape[axis + 1:]:
reshaped_shape.append(i)
self.paddle_graph.add_layer(
'paddle.reshape',
inputs={"x": node.name},
outputs=[node.name],
shape=reshaped_shape)
elif axis > 0 and len(indices_shape) > 1:
from functools import reduce
reshape_shape = reduce(lambda x, y: x * y, indices_shape)
indices_reshape = indices.name + '_shape'
self.paddle_graph.add_layer(
'paddle.reshape',
inputs={"x": indices.name},
outputs=[indices_reshape],
shape=[reshape_shape, ])

perm = list(range(len(val_x.out_shapes[0])))
perm = [axis] + perm[:axis] + perm[axis + 1:]
name_trans = val_x.name + '_transpose'
self.paddle_graph.add_layer(
'paddle.transpose',
inputs={"x": val_x.name},
outputs=[name_trans],
perm=perm)
self.paddle_graph.add_layer(
'paddle.gather',
inputs={'x': name_trans,
'index': indices_reshape},
outputs=[node.name])
input_transpose = node.name + '_transpose'
new_perm = [0] * len(perm)
for i in range(len(perm)):
new_perm[perm[i]] = i
self.paddle_graph.add_layer(
'paddle.transpose',
inputs={"x": node.name},
outputs=[input_transpose],
perm=new_perm)
perm = new_perm
val_x_shape = val_x.out_shapes[0]
reshaped_shape = []
for i in perm:
reshaped_shape.append(indices_shape[i])
for i in val_x_shape[:axis] + val_x_shape[axis + 1:]:
reshaped_shape.append(i)
self.paddle_graph.add_layer(
'paddle.reshape',
inputs={"x": input_transpose},
outputs=[node.name],
shape=reshaped_shape)
inputs={
'x': val_x.name,
'index': indices.name + "_reshape"
},
outputs=[gather_1d],
axis=axis)
# if shape is known
if len(indices_shape) != 0 and len(val_x_shape) != 0:
self.paddle_graph.add_layer(
'paddle.reshape',
inputs={'x': gather_1d},
outputs=[node.name],
shape=val_x_shape[:axis] + indices_shape +
val_x_shape[axis + 1:])
else:
all_shape_name = list()
self.paddle_graph.add_layer(
kernel="paddle.shape",
inputs={"input": val_x.name},
outputs=[val_x.name + "_shape"])
self.paddle_graph.add_layer(
kernel="paddle.shape",
inputs={"input": indices.name},
outputs=[indices.name + "_shape"])
self.paddle_graph.add_layer(
"paddle.slice",
inputs={"input": val_x.name + "_shape"},
outputs=[val_x.name + "_shape_slice_start"],
axes=[0],
starts=[0],
ends=[axis])
all_shape_name.append(val_x.name + "_shape_slice_start")
all_shape_name.append(indices.name + "_shape")
self.paddle_graph.add_layer(
"paddle.slice",
inputs={"input": val_x.name + "_shape"},
outputs=[val_x.name + "_shape_slice_end"],
axes=[0],
starts=[axis + 1],
ends=[2147483647])
all_shape_name.append(val_x.name + "_shape_slice_end")
self.paddle_graph.add_layer(
'paddle.concat',
inputs={"x": all_shape_name},
outputs=[node.name + "_all_shape"],
axis=0)
self.paddle_graph.add_layer(
'paddle.reshape',
inputs={'x': gather_1d},
outputs=[node.name],
shape=node.name + "_all_shape")

@print_mapping_info
def ScatterND(self, node):
Expand Down Expand Up @@ -1255,16 +1198,6 @@ def ConstantOfShape(self, node):
outputs=[node.name],
**layer_attrs)

@print_mapping_info
def GatherND(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.gather_nd",
inputs={"x": val_x.name,
"index": val_y.name},
outputs=[node.name])

@print_mapping_info
def Clip(self, node):
val_x = self.graph.get_input_node(node, idx=0, copy=True)
Expand Down Expand Up @@ -1420,16 +1353,6 @@ def GreaterOrEqual(self, node):
"y": val_y.name},
outputs=[node.name])

@print_mapping_info
def GatherND(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.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)
Expand Down Expand Up @@ -1710,7 +1633,8 @@ def MatMul(self, node):
x_shape = val_x.out_shapes[0]
y_shape = val_y.out_shapes[0]
inputs_dict = {"x": val_x.name, "y": val_y.name}
if y_shape[0] == 1 and x_shape[-1] != 1 and x_shape[0] != 1:
if len(y_shape) != 0 and y_shape[0] == 1 and len(
x_shape) != 0 and x_shape[-1] != 1 and x_shape[0] != 1:
y_squeeze = val_y.name + '_squeeze'
self.paddle_graph.add_layer(
"paddle.squeeze",
Expand Down