目前X2Paddle支持80+的TensorFlow OP,30+的Caffe Layer,60+的ONNX OP,110+的PyTorch Aten,10+的PyTorch Prim覆盖了大部分CV分类模型常用的操作。我们在如下列表中给出了目前X2Paddle支持的全部OP。
注: 目前,部分OP暂未支持,如您在转换过程中出现OP不支持的情况,可自行添加或反馈给我们。欢迎通过ISSUE反馈的方式告知我们(模型名,代码实现或模型获取方式),我们会及时跟进:)
序号 |
OP |
序号 |
OP |
序号 |
OP |
序号 |
OP |
1 |
Relu |
2 |
Relu6 |
3 |
Shape |
4 |
Abs |
5 |
Sigmoid |
6 |
Exp |
7 |
Rsqrt |
8 |
swish_f32 |
9 |
Tanh |
10 |
LeakyRelu |
11 |
Add |
12 |
RealDiv |
13 |
Sub |
14 |
Maximum |
15 |
Mul |
16 |
FloorDiv |
17 |
Placeholder |
18 |
Const |
19 |
Transpose |
20 |
FusedBatchNorm |
21 |
Conv2D |
22 |
BiasAdd |
23 |
MaxPool |
24 |
DepthwiseConv2dNative |
25 |
Reshape |
26 |
AvgPool |
27 |
SplitV |
28 |
SquaredDifference |
29 |
Tile |
30 |
Pack |
31 |
Pad |
32 |
ResizeBilinear |
33 |
Mean |
34 |
MatMul |
35 |
ArgMax |
36 |
StridedSlice |
37 |
Slice |
38 |
Sum |
39 |
Max |
40 |
Conv2DBackpropInput |
41 |
Cast |
42 |
Split |
43 |
Squeeze |
44 |
ResizeNearestNeighbor |
45 |
Softmax |
46 |
Range |
47 |
ConcatV2 |
48 |
MirrorPad |
49 |
Identity |
50 |
GreaterEqual |
51 |
StopGradient |
52 |
Minimum |
53 |
RadnomUniform |
54 |
Fill |
55 |
Floor |
56 |
DepthToSpace |
57 |
Sqrt |
58 |
Softplus |
59 |
Erf |
60 |
AddV2 |
61 |
LessEqual |
62 |
BatchMatMul |
63 |
BatchMatMulV2 |
64 |
ExpandDims |
65 |
BatchToSpaceND |
66 |
SpaceToBatchND |
67 |
OneHot |
68 |
Pow |
69 |
All |
70 |
GatherV2 |
71 |
IteratorV2 |
72 |
Neg |
73 |
Greater |
74 |
FloorMod |
75 |
LogicalAdd |
76 |
Prod |
77 |
Equal |
78 |
Conv3D |
79 |
Ceil |
80 |
AddN |
81 |
DivNoNan |
82 |
Where |
83 |
MirrorPad |
84 |
Size |
85 |
TopKv2 |
86 |
SplitV |
|
|
|
|
序号 |
OP |
序号 |
OP |
序号 |
OP |
序号 |
OP |
1 |
Input |
2 |
Convolution |
3 |
Deconvolution |
4 |
Pooling |
5 |
LRN |
6 |
InnerProduct |
7 |
Softmax |
8 |
Slice |
9 |
Concat |
10 |
PReLU |
11 |
Accuracy |
12 |
Eltwise |
13 |
BatchNorm |
14 |
Scale |
15 |
Reshape |
16 |
ArgMax |
17 |
Crop |
18 |
Flatten |
19 |
Power |
20 |
Reduction |
21 |
Axpy |
22 |
ROIPolling |
23 |
Permute |
24 |
DetectionOutput |
25 |
Normalize |
26 |
Select |
27 |
ShuffleChannel |
28 |
ConvolutionDepthwise |
29 |
ReLU |
30 |
AbsVal |
31 |
Sigmoid |
32 |
TanH |
33 |
ReLU6 |
34 |
Upsample |
|
|
|
|
序号 |
OP |
序号 |
OP |
序号 |
OP |
序号 |
OP |
1 |
Relu |
2 |
LeakyRelu |
3 |
Elu |
4 |
ThresholdedRelu |
5 |
Prelu |
6 |
Tanh |
7 |
Shrink |
8 |
Sigmoid |
9 |
Pow |
10 |
Softplus |
11 |
Softsign |
12 |
HardSigmoid |
13 |
Exp |
14 |
Add |
15 |
Div |
16 |
Sub |
17 |
Mul |
18 |
Shape |
19 |
Clip |
20 |
AveragePool |
21 |
Sqrt |
22 |
ReduceSum |
23 |
ReduceMin |
24 |
ReduceMean |
25 |
Constant |
26 |
Pad |
27 |
Unsqueeze |
28 |
Resize |
29 |
Upsample |
30 |
Expand |
31 |
Gather |
32 |
Slice |
33 |
Cast |
34 |
Split |
35 |
Reshape |
36 |
ConstantOfShape |
37 |
Ceil |
38 |
Concat |
39 |
Flatten |
40 |
ConvTranspose |
41 |
MatMul |
42 |
Sum |
43 |
Transpose |
44 |
BatchNormalization |
45 |
Squeeze |
46 |
Equal |
47 |
Identity |
48 |
GlobalAveragePool |
49 |
MaxPool |
50 |
Conv |
51 |
Gemm |
52 |
NonZero |
53 |
Abs |
54 |
Floor |
56 |
ArgMax |
57 |
Sign |
58 |
Reciprocal |
59 |
Size |
60 |
OneHot |
61 |
ReduceProd |
62 |
LogSoftmax |
63 |
LSTM |
|
|
|
|
Aten:
序号 |
OP |
序号 |
OP |
序号 |
OP |
序号 |
OP |
1 |
aten::abs |
2 |
aten::adaptive_avg_pool2d |
3 |
aten::addmm |
4 |
aten::add |
5 |
aten::add_ |
6 |
aten::__and__ |
7 |
aten::append |
8 |
aten::arange |
9 |
aten::avg_pool2d |
10 |
aten::avg_pool3d |
11 |
aten::avg_pool1d |
12 |
aten::batch_norm |
13 |
aten::cat |
14 |
aten::chunk |
15 |
aten::clamp |
16 |
aten::__contains__ |
17 |
aten::constant_pad_nd |
18 |
aten::contiguous |
19 |
aten::conv2d |
20 |
aten::_convolution |
21 |
aten::conv_transpose2d |
22 |
aten::cos |
23 |
aten::cumsum |
24 |
aten::detach |
25 |
aten::dict |
26 |
aten::dim |
27 |
aten::div_ |
28 |
aten::div |
29 |
aten::dropout |
30 |
aten::dropout_ |
31 |
aten::embedding |
32 |
aten::eq |
33 |
aten::exp |
34 |
aten::expand |
35 |
aten::expand_as |
36 |
aten::eye |
37 |
aten::feature_dropout |
38 |
aten::flatten |
39 |
aten::Float |
40 |
aten::floor |
41 |
aten::floordiv |
42 |
aten::floor_divide |
43 |
aten::full_like |
44 |
aten::gather |
45 |
aten::gelu |
46 |
aten::__getitem__ |
47 |
aten::gt |
48 |
aten::hardtanh_ |
49 |
aten::index_select |
50 |
aten::Int |
51 |
aten::__is__ |
52 |
aten::__isnot__ |
53 |
aten::layer_norm |
54 |
aten::le |
55 |
aten::leaky_relu_ |
56 |
aten::len |
57 |
aten::log |
58 |
aten::lt |
59 |
aten::masked_fil\l_ |
60 |
aten::masked_fill |
61 |
aten::max |
62 |
aten::max_pool2d |
63 |
aten::matmul |
64 |
aten_min |
65 |
aten::mean |
66 |
aten::meshgrid |
67 |
aten::mul |
68 |
aten::mul_ |
69 |
aten::ne |
70 |
aten::neg |
71 |
aten::__not__ |
72 |
aten::ones |
73 |
aten::permute |
74 |
aten::pow |
75 |
aten::relu |
76 |
aten::relu_ |
77 |
aten::relu6 |
78 |
aten::repeat |
79 |
aten::reshape |
80 |
aten::rsub |
81 |
aten::ScalarImplicit |
82 |
aten::select |
83 |
aten::_set_item |
84 |
aten::sigmoid |
85 |
aten::sin |
86 |
aten::size |
87 |
aten::slice |
88 |
aten::softmax |
89 |
aten::softplus |
90 |
aten::sqrt |
91 |
aten::squeeze |
92 |
aten::stack |
93 |
aten::sub |
94 |
aten::t |
95 |
aten::tanh |
96 |
aten::split |
97 |
aten::transpose |
98 |
aten::to |
99 |
aten::type_as |
100 |
aten::unsqueeze |
101 |
aten::upsample_bilinear2d |
102 |
aten::values |
103 |
aten::view |
104 |
aten::warn |
105 |
aten::where |
106 |
aten::zeros |
107 |
aten::zeros_like |
108 |
aten::bmm |
109 |
aten::sub_ |
110 |
aten:erf |
111 |
aten::lstm |
112 |
aten::gather |
113 |
aten::upsample_nearest2d |
|
|
|
|
|
|
Prim:
序号 |
OP |
序号 |
OP |
序号 |
OP |
序号 |
OP |
1 |
prim::Constant |
2 |
prim::data |
3 |
prim::DictConstruct |
4 |
prim::GetAttr |
5 |
prim::If |
6 |
prim::ListConstruct |
7 |
prim::ListUnpack |
8 |
prim::Loop |
9 |
prim::min |
10 |
prim::NumToTensor |
11 |
prim::RaiseException |
12 |
prim::requires_grad |
13 |
prim::SetAttr |
14 |
prim::shape |
15 |
prim::TupleConstruct |
16 |
prim::TupleUnpack |
17 |
prim::unchecked_cast |
18 |
prim::Uninitialized |
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