X2Paddle支持OP列表

目前X2Paddle支持50+的TensorFlow OP，30+的Caffe Layer，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：）

TensorFlow

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

Caffe

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

ONNX

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