mindspore.ops.Abs 
None 
mindspore.ops.ACos 
None 
mindspore.ops.Acosh 
None 
mindspore.ops.Add 
None 
mindspore.ops.AddN 
None 
mindspore.ops.ApproximateEqual 
None 
mindspore.ops.ArgMaxWithValue 
When the input_x is splited on the axis dimension, the distributed result may be inconsistent with that on the single machine. 
mindspore.ops.ArgMinWithValue 
When the input_x is splited on the axis dimension, the distributed result may be inconsistent with that on the single machine. 
mindspore.ops.Asin 
None 
mindspore.ops.Asinh 
None 
mindspore.ops.Assign 
None 
mindspore.ops.AssignAdd 
None 
mindspore.ops.AssignSub 
None 
mindspore.ops.Atan 
None 
mindspore.ops.Atan2 
None 
mindspore.ops.Atanh 
None 
mindspore.ops.AvgPool 
1. The data format only supports ‘NCHW’; 2. The shapes of output H/W dimension must be divisible by the split strategies of input H/W dimension; 3. If H/W is split: 1) If the kernel_size <= stride, the input slice size must be divisible by stride; 2) It does not support kernel_size > stride; 4. In auto_parallel mode, the strategy’s searching algorithm can not use “recursive_programming”. 
mindspore.ops.BatchMatMul 
transpore_a=True is not supported.

mindspore.ops.BatchNorm 
It does not support GPU. 
mindspore.ops.BesselI0e 
None 
mindspore.ops.BesselI1e 
None 
mindspore.ops.BiasAdd 
None 
mindspore.ops.BitwiseAnd 
None 
mindspore.ops.BitwiseOr 
None 
mindspore.ops.BitwiseXor 
None 
mindspore.ops.BoundingBoxEncode 
1. The first dimension of input (anchor_box) and input (groundtruth_box) can be split; 2. The sharding strategies of input (anchor_box) and input (groundtruth_box) must be the same. 
mindspore.ops.BroadcastTo 
None 
mindspore.ops.Cast 
The shard strategy is ignored in the Auto Parallel and Semi Auto Parallel mode. 
mindspore.ops.Cdist 
1. The strategy for ‘B’ dimension must be the same; 2.M dimension can’t be split. 
mindspore.ops.Ceil 
None 
mindspore.ops.Concat 
The input_x can’t be split into the dimension of axis, otherwise it’s inconsistent with the single machine in the mathematical logic. 
mindspore.ops.Conv2D 
1. The data format only supports ‘NCHW’; 2. If data exchange between adjacent nodes is involved, only Ascend is supported; 3. When the value of group is not 1, can not split Cin or Cout; 4. The last two dimensions of weight can not be split; 5. The output shape of H/W dimension must be divisible by the strategy of input H/W dimensions; 6. In valid mode: If H/W dimension is split: 1) When the kernel_size <= stride (kernel_size is dilation (kernel_size  1) + 1, the same below), the input‘s slice shape of H/W dimension must be divisible by stride; 2) It does not support that kernel_size > stride; 7. In the same/pad mode: If H/W dimension is split: 1) (Total input length including pad  kernel_size) must be divisible by stride; 2) (Output length stride  input length) must be divisible by strategy: 3) The length of data sent and received between adjacent cards must be greater than or equal to 0 and less than or equal to the slice size; 
mindspore.ops.Cos 
None 
mindspore.ops.Cosh 
None 
mindspore.ops.CropAndResize 
1. Sharding of the H/W dimension of input (x) and the second dimension of input (boxes) is not supported. 2. The shard strategy for the first dimension of inputs (boxes) and (box_index) must be the same. 
mindspore.ops.CumProd 
The axis dimension for input can’t be split. 
mindspore.ops.CumSum 
The same as CumProd. 
mindspore.ops.Div 
None 
mindspore.ops.DivNoNan 
None 
mindspore.ops.Dropout 
None 
mindspore.ops.Elu 
None 
mindspore.ops.EmbeddingLookup 
The same as Gather. 
mindspore.ops.Equal 
None 
mindspore.ops.Erf 
None 
mindspore.ops.Erfc 
None 
mindspore.ops.Erfinv 
None 
mindspore.ops.Exp 
None 
mindspore.ops.ExpandDims 
None 
mindspore.ops.Expm1 
None 
mindspore.ops.Floor 
None 
mindspore.ops.FloorDiv 
None 
mindspore.ops.FloorMod 
None 
mindspore.ops.Gamma 
1. Set the strategy for shape . e.g shape=(8, 16), the corresponding policy can be (2, 4); 2. The strategy for alpha and beta must be all1; 3. When the setting for shard is not all1 strategy, the result is inconsistent with standalone. 
mindspore.ops.Gather 
1. Uniform split: 1) Only support 1dim and 2dim parameters and the last dimension of the input_params should be 32byte aligned; 2) Scalar input_indices is not supported; 3) Repeated calculation is not supported when the parameters are split in the dimension of the axis; 4) Splitting input_indices and input_params at the same time is not supported; 5) When axis = 0 and the parameter is split in the dimension of axis, the output strategy can be configured. The legal output shard strategy is (indices_strategy, param_strategy[1:]) or ((indices_strategy[0]*param_strategy[0], indices_strategy[1:]), param_strategy[1:]) 2. Nonuniform split: 1) Only support axis = 0; 2) The nonuniform split only represents the nonuniformity of the 0th dimension of input_params, and the last dimension of the params slice should be aligned by 32 bytes; 3) The number of slices in the 0th dimension of input_params should be equal to that of the last dimension of input_indices; 4) Each dimension of input_params can be split, but input_indices can only split the last dimension, and does not support repeated calculations; 5) Input_indices shall meet the following requirements: the Tensor value of the next slice shall be greater than that of the previous slice. 
mindspore.ops.GatherD 
The dimension corresponding to dim cannot be segmented; In auto_parallel mode, the strategy’s searching algorithm can not use “recursive_programming”. 
mindspore.ops.GatherNd 
The first input can’t be split, and the last dimension of the second input can’t be split; In auto_parallel mode, the strategy’s searching algorithm can not use “recursive_programming”. 
mindspore.ops.GeLU 
None 
mindspore.ops.Greater 
None 
mindspore.ops.GreaterEqual 
None 
mindspore.ops.HShrink 
None 
mindspore.ops.HSigmoid 
None 
mindspore.ops.InplaceAdd 
The first dimension of x and input_v can’t be split. 
mindspore.ops.InplaceSub 
The same as InplaceAdd. 
mindspore.ops.InplaceUpdate 
The same as InplaceAdd. 
mindspore.ops.Inv 
None 
mindspore.ops.IOU 
The first dimension of the anchor_boxes and gt_boxes can be spilt. 
mindspore.ops.IsFinite 
None 
mindspore.ops.KLDivLoss 
None 
mindspore.ops.L2Loss 
None 
mindspore.ops.L2Normalize 
The input_x can’t be split into the dimension of axis, otherwise it’s inconsistent with the single machine in the mathematical logic. 
mindspore.ops.Lerp 
None 
mindspore.ops.Less 
None 
mindspore.ops.LessEqual 
None 
mindspore.ops.LinSpace 
You don’t need to configure strategy for start and end . You just need to pass in a strategy of length 1 whose value divisible into num . ｜ 
mindspore.ops.LogicalAnd 
None 
mindspore.ops.LogicalNot 
None 
mindspore.ops.LogicalOr 
None 
mindspore.ops.Log 
None 
mindspore.ops.Log1p 
None 
mindspore.ops.LogSoftmax 
The logits can’t be split into the dimension of axis, otherwise it’s inconsistent with the single machine in the mathematical logic. 
mindspore.ops.MaskedFill 
None 
mindspore.ops.MatMul 
1. transpose_a=True is not supported; 2. When transpose_b=True is set, the input’s split strategy must be in the form of ((A, B), (C, B)); 3. When transpose_b=False is set, the input’s split strategy must be in the form of ((A, B), (B, C)); 4. It is supported to set the output’s split strategy, the legal output’s split strategy is ((A, C),) or ((A * B, C),) 
mindspore.ops.Maximum 
None 
mindspore.ops.MaxPool 
1. The data format only supports ‘NCHW’; 2. The shapes of output H/W dimension must be divisible by the split strategies of input H/W dimension; 3. If H/W is split: 1) If the kernel_size <= stride, the input slice size must be divisible by stride; 2) It does not support kernel_size > stride; 4. In auto_parallel mode, the strategy’s searching algorithm can not use “recursive_programming”. 
mindspore.ops.Minimum 
None 
mindspore.ops.Mish 
None 
mindspore.ops.Mod 
None 
mindspore.ops.Mul 
None 
mindspore.ops.MulNoNan 
None 
mindspore.ops.Neg 
None 
mindspore.ops.NotEqual 
None 
mindspore.ops.OneHot 
Only support 1dim indices. Must configure strategy for the output and the first and second inputs. 
mindspore.ops.OnesLike 
None 
mindspore.ops.Pow 
None 
mindspore.ops.PReLU 
When the shape of weight is not [1], the shard strategy in channel dimension of input_x should be consistent with weight. 
mindspore.ops.RandomChoiceWithMask 
Only the all1 strategy is supported. 
mindspore.ops.RealDiv 
None 
mindspore.ops.Reciprocal 
None 
mindspore.ops.ReduceMax 
When the input_x is splited on the axis dimension, the distributed result may be inconsistent with that on the single machine. 
mindspore.ops.ReduceMin 
When the input_x is splited on the axis dimension, the distributed result may be inconsistent with that on the single machine. 
mindspore.ops.ReduceSum 
None 
mindspore.ops.ReduceMean 
None 
mindspore.ops.ReLU 
None 
mindspore.ops.ReLU6 
None 
mindspore.ops.Reshape 
Configuring shard strategy is not supported. In auto parallel mode, if multiple operators are followed by the reshape operator, different shard strategys are not allowed to be configured for these operators. 
mindspore.ops.ResizeBilinear 
Under GPU platform, can not split H or W dimension; Under Ascend platform, can not split H dimension, and the output shape of W dimension can be divided by the strategy. 
mindspore.ops.Rint 
None 
mindspore.ops.ResizeNearestNeighbor 
When align_corners=True is set, only the first dimension and the second dimension are supported to split. 
mindspore.ops.ROIAlign 
Sharding the H/W dimension of the input(features) and the second dimension of input(rois) is not supported. 
mindspore.ops.Round 
None 
mindspore.ops.Rsqrt 
None 
mindspore.ops.ScatterUpdate 
The first dimension of first input can not be split, the second input can not be split, and the first n dimensions (n is the dimension size of the second input) of the third input can not be split; In auto_parallel mode, the strategy’s searching algorithm can not use “recursive_programming”. 
mindspore.ops.Select 
In auto_parallel mode, the strategy’s searching algorithm can not use “recursive_programming”. 
mindspore.ops.SeLU 
None 
mindspore.ops.Sigmoid 
None 
mindspore.ops.SigmoidCrossEntropyWithLogits 
None 
mindspore.ops.Sign 
None 
mindspore.ops.Sin 
None 
mindspore.ops.Sinh 
None 
mindspore.ops.Softmax 
The logits can’t be split into the dimension of axis, otherwise it’s inconsistent with the single machine in the mathematical logic. 
mindspore.ops.SoftmaxCrossEntropyWithLogits 
The last dimension of logits and labels can’t be splited; Only supports using output[0]. 
mindspore.ops.Softplus 
None 
mindspore.ops.Softsign 
None 
mindspore.ops.SoftShrink 
None 
mindspore.ops.SparseGatherV2 
The same as Gather. 
mindspore.ops.Split 
The input_x can’t be split into the dimension of axis, otherwise it’s inconsistent with the single machine in the mathematical logic. 
mindspore.ops.Sqrt 
None 
mindspore.ops.Square 
None 
mindspore.ops.SquaredDifference 
None 
mindspore.ops.Squeeze 
None 
mindspore.ops.Stack 
None 
mindspore.ops.StridedSlice 
Only support mask with all 0 values; The dimension needs to be split should be all extracted; Split is supported when the strides of dimension is 1. 
mindspore.ops.Slice 
The dimension needs to be split should be all extracted. 
mindspore.ops.Sub 
None 
mindspore.ops.Tan 
None 
mindspore.ops.Tanh 
None 
mindspore.ops.Tile 
Only support configuring shard strategy for multiples. 
mindspore.ops.TopK 
The input_x can’t be split into the last dimension, otherwise it’s inconsistent with the single machine in the mathematical logic. 
mindspore.ops.Transpose 
None 
mindspore.ops.TruncateDiv 
None 
mindspore.ops.TruncateMod 
None 
mindspore.ops.Unique 
Only support the repeat calculate shard strategy (1,). 
mindspore.ops.UnsortedSegmentSum 
The shard of input_x and segment_ids must be the same as the dimension of segment_ids. 
mindspore.ops.UnsortedSegmentMin 
The shard of input_x and segment_ids must be the same as the dimension of segment_ids. Note that if the segment id i is missing, then the output[i] will be filled with the maximum of the input type. The user needs to mask the maximum value to avoid value overflow. The communication operation such as AllReudce will raise an Run Task Error due to overflow. 
mindspore.ops.UnsortedSegmentMax 
The shard of input_x and segment_ids must be the same as the dimension of segment_ids. Note that if the segment id i is missing, then the output[i] will be filled with the minimum of the input type. The user needs to mask the minimum value to avoid value overflow. The communication operation such as AllReudce will raise an Run Task Error due to overflow. 
mindspore.ops.Xdivy 
None 
mindspore.ops.Xlogy 
None 
mindspore.ops.ZerosLike 
None 