add warn info for op not converted

mindinsight/mindconverter/config.py

@@ -391,8 +391,71 @@ ALL_UNSUPPORTED = NN_UNSUPPORTED + F_UNSUPPORTED + TORCH_DOT_UNSUPPORTED + TENSO
 
 UNSUPPORTED_WARN_INFOS = {
     "nn.AdaptiveAvgPool2d": "maybe could convert to P.ReduceMean",
+    "nn.AvgPool1d": "maybe could convert to nn.AvgPool1d",
+    "nn.ConvTranspose2d": "maybe could convert to nn.Conv2dTranspose",
+    "nn.CrossEntropyLoss": "maybe could convert to nn.SoftmaxCrossEntropyWithLogits",
+    "nn.Embedding": "maybe could convert to nn.Embedding",
+    "nn.GroupNorm": "maybe could convert to nn.GroupNorm",
+    "nn.MSELoss": "maybe could convert to nn.MSELoss",
+    "nn.LSTM": "maybe could convert to nn.LSTM",
+    "nn.LSTMCell": "maybe could convert to nn.LSTMCell",
+    "nn.ModuleList": "maybe could convert to nn.CellList",
+    "nn.SmoothL1Loss": "maybe could convert to nn.SmoothL1Loss",
+    "nn.Tanh": "maybe could convert to nn.Tanh",
+    "nn.Upsample": "maybe could convert to P.ResizeBilinear",
+    "nn.L1Loss": "maybe could convert to nn.L1Loss",
+    "nn.Parameter": "maybe could convert to mindspore.Parameter",
+    "nn.ParameterList": "maybe could convert to mindspore.ParameterTuple",
+    "nn.Unfold": "maybe could convert to nn.Unfold",
+    "nn.PixelShuffle": "maybe could convert to P.DepthToSpace",
     "F.adaptive_avg_pool2d": "maybe could convert to P.ReduceMean",
+    "F.conv2d": "maybe could convert to mindspore.ops.operations.Conv2D",
     "F.dropout": "please use nn.Dropout in __init__()",
+    "F.interpolate": "maybe could convert to P.ResizeBilinear",
+    "torch.bmm": "maybe could convert to P.BatchMatMul",
+    "torch.cumsum": "maybe could convert to P.CumSum",
+    "F.relu": "maybe could convert to P.ReLU",
+    "F.pad": "maybe could convert to P.Pad",
+    "F.softmax": "maybe could convert to P.Softmax",
+    "torch.clamp": "maybe could convert to mindspore.ops.composite.clip_by_value",
+    "torch.eq": "maybe could convert to P.Equal",
+    "torch.load": "maybe could convert to mindspore.train.serialization.load_checkpoint",
+    "torch.matmul": "maybe could convert to P.MatMul",
     "torch.max": "try to use P.ArgMaxWithValue, notice that two values are returned by P.ArgMaxWithValue",
-    "torch.min": "try to use P.ArgMinWithValue, notice that two values are returned by P.ArgMinWithValue"
+    "torch.mean": "maybe could convert to P.ReduceMean",
+    "torch.min": "try to use P.ArgMinWithValue, notice that two values are returned by P.ArgMinWithValue",
+    "torch.mm": "maybe could convert to P.MatMul",
+    "torch.mul": "maybe could convert to P.Mul",
+    "torch.norm": "maybe could convert to nn.Norm",
+    "torch.numel": "maybe could convert to P.Size",
+    "F.one_hot": "maybe could convert to P.OneHot",
+    "torch.ones_like": "maybe could convert to P.OnesLike",
+    "torch.randn": "maybe could convert to P.TruncatedNormal",
+    "torch.round": "maybe could convert to P.Round",
+    "torch.save": "maybe could convert to mindspore.train.serialization.save_checkpoint",
+    "torch.sigmoid": "maybe could convert to P.Sigmoid",
+    "torch.split": "maybe could convert to P.Split",
+    "torch.squeeze": "maybe could convert to P.Squeeze",
+    "torch.stack": "maybe could convert to P.Pack",
+    "torch.sum": "maybe could convert to mindspore.ops.operations.ReduceSum",
+    "torch.tanh": "maybe could convert to mindspore.ops.operations.Tanh",
+    "torch.tensor": "maybe could convert to mindspore.Tensor",
+    "torch.transpose": "maybe could convert to P.Transpose",
+    "torch.unsqueeze": "maybe could convert to P.ExpandDims",
+    "torch.zeros_like": "maybe could convert to P.ZerosLike",
+    ".chunk": "maybe could convert to P.Split",
+    ".fill_": "maybe could convert to P.Fill",
+    ".float": "maybe could convert to P.Cast",
+    ".mm": "maybe could convert to P.MatMul",
+    "mul": "maybe could convert to P.Mul",
+    ".pow": "maybe could convert to P.Pow",
+    ".round": "maybe could convert to P.Round",
+    ".scatter": "maybe could convert to P.ScatterNd",
+    "sigmoid": "maybe could convert to nn.Sigmoid",
+    ".sign": "maybe could convert to P.Sign",
+    ".sqrt": "maybe could convert to P.Sqrt",
+    ".sub": "maybe could convert to P.Sub",
+    ".transpose": "maybe could convert to P.Transpose",
+    ".unsqueeze": "maybe could convert to P.ExpandDims",
+    ".zero_": "maybe could convert to P.ZerosLike",
 }