[GitHub] [incubator-mxnet] leezu commented on issue #19286: infer shape error in hybridized block for zero-size input

[GitBox <gi...@apache.org>]

leezu commented on issue #19286:
URL: https://github.com/apache/incubator-mxnet/issues/19286#issuecomment-703816274


   This bug is related to legacy (non-numpy) reshape operator. Reshape with `0` implies "copy this dimension from input".
   
   We can see that all shapes are correct prior to infer_shape pass:
   
   ```
   frame #6: 0x00007fff3bd1cb8b libmxnet.so`mxnet::imperative::SetShapeType(ctx=0x00007fffffff8f18, attrs=0x00007fffffff97a8, inputs=size=1, outputs=size=1, dispatch_mode=0x00007fffffff8f24) at imperative_utils.h:208:26
      205        common::ConvertToNumpyShape(&in_shapes);
      206        common::ConvertToNumpyShape(&out_shapes);
      207      }
   -> 208      const bool success = infershape[attrs.op](attrs, &in_shapes, &out_shapes);
      209      if (!success) {
      210        std::stringstream os;
      211        os << "Operator " << attrs.op->name << " inferring shapes failed.\n";
   (lldb) parray 5 in_shapes[0].data_heap_
   (long *) $15 = 0x0000555555f45700 {
     (long) [0] = 1
     (long) [1] = 2
     (long) [2] = 4
     (long) [3] = 0
     (long) [4] = 128
   }
   (lldb) p out_shapes                                                                                                                                                                    (mxnet::ShapeVector) $16 = size=1 {
     [0] = {
       mxnet::Tuple<long> = {
         ndim_ = 4
         num_heap_allocated_ = 0
         data_stack_ = ([0] = 2, [1] = 4, [2] = 0, [3] = 128)
         data_heap_ = 0x0000000000000000
       }
     }
   }
   ```
   
   But after infer_shape, `0` is replaced by `4`.
   
   ```
   frame #1: 0x00007fff4968c1be libmxnet.so`mxnet::op::ReshapeShape(attrs=0x00007fffffff97a8, in_attrs=0x00005555569cbb68, out_attrs=0x00005555569cbb80) at matrix_op-inl.h:235:3
      232      << "Target: " << oshape
      233      << "\nSource: " << dshape;
      234  #endif
   -> 235    SHAPE_ASSIGN_CHECK(*out_attrs, 0, oshape);
      236    return ReverseReshapeInferShape(&(*in_attrs)[0], (*out_attrs)[0]);
      237  }
      238
   (lldb) p oshape
   (mxnet::TShape) $17 = {
     mxnet::Tuple<long> = {
       ndim_ = 4
       num_heap_allocated_ = 0
       data_stack_ = ([0] = 2, [1] = 4, [2] = 4, [3] = 128)
       data_heap_ = 0x0000000000000000
     }
   }
   ```
   
   https://github.com/apache/incubator-mxnet/blob/f732530c8e1f8dcc11134e935430e3793ddbf4c8/src/operator/tensor/matrix_op-inl.h#L194-L237
   
   The root cause is that `MXNDArrayAt`, `MXNDArrayReshape` and `MXNDArraySlice` do not sufficiently distinguish between the numpy and non-numpy mode and always record legacy operators.
   
   We need to update the recording step to record numpy / legacy operator based on if numpy / legacy mode is enabled:
   
    https://github.com/apache/incubator-mxnet/blob/72eff9b66ecc683c3e7f9ad2c0ba69efa8dd423b/src/ndarray/ndarray.cc#L302-L308 


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