return false;
}
- std::vector<IndexExpr> oshape({dshape[0], dshape[1], dshape[2], dshape[3]});
+ std::vector<IndexExpr> oshape;
+ for (const auto& e : dshape) {
+ oshape.push_back(e);
+ }
+
if (param->ceil_mode) {
oshape[hidx] = ((dshape[hidx] + pad_h - param->pool_size[0] +
param->strides[0] - 1) / param->strides[0]) + 1;
.set_support_level(3)
.add_type_rel("Cast", CastRel)
.set_attr<FTVMCompute>("FTVMCompute", CastCompute)
-.set_attr<TOpPattern>("TOpPattern", kElemWise);
+.set_attr<TOpPattern>("TOpPattern", kElemWise)
+.set_attr<FInferCorrectLayout>("FInferCorrectLayout", ElemwiseArbitraryLayout);
// relay.expand_dims
TVM_REGISTER_NODE_TYPE(ExpandDimsAttrs);
# a useless tuple, which will be eliminated
y = relay.Tuple([y])[0]
y = relay.nn.relu(y)
+ y = relay.nn.max_pool2d(y, pool_size=(2, 2))
+ y = relay.cast(y, 'int32')
y = relay.nn.batch_flatten(y)
y = relay.Function(free_vars(y), y)
return y
y = relay.add(y, b)
y = relay.nn.relu(y)
+ y = relay.nn.max_pool2d(y, pool_size=(2, 2), layout="NCHW16c")
+ y = relay.cast(y, 'int32')
y = relay.layout_transform(y, "NCHW16c", "NCHW")
y = relay.nn.batch_flatten(y)
y = relay.Function(free_vars(y), y)