sshearn opened a new issue #16620: Incompatible input shape URL: https://github.com/apache/incubator-mxnet/issues/16620 ## Description I'm using scala / java 1.5.1 mxnet-full_2.11-osx-x86_64-cpu. I believe I'm correctly specifying my input shape as (1, 0, 1, 5961). But I'm getting: Incompatible input shape: expected [1,-1,1,1], got [1,-1,1,64] . I believe it has something to do with my number of factors which is 64. Here's my symbols json: ```{ "nodes": [ { "op": "null", "name": "data", "attrs": {"__storage_type__": "2"}, "inputs": [] }, { "op": "null", "name": "w1_weight", "attrs": { "__init__": "[\"normal\", {\"sigma\": 0.01}]", "__lr_mult__": "0.001", "__shape__": "(5961, 1)", "__storage_type__": "1", "__wd_mult__": "0.001" }, "inputs": [] }, { "op": "dot", "name": "dot0", "inputs": [[0, 0, 0], [1, 0, 0]] }, { "op": "null", "name": "w0_weight", "attrs": { "__init__": "[\"normal\", {\"sigma\": 0.01}]", "__lr_mult__": "0.01", "__shape__": "(1,)", "__wd_mult__": "0.01" }, "inputs": [] }, { "op": "broadcast_add", "name": "broadcast_plus0", "inputs": [[2, 0, 0], [3, 0, 0]] }, { "op": "null", "name": "v", "attrs": { "__init__": "[\"normal\", {\"sigma\": 0.001}]", "__lr_mult__": "0.0001", "__shape__": "(5961, 64)", "__storage_type__": "1", "__wd_mult__": "1e-05" }, "inputs": [] }, { "op": "dot", "name": "dot2", "inputs": [[0, 0, 0], [5, 0, 0]] }, { "op": "square", "name": "Square", "inputs": [[6, 0, 0]] }, { "op": "_mul_scalar", "name": "_mulscalar0", "attrs": {"scalar": "0.5"}, "inputs": [[7, 0, 0]] }, { "op": "Concat", "name": "concat0", "attrs": { "dim": "1", "num_args": "2" }, "inputs": [[4, 0, 0], [8, 0, 0]] }, { "op": "sum", "name": "sum0", "attrs": { "axis": "1", "keepdims": "True" }, "inputs": [[9, 0, 0]] }, { "op": "square", "name": "x_square", "inputs": [[0, 0, 0]] }, { "op": "_square_sum", "name": "_square_sum0", "attrs": { "axis": "1", "keepdims": "True" }, "inputs": [[5, 0, 0]] }, { "op": "dot", "name": "dot1", "inputs": [[11, 0, 0], [12, 0, 0]] }, { "op": "negative", "name": "negative0", "inputs": [[13, 0, 0]] }, { "op": "_mul_scalar", "name": "_mulscalar1", "attrs": {"scalar": "0.5"}, "inputs": [[14, 0, 0]] }, { "op": "elemwise_add", "name": "Final_Summation", "inputs": [[10, 0, 0], [15, 0, 0]] }, { "op": "null", "name": "out_label", "inputs": [] }, { "op": "LinearRegressionOutput", "name": "out", "inputs": [[16, 0, 0], [17, 0, 0]] } ], "arg_nodes": [0, 1, 3, 5, 17], "node_row_ptr": [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19 ], "heads": [[18, 0, 0]], "attrs": {"mxnet_version": ["int", 10100]} } ``` And here's the full output: ``` 22:36:10.674 [org.apache.mxnet.infer.MXNetThreadPoolHandler-0] INFO MXNetJVM::tryLoadLibraryOS - Try loading mxnet-scala from native path. 22:36:10.678 [org.apache.mxnet.infer.MXNetThreadPoolHandler-0] WARN MXNetJVM::<init> - MXNet Scala native library not found in path. Copying native library from the archive. Consider installing the library somewhere in the path (for Windows: PATH, for Linux: LD_LIBRARY_PATH), or specifying by Java cmd option -Djava.library.path=[lib path]. 22:36:10.679 [org.apache.mxnet.infer.MXNetThreadPoolHandler-0] WARN MXNetJVM::<init> - LD_LIBRARY_PATH=null 22:36:10.680 [org.apache.mxnet.infer.MXNetThreadPoolHandler-0] WARN MXNetJVM::<init> - java.library.path=/Users/shearn/Library/Java/Extensions:/Library/Java/Extensions:/Network/Library/Java/Extensions:/System/Library/Java/Extensions:/usr/lib/java:. 22:36:10.689 [org.apache.mxnet.infer.MXNetThreadPoolHandler-0] INFO org.apache.mxnet.util.NativeLibraryLoader::loadLibrary - Replaced .dylib with .jnilib [22:36:11] src/nnvm/legacy_json_util.cc:209: Loading symbol saved by previous version v1.1.0. Attempting to upgrade... [22:36:11] src/nnvm/legacy_json_util.cc:217: Symbol successfully upgraded! 22:36:11.880 [org.apache.mxnet.infer.MXNetThreadPoolHandler-0] WARN org.apache.mxnet.DataDesc::getBatchAxis - Found Undefined Layout, will use default index 0 for batch axis Exception in thread "main" org.apache.mxnet.MXNetError: Error in operator concat0: [22:36:11] src/operator/nn/concat.cc:67: Check failed: shape_assign(&(*in_shape)[i], dshape): Incompatible input shape: expected [1,-1,1,1], got [1,-1,1,64] Stack trace: [bt] (0) 1 libmxnet.so 0x000000012d540509 mxnet::op::MKLDNNActivationBackward(nnvm::NodeAttrs const&, mxnet::OpContext const&, mxnet::NDArray const&, mxnet::NDArray const&, mxnet::OpReqType const&, mxnet::NDArray const&) + 9113 [bt] (1) 2 libmxnet.so 0x000000012d91a129 mxnet::op::SupportMKLDNNConcat(std::__1::vector<mxnet::NDArray, std::__1::allocator<mxnet::NDArray> > const&) + 7977 [bt] (2) 3 libmxnet.so 0x000000012edaad39 std::__1::__tree<std::__1::__value_type<unsigned long, mxnet::NDArray>, std::__1::__map_value_compare<unsigned long, std::__1::__value_type<unsigned long, mxnet::NDArray>, std::__1::less<unsigned long>, true>, std::__1::allocator<std::__1::__value_type<unsigned long, mxnet::NDArray> > >::erase(std::__1::__tree_const_iterator<std::__1::__value_type<unsigned long, mxnet::NDArray>, std::__1::__tree_node<std::__1::__value_type<unsigned long, mxnet::NDArray>, void*>*, long>) + 50089 [bt] (3) 4 libmxnet.so 0x000000012eda191a std::__1::__tree<std::__1::__value_type<unsigned long, mxnet::NDArray>, std::__1::__map_value_compare<unsigned long, std::__1::__value_type<unsigned long, mxnet::NDArray>, std::__1::less<unsigned long>, true>, std::__1::allocator<std::__1::__value_type<unsigned long, mxnet::NDArray> > >::erase(std::__1::__tree_const_iterator<std::__1::__value_type<unsigned long, mxnet::NDArray>, std::__1::__tree_node<std::__1::__value_type<unsigned long, mxnet::NDArray>, void*>*, long>) + 12170 [bt] (4) 5 libmxnet.so 0x000000012ed30616 MXSymbolInferShapeEx + 2422 [bt] (5) 6 mxnet-scala 0x000000012cda054d Java_org_apache_mxnet_LibInfo_mxSymbolCreateFromFile + 957 [bt] (6) 7 mxnet-scala 0x000000012cda08b3 Java_org_apache_mxnet_LibInfo_mxSymbolInferShape + 195 [bt] (7) 8 ??? 0x0000000112ac8667 0x0 + 4608263783 at org.apache.mxnet.Base$.checkCall(Base.scala:111) at org.apache.mxnet.Symbol.inferShapeImpl(Symbol.scala:323) at org.apache.mxnet.Symbol.inferShape(Symbol.scala:291) at org.apache.mxnet.Symbol.inferShape(Symbol.scala:286) at org.apache.mxnet.module.DataParallelExecutorGroup.org$apache$mxnet$module$DataParallelExecutorGroup$$bindIthExec(DataParallelExecutorGroup.scala:637) at org.apache.mxnet.module.DataParallelExecutorGroup$$anonfun$bindExec$2.apply(DataParallelExecutorGroup.scala:384) at org.apache.mxnet.module.DataParallelExecutorGroup$$anonfun$bindExec$2.apply(DataParallelExecutorGroup.scala:383) at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234) at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234) at scala.collection.immutable.Range.foreach(Range.scala:160) at scala.collection.TraversableLike$class.map(TraversableLike.scala:234) at scala.collection.AbstractTraversable.map(Traversable.scala:104) at org.apache.mxnet.module.DataParallelExecutorGroup.bindExec(DataParallelExecutorGroup.scala:383) at org.apache.mxnet.module.DataParallelExecutorGroup.<init>(DataParallelExecutorGroup.scala:323) at org.apache.mxnet.module.DataParallelExecutorGroup$Builder.build(DataParallelExecutorGroup.scala:225) at org.apache.mxnet.module.Module.bind(Module.scala:285) at org.apache.mxnet.infer.Predictor$$anonfun$loadModule$1.apply$mcV$sp(Predictor.scala:258) at org.apache.mxnet.infer.Predictor$$anonfun$loadModule$1.apply(Predictor.scala:258) at org.apache.mxnet.infer.Predictor$$anonfun$loadModule$1.apply(Predictor.scala:258) at org.apache.mxnet.infer.MXNetThreadPoolHandler$$anon$4.call(MXNetHandler.scala:83) at java.util.concurrent.FutureTask.run(FutureTask.java:266) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748) ```
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