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Posted to commits@mxnet.apache.org by re...@apache.org on 2019/03/26 04:08:57 UTC

[incubator-mxnet] branch numpy updated: Fix a bug to pass the test in test_contrib_rnn (#14520)

This is an automated email from the ASF dual-hosted git repository.

reminisce pushed a commit to branch numpy
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git


The following commit(s) were added to refs/heads/numpy by this push:
     new 38f2e06  Fix a bug to pass the test in test_contrib_rnn (#14520)
38f2e06 is described below

commit 38f2e069e6c28eead4aaa0ca116b770a15989e3b
Author: Da Zheng <zh...@gmail.com>
AuthorDate: Mon Mar 25 21:08:41 2019 -0700

    Fix a bug to pass the test in test_contrib_rnn (#14520)
    
    * fix.
    
    * remove type conversion.
    
    * remove type cast.
---
 src/common/utils.h                       | 1 -
 src/ndarray/ndarray_function.cc          | 6 ++++--
 src/operator/nn/mkldnn/mkldnn_base-inl.h | 2 +-
 3 files changed, 5 insertions(+), 4 deletions(-)

diff --git a/src/common/utils.h b/src/common/utils.h
index f3df2e1..4843d7e 100644
--- a/src/common/utils.h
+++ b/src/common/utils.h
@@ -752,7 +752,6 @@ inline void ConvertToNumpyShape(mxnet::TShape* shape) {
     *shape = mxnet::TShape();  // unknown shape ndim = -1
   } else {
     for (int j = 0; j < shape->ndim(); ++j) {
-      CHECK_GE((*shape)[j], 0) << "Legacy shape cannot have dim size < 0";
       if ((*shape)[j] == 0) {  // legacy shape dim_size = 0 means unknown
         (*shape)[j] = -1;  // unknown dim size = -1
       }
diff --git a/src/ndarray/ndarray_function.cc b/src/ndarray/ndarray_function.cc
index a613d5a..8f72bc2 100644
--- a/src/ndarray/ndarray_function.cc
+++ b/src/ndarray/ndarray_function.cc
@@ -210,8 +210,6 @@ void ElementwiseSumContainsDnsImpl(mshadow::Stream<cpu>* s,
     Kernel<set_zero, cpu>::Launch(s, out_data.Size(), out_data.dptr<DType>());
     for (size_t i = 0; i < nds.size(); ++i) {
       const NDArray& nd = nds[i];
-      const nnvm::dim_t num_rows = nd.shape()[0];
-      const nnvm::dim_t num_cols = nd.shape()[1];
       const TBlob& nd_data = nd.data();
 
       if (i == 0) {
@@ -234,6 +232,8 @@ void ElementwiseSumContainsDnsImpl(mshadow::Stream<cpu>* s,
         case kCSRStorage: {
           const TBlob& nd_indices = nd.aux_data(csr::kIdx);
           const TBlob& nd_indptr = nd.aux_data(csr::kIndPtr);
+          const nnvm::dim_t num_rows = nd.shape()[0];
+          const nnvm::dim_t num_cols = nd.shape()[1];
           MSHADOW_IDX_TYPE_SWITCH(nd_indices.type_flag_, IType, {  // indices type
             MSHADOW_IDX_TYPE_SWITCH(nd_indptr.type_flag_, CType, {  // indptr type
               if (nd.storage_initialized()) {
@@ -248,6 +248,8 @@ void ElementwiseSumContainsDnsImpl(mshadow::Stream<cpu>* s,
         }
         case kRowSparseStorage: {
           const TBlob& nd_indices = nd.aux_data(rowsparse::kIdx);
+          const nnvm::dim_t num_rows = nd.shape()[0];
+          const nnvm::dim_t num_cols = nd.shape()[1];
           MSHADOW_IDX_TYPE_SWITCH(nd_indices.type_flag_, IType, {  // indices type
             if (nd.storage_initialized()) {
               const nnvm::dim_t nz_rows = nd_indices.Size();
diff --git a/src/operator/nn/mkldnn/mkldnn_base-inl.h b/src/operator/nn/mkldnn/mkldnn_base-inl.h
index 0a89c0f..294723b 100644
--- a/src/operator/nn/mkldnn/mkldnn_base-inl.h
+++ b/src/operator/nn/mkldnn/mkldnn_base-inl.h
@@ -462,7 +462,7 @@ mkldnn::memory::primitive_desc GetPrimitiveDesc(mkldnn::memory::primitive_desc p
                                                 mkldnn_memory_format_t format);
 
 inline bool same_shape(const mxnet::TShape &shape, const mkldnn_dims_t dims, int ndims) {
-  if (shape.ndim() != (size_t)ndims)
+  if (shape.ndim() != ndims)
     return false;
   for (int i = 0; i < ndims; i++)
     if (shape[i] != dims[i])