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Fix sparse L2Norm's fallback regression #17146

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Fix sparse L2Norm's fallback regression #17146

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92f18b8
fix sparse L2Norm's fallback regression
haojin2 Dec 23, 2019
c6d1f02
fix numpy version problem
haojin2 Dec 25, 2019
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2 changes: 1 addition & 1 deletion ci/docker/install/requirements
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Expand Up @@ -26,7 +26,7 @@ h5py==2.8.0rc1
mock==2.0.0
nose==1.3.7
nose-timer==0.7.3
numpy>1.16.0,<2.0.0
numpy>1.16.0,<1.18.0
pylint==2.3.1; python_version >= '3.0'
requests<2.19.0,>=2.18.4
scipy==1.0.1
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2 changes: 1 addition & 1 deletion src/operator/tensor/broadcast_reduce_norm_value.cc
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Expand Up @@ -40,7 +40,7 @@ void L2NormComputeEx<cpu>(const nnvm::NodeAttrs& attrs,
const NormParam& param = nnvm::get<NormParam>(attrs.parsed);
mshadow::Stream<cpu>* s = ctx.get_stream<cpu>();
const NDArrayStorageType istype = inputs[0].storage_type();
const mxnet::TShape axis = param.axis.has_value() ? param.axis.value() : mxnet::TShape();
const mxnet::TShape axis = param.axis.has_value() ? param.axis.value() : mxnet::TShape(0, -1);
if ((istype == kRowSparseStorage || istype == kCSRStorage) && axis.ndim() == 0 &&
param.ord == 2) {
// l2 norm on the entire array
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2 changes: 1 addition & 1 deletion src/operator/tensor/broadcast_reduce_norm_value.cu
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Expand Up @@ -39,7 +39,7 @@ void L2NormComputeEx<gpu>(const nnvm::NodeAttrs& attrs,
const NormParam& param = nnvm::get<NormParam>(attrs.parsed);
mshadow::Stream<gpu>* s = ctx.get_stream<gpu>();
const NDArrayStorageType istype = inputs[0].storage_type();
const mxnet::TShape axis = param.axis.has_value() ? param.axis.value() : mxnet::TShape();
const mxnet::TShape axis = param.axis.has_value() ? param.axis.value() : mxnet::TShape(0, -1);
if ((istype == kRowSparseStorage || istype == kCSRStorage) && axis.ndim() == 0 &&
param.ord == 2) {
// l2 norm on the entire array
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2 changes: 1 addition & 1 deletion src/operator/tensor/broadcast_reduce_op.h
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Expand Up @@ -1152,7 +1152,7 @@ inline bool LpNormStorageType(const nnvm::NodeAttrs& attrs,
DispatchMode::kFCompute);
}
if (param.ord == 2) {
const mxnet::TShape axis = param.axis.has_value() ? param.axis.value() : mxnet::TShape();
const mxnet::TShape axis = param.axis.has_value() ? param.axis.value() : mxnet::TShape(0, -1);
if (!dispatched && (in_stype == kRowSparseStorage || in_stype == kCSRStorage) &&
axis.ndim() == 0 && param.ord == 2) {
// l2 norm: rsp/csr, axis = () -> dns
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