eric-haibin-lin commented on a change in pull request #10208: [MXNET-117]
Sparse operator broadcast_mul/div(csr, dense) = csr
URL: https://github.com/apache/incubator-mxnet/pull/10208#discussion_r178997634
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File path: src/operator/tensor/elemwise_binary_broadcast_op.h
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@@ -185,6 +230,84 @@ void BinaryBroadcastCompute(const nnvm::NodeAttrs& attrs,
}
}
+template<typename xpu, typename OP>
+void BinaryBroadcastCsrDnsCsrImpl(const OpContext& ctx,
+ const NDArray& csr,
+ const NDArray& dns,
+ const OpReqType req,
+ const NDArray& output) {
+ using namespace mshadow;
+ using namespace mxnet_op;
+ using namespace csr;
+ CHECK(req != kAddTo && req != kWriteInplace);
+ mshadow::Stream<xpu> *s = ctx.get_stream<xpu>();
+ bool col_vec;
+ if (dns.shape().ndim() == 1) {
+ col_vec = false;
+ } else {
+ col_vec = (dns.shape()[0] == csr.shape()[0])? true : false;
+ }
+
+ if (csr.storage_initialized()) {
+ const nnvm::dim_t nnz = csr.storage_shape()[0];
+ const nnvm::dim_t num_rows = output.shape()[0];
+ output.CheckAndAlloc({Shape1(num_rows + 1), Shape1(nnz)});
+
+ MSHADOW_TYPE_SWITCH(output.dtype(), DType, {
+ MSHADOW_IDX_TYPE_SWITCH(output.aux_type(kIdx), CType, {
+ MSHADOW_IDX_TYPE_SWITCH(output.aux_type(kIndPtr), RType, {
+ MXNET_ASSIGN_REQ_SWITCH(req, req_type, {
+ Kernel<csr_dns_csr_broadcast_kernel<req_type, OP>, xpu>::Launch(
+ s, num_rows, csr.data().dptr<DType>(),
csr.aux_data(kIdx).dptr<CType>(),
+ csr.aux_data(kIndPtr).dptr<RType>(), dns.data().dptr<DType>(),
+ output.data().dptr<DType>(), csr.shape()[1], col_vec);
+ Copy(output.aux_data(kIdx).FlatTo1D<xpu, CType>(),
+ csr.aux_data(kIdx).FlatTo1D<xpu, CType>());
+ Copy(output.aux_data(kIndPtr).FlatTo1D<xpu, RType>(),
+ csr.aux_data(kIndPtr).FlatTo1D<xpu, RType>());
+ });
+ });
+ });
+ });
+ // If input csr is an empty matrix, fill zeros and return
+ } else {
+ FillZerosCsrImpl(s, output);
+ return;
+ }
+}
+
+template<typename xpu, typename OP>
+void BinaryBroadcastComputeCsrEx(const nnvm::NodeAttrs& attrs,
+ const OpContext& ctx,
+ const std::vector<NDArray>& inputs,
+ const std::vector<OpReqType>& req,
+ const std::vector<NDArray>& outputs) {
+ CHECK_EQ(inputs.size(), 2U);
+ CHECK_EQ(outputs.size(), 1U);
+ CHECK_EQ(req.size(), 1U);
+ CHECK_LE(inputs[1].shape().ndim(), 2U) << "input dense matrix should have
less than 2 dimensions";
Review comment:
`less than` -> `less than or equal`?
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