piotrwolinski-intel commented on a change in pull request #20825:
URL: https://github.com/apache/incubator-mxnet/pull/20825#discussion_r806644597
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File path: src/operator/contrib/adaptive_avg_pooling.cc
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@@ -238,18 +277,45 @@ void AdaptiveAvgPoolComputeExCPU(const nnvm::NodeAttrs&
attrs,
oneDNN doesn't support adaptive pooling.
Fallback is needed when padding is not equal 0;
*/
- const PoolingParam& param = nnvm::get<PoolingParam>(attrs.parsed);
if (SupportDNNL(inputs[0]) && SupportDNNLAveragePooling(inputs[0],
outputs[0])) {
- const NDArray* workspace = nullptr;
DNNL_OPCHECK_INIT(false, 1, inputs, outputs);
- DNNLPoolingCompute(ctx, param, inputs[0], req[0], outputs[0], workspace,
true);
+ DNNLRun(DNNLPoolingCompute, attrs, ctx, inputs, req, outputs);
DNNL_OPCHECK_RUN(PoolingCompute<cpu>, attrs, ctx, inputs, req, outputs);
return;
}
FallBackCompute(AdaptiveAvgPoolOpForward<cpu>, attrs, ctx, inputs, req,
outputs);
}
#endif
+inline static bool AdaptivePoolingStorageType(const nnvm::NodeAttrs& attrs,
+ const int dev_mask,
+ DispatchMode* dispatch_mode,
+ std::vector<int>* in_attrs,
+ std::vector<int>* out_attrs) {
+ CHECK_EQ(in_attrs->size(), 1);
+ bool dispatched = false;
+#if MXNET_USE_ONEDNN == 1
+ if (!dispatched) {
+ dispatched = DNNLStorageType(attrs, dev_mask, true, dispatch_mode,
in_attrs, out_attrs);
+ }
+ if (!DNNLEnvSet()) {
+ *dispatch_mode = DispatchMode::kFComputeFallback;
+ }
+#else
+ for (int& v : *in_attrs)
+ if (v == -1)
+ v = kDefaultStorage;
+ if (!dispatched && common::ContainsOnlyStorage(*in_attrs, kDefaultStorage)) {
+ dispatched =
+ storage_type_assign(out_attrs, kDefaultStorage, dispatch_mode,
DispatchMode::kFCompute);
+ }
+ if (!dispatched) {
+ dispatched = dispatch_fallback(out_attrs, dispatch_mode);
+ }
+#endif
+ return dispatched;
+}
Review comment:
As I checked earlier I thought it was necessary to do it this way, but
from what I've checked now it should be okay to make it similar way as in
pooling for instance.
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