addConfig(layer, {DataConfigurator(ConfLayout::PLN)}, {DataConfigurator(ConfLayout::PLN)});
if (type == "caffe.ResampleParameter.NEAREST")
addConfig(layer, {DataConfigurator(blk_layout)}, {DataConfigurator(blk_layout)});
+
+ // WA to enable the implementation only for equal input and output precisions
+ for (auto &conf : confs) {
+ conf.inConfs[0].desc.setPrecision(conf.outConfs[0].desc.getPrecision());
+ }
} catch (InferenceEngine::details::InferenceEngineException &ex) {
errorMsg = ex.what();
}
ResponseDesc *resp) noexcept override {
const auto *src_data = inputs[0]->cbuffer().as<const float *>();
auto *dst_data = outputs[0]->buffer().as<float *>();
-#ifdef WIN32
+#ifdef _WIN32
#undef IN
#endif
const Layout &layout = inputs[0]->getTensorDesc().getLayout();