add chanel first format support for rand=3 Deconv to use amx fp16 kernel

liubo-intel · Oct 23, 2024 · bdf3b0a · bdf3b0a
1 parent a4b7f35
commit bdf3b0a
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Showing 2 changed files with 8 additions and 20 deletions.
diff --git a/src/plugins/intel_cpu/src/nodes/deconv.cpp b/src/plugins/intel_cpu/src/nodes/deconv.cpp
@@ -426,8 +426,12 @@ std::vector<memory::format_tag> Deconvolution::getAvailableFormatsForDims(const
     else if (dims.getRank() == 2)
         return {memory::format_tag::nc};
     else if (dims.getRank() == 3)
-        return {memory::format_tag::tnc, memory::format_tag::ntc,
-                memory::format_tag::ncw, memory::format_tag::nCw8c, memory::format_tag::nCw16c };
+        return {memory::format_tag::tnc,
+                memory::format_tag::ntc,
+                memory::format_tag::nwc,
+                memory::format_tag::ncw,
+                memory::format_tag::nCw8c,
+                memory::format_tag::nCw16c};
     else if (dims.getRank() == 4)
         return {memory::format_tag::nchw, memory::format_tag::nChw8c,
                 memory::format_tag::nChw16c, memory::format_tag::nhwc };
@@ -461,18 +465,8 @@ void Deconvolution::getSupportedDescriptors() {
     outputDataType = DnnlExtensionUtils::ElementTypeToDataType(outPrecision);
     if (inputDataType == memory::data_type::bf16 || outputDataType == memory::data_type::bf16)
        inputDataType = outputDataType = memory::data_type::bf16;
-
-    if (inputDataType == memory::data_type::f16 || outputDataType == memory::data_type::f16) {
-        // TODO: remove this limitation after adding support for f16 in oneDNN MFDNN-12580
-        if (std::any_of(deconvAttrs.stride.begin(), deconvAttrs.stride.end(), [](ptrdiff_t stride) {
-                return stride != 1;
-            })) {
-            inputDataType = outputDataType = memory::data_type::f32;
-        } else {
-            inputDataType = outputDataType = memory::data_type::f16;
-        }
-    }
-
+    if (inputDataType == memory::data_type::f16 || outputDataType == memory::data_type::f16)
+       inputDataType = outputDataType = memory::data_type::f16;
     if (!fusedWith.empty()) {
         outputDataType = DnnlExtensionUtils::ElementTypeToDataType(fusedWith[fusedWith.size() - 1]->getOriginalOutputPrecisionAtPort(0));
     }

diff --git a/src/plugins/intel_cpu/src/nodes/executors/acl/acl_convert.cpp b/src/plugins/intel_cpu/src/nodes/executors/acl/acl_convert.cpp
@@ -92,12 +92,6 @@ bool ACLConvertExecutorBuilder::isSupported(const ConvertParams& convertParams,
             DEBUG_LOG("NECopy does not support source precision: ", convertParams.srcPrc.to_string());
             return false;
         }
-        auto srcDataLayout = getAclDataLayoutByMemoryDesc(srcDesc);
-        auto dstDataLayout = getAclDataLayoutByMemoryDesc(dstDesc);
-        if (srcDataLayout == DataLayout::UNKNOWN || dstDataLayout == DataLayout::UNKNOWN) {
-            DEBUG_LOG("NECopy does not support source or destination layout");
-            return false;
-        }
         if ((convertParams.srcPrc == ov::element::i8 && !one_of(convertParams.dstPrc,
                                                               ov::element::i16,
                                                               ov::element::i32,