Create hashcode for operator parameters properly.

src/operator/nn/activation-inl.h

@@ -65,13 +65,22 @@ struct ActivationParam : public dmlc::Parameter<ActivationParam> {
   bool operator==(const ActivationParam& other) const {
     return this->act_type == other.act_type;
   }
+};
+
+}  // namespace op
+}  // namespace mxnet
 
-#if MXNET_USE_MKLDNN == 1
-  uint64_t GetHash() const {
-    return act_type;
+namespace std {
+template<>
+struct hash<mxnet::op::ActivationParam> {
+  size_t operator()(const mxnet::op::ActivationParam& val) {
+    return val.act_type;
   }
-#endif
 };
+}  // namespace std
+
+namespace mxnet {
+namespace op {
 
 template<typename xpu, typename ForwardOp, typename BackwardOp, typename DType>
 void ActivationForward(const OpContext &ctx, const TBlob &in_data,

src/operator/nn/batch_norm-inl.h

@@ -95,19 +95,28 @@ struct BatchNormParam : public dmlc::Parameter<BatchNormParam> {
            this->axis == other.axis &&
            this->cudnn_off == other.cudnn_off;
   }
+};
+
+}  // namespace op
+}  // namespace mxnet
 
-#if MXNET_USE_MKLDNN == 1
-  uint64_t GetHash() const {
-    uint64_t hash = 0;
-    hash = hash * 2 + momentum * 10;
-    hash = hash * 2 + fix_gamma;
-    hash = hash * 2 + use_global_stats;
-    hash = hash * 2 + output_mean_var;
-    hash = hash * 2 + axis;
-    return hash;
+namespace std {
+template<>
+struct hash<mxnet::op::BatchNormParam> {
+  size_t operator()(const mxnet::op::BatchNormParam& val) {
+    size_t ret = 0;
+    ret = dmlc::HashCombine(ret, val.momentum);
+    ret = dmlc::HashCombine(ret, val.fix_gamma);
+    ret = dmlc::HashCombine(ret, val.use_global_stats);
+    ret = dmlc::HashCombine(ret, val.output_mean_var);
+    ret = dmlc::HashCombine(ret, val.axis);
+    return ret;
   }
-#endif
 };
+}  // namespace std
+
+namespace mxnet {
+namespace op {
 
 static inline bool IsBNWriting(const OpReqType ort) {
   return ort == kWriteTo || ort == kWriteInplace;

src/operator/nn/convolution-inl.h

@@ -118,29 +118,6 @@ struct ConvolutionParam : public dmlc::Parameter<ConvolutionParam> {
            this->cudnn_off == other.cudnn_off &&
            this->layout == other.layout;
   }
-#if MXNET_USE_MKLDNN == 1
-  static uint64_t ComputeHash(const TShape &shape) {
-    uint64_t hash = 0;
-    for (size_t i = 0; i < shape.ndim(); i++)
-      hash = hash * 2 + shape[i];
-    return hash;
-  }
-
-  uint64_t GetHash() const {
-    uint64_t hash = 0;
-    hash = hash * 2 + ComputeHash(kernel);
-    hash = hash * 2 + ComputeHash(stride);
-    hash = hash * 2 + ComputeHash(dilate);
-    hash = hash * 2 + ComputeHash(pad);
-    hash = hash * 2 + num_filter;
-    hash = hash * 2 + num_group;
-    hash = hash * 2 + workspace;
-    hash = hash * 2 + no_bias;
-    if (layout.has_value())
-      hash = hash * 2 + layout.value();
-    return hash;
-  }
-#endif
 };
 
 }  // namespace op

src/operator/nn/deconvolution-inl.h

@@ -163,31 +163,6 @@ struct DeconvolutionParam : public dmlc::Parameter<DeconvolutionParam> {
            this->cudnn_off == other.cudnn_off &&
            this->layout == other.layout;
   }
-#if MXNET_USE_MKLDNN == 1
-  static uint64_t ComputeHash(const TShape &shape) {
-    uint64_t hash = 0;
-    for (size_t i = 0; i < shape.ndim(); i++)
-      hash = hash * 2 + shape[i];
-    return hash;
-  }
-
-  uint64_t GetHash() const {
-    uint64_t hash = 0;
-    hash = hash * 2 + ComputeHash(kernel);
-    hash = hash * 2 + ComputeHash(stride);
-    hash = hash * 2 + ComputeHash(dilate);
-    hash = hash * 2 + ComputeHash(pad);
-    hash = hash * 2 + ComputeHash(adj);
-    hash = hash * 2 + ComputeHash(target_shape);
-    hash = hash * 2 + num_filter;
-    hash = hash * 2 + num_group;
-    hash = hash * 2 + workspace;
-    hash = hash * 2 + no_bias;
-    if (layout.has_value())
-      hash = hash * 2 + layout.value();
-    return hash;
-  }
-#endif
 };
 
 }  // namespace op

src/operator/nn/mkldnn/mkldnn_base-inl.h

@@ -386,7 +386,7 @@ class MKLDNNParamOpSign: public MKLDNNOpSignature {
 
  public:
   explicit MKLDNNParamOpSign(const ParamType &_param): MKLDNNOpSignature(
-      _param.GetHash()), param(_param) {
+      std::hash<ParamType>(_param)), param(_param) {
   }
 
   bool operator==(const MKLDNNParamOpSign<ParamType> &sign) const {

src/operator/nn/pooling-inl.h

@@ -88,28 +88,30 @@ struct PoolingParam : public dmlc::Parameter<PoolingParam> {
            this->global_pool        == other.global_pool &&
            this->cudnn_off          == other.cudnn_off;
   }
+};
 
-#if MXNET_USE_MKLDNN == 1
-  static uint64_t ComputeHash(const TShape &shape) {
-    uint64_t hash = 0;
-    for (size_t i = 0; i < shape.ndim(); i++)
-      hash = hash * 2 + shape[i];
-    return hash;
-  }
+}  // namespace op
+}  // namespace mxnet
 
-  uint64_t GetHash() const {
-    uint64_t hash = 0;
-    hash = hash * 2 + ComputeHash(kernel);
-    hash = hash * 2 + ComputeHash(stride);
-    hash = hash * 2 + ComputeHash(pad);
-    hash = hash * 2 + pool_type;
-    hash = hash * 2 + pooling_convention;
-    hash = hash * 2 + global_pool;
-    hash = hash * 2 + cudnn_off;
-    return hash;
+namespace std {
+template<>
+struct hash<mxnet::op::PoolingParam> {
+  size_t operator()(const mxnet::op::PoolingParam& val) {
+    size_t ret = 0;
+    ret = dmlc::HashCombine(ret, val.kernel);
+    ret = dmlc::HashCombine(ret, val.stride);
+    ret = dmlc::HashCombine(ret, val.pad);
+    ret = dmlc::HashCombine(ret, val.pool_type);
+    ret = dmlc::HashCombine(ret, val.pooling_convention);
+    ret = dmlc::HashCombine(ret, val.global_pool);
+    ret = dmlc::HashCombine(ret, val.cudnn_off);
+    return ret;
   }
-#endif
 };
+}  // namespace std
+
+namespace mxnet {
+namespace op {
 
 /*
  * When MKLDNN is enabled, we might want 2 outputs instead of one inputs, which