fix

include/mxnet/operator_util.h

@@ -481,45 +481,6 @@ class SimpleOpRegistry {
   __make_ ## SimpleOpRegEntry ## _ ## Name ## __ ## DEV ##__ =          \
       ::mxnet::op::SimpleOpRegistry::Get()->__REGISTER_OR_FIND__(#Name)
 
-//-----------------------------------------------
-// Utility functions for building NNVM operators
-//-----------------------------------------------
-/*! \brief Set shape of all inputs/outputs to shape of the first input */
-inline bool UniformShape(const nnvm::NodeAttrs& attrs,
-                          std::vector<TShape> *ishape,
-                          std::vector<TShape> *oshape) {
-  if (ishape->size() == 0 || (*ishape)[0].ndim() == 0) return false;
-  for (TShape& pshape : *oshape) {
-    pshape = (*ishape)[0];
-  }
-  for (TShape& pshape : *ishape) {
-    pshape = (*ishape)[0];
-  }
-  return true;
-}
-
-/*! \brief Set dtype of all inputs/outputs to dtype of the first input */
-inline bool UniformType(const nnvm::NodeAttrs& attrs,
-                        std::vector<int> *itype,
-                        std::vector<int> *otype) {
-  if (itype->size() == 0 || (*itype)[0] == -1) return false;
-  for (int& ptype : *otype) {
-    ptype = (*itype)[0];
-  }
-  for (int& ptype : *itype) {
-    ptype = (*itype)[0];
-  }
-  return true;
-}
-
-/*! \brief Parse keyword arguments as PType arguments and save to parsed */
-template<typename PType>
-inline void ParamParser(nnvm::NodeAttrs* attrs) {
-  PType param;
-  param.Init(attrs->dict);
-  attrs->parsed = std::move(param);
-}
-
 }  // namespace op
 }  // namespace mxnet
 #endif  // MXNET_OPERATOR_UTIL_H_

python/mxnet/image.py

@@ -180,7 +180,6 @@ def aug(src):
 def CastAug():
     def aug(src):
         src = src.astype(np.float32)
-        src /= 255.0
         return src
     return aug
 
@@ -206,12 +205,16 @@ def CreateAugmenter(data_shape, rand_crop=False, rand_resize=False, rand_mirror=
         auglist.append(ColorJitterAug(brightness, contrast, saturation))
 
     if pca_noise > 0:
-        eigval = np.array([0.2175, 0.0188, 0.0045])
+        eigval = np.array([ 55.46, 4.794, 1.148 ])
         eigvec = np.array([[ -0.5675,  0.7192,  0.4009 ],
                            [ -0.5808, -0.0045, -0.8140 ],
                            [ -0.5836, -0.6948,  0.4203 ]])
         auglist.append(LightingAug(pca_noise, eigval, eigvec))
 
+    if mean is True:
+        mean = np.array([ 123.68,  116.28 ,  103.53 ])
+    if std is True:
+        std = np.array([ 58.395,  57.12 ,  57.375])
     if mean:
         auglist.append(ColorNormalizeAug(mean, std))
 
@@ -307,7 +310,6 @@ def next(self):
         c, h, w = self.data_shape
         batch_data = nd.zeros((batch_size, h, w, c))
         batch_label = nd.zeros((batch_size, self.label_width))
-
         try:
             for i in range(batch_size):
                 label, data = self.next_sample()

src/io/image_io.cc

@@ -13,6 +13,8 @@
 #include <nnvm/op.h>
 #include <nnvm/op_attr_types.h>
 
+#include "../operator/elemwise_op_common.h"
+
 #if MXNET_USE_OPENCV
   #include <opencv2/opencv.hpp>
 #endif  // MXNET_USE_OPENCV
@@ -243,7 +245,7 @@ NNVM_REGISTER_OP(_cvimdecode)
 .set_num_inputs(1)
 .set_num_outputs(1)
 .set_attr_parser(op::ParamParser<ImdecodeParam>)
-.attr<FNDArrayFunction>("FNDArrayFunction", Imdecode)
+.set_attr<FNDArrayFunction>("FNDArrayFunction", Imdecode)
 .add_argument("buf", "NDArray", "Buffer containing binary encoded image")
 .add_arguments(ImdecodeParam::__FIELDS__());
 
@@ -252,9 +254,9 @@ NNVM_REGISTER_OP(_cvimresize)
 .set_num_inputs(1)
 .set_num_outputs(1)
 .set_attr_parser(op::ParamParser<ResizeParam>)
-.attr<nnvm::FInferShape>("FInferShape", ResizeShape)
-.attr<nnvm::FInferType>("FInferType", op::UniformType)
-.attr<FCompute>("FCompute<cpu>", Imresize)
+.set_attr<nnvm::FInferShape>("FInferShape", ResizeShape)
+.set_attr<nnvm::FInferType>("FInferType", op::ElemwiseType<1,1>)
+.set_attr<FCompute>("FCompute<cpu>", Imresize)
 .add_argument("src", "NDArray", "source image")
 .add_arguments(ResizeParam::__FIELDS__());
 
@@ -263,9 +265,9 @@ NNVM_REGISTER_OP(_cvcopyMakeBorder)
 .set_num_inputs(1)
 .set_num_outputs(1)
 .set_attr_parser(op::ParamParser<MakeBorderParam>)
-.attr<nnvm::FInferShape>("FInferShape", MakeBorderShape)
-.attr<nnvm::FInferType>("FInferType", op::UniformType)
-.attr<FCompute>("FCompute<cpu>", copyMakeBorder)
+.set_attr<nnvm::FInferShape>("FInferShape", MakeBorderShape)
+.set_attr<nnvm::FInferType>("FInferType", op::ElemwiseType<1,1>)
+.set_attr<FCompute>("FCompute<cpu>", copyMakeBorder)
 .add_argument("src", "NDArray", "source image")
 .add_arguments(MakeBorderParam::__FIELDS__());
 

src/operator/tensor/elemwise_binary_broadcast_op.h

@@ -70,7 +70,7 @@ inline bool BinaryBroadcastShapeCompact(const TShape& lshape, const TShape& rsha
   for (index_t i = 0; i < oshape.ndim(); ++i) {
     index_t l = 1, r = 1, o = oshape[i];
     if (i >= bl) l = lshape[i-bl];
-    if (j >= br) r = rshape[i-br];
+    if (i >= br) r = rshape[i-br];
     if ((lprod != rprod || l != r) &&
         lprod*l > 1 && rprod*r > 1) {
       (*new_lshape)[j] = lprod;