add contrib package

example/rcnn/README.md

@@ -58,9 +58,6 @@ See if `bash script/additional_deps.sh` will do the following for you.
 * Suppose `HOME` represents where this file is located. All commands, unless stated otherwise, should be started from `HOME`.
   Executing scripts in `script` must also be from `HOME`.
 * Install python package `cython easydict matplotlib scikit-image`.
-* Install MXNet with additional operators.
-If you know Makefile, change `EXTRA_OPERATORS` in `config.mk` to include the `example/rcnn/operator` folder.  
-If not, copy all files in `operator` to `../../src/operator` (namely `mxnet/src/operator`).  
 * Install MXNet Python Interface. Open `python` type `import mxnet` to confirm.
 * Run `make` in `HOME`.
 

example/rcnn/rcnn/symbol/symbol_resnet.py

@@ -96,7 +96,7 @@ def get_resnet_train(num_classes=config.NUM_CLASSES, num_anchors=config.NUM_ANCH
     rpn_cls_act_reshape = mx.symbol.Reshape(
         data=rpn_cls_act, shape=(0, 2 * num_anchors, -1, 0), name='rpn_cls_act_reshape')
     if config.TRAIN.CXX_PROPOSAL:
-        rois = mx.symbol.Proposal(
+        rois = mx.symbol.contrib.Proposal(
             cls_prob=rpn_cls_act_reshape, bbox_pred=rpn_bbox_pred, im_info=im_info, name='rois',
             feature_stride=config.RPN_FEAT_STRIDE, scales=tuple(config.ANCHOR_SCALES), ratios=tuple(config.ANCHOR_RATIOS),
             rpn_pre_nms_top_n=config.TRAIN.RPN_PRE_NMS_TOP_N, rpn_post_nms_top_n=config.TRAIN.RPN_POST_NMS_TOP_N,
@@ -172,7 +172,7 @@ def get_resnet_test(num_classes=config.NUM_CLASSES, num_anchors=config.NUM_ANCHO
     rpn_cls_prob_reshape = mx.symbol.Reshape(
         data=rpn_cls_prob, shape=(0, 2 * num_anchors, -1, 0), name='rpn_cls_prob_reshape')
     if config.TEST.CXX_PROPOSAL:
-        rois = mx.symbol.Proposal(
+        rois = mx.symbol.contrib.Proposal(
             cls_prob=rpn_cls_prob_reshape, bbox_pred=rpn_bbox_pred, im_info=im_info, name='rois',
             feature_stride=config.RPN_FEAT_STRIDE, scales=tuple(config.ANCHOR_SCALES), ratios=tuple(config.ANCHOR_RATIOS),
             rpn_pre_nms_top_n=config.TEST.RPN_PRE_NMS_TOP_N, rpn_post_nms_top_n=config.TEST.RPN_POST_NMS_TOP_N,

example/rcnn/rcnn/symbol/symbol_vgg.py

@@ -225,7 +225,7 @@ def get_vgg_rpn_test(num_anchors=config.NUM_ANCHORS):
     rpn_cls_prob_reshape = mx.symbol.Reshape(
         data=rpn_cls_prob, shape=(0, 2 * num_anchors, -1, 0), name='rpn_cls_prob_reshape')
     if config.TEST.CXX_PROPOSAL:
-        group = mx.symbol.Proposal(
+        group = mx.symbol.contrib.Proposal(
             cls_prob=rpn_cls_prob_reshape, bbox_pred=rpn_bbox_pred, im_info=im_info, name='rois', output_score=True,
             feature_stride=config.RPN_FEAT_STRIDE, scales=tuple(config.ANCHOR_SCALES), ratios=tuple(config.ANCHOR_RATIOS),
             rpn_pre_nms_top_n=config.TEST.PROPOSAL_PRE_NMS_TOP_N, rpn_post_nms_top_n=config.TEST.PROPOSAL_POST_NMS_TOP_N,
@@ -273,7 +273,7 @@ def get_vgg_test(num_classes=config.NUM_CLASSES, num_anchors=config.NUM_ANCHORS)
     rpn_cls_prob_reshape = mx.symbol.Reshape(
         data=rpn_cls_prob, shape=(0, 2 * num_anchors, -1, 0), name='rpn_cls_prob_reshape')
     if config.TEST.CXX_PROPOSAL:
-        rois = mx.symbol.Proposal(
+        rois = mx.symbol.contrib.Proposal(
             cls_prob=rpn_cls_prob_reshape, bbox_pred=rpn_bbox_pred, im_info=im_info, name='rois',
             feature_stride=config.RPN_FEAT_STRIDE, scales=tuple(config.ANCHOR_SCALES), ratios=tuple(config.ANCHOR_RATIOS),
             rpn_pre_nms_top_n=config.TEST.RPN_PRE_NMS_TOP_N, rpn_post_nms_top_n=config.TEST.RPN_POST_NMS_TOP_N,
@@ -356,7 +356,7 @@ def get_vgg_train(num_classes=config.NUM_CLASSES, num_anchors=config.NUM_ANCHORS
     rpn_cls_act_reshape = mx.symbol.Reshape(
         data=rpn_cls_act, shape=(0, 2 * num_anchors, -1, 0), name='rpn_cls_act_reshape')
     if config.TRAIN.CXX_PROPOSAL:
-        rois = mx.symbol.Proposal(
+        rois = mx.symbol.contrib.Proposal(
             cls_prob=rpn_cls_act_reshape, bbox_pred=rpn_bbox_pred, im_info=im_info, name='rois',
             feature_stride=config.RPN_FEAT_STRIDE, scales=tuple(config.ANCHOR_SCALES), ratios=tuple(config.ANCHOR_RATIOS),
             rpn_pre_nms_top_n=config.TRAIN.RPN_PRE_NMS_TOP_N, rpn_post_nms_top_n=config.TRAIN.RPN_POST_NMS_TOP_N,

example/ssd/README.md

@@ -45,14 +45,10 @@ sudo apt-get install python-opencv python-matplotlib python-numpy
 sudo pip install easydict
 ```
 
-* Build MXNet: Follow the official instructions, make sure the extra operators for this example is enabled
+* Build MXNet: Follow the official instructions
 ```
 # for Ubuntu/Debian
 cp make/config.mk ./config.mk
-# modify it if with vim or whatever editor
-EXTRA_OPERATORS = example/ssd/operator
-# or add a line if you have other EXTRA_OPERATORS directory
-EXTRA_OPERATORS += example/ssd/operator
 ```
 Remember to enable CUDA if you want to be able to train, since CPU training is
 insanely slow. Using CUDNN is optional.

example/ssd/symbol/common.py

@@ -161,7 +161,7 @@ def multibox_layer(from_layers, num_classes, sizes=[.2, .95],
         cls_pred_layers.append(cls_pred)
 
         # create anchor generation layer
-        anchors = mx.symbol.MultiBoxPrior(from_layer, sizes=size_str, ratios=ratio_str, \
+        anchors = mx.symbol.contrib.MultiBoxPrior(from_layer, sizes=size_str, ratios=ratio_str, \
             clip=clip, name="{}_anchors".format(from_name))
         anchors = mx.symbol.Flatten(data=anchors)
         anchor_layers.append(anchors)

example/ssd/symbol/symbol_vgg16_reduced.py

@@ -118,7 +118,7 @@ def get_symbol_train(num_classes=20):
         num_classes, sizes=sizes, ratios=ratios, normalization=normalizations, \
         num_channels=num_channels, clip=True, interm_layer=0)
 
-    tmp = mx.symbol.MultiBoxTarget(
+    tmp = mx.symbol.contrib.MultiBoxTarget(
         *[anchor_boxes, label, cls_preds], overlap_threshold=.5, \
         ignore_label=-1, negative_mining_ratio=3, minimum_negative_samples=0, \
         negative_mining_thresh=.5, variances=(0.1, 0.1, 0.2, 0.2),
@@ -170,7 +170,7 @@ def get_symbol(num_classes=20, nms_thresh=0.5, force_suppress=True):
         name='cls_prob')
     # group output
     # out = mx.symbol.Group([loc_preds, cls_preds, anchor_boxes])
-    out = mx.symbol.MultiBoxDetection(*[cls_prob, loc_preds, anchor_boxes], \
+    out = mx.symbol.contrib.MultiBoxDetection(*[cls_prob, loc_preds, anchor_boxes], \
         name="detection", nms_threshold=nms_thresh, force_suppress=force_suppress,
         variances=(0.1, 0.1, 0.2, 0.2))
     return out

python/mxnet/__init__.py

@@ -6,6 +6,7 @@
 from .context import Context, current_context, cpu, gpu
 from .base import MXNetError
 from . import base
+from . import contrib
 from . import ndarray
 from . import name
 # use mx.sym as short for symbol

python/mxnet/_ctypes/ndarray.py

@@ -166,11 +166,16 @@ def _init_ndarray_module(ndarray_class, root_namespace):
 
     module_obj = _sys.modules["%s.ndarray" % root_namespace]
     module_internal = _sys.modules["%s._ndarray_internal" % root_namespace]
+    module_contrib = _sys.modules["%s.contrib.ndarray" % root_namespace]
     for name in op_names:
         hdl = OpHandle()
         check_call(_LIB.NNGetOpHandle(c_str(name), ctypes.byref(hdl)))
         function = _make_ndarray_function(hdl, name)
-        if function.__name__.startswith('_'):
+        if function.__name__.startswith('_contrib_'):
+            function.__name__ = function.__name__[9:]
+            function.__module__ = 'mxnet.contrib.ndarray'
+            setattr(module_contrib, function.__name__, function)
+        elif function.__name__.startswith('_'):
             setattr(module_internal, function.__name__, function)
         else:
             setattr(module_obj, function.__name__, function)

python/mxnet/_ctypes/symbol.py

@@ -211,11 +211,16 @@ def _init_symbol_module(symbol_class, root_namespace):
 
     module_obj = sys.modules["%s.symbol" % root_namespace]
     module_internal = sys.modules["%s._symbol_internal" % root_namespace]
+    module_contrib = sys.modules["%s.contrib.symbol" % root_namespace]
     for name in op_names:
         hdl = OpHandle()
         check_call(_LIB.NNGetOpHandle(c_str(name), ctypes.byref(hdl)))
         function = _make_atomic_symbol_function(hdl, name)
-        if function.__name__.startswith('_'):
+        if function.__name__.startswith('_contrib_'):
+            function.__name__ = function.__name__[9:]
+            function.__module__ = 'mxnet.contrib.symbol'
+            setattr(module_contrib, function.__name__, function)
+        elif function.__name__.startswith('_'):
             setattr(module_internal, function.__name__, function)
         else:
             setattr(module_obj, function.__name__, function)

python/mxnet/contrib/__init__.py

@@ -0,0 +1,8 @@
+# coding: utf-8
+"""Experimental contributions"""
+
+from . import symbol
+from . import ndarray
+
+from . import symbol as sym
+from . import ndarray as nd

python/mxnet/contrib/ndarray.py

@@ -0,0 +1,2 @@
+# coding: utf-8
+"""NDArray namespace used to register contrib functions"""

python/mxnet/contrib/symbol.py

@@ -0,0 +1,2 @@
+# coding: utf-8
+"""Symbol namespace used to register contrib functions"""

python/setup.py

@@ -71,7 +71,7 @@ def config_cython():
       zip_safe=False,
       packages=[
           'mxnet', 'mxnet.module', 'mxnet._ctypes', 'mxnet.rnn',
-          'mxnet._cy2', 'mxnet._cy3', 'mxnet.notebook'
+          'mxnet._cy2', 'mxnet._cy3', 'mxnet.notebook', 'mxnet.contrib'
           ],
       data_files=[('mxnet', [LIB_PATH[0]])],
       url='https://github.com/dmlc/mxnet',

example/ssd/operator/multibox_detection-inl.h → src/operator/contrib/multibox_detection-inl.h

@@ -4,8 +4,8 @@
  * \brief post-process multibox detection predictions
  * \author Joshua Zhang
 */
-#ifndef MXNET_OPERATOR_MULTIBOX_DETECTION_INL_H_
-#define MXNET_OPERATOR_MULTIBOX_DETECTION_INL_H_
+#ifndef MXNET_OPERATOR_CONTRIB_MULTIBOX_DETECTION_INL_H_
+#define MXNET_OPERATOR_CONTRIB_MULTIBOX_DETECTION_INL_H_
 #include <dmlc/logging.h>
 #include <dmlc/parameter.h>
 #include <mxnet/operator.h>
@@ -15,7 +15,7 @@
 #include <string>
 #include <utility>
 #include <valarray>
-#include "./operator_common.h"
+#include "../operator_common.h"
 
 namespace mxnet {
 namespace op {
@@ -216,7 +216,7 @@ class MultiBoxDetectionProp : public OperatorProperty {
   }
 
   std::string TypeString() const override {
-    return "MultiBoxDetection";
+    return "_contrib_MultiBoxDetection";
   }
 
   std::vector<ResourceRequest> ForwardResource(
@@ -240,4 +240,4 @@ class MultiBoxDetectionProp : public OperatorProperty {
 }  // namespace op
 }  // namespace mxnet
 
-#endif  // MXNET_OPERATOR_MULTIBOX_DETECTION_INL_H_
+#endif  // MXNET_OPERATOR_CONTRIB_MULTIBOX_DETECTION_INL_H_

example/ssd/operator/multibox_detection.cc → src/operator/contrib/multibox_detection.cc

@@ -165,7 +165,7 @@ Operator* MultiBoxDetectionProp::CreateOperatorEx(Context ctx,
 }
 
 DMLC_REGISTER_PARAMETER(MultiBoxDetectionParam);
-MXNET_REGISTER_OP_PROPERTY(MultiBoxDetection, MultiBoxDetectionProp)
+MXNET_REGISTER_OP_PROPERTY(_contrib_MultiBoxDetection, MultiBoxDetectionProp)
 .describe("Convert multibox detection predictions.")
 .add_argument("cls_prob", "Symbol", "Class probabilities.")
 .add_argument("loc_pred", "Symbol", "Location regression predictions.")

example/ssd/operator/multibox_prior-inl.h → src/operator/contrib/multibox_prior-inl.h

@@ -4,8 +4,8 @@
  * \brief generate multibox prior boxes
  * \author Joshua Zhang
 */
-#ifndef MXNET_OPERATOR_MULTIBOX_PRIOR_INL_H_
-#define MXNET_OPERATOR_MULTIBOX_PRIOR_INL_H_
+#ifndef MXNET_OPERATOR_CONTRIB_MULTIBOX_PRIOR_INL_H_
+#define MXNET_OPERATOR_CONTRIB_MULTIBOX_PRIOR_INL_H_
 #include <dmlc/logging.h>
 #include <dmlc/parameter.h>
 #include <mxnet/operator.h>
@@ -15,7 +15,7 @@
 #include <string>
 #include <utility>
 #include <valarray>
-#include "./operator_common.h"
+#include "../operator_common.h"
 
 
 namespace mxnet {
@@ -228,7 +228,7 @@ class MultiBoxPriorProp: public OperatorProperty {
   }
 
   std::string TypeString() const override {
-    return "MultiBoxPrior";
+    return "_contrib_MultiBoxPrior";
   }
 
   Operator* CreateOperator(Context ctx) const override {
@@ -247,4 +247,4 @@ class MultiBoxPriorProp: public OperatorProperty {
 }  // namespace op
 }  // namespace mxnet
 
-#endif  // MXNET_OPERATOR_MULTIBOX_PRIOR_INL_H_
+#endif  // MXNET_OPERATOR_CONTRIB_MULTIBOX_PRIOR_INL_H_

example/ssd/operator/multibox_prior.cc → src/operator/contrib/multibox_prior.cc

@@ -73,7 +73,7 @@ Operator* MultiBoxPriorProp::CreateOperatorEx(Context ctx, std::vector<TShape> *
 
 DMLC_REGISTER_PARAMETER(MultiBoxPriorParam);
 
-MXNET_REGISTER_OP_PROPERTY(MultiBoxPrior, MultiBoxPriorProp)
+MXNET_REGISTER_OP_PROPERTY(_contrib_MultiBoxPrior, MultiBoxPriorProp)
 .add_argument("data", "Symbol", "Input data.")
 .add_arguments(MultiBoxPriorParam::__FIELDS__())
 .describe("Generate prior(anchor) boxes from data, sizes and ratios.");

example/ssd/operator/multibox_target-inl.h → src/operator/contrib/multibox_target-inl.h

@@ -4,8 +4,8 @@
  * \brief
  * \author Joshua Zhang
 */
-#ifndef MXNET_OPERATOR_MULTIBOX_TARGET_INL_H_
-#define MXNET_OPERATOR_MULTIBOX_TARGET_INL_H_
+#ifndef MXNET_OPERATOR_CONTRIB_MULTIBOX_TARGET_INL_H_
+#define MXNET_OPERATOR_CONTRIB_MULTIBOX_TARGET_INL_H_
 #include <dmlc/logging.h>
 #include <dmlc/parameter.h>
 #include <mxnet/operator.h>
@@ -15,8 +15,8 @@
 #include <string>
 #include <utility>
 #include <valarray>
-#include "./operator_common.h"
-#include "./mshadow_op.h"
+#include "../operator_common.h"
+#include "../mshadow_op.h"
 
 namespace mxnet {
 namespace op {
@@ -294,7 +294,7 @@ class MultiBoxTargetProp : public OperatorProperty {
   }
 
   std::string TypeString() const override {
-    return "MultiBoxTarget";
+    return "_contrib_MultiBoxTarget";
   }
 
   //  decalre dependency and inplace optimization options
@@ -326,4 +326,4 @@ class MultiBoxTargetProp : public OperatorProperty {
 }  // namespace op
 }  // namespace mxnet
 
-#endif  // MXNET_OPERATOR_MULTIBOX_TARGET_INL_H_
+#endif  // MXNET_OPERATOR_CONTRIB_MULTIBOX_TARGET_INL_H_

example/ssd/operator/multibox_target.cc → src/operator/contrib/multibox_target.cc

@@ -4,9 +4,9 @@
  * \brief MultiBoxTarget op
  * \author Joshua Zhang
 */
-#include "./multibox_target-inl.h"
-#include "./mshadow_op.h"
 #include <algorithm>
+#include "./multibox_target-inl.h"
+#include "../mshadow_op.h"
 
 namespace mshadow {
 template<typename DType>
@@ -281,7 +281,7 @@ Operator* MultiBoxTargetProp::CreateOperatorEx(Context ctx, std::vector<TShape>
 }
 
 DMLC_REGISTER_PARAMETER(MultiBoxTargetParam);
-MXNET_REGISTER_OP_PROPERTY(MultiBoxTarget, MultiBoxTargetProp)
+MXNET_REGISTER_OP_PROPERTY(_contrib_MultiBoxTarget, MultiBoxTargetProp)
 .describe("Compute Multibox training targets")
 .add_argument("anchor", "Symbol", "Generated anchor boxes.")
 .add_argument("label", "Symbol", "Object detection labels.")