Update LMDB format

Dragon/include/core/common.h

@@ -52,9 +52,9 @@ using Set = std::unordered_set<Value> ;
 /*
  * Define the Kernel version.
  *
- * | Major(2) | Minor(2) | Patch(08) |
+ * | Major(2) | Minor(2) | Patch(09) |
  */
-#define DRAGON_VERSION 2208
+#define DRAGON_VERSION 2209
 
 /*
  * Define the default random seed.

Dragon/include/operators/arithmetic/fundamental_op.h

@@ -259,16 +259,18 @@ class RDivGradientOp final : public Operator<Context> {
 
 #define RunByX1X2(dtype) \
     DefineX1X2; \
-    if (X1->dims() == X2->dims()) { \
-        EltwiseRunWithType<dtype>(); \
-    } else if (X1->dim(0) == X2->dim(0) && \
-        X2->count(1) == 1) { \
-        BroadcastRunWithType<dtype>(2); \
+    if (X2->ndim() == 0) { \
+        BroadcastRunWithType<dtype>(0); \
+    } else if (X2->ndim() == 1 && X2->dim(0) == 1) { \
+        BroadcastRunWithType<dtype>(0); \
     } else if (X1->dim(-1) == X2->dim(-1) && \
         X2->count(0, X2->axis(-1)) == 1) { \
         BroadcastRunWithType<dtype>(1); \
-    } else if (X2->ndim() == 1 && X2->dim(0) == 1) { \
-        BroadcastRunWithType<dtype>(0); \
+    } else if (X1->dim(0) == X2->dim(0) && \
+               X2->count(1) == 1) { \
+        BroadcastRunWithType<dtype>(2); \
+    } else if (X1->dims() == X2->dims()) { \
+        EltwiseRunWithType<dtype>(); \
     } else { \
         LOG(FATAL) << "Could not broadcast with shapes " \
                    << X1->DimString() << "  " \
@@ -277,16 +279,18 @@ class RDivGradientOp final : public Operator<Context> {
 
 #define RRunByX1X2(dtype) \
     DefineX1X2; \
-    if (X1->dims() == X2->dims()) { \
-        EltwiseRunWithType<dtype>(); \
-    } else if (X1->dim(0) == X2->dim(0) && \
-        X1->count(1) == 1) { \
-        BroadcastRunWithType<dtype>(2); \
+    if (X1->ndim() == 0) { \
+        BroadcastRunWithType<dtype>(0); \
+    } else if (X1->ndim() == 1 && X1->dim(0) == 1) { \
+        BroadcastRunWithType<dtype>(0); \
     } else if (X1->dim(-1) == X2->dim(-1) && \
         X1->count(0, X1->axis(-1)) == 1) { \
         BroadcastRunWithType<dtype>(1); \
-    } else if (X1->ndim() == 1 && X1->dim(0) == 1) { \
-        BroadcastRunWithType<dtype>(0); \
+    } else if (X1->dim(0) == X2->dim(0) && \
+        X1->count(1) == 1) { \
+        BroadcastRunWithType<dtype>(2); \
+    } else if (X1->dims() == X2->dims()) { \
+        EltwiseRunWithType<dtype>(); \
     } else { \
         LOG(FATAL) << "Could not broadcast with shapes " \
                    << X1->DimString() << "  " \

Dragon/python/dragon/config.py

@@ -41,8 +41,8 @@ option['random_seed'] = 3
 # Disable the memonger if true
 option['debug_mode'] = False
 
-# Set it by the memonger
-option['share_grads'] = False
+# Whether to share grads
+option['share_grads'] = True
 
 # Whether to log the meta graphs
 option['log_meta_graph'] = False

Dragon/python/dragon/docs/contents/ops.rst

@@ -82,7 +82,8 @@ List                               Brief
 `SmoothL1Loss`_                    SmoothL1Loss. `[Girshick, 2015] <https://arxiv.org/abs/1504.08083>`_.
 `L1Loss`_                          L1Loss.
 `L2Loss`_                          L2Loss(EuclideanLoss).
-`SparseSoftmaxFocalLoss`_          SoftmaxFocalLoss with sparse labels. `[Lin et.al, 2017] <https://arxiv.org/abs/1708.02002>`_.
+`SigmoidFocalLoss`_                SigmoidFocalLoss with sparse labels. `[Lin et.al, 2017] <https://arxiv.org/abs/1708.02002>`_.
+`SoftmaxFocalLoss`_                SoftmaxFocalLoss with sparse labels. `[Lin et.al, 2017] <https://arxiv.org/abs/1708.02002>`_.
 `CTCLoss`_                         CTCLoss with batched variable length of labels. `[Graves & Gomez, 2006] <http://www.cs.utoronto.ca/~graves/icml_2006.pdf>`_.
 =============================      ======================================================================
 
@@ -235,7 +236,8 @@ List                 Brief
 .. _SmoothL1Loss: operators/loss.html#dragon.operators.loss.SmoothL1Loss
 .. _L1Loss: operators/loss.html#dragon.operators.loss.L1Loss
 .. _L2Loss: operators/loss.html#dragon.operators.loss.L2Loss
-.. _SparseSoftmaxFocalLoss: operators/loss.html#dragon.operators.loss.SparseSoftmaxFocalLoss
+.. _SigmoidFocalLoss: operators/loss.html#dragon.operators.loss.SigmoidFocalLoss
+.. _SoftmaxFocalLoss: operators/loss.html#dragon.operators.loss.SoftmaxFocalLoss
 .. _CTCLoss: operators/loss.html#dragon.operators.loss.CTCLoss
 
 .. _Add: operators/arithmetic.html#dragon.operators.arithmetic.Add

Dragon/python/dragon/docs/contents/vm/caffe/layer.rst

@@ -95,6 +95,8 @@ List                                  Brief
 `SigmoidCrossEntropyLossLayer`_       The implementation of ``SigmoidCrossEntropyLossLayer``.
 `L2LossLayer`_                        The implementation of ``L2LossLayer``.
 `SmoothL1LossLayer`_                  The implementation of ``SmoothL1LossLayer``.
+`SigmoidWithFocalLossLayer`_          The implementation of ``SigmoidWithFocalLossLayer``.
+`SoftmaxWithFocalLossLayer`_          The implementation of ``SoftmaxWithFocalLossLayer``.
 =================================     =============================================================================
 
 MPI
@@ -198,6 +200,8 @@ API Reference
 .. _SigmoidCrossEntropyLossLayer: #dragon.vm.caffe.layers.loss.SigmoidCrossEntropyLossLayer
 .. _L2LossLayer: #dragon.vm.caffe.layers.loss.L2LossLayer
 .. _SmoothL1LossLayer: #dragon.vm.caffe.layers.loss.SmoothL1LossLayer
+.. _SigmoidWithFocalLossLayer: #dragon.vm.caffe.layers.loss.SigmoidWithFocalLossLayer
+.. _SoftmaxWithFocalLossLayer: #dragon.vm.caffe.layers.loss.SoftmaxWithFocalLossLayer
 
 .. _MPIBroadcastLayer: #dragon.vm.caffe.layers.mpi.MPIBroadcastLayer
 .. _MPIGatherLayer: #dragon.vm.caffe.layers.mpi.MPIGatherLayer

Dragon/python/dragon/docs/contents/vm/caffe/net.rst

@@ -47,8 +47,8 @@ API Reference
 .. _Net.replace: #dragon.vm.caffe.net.Net.replace
 .. _Net.function: #dragon.vm.caffe.net.Net.function
 
-.. _NetInit(prototxt, phase): #dragon.vm.caffe.net.Net.NetInit
-.. _NetInitLoad(prototxt, model, phase): #dragon.vm.caffe.net.Net.NetInitLoad
+.. _NetInit(proto_txt, phase): #dragon.vm.caffe.net.Net.NetInit
+.. _NetInitLoad(proto_txt, model, phase): #dragon.vm.caffe.net.Net.NetInitLoad
 .. _workspace.Snapshot(*args, **kwargs): ../../core/workspace.html#dragon.core.workspace.Snapshot
 .. _workspace.Restore(*args, **kwargs): ../../core/workspace.html#dragon.core.workspace.Restore
 

Dragon/python/dragon/io/data_reader.py

@@ -165,8 +165,8 @@ class DataReader(Process):
         # init db
         self._db = LMDB()
         self._db.open(self._source)
-        self._db_size = int(self._db.get('size'))
-        self._db_zfill = int(self._db.get('zfill'))
+        self._db_zfill = self._db.zfill()
+        self._db_size = self._db.num_entries()
         self._epoch_size = int(self._db_size / self._num_parts + 1)
 
         if self._use_shuffle:

Dragon/python/dragon/operators/loss.py

@@ -219,7 +219,7 @@ def L2Loss(inputs, normalization='BATCH_SIZE', **kwargs):
 
 def SigmoidFocalLoss(inputs, axis=1, normalization='VALID',
                      alpha=0.25, gamma=2.0, neg_id=0, **kwargs):
-    """SoftmaxFocalLoss with sparse labels. `[Lin et.al, 2017] <https://arxiv.org/abs/1708.02002>`_.
+    """SigmoidFocalLoss with sparse labels. `[Lin et.al, 2017] <https://arxiv.org/abs/1708.02002>`_.
 
     Parameters
     ----------

Dragon/python/dragon/tools/db.py

@@ -88,6 +88,13 @@ class LMDB(object):
         self.txn = self.env.begin(write=(mode == 'w'))
         self.cursor = self.txn.cursor()
 
+    def zfill(self):
+        self.cursor.first()
+        return len(self.key())
+
+    def num_entries(self):
+        return self.env.stat()['entries']
+
     def _try_put(self):
         """Try to commit the buffers.
 

Dragon/python/dragon/tools/summary_writer.py

@@ -39,7 +39,6 @@ class ScalarSummary(object):
 
         """
         self.log_dir = os.path.join(log_dir, 'scalar')
-        if not os.path.exists(self.log_dir): os.makedirs(self.log_dir)
 
     def add_summary(self, scalar, global_step):
         """Add a summary.
@@ -62,5 +61,6 @@ class ScalarSummary(object):
         else: raise TypeError()
         key = key.replace('/', '_')
 
+        if not os.path.exists(self.log_dir): os.makedirs(self.log_dir)
         with open(os.path.join(self.log_dir, key + '.txt'), 'a') as f:
             f.write(str(global_step) + ' ' + str(value) + '\n')
\ No newline at end of file

Dragon/python/dragon/version.py

@@ -14,7 +14,7 @@ from __future__ import division
 from __future__ import print_function
 
 version = '0.2.2'
-full_version = '0.2.2.8'
+full_version = '0.2.2.9'
 release = False
 
 if not release:

Dragon/python/dragon/vm/caffe/layer.py

@@ -58,22 +58,6 @@ class Layer(object):
             self._common_param['mirror_stage'] = LayerParameter.mirror_stage
 
     def Setup(self, bottom):
-        """Setup the parameters.
-
-        Parameters
-        ----------
-        bottom : list of Tensor
-            The inputs.
-
-        Returns
-        -------
-        None
-
-        References
-        ---------=
-        The implementation of `LayerSetUp(layer.hpp, L91)`_.
-
-        """
         self._param = dict(self._param, **self._common_param)
 
     def Fill(self, tensor, layer_param, filler):

Dragon/python/dragon/vm/torch/__init__.py

@@ -9,10 +9,6 @@
 #
 # ------------------------------------------------------------
 
-# Default configs
-import dragon.memonger as opt
-opt.ShareGrads(enabled=True)
-
 # Import Dynamic Methods
 import dragon.vm.torch.ops.builtin
 

Dragon/python/setup.py

@@ -42,7 +42,7 @@ find_modules()
 
 
 setup(name = 'dragon',
-      version='0.2.2.8',
+      version='0.2.2.9',
       description = 'Dragon: A Computation Graph Virtual Machine Based Deep Learning Framework',
       url='https://github.com/seetaresearch/Dragon',
       author='Ting Pan',

DragonLair @ a4a90cc6

-Subproject commit 0e7c32d84ba3758cb1ae703923d73a47add5442d
+Subproject commit a4a90cc6a8757fe7bc0d5d1ce8b7af35a0679438