Rewrote shownet so that it extends the model class now, making it eas…

…y to run the model from that script. Added ability to show predictions made by the net.

convdata.py

@@ -30,13 +30,13 @@
 class CIFARDataProvider(LabeledMemoryDataProvider):
     def __init__(self, data_dir, batch_range, init_epoch=1, init_batchnum=None, dp_params={}, test=False):
         LabeledMemoryDataProvider.__init__(self, data_dir, batch_range, init_epoch, init_batchnum, dp_params, test)
-        data_mean = self.batch_meta['data_mean']
-
+        self.data_mean = self.batch_meta['data_mean']
+        self.num_colors = 3
         # Subtract the mean from the data and make sure that both data and
         # labels are in single-precision floating point.
         for d in self.data_dic:
             # This converts the data matrix to single precision and makes sure that it is C-ordered
-            d['data'] = n.require((d['data'] - data_mean), dtype=n.single, requirements='C')
+            d['data'] = n.require((d['data'] - self.data_mean), dtype=n.single, requirements='C')
             d['labels'] = n.require(d['labels'].reshape((1, d['data'].shape[1])), dtype=n.single)
 
     def get_next_batch(self):
@@ -55,6 +55,7 @@ def __init__(self, data_dir, batch_range=None, init_epoch=1, init_batchnum=None,
         self.multiview = dp_params['multiview_test'] and test
         self.num_views = 9
         self.data_mult = self.num_views if self.multiview else 1
+        self.num_colors = 3
 
         for d in self.data_dic:
             d['data'] = n.require(d['data'], requirements='C')

convnet.py

@@ -51,8 +51,8 @@ def init_model_state(self):
         else:
             ms['layers'] = LayerParser.parse_layers(self.layer_def, self.layer_params, self)
 
-        if self.op.get_value('multiview_test'):
-            logreg_name = self.op.get_value('logreg_name')
+        logreg_name = self.op.get_value('logreg_name')
+        if logreg_name:
             try:
                 self.logreg_idx = [l['name'] for l in ms['layers']].index(logreg_name)
                 if ms['layers'][self.logreg_idx]['type'] != 'cost.logreg':
@@ -136,7 +136,7 @@ def get_options_parser(cls):
         op.add_option("layer-def", "layer_def", StringOptionParser, "Layer definition file", set_once=True)
         op.add_option("layer-params", "layer_params", StringOptionParser, "Layer parameter file")
         op.add_option("check-grads", "check_grads", BooleanOptionParser, "Check gradients and quit?", default=0, excuses=['data_path','save_path','train_batch_range','test_batch_range'])
-        op.add_option("multiview-test", "multiview_test", BooleanOptionParser, "Cropped DP: test on multiple patches?", default=0)
+        op.add_option("multiview-test", "multiview_test", BooleanOptionParser, "Cropped DP: test on multiple patches?", default=0, requires=['logreg_name'])
         op.add_option("crop-border", "crop_border", IntegerOptionParser, "Cropped DP: crop border size", default=4)
         op.add_option("logreg-name", "logreg_name", StringOptionParser, "Cropped DP: logreg layer name", default="")
 
@@ -146,16 +146,16 @@ def get_options_parser(cls):
         op.options["num_epochs"].default = 50000
         op.options['dp_type'].default = None
 
+        DataProvider.register_data_provider('cifar', 'CIFAR', CIFARDataProvider)
+        DataProvider.register_data_provider('dummy-cn-n', 'Dummy ConvNet', DummyConvNetDataProvider)
+        DataProvider.register_data_provider('cifar-cropped', 'Cropped CIFAR', CroppedCIFARDataProvider)
+
         return op
 
 if __name__ == "__main__":
     #nr.seed(5)
     op = GPUModel.get_options_parser()
-
-    DataProvider.register_data_provider('cifar', 'CIFAR', CIFARDataProvider)
-    DataProvider.register_data_provider('dummy-cn-n', 'Dummy ConvNet', DummyConvNetDataProvider)
-    DataProvider.register_data_provider('cifar-cropped', 'Cropped CIFAR', CroppedCIFARDataProvider)
-
+
     op, load_dic = IGPUModel.parse_options(op)
     model = GPUModel("ConvNet", op, load_dic)
     model.start()

include/common/matrix.h

@@ -197,6 +197,7 @@ class Matrix {
      * Use transpose() if you want to get the transpose of this matrix.
      */
     inline void setTrans(bool trans) {
+        assert(!isView());
         _trans = trans ? CblasTrans : CblasNoTrans;
     }
 

include/pyconvnet.cuh

@@ -30,9 +30,6 @@
 #define _QUOTEME(x) #x
 #define QUOTEME(x) _QUOTEME(x)
 
-#ifdef EXEC
-int main(int argc, char** argv);
-#else
 extern "C" void INITNAME();
 
 PyObject* initModel(PyObject *self, PyObject *args);
@@ -41,7 +38,7 @@ PyObject* finishBatch(PyObject *self, PyObject *args);
 PyObject* checkGradients(PyObject *self, PyObject *args);
 PyObject* syncWithHost(PyObject *self, PyObject *args);
 PyObject* startMultiviewTest(PyObject *self, PyObject *args);
-#endif
+PyObject* startLabeler(PyObject *self, PyObject *args);
 
 #endif	/* PYCONVNET3_CUH */
 

include/worker.cuh

@@ -88,5 +88,15 @@ public:
     void run();
 };
 
+class LabelWorker : public Worker {
+protected:
+    CPUData* _data;
+    Matrix* _preds;
+    int _logregIdx;
+public:
+    LabelWorker(ConvNet& convNet, CPUData& data, Matrix& preds, int logregIdx);
+    void run();
+};
+
 #endif	/* WORKER_CUH */
 

options.py

@@ -150,7 +150,7 @@ def parse(self, eval_expr_defaults=False):
             # check requirements
             if o.prefixed_letter in dic:
                 for o2 in self.get_options_list(sort_order=self.SORT_LETTER):
-                    if o2.name in o.requires and o2.prefixed_letter not in dic and o2.default is None:
+                    if o2.name in o.requires and o2.prefixed_letter not in dic:
                         raise OptionMissingException("Option %s (%s) requires option %s (%s)" % (o.prefixed_letter, o.desc,
                                                                                                  o2.prefixed_letter, o2.desc))
         if eval_expr_defaults: