toy example of training model for turing

Summary:
Add toy example to illustrate the Turing workflow.
- modify the model building, add converting to helios step. Note that we need to hide this from OSS, so create FB version of the runner, in order to modify `build_model` and `get_default_cfg`.
- make the `D2 (https://github.com/facebookresearch/d2go/commit/7992f91324aee6ae59795063a007c6837e60cdb8)GoCompatibleMNISTRunner` up-to-date, and use the "tutorial" meta-arch for writing unit test since it's the simplest model. Note that even `TutorialNet` is very simple, there's still a constraint that the FC has to run on 4D tensor with 1x1 spatial dimension because it's been mapped to 1x1 Conv by Helios, modify the `TutorialNet` to make it compatible.

Reviewed By: newstzpz

Differential Revision: D31705305

fbshipit-source-id: 77949dfbf08252be5495e9273210274c8ad86abb

d2go/runner/default_runner.py

@@ -232,7 +232,8 @@ class Detectron2GoRunner(BaseRunner):
         _C = super(Detectron2GoRunner, Detectron2GoRunner).get_default_cfg()
         return get_default_cfg(_C)
 
-    def build_model(self, cfg, eval_only=False):
+    # temporary API
+    def _build_model(self, cfg, eval_only=False):
         # build_model might modify the cfg, thus clone
         cfg = cfg.clone()
 
@@ -266,6 +267,11 @@ class Detectron2GoRunner(BaseRunner):
             if cfg.MODEL_EMA.ENABLED and cfg.MODEL_EMA.USE_EMA_WEIGHTS_FOR_EVAL_ONLY:
                 model_ema.apply_model_ema(model)
 
+        return model
+
+    def build_model(self, cfg, eval_only=False):
+        model = self._build_model(cfg, eval_only)
+
         # Note: the _visualize_model API is experimental
         if comm.is_main_process():
             if hasattr(model, "_visualize_model"):
@@ -602,15 +608,18 @@ class Detectron2GoRunner(BaseRunner):
         return QATHook(cfg, self.build_detection_train_loader)
 
 
+def _add_rcnn_default_config(_C):
+    _C.EXPORT_CAFFE2 = CfgNode()
+    _C.EXPORT_CAFFE2.USE_HEATMAP_MAX_KEYPOINT = False
+
+    _C.RCNN_PREPARE_FOR_EXPORT = "default_rcnn_prepare_for_export"
+    _C.RCNN_PREPARE_FOR_QUANT = "default_rcnn_prepare_for_quant"
+    _C.RCNN_PREPARE_FOR_QUANT_CONVERT = "default_rcnn_prepare_for_quant_convert"
+
+
 class GeneralizedRCNNRunner(Detectron2GoRunner):
     @staticmethod
     def get_default_cfg():
         _C = super(GeneralizedRCNNRunner, GeneralizedRCNNRunner).get_default_cfg()
-        _C.EXPORT_CAFFE2 = CfgNode()
-        _C.EXPORT_CAFFE2.USE_HEATMAP_MAX_KEYPOINT = False
-
-        _C.RCNN_PREPARE_FOR_EXPORT = "default_rcnn_prepare_for_export"
-        _C.RCNN_PREPARE_FOR_QUANT = "default_rcnn_prepare_for_quant"
-        _C.RCNN_PREPARE_FOR_QUANT_CONVERT = "default_rcnn_prepare_for_quant_convert"
-
+        _add_rcnn_default_config(_C)
         return _C