Delete absolute mode path from train executor (blue-oil#431)

* delete absolute mode class path

* add task type to test config

lmnet/executor/train.py

@@ -26,6 +26,7 @@
 from lmnet.datasets.base import ObjectDetectionBase
 from lmnet.datasets.dataset_iterator import DatasetIterator
 from lmnet.datasets.tfds import TFDSClassification, TFDSObjectDetection
+from lmnet.common import Tasks
 
 
 def _save_checkpoint(saver, sess, global_step, step):
@@ -85,7 +86,7 @@ def start_training(config):
 
     graph = tf.Graph()
     with graph.as_default():
-        if ModelClass.__module__.startswith("lmnet.networks.object_detection"):
+        if config.TASK == Tasks.OBJECT_DETECTION:
             model = ModelClass(
                 classes=train_dataset.classes,
                 num_max_boxes=train_dataset.num_max_boxes,
@@ -105,7 +106,7 @@ def start_training(config):
         images_placeholder, labels_placeholder = model.placeholders()
 
         output = model.inference(images_placeholder, is_training_placeholder)
-        if ModelClass.__module__.startswith("lmnet.networks.object_detection"):
+        if config.TASK == Tasks.OBJECT_DETECTION:
             loss = model.loss(output, labels_placeholder, global_step)
         else:
             loss = model.loss(output, labels_placeholder)

lmnet/tests/lmnet_tests/networks_tests/classification_test/test_darknet.py

@@ -22,6 +22,7 @@
 from lmnet.networks.classification.darknet import Darknet
 from lmnet.utils.executor import prepare_dirs
 from lmnet.pre_processor import Resize
+from lmnet.common import Tasks
 from executor.train import start_training
 
 
@@ -50,6 +51,7 @@ def test_training():
     config.KEEP_CHECKPOINT_MAX = 5
     config.SUMMARISE_STEPS = 1
     config.IS_PRETRAIN = False
+    config.TASK = Tasks.CLASSIFICATION
 
     # network model config
     config.NETWORK = EasyDict()

lmnet/tests/lmnet_tests/networks_tests/classification_test/test_lmnet_quantize.py

@@ -26,6 +26,7 @@
     binary_mean_scaling_quantizer,
     linear_mid_tread_half_quantizer,
 )
+from lmnet.common import Tasks
 from executor.train import start_training
 
 # Apply reset_default_graph() in conftest.py to all tests in this file.
@@ -53,6 +54,7 @@ def test_training():
     config.KEEP_CHECKPOINT_MAX = 5
     config.SUMMARISE_STEPS = 1
     config.IS_PRETRAIN = False
+    config.TASK = Tasks.CLASSIFICATION
 
     # network model config
     config.NETWORK = EasyDict()

lmnet/tests/lmnet_tests/networks_tests/object_detection_tests/test_yolo_v1.py

@@ -23,6 +23,7 @@
 from lmnet.networks.object_detection.yolo_v1 import YoloV1
 from lmnet.utils.executor import prepare_dirs
 from lmnet.pre_processor import ResizeWithGtBoxes
+from lmnet.common import Tasks
 from executor.train import start_training
 
 # Apply reset_default_graph() in conftest.py to all tests in this file.
@@ -279,6 +280,7 @@ def test_training():
     config.KEEP_CHECKPOINT_MAX = 5
     config.SUMMARISE_STEPS = 1
     config.IS_PRETRAIN = False
+    config.TASK = Tasks.OBJECT_DETECTION
 
     # network model config
     config.NETWORK = EasyDict()

lmnet/tests/lmnet_tests/networks_tests/object_detection_tests/test_yolo_v2.py

@@ -30,6 +30,7 @@
     ExcludeLowScoreBox,
     NMS,
 )
+from lmnet.common import Tasks
 
 # Apply reset_default_graph() in conftest.py to all tests in this file.
 # Set test environment
@@ -713,6 +714,7 @@ def test_training():
     config.KEEP_CHECKPOINT_MAX = 5
     config.SUMMARISE_STEPS = 1
     config.IS_PRETRAIN = False
+    config.TASK = Tasks.OBJECT_DETECTION
 
     # network model config
     config.NETWORK = EasyDict()

lmnet/tests/lmnet_tests/networks_tests/object_detection_tests/test_yolo_v2_quantize.py

@@ -26,6 +26,7 @@
     binary_channel_wise_mean_scaling_quantizer,
     linear_mid_tread_half_quantizer,
 )
+from lmnet.common import Tasks
 from executor.train import start_training
 
 
@@ -51,6 +52,7 @@ def test_training():
     config.KEEP_CHECKPOINT_MAX = 5
     config.SUMMARISE_STEPS = 1
     config.IS_PRETRAIN = False
+    config.TASK = Tasks.OBJECT_DETECTION
 
     # network model config
     config.NETWORK = EasyDict()

lmnet/tests/lmnet_tests/networks_tests/segmentation_tests/test_lm_bisenet.py

@@ -30,6 +30,7 @@
 )
 from lmnet.pre_processor import Resize
 from lmnet.utils.executor import prepare_dirs
+from lmnet.common import Tasks
 
 
 # Apply reset_default_graph() and set_test_environment() in conftest.py to all tests in this file.
@@ -56,6 +57,7 @@ def test_training():
     config.KEEP_CHECKPOINT_MAX = 5
     config.SUMMARISE_STEPS = 1
     config.IS_PRETRAIN = False
+    config.TASK = Tasks.SEMANTIC_SEGMENTATION
 
     # network model config
     config.NETWORK = EasyDict()