🚧 Work in progress.

BrikerMan · May 9, 2020 · d7e4f72 · d7e4f72
1 parent 2b26333
commit d7e4f72
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Showing 6 changed files with 23 additions and 19 deletions.
diff --git a/kashgari/callbacks/eval_callBack.py b/kashgari/callbacks/eval_callBack.py
@@ -16,33 +16,37 @@
 class EvalCallBack(keras.callbacks.Callback):
 
     def __init__(self,
+                 kash_model: ABCTaskModel,
+                 x_data: List[Any],
+                 y_data: List[Any],
                  *,
-                 task_model: ABCTaskModel,
-                 valid_x: List[Any],
-                 valid_y: List[Any],
                  step: int = 5,
+                 truncating: bool = False,
                  batch_size: int = 256) -> None:
         """
         Evaluate callback, calculate precision, recall and f1
         Args:
-            task_model: the kashgari task model to evaluate
-            valid_x: feature data
-            valid_y: label data
+            kash_model: the kashgari task model to evaluate
+            x_data: feature data for evaluation
+            y_data: label data for evaluation
             step: step, default 5
+            truncating: truncating: remove values from sequences larger than `model.embedding.sequence_length`
             batch_size: batch size, default 256
         """
         super(EvalCallBack, self).__init__()
-        self.task_model: ABCTaskModel = task_model
-        self.valid_x = valid_x
-        self.valid_y = valid_y
+        self.kash_model: ABCTaskModel = kash_model
+        self.x_data = x_data
+        self.y_data = y_data
         self.step = step
+        self.truncating = truncating
         self.batch_size = batch_size
         self.logs: List[Dict] = []
 
     def on_epoch_end(self, epoch: int, logs: Any = None) -> None:
         if (epoch + 1) % self.step == 0:
-            report = self.task_model.evaluate(self.valid_x,
-                                              self.valid_y,
+            report = self.task_model.evaluate(self.x_data,
+                                              self.y_data,
+                                              truncating=self.truncating,
                                               batch_size=self.batch_size)
 
             self.logs.append({

diff --git a/kashgari/tasks/abs_task_model.py b/kashgari/tasks/abs_task_model.py
@@ -180,7 +180,9 @@ def evaluate(self,
                  *,
                  batch_size: int = 32,
                  digits: int = 4,
-                 debug_info: bool = False, ) -> Dict:
+                 truncating: bool = False,
+                 debug_info: bool = False,
+                 **kwargs: Dict) -> Dict:
         raise NotImplementedError
 
 

diff --git a/kashgari/tasks/classification/abc_model.py b/kashgari/tasks/classification/abc_model.py
@@ -241,15 +241,16 @@ def predict(self,  # type: ignore[override]
                 print('output argmax: {}'.format(pred.argmax(-1)))
         return res
 
-    def evaluate(self,
+    def evaluate(self,  # type: ignore[override]
                  x_data: TextSamplesVar,
                  y_data: Union[ClassificationLabelVar, MultiLabelClassificationLabelVar],
                  *,
                  batch_size: int = 32,
                  digits: int = 4,
                  multi_label_threshold: float = 0.5,
                  truncating: bool = False,
-                 debug_info: bool = False) -> Dict:
+                 debug_info: bool = False,
+                 **kwargs: Dict) -> Dict:
         y_pred = self.predict(x_data,
                               batch_size=batch_size,
                               truncating=truncating,

diff --git a/kashgari/tasks/labeling/abc_model.py b/kashgari/tasks/labeling/abc_model.py
@@ -271,7 +271,8 @@ def evaluate(self,
                  batch_size: int = 32,
                  digits: int = 4,
                  truncating: bool = False,
-                 debug_info: bool = False) -> Dict:
+                 debug_info: bool = False,
+                 **kwargs: Dict) -> Dict:
         """
         Build a text report showing the main labeling metrics.
 

diff --git a/kashgari/tasks/labeling/bi_gru_model.py b/kashgari/tasks/labeling/bi_gru_model.py
@@ -17,8 +17,6 @@
 
 class BiGRU_Model(ABCLabelingModel):
 
-    __task__ = 'labeling'
-
     @classmethod
     def default_hyper_parameters(cls) -> Dict[str, Dict[str, Any]]:
         return {
@@ -44,7 +42,6 @@ def build_model_arc(self) -> None:
         layer_stack = [
             L.Bidirectional(L.GRU(**config['layer_bgru']), name='layer_bgru'),
             L.Dropout(**config['layer_dropout'], name='layer_dropout'),
-            # L.Dense(output_dim, **config['layer_time_distributed']),
             L.TimeDistributed(L.Dense(output_dim, **config['layer_time_distributed']), name='layer_time_distributed'),
             L.Activation(**config['layer_activation'])
         ]

diff --git a/kashgari/tasks/labeling/cnn_lstm_model.py b/kashgari/tasks/labeling/cnn_lstm_model.py
@@ -42,7 +42,6 @@ def build_model_arc(self) -> None:
         layer_stack = [
             L.Bidirectional(L.GRU(**config['layer_bgru']), name='layer_bgru'),
             L.Dropout(**config['layer_dropout'], name='layer_dropout'),
-            # L.Dense(output_dim, **config['layer_time_distributed']),
             L.TimeDistributed(L.Dense(output_dim, **config['layer_time_distributed']), name='layer_time_distributed'),
             L.Activation(**config['layer_activation'])
         ]