Delete pipeline.py

pipeline.py

@@ -1,31 +0,0 @@
-from torchvision import transforms
-from pair_classification import PairClassificationPipeline
-
-class PreTrainedPipeline():
-    def __init__(self, path):
-        """
-        Initialize model
-        """
-        model_flag = 'google/vit-base-patch16-224-in21k'
-        # self.processor = feature_extractor = ViTFeatureExtractor.from_pretrained(model_flag)
-        self.pipe = pipeline("pair-classification", model=model_flag , feature_extractor=model_flag , 
-                model_kwargs={'num_labels':len(label2id),
-                            'label2id':label2id,
-                            'id2label':id2label,
-                            'num_channels':6,
-                            'ignore_mismatched_sizes': True })
-        self.model = self.pipe.model.from_pretrained(path)
-        
-
-    def __call__(self, inputs):
-        """
-        Args:
-            inputs (:obj:`np.array`):
-                The raw waveform of audio received. By default at 16KHz.
-        Return:
-            A :obj:`dict`:. The object return should be liked {"text": "XXX"} containing
-            the detected text from the input audio.
-        """
-        # input_values = self.processor(inputs, return_tensors="pt", sampling_rate=self.sampling_rate).input_values  # Batch size 1
-        # logits = self.model(input_values).logits.cpu().detach().numpy()[0]
-        return self.pipe(inputs)