Create pipeline.py

pipeline.py

@@ -0,0 +1,28 @@
+from typing import  Dict
+import numpy as np
+
+class PreTrainedPipeline():
+    def __init__(self, path=""):
+        # IMPLEMENT_THIS
+        # Preload all the elements you are going to need at inference.
+        # For instance your model, processors, tokenizer that might be needed.
+        # This function is only called once, so do all the heavy processing I/O here"""
+        self.sampling_rate = # IMPLEMENT THIS
+        
+        raise NotImplementedError(
+            "Please implement PreTrainedPipeline __init__ function"
+        )
+
+    def __call__(self, inputs: np.array)-> Dict[str, str]:
+        """
+        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.
+        """
+        # IMPLEMENT_THIS
+        raise NotImplementedError(
+            "Please implement PreTrainedPipeline __call__ function"
+        )