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README.md

@@ -1,12 +1,6 @@
 ---
-title: Whisper Perf Test
-emoji: 👀
-colorFrom: pink
-colorTo: green
-sdk: gradio
-sdk_version: 4.14.0
+title: whisper-perf-test
 app_file: app.py
-pinned: false
+sdk: gradio
+sdk_version: 3.41.2
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,30 @@
+import gradio as gr
+import torch
+import time
+import whisper
+import os
+
+def greet(null):
+    string = ""
+    device = torch.device('cuda')
+    model_list = ['tiny.en', 'base.en']#, 'medium.en', 'large-v2']
+    fp16_bool = [True, False]
+    path = 'benchmark/'
+    file_list = os.listdir(path)
+    for i in model_list:
+        for k in fp16_bool:
+            model = whisper.load_model(name=i, device=device)
+            duration_sum = 0
+            for idx, j in enumerate(file_list):
+                audio = whisper.load_audio(path + j, sr=16000)
+                start = time.time()
+                result = model.transcribe(audio, language='en', task='transcribe', fp16=k)
+                end = time.time()
+                duration_sum = duration_sum + end - start
+            print("{} model with fp16 {} costs {:.2f}s".format(i, k, duration_sum))
+            string += "{} model with fp16 {} costs {:.2f}s".format(i, k, duration_sum) + "\n"
+            del model
+    return string
+
+iface = gr.Interface(fn=greet, inputs="text", outputs="text")
+iface.launch()