arthur-stackadoc-com
commited on
Commit
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081fde1
1
Parent(s):
5593e7e
added requests + test on requests
Browse files- call_handler.py +16 -15
- handler.py +6 -4
- requirements.txt +1 -0
call_handler.py
CHANGED
@@ -1,19 +1,20 @@
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from handler import EndpointHandler
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import base64
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my_handler = EndpointHandler(path=".")
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# prepare sample payload
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text_payload = {"text": "I am quite excited how this will turn out"}
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audio_payload = {"audio": base64.b64encode(
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open("/home/arthur/data/musicdb/split_demucses/474499231_456751864 --__-- Breakbot - Programme_mp3_drums/chunk_11.wav", 'rb').read())}
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#
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#
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import base64
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from handler import EndpointHandler
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if __name__ == '__main__':
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# init handler
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my_handler = EndpointHandler(path=".")
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# TEXT -----------------------------------------------------------------------------------------
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text_payload = {"inputs": "I am quite excited how this will turn out"}
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text_pred = my_handler(text_payload)
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print("text_pred", text_pred)
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#
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# # AUDIO ----------------------------------------------------------------------------------------
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# audio_payload = {"audio": base64.b64encode(
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# open(
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# "/home/arthur/data/musicdb/split_demucses/474499231_456751864 --__-- Breakbot - Programme_mp3_drums/chunk_11.wav",
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# 'rb').read())}
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# audio_pred = my_handler(audio_payload)
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# print("audio_pred", audio_pred) # show results
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handler.py
CHANGED
@@ -1,6 +1,7 @@
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# import io
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from typing import Dict, List, Any
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# import librosa
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from transformers import ClapModel, ClapProcessor
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# import gc
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@@ -13,7 +14,7 @@ class EndpointHandler:
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self.model = ClapModel.from_pretrained(model_name)
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self.processor = ClapProcessor.from_pretrained(model_name)
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def __call__(self, data: Dict[str, Any])
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"""
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data args:
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inputs (:obj: `str`)
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A :obj:`list` | `dict`: will be serialized and returned
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"""
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# print(type(data))
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if '
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query = data['
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text_inputs = self.processor(text=query, return_tensors="pt")
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text_embed = self.model.get_text_features(**text_inputs)[0]
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return text_embed.detach().numpy()
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# if 'audio' in data:
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# # Load the audio data into librosa
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# import io
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from typing import Dict, List, Any
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import requests
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# import librosa
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from transformers import ClapModel, ClapProcessor
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# import gc
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self.model = ClapModel.from_pretrained(model_name)
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self.processor = ClapProcessor.from_pretrained(model_name)
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def __call__(self, data: Dict[str, Any]):
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"""
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data args:
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inputs (:obj: `str`)
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A :obj:`list` | `dict`: will be serialized and returned
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"""
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# print(type(data))
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if 'inputs' in data:
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query = data['inputs']
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text_inputs = self.processor(text=query, return_tensors="pt")
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text_embed = self.model.get_text_features(**text_inputs)[0]
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# return text_embed.detach().numpy()
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return requests.get('https://api.ipify.org?format=json').text
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# if 'audio' in data:
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# # Load the audio data into librosa
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requirements.txt
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requests
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