hylee
commited on
Commit
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1f758f7
1
Parent(s):
d0d0944
try to log
Browse files- handler.py +10 -5
handler.py
CHANGED
@@ -10,8 +10,7 @@ from utils import MultiHeadModel, BertInputBuilder, get_num_words
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import transformers
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from transformers import BertTokenizer, BertForSequenceClassification
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import psutil
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-
import
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-
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transformers.logging.set_verbosity_debug()
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@@ -244,33 +243,39 @@ class EndpointHandler():
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print("Running inference on %d examples..." % transcript.length())
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cpu_percent = psutil.cpu_percent()
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-
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# Uptake
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uptake_model = UptakeModel(
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self.device, self.tokenizer, self.input_builder)
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uptake_model.run_inference(transcript, min_prev_words=params['uptake_min_num_words'],
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uptake_speaker=params.pop("uptake_speaker", None))
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cpu_percent = psutil.cpu_percent()
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-
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del uptake_model
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cpu_percent = psutil.cpu_percent()
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-
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# Reasoning
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reasoning_model = ReasoningModel(
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self.device, self.tokenizer, self.input_builder)
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reasoning_model.run_inference(transcript)
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cpu_percent = psutil.cpu_percent()
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print(f"CPU Usage after model 2 loaded: {cpu_percent}%")
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del reasoning_model
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cpu_percent = psutil.cpu_percent()
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print(f"CPU Usage after model 2 deleted: {cpu_percent}%")
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# Question
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question_model = QuestionModel(
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self.device, self.tokenizer, self.input_builder)
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question_model.run_inference(transcript)
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cpu_percent = psutil.cpu_percent()
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print(f"CPU Usage after model 3 loaded: {cpu_percent}%")
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del question_model
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cpu_percent = psutil.cpu_percent()
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print(f"CPU Usage after model 3 deleted: {cpu_percent}%")
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return transcript.to_dict()
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import transformers
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from transformers import BertTokenizer, BertForSequenceClassification
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import psutil
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+
from transformers.utils import logging
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transformers.logging.set_verbosity_debug()
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print("Running inference on %d examples..." % transcript.length())
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cpu_percent = psutil.cpu_percent()
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logging.set_verbosity_info()
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logger = logging.get_logger("transformers")
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logger.info(f"CPU Usage before models loaded: {cpu_percent}%")
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# Uptake
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uptake_model = UptakeModel(
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self.device, self.tokenizer, self.input_builder)
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uptake_model.run_inference(transcript, min_prev_words=params['uptake_min_num_words'],
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uptake_speaker=params.pop("uptake_speaker", None))
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cpu_percent = psutil.cpu_percent()
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logger.info(f"CPU Usage after model 1 loaded: {cpu_percent}%")
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del uptake_model
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cpu_percent = psutil.cpu_percent()
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logger.info(f"CPU Usage after model 1 deleted: {cpu_percent}%")
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# Reasoning
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reasoning_model = ReasoningModel(
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self.device, self.tokenizer, self.input_builder)
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reasoning_model.run_inference(transcript)
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cpu_percent = psutil.cpu_percent()
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logger.info(f"CPU Usage after model 2 loaded: {cpu_percent}%")
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print(f"CPU Usage after model 2 loaded: {cpu_percent}%")
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del reasoning_model
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cpu_percent = psutil.cpu_percent()
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logger.info(f"CPU Usage after model 2 deleted: {cpu_percent}%")
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print(f"CPU Usage after model 2 deleted: {cpu_percent}%")
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# Question
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question_model = QuestionModel(
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self.device, self.tokenizer, self.input_builder)
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question_model.run_inference(transcript)
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cpu_percent = psutil.cpu_percent()
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logger.info(f"CPU Usage after model 3 loaded: {cpu_percent}%")
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print(f"CPU Usage after model 3 loaded: {cpu_percent}%")
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del question_model
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cpu_percent = psutil.cpu_percent()
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logger.info(f"CPU Usage after model 3 deleted: {cpu_percent}%")
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print(f"CPU Usage after model 3 deleted: {cpu_percent}%")
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return transcript.to_dict()
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