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•
b760fd0
1
Parent(s):
f4ed0cd
Commented torch_directml
Browse files- AI/question_answering.py +6 -6
- AI/sentiment_analysis.py +6 -6
- AI/summarization.py +6 -6
- AI/text_generation.py +6 -6
- AI/zero_shot_classification.py +6 -6
- requirements.txt +0 -1
AI/question_answering.py
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@@ -2,7 +2,7 @@
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# Creation date: 2024-01-10
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import torch
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import torch_directml
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from transformers import pipeline
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def getDevice(DEVICE):
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@@ -13,9 +13,9 @@ def getDevice(DEVICE):
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elif DEVICE == "cuda":
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device = torch.device("cuda")
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dtype = torch.float16
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elif DEVICE == "directml":
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-
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return device
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def loadGenerator(device):
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@@ -33,5 +33,5 @@ def clearCache(DEVICE, generator):
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generator.tokenizer.save_pretrained("cache")
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generator.model.save_pretrained("cache")
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del generator
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if DEVICE == "directml":
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# Creation date: 2024-01-10
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import torch
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# import torch_directml
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from transformers import pipeline
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def getDevice(DEVICE):
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elif DEVICE == "cuda":
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device = torch.device("cuda")
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dtype = torch.float16
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# elif DEVICE == "directml":
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# device = torch_directml.device()
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# dtype = torch.float16
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return device
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def loadGenerator(device):
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generator.tokenizer.save_pretrained("cache")
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generator.model.save_pretrained("cache")
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del generator
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# if DEVICE == "directml":
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# torch_directml.empty_cache()
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AI/sentiment_analysis.py
CHANGED
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@@ -2,7 +2,7 @@
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# Creation date: 2024-01-10
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import torch
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import torch_directml
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from transformers import pipeline
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def getDevice(DEVICE):
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@@ -13,9 +13,9 @@ def getDevice(DEVICE):
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elif DEVICE == "cuda":
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device = torch.device("cuda")
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dtype = torch.float16
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elif DEVICE == "directml":
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return device
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def loadClassifier(device):
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@@ -30,5 +30,5 @@ def clearCache(DEVICE, classifier):
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classifier.tokenizer.save_pretrained("cache")
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classifier.model.save_pretrained("cache")
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del classifier
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if DEVICE == "directml":
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# Creation date: 2024-01-10
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import torch
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# import torch_directml
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from transformers import pipeline
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def getDevice(DEVICE):
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elif DEVICE == "cuda":
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device = torch.device("cuda")
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dtype = torch.float16
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# elif DEVICE == "directml":
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# device = torch_directml.device()
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# dtype = torch.float16
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return device
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def loadClassifier(device):
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classifier.tokenizer.save_pretrained("cache")
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classifier.model.save_pretrained("cache")
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del classifier
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# if DEVICE == "directml":
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# torch_directml.empty_cache()
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AI/summarization.py
CHANGED
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@@ -2,7 +2,7 @@
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# Creation date: 2024-01-10
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import torch
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import torch_directml
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from transformers import pipeline
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def getDevice(DEVICE):
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@@ -13,9 +13,9 @@ def getDevice(DEVICE):
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elif DEVICE == "cuda":
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device = torch.device("cuda")
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dtype = torch.float16
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-
elif DEVICE == "directml":
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return device
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def loadSummarizer(device):
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@@ -30,5 +30,5 @@ def clearCache(DEVICE, summarizer):
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summarizer.tokenizer.save_pretrained("cache")
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summarizer.model.save_pretrained("cache")
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del summarizer
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if DEVICE == "directml":
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# Creation date: 2024-01-10
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import torch
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# import torch_directml
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from transformers import pipeline
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def getDevice(DEVICE):
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elif DEVICE == "cuda":
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device = torch.device("cuda")
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dtype = torch.float16
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# elif DEVICE == "directml":
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# device = torch_directml.device()
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# dtype = torch.float16
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return device
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def loadSummarizer(device):
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summarizer.tokenizer.save_pretrained("cache")
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summarizer.model.save_pretrained("cache")
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del summarizer
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# if DEVICE == "directml":
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# torch_directml.empty_cache()
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AI/text_generation.py
CHANGED
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@@ -2,7 +2,7 @@
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# Creation date: 2024-01-10
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import torch
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-
import torch_directml
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from transformers import pipeline
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def getDevice(DEVICE):
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@@ -13,9 +13,9 @@ def getDevice(DEVICE):
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elif DEVICE == "cuda":
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device = torch.device("cuda")
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dtype = torch.float16
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-
elif DEVICE == "directml":
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-
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-
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return device
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def loadGenerator(device):
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@@ -30,5 +30,5 @@ def clearCache(DEVICE, generator):
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generator.tokenizer.save_pretrained("cache")
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generator.model.save_pretrained("cache")
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del generator
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-
if DEVICE == "directml":
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-
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# Creation date: 2024-01-10
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import torch
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# import torch_directml
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from transformers import pipeline
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def getDevice(DEVICE):
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elif DEVICE == "cuda":
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device = torch.device("cuda")
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dtype = torch.float16
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# elif DEVICE == "directml":
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# device = torch_directml.device()
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# dtype = torch.float16
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return device
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def loadGenerator(device):
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generator.tokenizer.save_pretrained("cache")
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generator.model.save_pretrained("cache")
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del generator
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# if DEVICE == "directml":
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# torch_directml.empty_cache()
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AI/zero_shot_classification.py
CHANGED
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@@ -2,7 +2,7 @@
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# Creation date: 2024-01-10
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import torch
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-
import torch_directml
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from transformers import pipeline
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def getDevice(DEVICE):
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@@ -13,9 +13,9 @@ def getDevice(DEVICE):
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elif DEVICE == "cuda":
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device = torch.device("cuda")
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dtype = torch.float16
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-
elif DEVICE == "directml":
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-
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-
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return device
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def loadGenerator(device):
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@@ -30,5 +30,5 @@ def clearCache(DEVICE, generator):
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generator.tokenizer.save_pretrained("cache")
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generator.model.save_pretrained("cache")
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del generator
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-
if DEVICE == "directml":
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-
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# Creation date: 2024-01-10
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import torch
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+
# import torch_directml
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from transformers import pipeline
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def getDevice(DEVICE):
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elif DEVICE == "cuda":
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device = torch.device("cuda")
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dtype = torch.float16
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+
# elif DEVICE == "directml":
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# device = torch_directml.device()
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# dtype = torch.float16
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return device
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def loadGenerator(device):
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generator.tokenizer.save_pretrained("cache")
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generator.model.save_pretrained("cache")
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del generator
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# if DEVICE == "directml":
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# torch_directml.empty_cache()
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requirements.txt
CHANGED
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@@ -1,3 +1,2 @@
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torch
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torch_directml
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transformers
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torch
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transformers
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