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raise exception on device error (#1342)
* display the unavailable torch device on error * Raise exception on device error --------- Signed-off-by: Emmanuel Ferdman <emmanuelferdman@gmail.com>
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1 changed files with 2 additions and 2 deletions
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@ -243,7 +243,7 @@ def prefill_and_generate(model, tokenizer, inputs, max_new_tokens=10000, use_cud
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elif torch.xpu.is_available():
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elif torch.xpu.is_available():
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torch.xpu.set_device(torch_device)
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torch.xpu.set_device(torch_device)
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else:
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else:
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RuntimeError("The device: {torch_device} is not available")
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raise RuntimeError(f"The device: {torch_device} is not available")
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inputs_embeds = model.model.embed_tokens(cur_token.to("cpu")).to(torch_device)
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inputs_embeds = model.model.embed_tokens(cur_token.to("cpu")).to(torch_device)
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# with torch.cuda.stream(custom_stream):
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# with torch.cuda.stream(custom_stream):
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logits=model(inputs_embeds=inputs_embeds,
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logits=model(inputs_embeds=inputs_embeds,
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@ -284,7 +284,7 @@ def prefill_and_generate(model, tokenizer, inputs, max_new_tokens=10000, use_cud
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elif torch.xpu.is_available():
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elif torch.xpu.is_available():
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torch.xpu.set_device(torch_device)
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torch.xpu.set_device(torch_device)
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else:
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else:
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RuntimeError("The device: {torch_device} is not available")
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raise RuntimeError(f"The device: {torch_device} is not available")
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with torch.no_grad():
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with torch.no_grad():
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stream = TextStreamer(tokenizer)
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stream = TextStreamer(tokenizer)
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