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Merged
regisss merged 1 commit into from
Jan 5, 2024
Merged

Update CI diff file #624

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31 changes: 17 additions & 14 deletions tests/example_diff/run_generation.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -498,25 +498,28 @@
< help="Whether to use 16-bit (mixed) precision (through NVIDIA apex) instead of 32-bit",
---
> help="Whether to enable Habana Flash Attention, provided that the model supports it.",
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< parser.add_argument("--jit", action="store_true", help="Whether or not to use jit trace to accelerate inference")
< args = parser.parse_args()
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---
> parser.add_argument("--temperature", default=1.0, type=float, help="Temperature value for text generation")
> parser.add_argument("--top_p", default=1.0, type=float, help="Top_p value for generating text via sampling")
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< # Initialize the distributed state.
< distributed_state = PartialState(cpu=args.use_cpu)
---
> args = parser.parse_args()
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< logger.warning(f"device: {distributed_state.device}, 16-bits inference: {args.fp16}")
---
> if not args.use_hpu_graphs:
> args.limit_hpu_graphs = False
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< if args.seed is not None:
< set_seed(args.seed)
---
> return args
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< # Initialize the model and tokenizer
< try:
< args.model_type = args.model_type.lower()
Expand Down Expand Up @@ -545,7 +548,7 @@
< if requires_preprocessing:
< prepare_input = PREPROCESSING_FUNCTIONS.get(args.model_type)
< preprocessed_prompt_text = prepare_input(args, model, tokenizer, prompt_text)
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< if model.__class__.__name__ in ["TransfoXLLMHeadModel"]:
< tokenizer_kwargs = {"add_space_before_punct_symbol": True}
< else:
Expand All @@ -555,7 +558,7 @@
> parser = argparse.ArgumentParser()
> args = setup_parser(parser)
> model, tokenizer, generation_config = initialize_model(args, logger)
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< encoded_prompt = tokenizer.encode(
< preprocessed_prompt_text, add_special_tokens=False, return_tensors="pt", **tokenizer_kwargs
< )
Expand All @@ -565,7 +568,7 @@
< encoded_prompt = encoded_prompt.to(distributed_state.device)
---
> import habana_frameworks.torch.hpu as torch_hpu
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< if encoded_prompt.size()[-1] == 0:
< input_ids = None
---
Expand Down Expand Up @@ -713,7 +716,7 @@
> print(f"Graph compilation duration = {compilation_duration} seconds")
> print(separator)
> print()
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< input_ids = encoded_prompt
---
> # Downloading and loading a dataset from the hub.
Expand All @@ -734,7 +737,7 @@
> .shuffle()
> .select(range(args.dataset_max_samples if args.dataset_max_samples > 0 else (raw_dataset[split]).num_rows))
> )
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< if args.jit:
< jit_input_texts = ["enable jit"]
< jit_inputs = prepare_jit_inputs(jit_input_texts, model, tokenizer)
Expand All @@ -751,7 +754,7 @@
> logger.info(
> f"No column name was given so automatically choosing '{column_name}' for prompts. If you would like to use another column of the dataset, you can set the argument `--column_name`."
> )
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< sig = inspect.signature(model.__call__)
< jit_inputs = tuple(jit_inputs[key] for key in sig.parameters if jit_inputs.get(key, None) is not None)
< traced_model = torch.jit.trace(model, jit_inputs, strict=False)
Expand Down Expand Up @@ -813,7 +816,7 @@
> preprocess_function,
> batched=True,
> desc="Running tokenizer on dataset",
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> # After tokenization, we can remove the column of interest
> raw_dataset = raw_dataset.remove_columns([column_name])
> raw_dataset.set_format(type="torch")
Expand Down Expand Up @@ -892,13 +895,13 @@
> )
> print(separator)
> t_end = time.time()
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< generated_sequences.append(total_sequence)
< print(total_sequence)
---
> throughput = total_new_tokens_generated / duration
> # Print Stats
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< return generated_sequences
---
> stats = f"Throughput (including tokenization) = {throughput} tokens/second"
Expand Down