import pytest from transformers import AutoTokenizer, GenerationConfig import colossalai from colossalai.inference.config import InferenceConfig from colossalai.inference.core.engine import InferenceEngine from colossalai.testing import spawn def check_inference_engine(test_cai=False): tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/llama-tokenizer") model = transformers.LlamaForCausalLM( transformers.LlamaConfig( vocab_size=50000, hidden_size=512, intermediate_size=1536, num_attention_heads=4, num_hidden_layers=4 ) ) inputs = [ "介绍一下今天的北京", "介绍一下武汉", ] if test_cai: inference_config = InferenceConfig(max_output_len=1) inference_engine = InferenceEngine(model, tokenizer, inference_config, verbose=True) inference_engine.add_request(prompts=inputs) assert inference_engine.request_handler._has_waiting() generation_config = GenerationConfig(top_k=2, top_p=0.8, do_sample=True) outputs = inference_engine.generate(generation_config) else: tokenizer.pad_token = tokenizer.eos_token tokenizer.pad_token_id = tokenizer.eos_token_id inputs = tokenizer.batch_encode_plus(inputs, padding=True, return_tensors="pt")["input_ids"] generation_config = GenerationConfig( top_k=2, top_p=0.8, do_sample=True, pad_token_id=tokenizer.pad_token_id, max_new_tokens=1 ) outputs = model.generate(inputs, generation_config=generation_config) outputs = tokenizer.batch_decode(outputs, skip_special_tokens=True) return outputs def run_dist(rank, world_size, port): colossalai.launch(config={}, rank=rank, world_size=world_size, port=port, host="localhost") check_inference_engine(True) check_inference_engine(False) # TODO: There are some in sampler # for s1, s2 in zip(cai_outputs, transformer_outputs): # assert s1 == s2 @pytest.mark.dist def test_inference_engine(): spawn(run_dist, 1) if __name__ == "__main__": test_inference_engine()