import pytest @pytest.fixture(scope="module") def flash_llama_fp8_kv_cache_handle(launcher): with launcher( "neuralmagic/Meta-Llama-3-8B-Instruct-FP8-KV", num_shard=2, kv_cache_dtype="fp8_e4m3fn", ) as handle: yield handle @pytest.fixture(scope="module") async def flash_llama_fp8_kv_cache(flash_llama_fp8_kv_cache_handle): await flash_llama_fp8_kv_cache_handle.health(300) return flash_llama_fp8_kv_cache_handle.client @pytest.mark.release @pytest.mark.asyncio @pytest.mark.private async def test_flash_llama_fp8_kv_cache(flash_llama_fp8_kv_cache, response_snapshot): response = await flash_llama_fp8_kv_cache.generate( "What is deep learning?", max_new_tokens=10, decoder_input_details=True ) assert ( response.generated_text == " Deep learning is a subset of machine learning that involves" ) assert response.details.generated_tokens == 10 assert response == response_snapshot @pytest.mark.release @pytest.mark.asyncio @pytest.mark.private async def test_flash_llama_fp8_kv_cache_all_params( flash_llama_fp8_kv_cache, response_snapshot ): response = await flash_llama_fp8_kv_cache.generate( "What is deep learning?", max_new_tokens=10, repetition_penalty=1.2, return_full_text=True, stop_sequences=["test"], temperature=0.5, top_p=0.9, top_k=10, truncate=5, typical_p=0.9, watermark=True, decoder_input_details=True, seed=0, ) assert response == response_snapshot @pytest.mark.release @pytest.mark.asyncio @pytest.mark.private async def test_flash_llama_fp8_kv_cache_load( flash_llama_fp8_kv_cache, generate_load, response_snapshot ): responses = await generate_load( flash_llama_fp8_kv_cache, "What is deep learning?", max_new_tokens=10, n=4 ) assert len(responses) == 4 assert ( responses[0].generated_text == " Deep learning is a subset of machine learning that involves" ) assert all( [r.generated_text == responses[0].generated_text for r in responses] ), f"Different messages : {[r.generated_text for r in responses]}" assert responses == response_snapshot