mirror of
https://github.com/huggingface/text-generation-inference.git
synced 2025-04-23 16:02:10 +00:00
change defualt behaviour to only run a subset of all the models
This commit is contained in:
baptiste
parent
2821274a88
commit
d98ae4890e
@ -54,6 +54,11 @@ run-integration-tests:
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HF_TOKEN=`cat ${HOME}/.cache/huggingface/token` \
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pytest --durations=0 -s -vv ${root_dir}/integration-tests --gaudi
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run-integration-tests-with-all-models:
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DOCKER_VOLUME=${root_dir}/data \
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HF_TOKEN=`cat ${HOME}/.cache/huggingface/token` \
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pytest --durations=0 -s -vv ${root_dir}/integration-tests --gaudi --gaudi-all-models
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# This is used to capture the expected outputs for the integration tests offering an easy way to add more models to the integration tests
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capture-expected-outputs-for-integration-tests:
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DOCKER_VOLUME=${root_dir}/data \
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@ -74,6 +74,12 @@ def pytest_addoption(parser):
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parser.addoption(
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"--gaudi", action="store_true", default=False, help="run gaudi tests"
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)
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parser.addoption(
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"--gaudi-all-models",
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action="store_true",
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default=False,
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help="Run tests for all models instead of just the default subset",
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)
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def pytest_configure(config):
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@ -1,30 +1,39 @@
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from typing import Any, Dict
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from typing import Any, Dict, Generator
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from _pytest.fixtures import SubRequest
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from text_generation import AsyncClient
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import pytest
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def pytest_configure(config):
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config.addinivalue_line(
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"markers", "gaudi_all_models: mark test to run with all models"
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)
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# The "args" values in TEST_CONFIGS are not optimized for speed but only check that the inference is working for the different models architectures.
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TEST_CONFIGS = {
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# "meta-llama/Llama-3.1-8B-Instruct-shared": {
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# "model_id": "meta-llama/Llama-3.1-8B-Instruct",
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# "input": "What is Deep Learning?",
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# "expected_greedy_output": " A Beginner’s Guide\nDeep learning is a subset of machine learning that involves the use of artificial neural networks to analyze and interpret data. It is a type of",
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# "expected_batch_output": " A Beginner’s Guide\nDeep learning is a subset of machine learning that involves the use of artificial neural networks to analyze and interpret data. It is a type of",
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# "args": [
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# "--sharded",
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# "true",
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# "--num-shard",
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# "8",
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# "--max-input-tokens",
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# "512",
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# "--max-total-tokens",
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# "1024",
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# "--max-batch-size",
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# "8",
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# "--max-batch-prefill-tokens",
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# "2048",
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# ],
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# },
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"meta-llama/Llama-3.1-8B-Instruct-shared": {
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"model_id": "meta-llama/Llama-3.1-8B-Instruct",
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"input": "What is Deep Learning?",
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"expected_greedy_output": " A Beginner’s Guide\nDeep learning is a subset of machine learning that involves the use of artificial neural networks to analyze and interpret data. It is a type of",
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"expected_batch_output": " A Beginner’s Guide\nDeep learning is a subset of machine learning that involves the use of artificial neural networks to analyze and interpret data. It is a type of",
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"args": [
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"--sharded",
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"true",
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"--num-shard",
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"8",
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"--max-input-tokens",
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"512",
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"--max-total-tokens",
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"1024",
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"--max-batch-size",
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"8",
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"--max-batch-prefill-tokens",
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"2048",
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],
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"run_by_default": True,
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},
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"meta-llama/Llama-3.1-8B-Instruct": {
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"model_id": "meta-llama/Llama-3.1-8B-Instruct",
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"input": "What is Deep Learning?",
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@ -41,196 +50,195 @@ TEST_CONFIGS = {
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"--max-batch-prefill-tokens",
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"2048",
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],
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"run_by_default": True,
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},
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"meta-llama/Llama-2-7b-chat-hf": {
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"model_id": "meta-llama/Llama-2-7b-chat-hf",
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"input": "What is Deep Learning?",
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"expected_greedy_output": "\n\nDeep learning (also known as deep structured learning) is part of a broader family of machine learning techniques based on artificial neural networks\u2014specific",
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"expected_batch_output": "\n\nDeep learning (also known as deep structured learning) is part of a broader family of machine learning techniques based on artificial neural networks\u2014specific",
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"args": [
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"--max-input-tokens",
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"512",
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"--max-total-tokens",
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"1024",
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"--max-batch-size",
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"4",
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"--max-batch-prefill-tokens",
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"2048",
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],
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},
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"mistralai/Mistral-7B-Instruct-v0.3": {
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"model_id": "mistralai/Mistral-7B-Instruct-v0.3",
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"input": "What is Deep Learning?",
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"expected_greedy_output": "\n\nDeep learning is a subset of machine learning in artificial intelligence (AI) that has networks capable of learning unsupervised from data that is unstructured",
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"expected_batch_output": "\n\nDeep learning is a subset of machine learning in artificial intelligence (AI) that has networks capable of learning unsupervised from data that is unstructured",
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"args": [
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"--max-input-tokens",
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"512",
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"--max-total-tokens",
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"1024",
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"--max-batch-size",
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"4",
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"--max-batch-prefill-tokens",
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"2048",
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],
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},
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"bigcode/starcoder2-3b": {
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"model_id": "bigcode/starcoder2-3b",
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"input": "What is Deep Learning?",
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"expected_greedy_output": "\n\nDeep learning is a subset of machine learning that uses artificial neural networks to perform tasks.\n\nNeural networks are a type of machine learning algorithm that",
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"expected_batch_output": "\n\nDeep learning is a subset of machine learning that uses artificial neural networks to perform tasks.\n\nNeural networks are a type of machine learning algorithm that",
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"args": [
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"--max-input-tokens",
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"512",
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"--max-total-tokens",
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"1024",
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"--max-batch-size",
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"4",
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"--max-batch-prefill-tokens",
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"2048",
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],
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},
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"google/gemma-7b-it": {
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"model_id": "google/gemma-7b-it",
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"input": "What is Deep Learning?",
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"expected_greedy_output": "\n\nDeep learning is a subset of machine learning that uses artificial neural networks to learn from large amounts of data. Neural networks are inspired by the structure and function of",
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"expected_batch_output": "\n\nDeep learning is a subset of machine learning that uses artificial neural networks to learn from large amounts of data. Neural networks are inspired by the structure and function of",
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"args": [
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"--max-input-tokens",
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"512",
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"--max-total-tokens",
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"1024",
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"--max-batch-size",
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"4",
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"--max-batch-prefill-tokens",
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"2048",
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],
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},
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"Qwen/Qwen2-0.5B-Instruct": {
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"model_id": "Qwen/Qwen2-0.5B-Instruct",
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"input": "What is Deep Learning?",
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"expected_greedy_output": " Deep Learning is a type of machine learning that is based on the principles of artificial neural networks. It is a type of machine learning that is used to train models",
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"expected_batch_output": " Deep Learning is a type of machine learning that is based on the principles of artificial neural networks. It is a type of machine learning that is used to train models",
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"args": [
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"--max-input-tokens",
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"512",
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"--max-total-tokens",
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"1024",
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"--max-batch-size",
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"4",
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"--max-batch-prefill-tokens",
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"2048",
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],
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},
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"tiiuae/falcon-7b-instruct": {
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"model_id": "tiiuae/falcon-7b-instruct",
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"input": "What is Deep Learning?",
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"expected_greedy_output": "\nDeep learning is a branch of machine learning that uses artificial neural networks to learn and make decisions. It is based on the concept of hierarchical learning, where a",
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"expected_batch_output": "\nDeep learning is a branch of machine learning that uses artificial neural networks to learn and make decisions. It is based on the concept of hierarchical learning, where a",
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"args": [
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"--max-input-tokens",
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"512",
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"--max-total-tokens",
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"1024",
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"--max-batch-size",
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"4",
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],
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},
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"microsoft/phi-1_5": {
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"model_id": "microsoft/phi-1_5",
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"input": "What is Deep Learning?",
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"expected_greedy_output": "\n\nDeep Learning is a subfield of Machine Learning that focuses on building neural networks with multiple layers of interconnected nodes. These networks are designed to learn from large",
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"expected_batch_output": "\n\nDeep Learning is a subfield of Machine Learning that focuses on building neural networks with multiple layers of interconnected nodes. These networks are designed to learn from large",
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"args": [
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"--max-input-tokens",
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"512",
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"--max-total-tokens",
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"1024",
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"--max-batch-size",
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"4",
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],
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},
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"openai-community/gpt2": {
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"model_id": "openai-community/gpt2",
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"input": "What is Deep Learning?",
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"expected_greedy_output": "\n\nDeep learning is a new field of research that has been around for a long time. It is a new field of research that has been around for a",
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"expected_batch_output": "\n\nDeep learning is a new field of research that has been around for a long time. It is a new field of research that has been around for a",
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"args": [
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"--max-input-tokens",
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"512",
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"--max-total-tokens",
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"1024",
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"--max-batch-size",
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"4",
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],
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},
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"EleutherAI/gpt-j-6b": {
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"model_id": "EleutherAI/gpt-j-6b",
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"input": "What is Deep Learning?",
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"expected_greedy_output": "\n\nDeep learning is a subset of machine learning that is based on the idea of neural networks. Neural networks are a type of artificial intelligence that is inspired by",
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"expected_batch_output": "\n\nDeep learning is a subset of machine learning that is based on the idea of neural networks. Neural networks are a type of artificial intelligence that is inspired by",
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"args": [
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"--max-input-tokens",
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"512",
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"--max-total-tokens",
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"1024",
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"--max-batch-size",
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"4",
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],
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},
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# "meta-llama/Llama-2-7b-chat-hf": {
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# "model_id": "meta-llama/Llama-2-7b-chat-hf",
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# "input": "What is Deep Learning?",
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# "expected_greedy_output": "\n\nDeep learning (also known as deep structured learning) is part of a broader family of machine learning techniques based on artificial neural networks\u2014specific",
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# "expected_batch_output": "\n\nDeep learning (also known as deep structured learning) is part of a broader family of machine learning techniques based on artificial neural networks\u2014specific",
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# "args": [
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# "--max-input-tokens",
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# "512",
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# "--max-total-tokens",
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# "1024",
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# "--max-batch-size",
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# "4",
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# "--max-batch-prefill-tokens",
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# "2048",
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# ],
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# },
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# "mistralai/Mistral-7B-Instruct-v0.3": {
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# "model_id": "mistralai/Mistral-7B-Instruct-v0.3",
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# "input": "What is Deep Learning?",
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# "expected_greedy_output": "\n\nDeep learning is a subset of machine learning in artificial intelligence (AI) that has networks capable of learning unsupervised from data that is unstructured",
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# "expected_batch_output": "\n\nDeep learning is a subset of machine learning in artificial intelligence (AI) that has networks capable of learning unsupervised from data that is unstructured",
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# "args": [
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# "--max-input-tokens",
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# "512",
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# "--max-total-tokens",
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# "1024",
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# "--max-batch-size",
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# "4",
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# "--max-batch-prefill-tokens",
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# "2048",
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# ],
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# },
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# "bigcode/starcoder2-3b": {
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# "model_id": "bigcode/starcoder2-3b",
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# "input": "What is Deep Learning?",
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# "expected_greedy_output": "\n\nDeep learning is a subset of machine learning that uses artificial neural networks to perform tasks.\n\nNeural networks are a type of machine learning algorithm that",
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# "expected_batch_output": "\n\nDeep learning is a subset of machine learning that uses artificial neural networks to perform tasks.\n\nNeural networks are a type of machine learning algorithm that",
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# "args": [
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# "--max-input-tokens",
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# "512",
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# "--max-total-tokens",
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# "1024",
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# "--max-batch-size",
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# "4",
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# "--max-batch-prefill-tokens",
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# "2048",
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# ],
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# },
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# "google/gemma-7b-it": {
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# "model_id": "google/gemma-7b-it",
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# "input": "What is Deep Learning?",
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# "expected_greedy_output": "\n\nDeep learning is a subset of machine learning that uses artificial neural networks to learn from large amounts of data. Neural networks are inspired by the structure and function of",
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# "expected_batch_output": "\n\nDeep learning is a subset of machine learning that uses artificial neural networks to learn from large amounts of data. Neural networks are inspired by the structure and function of",
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# "args": [
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# "--max-input-tokens",
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# "512",
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# "--max-total-tokens",
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# "1024",
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# "--max-batch-size",
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# "4",
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# "--max-batch-prefill-tokens",
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# "2048",
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# ],
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# },
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# "Qwen/Qwen2-0.5B-Instruct": {
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# "model_id": "Qwen/Qwen2-0.5B-Instruct",
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# "input": "What is Deep Learning?",
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# "expected_greedy_output": " Deep Learning is a type of machine learning that is based on the principles of artificial neural networks. It is a type of machine learning that is used to train models",
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# "expected_batch_output": " Deep Learning is a type of machine learning that is based on the principles of artificial neural networks. It is a type of machine learning that is used to train models",
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# "args": [
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# "--max-input-tokens",
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# "512",
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# "--max-total-tokens",
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# "1024",
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# "--max-batch-size",
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# "4",
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# "--max-batch-prefill-tokens",
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# "2048",
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# ],
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# },
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# "tiiuae/falcon-7b-instruct": {
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# "model_id": "tiiuae/falcon-7b-instruct",
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# "input": "What is Deep Learning?",
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# "expected_greedy_output": "\nDeep learning is a branch of machine learning that uses artificial neural networks to learn and make decisions. It is based on the concept of hierarchical learning, where a",
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# "expected_batch_output": "\nDeep learning is a branch of machine learning that uses artificial neural networks to learn and make decisions. It is based on the concept of hierarchical learning, where a",
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# "args": [
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# "--max-input-tokens",
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# "512",
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# "--max-total-tokens",
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# "1024",
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# "--max-batch-size",
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# "4",
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# ],
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# },
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# "microsoft/phi-1_5": {
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# "model_id": "microsoft/phi-1_5",
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# "input": "What is Deep Learning?",
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# "expected_greedy_output": "\n\nDeep Learning is a subfield of Machine Learning that focuses on building neural networks with multiple layers of interconnected nodes. These networks are designed to learn from large",
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# "expected_batch_output": "\n\nDeep Learning is a subfield of Machine Learning that focuses on building neural networks with multiple layers of interconnected nodes. These networks are designed to learn from large",
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# "args": [
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# "--max-input-tokens",
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# "512",
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# "--max-total-tokens",
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# "1024",
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# "--max-batch-size",
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# "4",
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# ],
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# },
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# "openai-community/gpt2": {
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# "model_id": "openai-community/gpt2",
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# "input": "What is Deep Learning?",
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# "expected_greedy_output": "\n\nDeep learning is a new field of research that has been around for a long time. It is a new field of research that has been around for a",
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# "expected_batch_output": "\n\nDeep learning is a new field of research that has been around for a long time. It is a new field of research that has been around for a",
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# "args": [
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# "--max-input-tokens",
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# "512",
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# "--max-total-tokens",
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# "1024",
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# "--max-batch-size",
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# "4",
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# ],
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# },
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# "facebook/opt-125m": {
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# "model_id": "facebook/opt-125m",
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# "input": "What is Deep Learning?",
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# "expected_greedy_output": "\nAbout the Author\n\nAbout the Author\n\nAbout the Author\n\nAbout the Author\n\nAbout the Author\n\nAbout the Author\n\nAbout",
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# "expected_batch_output": "\nAbout the Author\n\nAbout the Author\n\nAbout the Author\n\nAbout the Author\n\nAbout the Author\n\nAbout the Author\n\nAbout",
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# "args": [
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# "--max-input-tokens",
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# "512",
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# "--max-total-tokens",
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# "1024",
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# "--max-batch-size",
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# "4",
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# ],
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# },
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# "EleutherAI/gpt-j-6b": {
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# "model_id": "EleutherAI/gpt-j-6b",
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# "input": "What is Deep Learning?",
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# "expected_greedy_output": "\n\nDeep learning is a subset of machine learning that is based on the idea of neural networks. Neural networks are a type of artificial intelligence that is inspired by",
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# "expected_batch_output": "\n\nDeep learning is a subset of machine learning that is based on the idea of neural networks. Neural networks are a type of artificial intelligence that is inspired by",
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# "args": [
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# "--max-input-tokens",
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# "512",
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# "--max-total-tokens",
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# "1024",
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# "--max-batch-size",
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# "4",
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# ],
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# },
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}
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print(f"Testing {len(TEST_CONFIGS)} models")
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def pytest_generate_tests(metafunc):
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if "test_config" in metafunc.fixturenames:
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if metafunc.config.getoption("--gaudi-all-models"):
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models = list(TEST_CONFIGS.keys())
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else:
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models = [
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name
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for name, config in TEST_CONFIGS.items()
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if config.get("run_by_default", False)
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]
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print(f"Testing {len(models)} models")
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metafunc.parametrize("test_config", models, indirect=True)
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@pytest.fixture(scope="module", params=TEST_CONFIGS.keys())
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def test_config(request) -> Dict[str, Any]:
|
||||
@pytest.fixture(scope="module")
|
||||
def test_config(request: SubRequest) -> Dict[str, Any]:
|
||||
"""Fixture that provides model configurations for testing."""
|
||||
test_config = TEST_CONFIGS[request.param]
|
||||
test_config["test_name"] = request.param
|
||||
model_name = request.param
|
||||
test_config = TEST_CONFIGS[model_name]
|
||||
test_config["test_name"] = model_name
|
||||
return test_config
|
||||
|
||||
|
||||
@pytest.fixture(scope="module")
|
||||
def model_id(test_config):
|
||||
def model_id(test_config: Dict[str, Any]) -> Generator[str, None, None]:
|
||||
yield test_config["model_id"]
|
||||
|
||||
|
||||
@pytest.fixture(scope="module")
|
||||
def test_name(test_config):
|
||||
def test_name(test_config: Dict[str, Any]) -> Generator[str, None, None]:
|
||||
yield test_config["test_name"]
|
||||
|
||||
|
||||
@pytest.fixture(scope="module")
|
||||
def expected_outputs(test_config):
|
||||
def expected_outputs(test_config: Dict[str, Any]) -> Dict[str, str]:
|
||||
return {
|
||||
"greedy": test_config["expected_greedy_output"],
|
||||
# "sampling": model_config["expected_sampling_output"],
|
||||
"batch": test_config["expected_batch_output"],
|
||||
}
|
||||
|
||||
|
||||
@pytest.fixture(scope="module")
|
||||
def input(test_config):
|
||||
def input(test_config: Dict[str, Any]) -> str:
|
||||
return test_config["input"]
|
||||
|
||||
|
||||
@pytest.fixture(scope="module")
|
||||
def tgi_service(gaudi_launcher, model_id, test_name):
|
||||
def tgi_service(gaudi_launcher, model_id: str, test_name: str):
|
||||
with gaudi_launcher(model_id, test_name) as tgi_service:
|
||||
yield tgi_service
|
||||
|
||||
@ -242,8 +250,9 @@ async def tgi_client(tgi_service) -> AsyncClient:
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@pytest.mark.all_models
|
||||
async def test_model_single_request(
|
||||
tgi_client: AsyncClient, expected_outputs: Dict[str, Any], input: str
|
||||
tgi_client: AsyncClient, expected_outputs: Dict[str, str], input: str
|
||||
):
|
||||
# Bounded greedy decoding without input
|
||||
response = await tgi_client.generate(
|
||||
@ -255,8 +264,12 @@ async def test_model_single_request(
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@pytest.mark.all_models
|
||||
async def test_model_multiple_requests(
|
||||
tgi_client, gaudi_generate_load, expected_outputs, input
|
||||
tgi_client: AsyncClient,
|
||||
gaudi_generate_load,
|
||||
expected_outputs: Dict[str, str],
|
||||
input: str,
|
||||
):
|
||||
num_requests = 4
|
||||
responses = await gaudi_generate_load(
|
||||
|
||||
Loading…
Reference in New Issue
Block a user