Test readme commands

pyproject.toml

@@ -26,6 +26,7 @@ test = [
     "pytest>=8.1.1",
     "pytest-rerunfailures>=14.0",
     "pytest-timeout>=2.3.1",
+    "pytest-dependency>=0.6.0",
     "transformers>=4.38.0",  # numerical comparisons
     "einops>=0.7.0",
     "protobuf>=4.23.4",

tests/test_readme.py

@@ -0,0 +1,170 @@
+# Copyright Lightning AI. Licensed under the Apache License 2.0, see LICENSE file.
+
+from pathlib import Path
+import os
+import pytest
+import requests
+import subprocess
+import sys
+import threading
+import time
+
+
+REPO_ID = Path("EleutherAI/pythia-14m")
+CUSTOM_TEXTS_DIR = Path("custom_texts")
+
+
+def run_command(command):
+    try:
+        result = subprocess.run(command, capture_output=True, text=True, check=True)
+        return result.stdout
+    except subprocess.CalledProcessError as e:
+        error_message = (
+            f"Command '{' '.join(command)}' failed with exit status {e.returncode}\n"
+            f"Output:\n{e.stdout}\n"
+            f"Error:\n{e.stderr}"
+        )
+        # You can either print the message, log it, or raise an exception with it
+        print(error_message)
+        raise RuntimeError(error_message) from None
+
+
+@pytest.mark.skipif(
+    sys.platform.startswith("win") or
+    sys.platform == "darwin" or
+    'AGENT_NAME' in os.environ,
+    reason="Does not run on Windows, macOS, or Azure Pipelines"
+)
+@pytest.mark.dependency()
+def test_download_model():
+    repo_id = str(REPO_ID).replace("\\", "/")  # fix for Windows CI
+    command = ["litgpt", "download", "--repo_id", str(repo_id)]
+    output = run_command(command)
+
+    s = Path("checkpoints") / repo_id
+    assert f"Saving converted checkpoint to {str(s)}" in output
+    assert ("checkpoints" / REPO_ID).exists()
+
+
+@pytest.mark.dependency()
+def test_download_books():
+    CUSTOM_TEXTS_DIR.mkdir(parents=True, exist_ok=True)
+
+    books = [
+        ("https://www.gutenberg.org/cache/epub/24440/pg24440.txt", "book1.txt"),
+        ("https://www.gutenberg.org/cache/epub/26393/pg26393.txt", "book2.txt")
+    ]
+    for url, filename in books:
+        subprocess.run(["curl", url, "--output", str(CUSTOM_TEXTS_DIR / filename)], check=True)
+        # Verify each book is downloaded
+        assert (CUSTOM_TEXTS_DIR / filename).exists(), f"{filename} not downloaded"
+
+
+@pytest.mark.dependency(depends=["test_download_model"])
+def test_chat_with_model():
+    command = ["litgpt", "generate", "base", "--checkpoint_dir", f"checkpoints"/REPO_ID]
+    prompt = "What do Llamas eat?"
+    result = subprocess.run(command, input=prompt, text=True, capture_output=True, check=True)
+    assert "What food do llamas eat?" in result.stdout
+
+
+@pytest.mark.dependency(depends=["test_download_model"])
+@pytest.mark.timeout(300)
+def test_finetune_model():
+
+    OUT_DIR = Path("out") / "lora"
+    DATASET_PATH = Path("custom_finetuning_dataset.json")
+    CHECKPOINT_DIR = "checkpoints" / REPO_ID
+
+    download_command = ["curl", "-L", "https://huggingface.co/datasets/medalpaca/medical_meadow_health_advice/raw/main/medical_meadow_health_advice.json", "-o", str(DATASET_PATH)]
+    subprocess.run(download_command, check=True)
+
+    assert DATASET_PATH.exists(), "Dataset file not downloaded"
+
+    finetune_command = [
+        "litgpt", "finetune", "lora",
+        "--checkpoint_dir", str(CHECKPOINT_DIR),
+        "--lora_r", "1",
+        "--data", "JSON",
+        "--data.json_path", str(DATASET_PATH),
+        "--data.val_split_fraction", "0.00001",  # Keep small because new final validation is expensive
+        "--train.max_steps", "1",
+        "--out_dir", str(OUT_DIR)
+    ]
+    run_command(finetune_command)
+
+    assert (OUT_DIR/"final").exists(), "Finetuning output directory was not created"
+    assert (OUT_DIR/"final"/"lit_model.pth").exists(), "Model file was not created"
+
+
+@pytest.mark.dependency(depends=["test_download_model", "test_download_books"])
+def test_pretrain_model():
+    OUT_DIR = Path("out") / "custom_pretrained"
+    pretrain_command = [
+        "litgpt", "pretrain",
+        "--model_name", "pythia-14m",
+        "--tokenizer_dir", str("checkpoints" / REPO_ID),
+        "--data", "TextFiles",
+        "--data.train_data_path", str(CUSTOM_TEXTS_DIR),
+        "--train.max_tokens", "100",     # to accelerate things for CI
+        "--eval.max_iters", "1",         # to accelerate things for CI
+        "--out_dir", str(OUT_DIR)
+    ]
+    run_command(pretrain_command)
+
+    assert (OUT_DIR / "final").exists(), "Pretraining output directory was not created"
+    assert (OUT_DIR / "final" / "lit_model.pth").exists(), "Model file was not created"
+
+
+@pytest.mark.dependency(depends=["test_download_model", "test_download_books"])
+def test_continue_pretrain_model():
+    OUT_DIR = Path("out") / "custom_continue_pretrained"
+    pretrain_command = [
+        "litgpt", "pretrain",
+        "--model_name", "pythia-14m",
+        "--initial_checkpoint", str("checkpoints" / REPO_ID),
+        "--tokenizer_dir", str("checkpoints" / REPO_ID),
+        "--data", "TextFiles",
+        "--data.train_data_path", str(CUSTOM_TEXTS_DIR),
+        "--train.max_tokens", "100",     # to accelerate things for CI
+        "--eval.max_iters", "1",         # to accelerate things for CI
+        "--out_dir", str(OUT_DIR)
+    ]
+    run_command(pretrain_command)
+
+    assert (OUT_DIR / "final").exists(), "Continued pretraining output directory was not created"
+    assert (OUT_DIR / "final" / "lit_model.pth").exists(), "Model file was not created"
+
+
+@pytest.mark.dependency(depends=["test_download_model"])
+def test_serve():
+    CHECKPOINT_DIR = str("checkpoints" / REPO_ID)
+    run_command = [
+        "litgpt", "serve",
+        "--checkpoint_dir", str(CHECKPOINT_DIR)
+    ]
+
+    process = None
+
+    def run_server():
+        nonlocal process
+        try:
+            process = subprocess.Popen(run_command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True)
+            stdout, stderr = process.communicate(timeout=60)
+        except subprocess.TimeoutExpired:
+            print('Server start-up timeout expired')
+
+    server_thread = threading.Thread(target=run_server)
+    server_thread.start()
+
+    # Allow time to initialize and start serving
+    time.sleep(30)
+
+    try:
+        response = requests.get("http://127.0.0.1:8000")
+        print(response.status_code)
+        assert response.status_code == 200, "Server did not respond as expected."
+    finally:
+        if process:
+            process.kill()
+        server_thread.join()