add e2e tests

Former-commit-id: 0156a37450604641c4f5f9756ad84324698fc88c

tests/e2e/test_chat.py

@@ -0,0 +1,49 @@
+# Copyright 2024 the LlamaFactory team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+
+from llamafactory.chat import ChatModel
+
+
+TINY_LLAMA = os.environ.get("TINY_LLAMA", "llamafactory/tiny-random-Llama-3")
+
+INFER_ARGS = {
+    "model_name_or_path": TINY_LLAMA,
+    "finetuning_type": "lora",
+    "template": "llama3",
+    "infer_dtype": "float16",
+    "do_sample": False,
+    "max_new_tokens": 1,
+}
+
+MESSAGES = [
+    {"role": "user", "content": "Hi"},
+]
+
+EXPECTED_RESPONSE = "_rho"
+
+
+def test_chat():
+    chat_model = ChatModel(INFER_ARGS)
+    assert chat_model.chat(MESSAGES)[0].response_text == EXPECTED_RESPONSE
+
+
+def test_stream_chat():
+    chat_model = ChatModel(INFER_ARGS)
+    response = ""
+    for token in chat_model.stream_chat(MESSAGES):
+        response += token
+
+    assert response == EXPECTED_RESPONSE

tests/e2e/test_train.py

@@ -0,0 +1,70 @@
+# Copyright 2024 the LlamaFactory team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+
+import pytest
+
+from llamafactory.train.tuner import export_model, run_exp
+
+
+DEMO_DATA = os.environ.get("DEMO_DATA", "llamafactory/demo_data")
+
+TINY_LLAMA = os.environ.get("TINY_LLAMA", "llamafactory/tiny-random-Llama-3")
+
+TINY_LLAMA_ADAPTER = os.environ.get("TINY_LLAMA_ADAPTER", "llamafactory/tiny-random-Llama-3-lora")
+
+TRAIN_ARGS = {
+    "model_name_or_path": TINY_LLAMA,
+    "do_train": True,
+    "finetuning_type": "lora",
+    "dataset_dir": "REMOTE:" + DEMO_DATA,
+    "template": "llama3",
+    "cutoff_len": 1,
+    "overwrite_cache": True,
+    "overwrite_output_dir": True,
+    "per_device_train_batch_size": 1,
+    "max_steps": 1,
+    "fp16": True,
+}
+
+INFER_ARGS = {
+    "model_name_or_path": TINY_LLAMA,
+    "adapter_name_or_path": TINY_LLAMA_ADAPTER,
+    "finetuning_type": "lora",
+    "template": "llama3",
+    "infer_dtype": "float16",
+    "export_dir": "llama3_export",
+}
+
+
+@pytest.mark.parametrize(
+    "stage,dataset",
+    [
+        ("pt", "c4_demo"),
+        ("sft", "alpaca_en_demo"),
+        ("rm", "dpo_en_demo"),
+        ("dpo", "dpo_en_demo"),
+        ("kto", "kto_en_demo"),
+    ],
+)
+def test_train(stage: str, dataset: str):
+    output_dir = "train_{}".format(stage)
+    run_exp({"stage": stage, "dataset": dataset, "output_dir": output_dir, **TRAIN_ARGS})
+    assert os.path.exists(output_dir)
+
+
+def test_export():
+    export_model(INFER_ARGS)
+    assert os.path.exists("llama3_export")