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test translating to vertex ai params

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This commit is contained in:
Ishaan Jaff 2024-08-03 08:44:54 -07:00
parent 81bc8d8d16
commit 31c31950a0
3 changed files with 88 additions and 6 deletions
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61
litellm/tests/test_fine_tuning_api.py
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@ -20,6 +20,12 @@ from test_gcs_bucket import load_vertex_ai_credentials
from litellm import create_fine_tuning_job
from litellm._logging import verbose_logger
from litellm.llms.fine_tuning_apis.vertex_ai import (
FineTuningJobCreate,
VertexFineTuningAPI,
)
vertex_finetune_api = VertexFineTuningAPI()
def test_create_fine_tune_job():
@ -210,3 +216,58 @@ async def test_create_vertex_fine_tune_jobs():
assert create_fine_tuning_response.object == "fine_tuning.job"
except:
pass
# Testing OpenAI -> Vertex AI param mapping
def test_convert_openai_request_to_vertex_basic():
openai_data = FineTuningJobCreate(
training_file="gs://bucket/train.jsonl",
validation_file="gs://bucket/val.jsonl",
model="text-davinci-002",
hyperparameters={"n_epochs": 3, "learning_rate_multiplier": 0.1},
suffix="my_fine_tuned_model",
)
result = vertex_finetune_api.convert_openai_request_to_vertex(openai_data)
print("converted vertex ai result=", result)
assert result["baseModel"] == "text-davinci-002"
assert result["tunedModelDisplayName"] == "my_fine_tuned_model"
assert (
result["supervisedTuningSpec"]["training_dataset_uri"]
== "gs://bucket/train.jsonl"
)
assert (
result["supervisedTuningSpec"]["validation_dataset"] == "gs://bucket/val.jsonl"
)
assert result["supervisedTuningSpec"]["epoch_count"] == 3
assert result["supervisedTuningSpec"]["learning_rate_multiplier"] == 0.1
def test_convert_openai_request_to_vertex_with_adapter_size():
openai_data = FineTuningJobCreate(
training_file="gs://bucket/train.jsonl",
model="text-davinci-002",
hyperparameters={"n_epochs": 5, "learning_rate_multiplier": 0.2},
suffix="custom_model",
)
result = vertex_finetune_api.convert_openai_request_to_vertex(
openai_data, AdapterSize="SMALL"
)
print("converted vertex ai result=", result)
assert result["baseModel"] == "text-davinci-002"
assert result["tunedModelDisplayName"] == "custom_model"
assert (
result["supervisedTuningSpec"]["training_dataset_uri"]
== "gs://bucket/train.jsonl"
)
assert result["supervisedTuningSpec"]["validation_dataset"] is None
assert result["supervisedTuningSpec"]["epoch_count"] == 5
assert result["supervisedTuningSpec"]["learning_rate_multiplier"] == 0.2
assert result["supervisedTuningSpec"]["adapter_size"] == "SMALL"