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Jul 18, 2023
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chore: add jumpstart llama 2 tests #4004

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35 changes: 35 additions & 0 deletions tests/integ/sagemaker/jumpstart/model/test_jumpstart_model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,6 +14,10 @@
import os
import time

import pytest

import tests.integ

from sagemaker.jumpstart.model import JumpStartModel
from tests.integ.sagemaker.jumpstart.constants import (
ENV_VAR_JUMPSTART_SDK_TEST_SUITE_ID,
Expand All @@ -29,6 +33,8 @@

MAX_INIT_TIME_SECONDS = 5

MODEL_PACKAGE_ARN_SUPPORTED_REGIONS = {"us-west-2", "us-east-1"}
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FYI: this is going to expand very soon to 16 or so regions

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Yes I know. If I don't do this then the test would fail in the other regions.

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just FYI, we might only need IAD, PDX, DUBandSIN` initially, and see if we receive PFRs



def test_non_prepacked_jumpstart_model(setup):

Expand Down Expand Up @@ -73,6 +79,35 @@ def test_prepacked_jumpstart_model(setup):
assert response is not None


@pytest.mark.skipif(
tests.integ.test_region() not in MODEL_PACKAGE_ARN_SUPPORTED_REGIONS,
reason=f"JumpStart Model Package models unavailable in {tests.integ.test_region()}.",
)
def test_model_package_arn_jumpstart_model(setup):

model_id = "meta-textgeneration-llama-2-7b"

model = JumpStartModel(
model_id=model_id,
role=get_sm_session().get_caller_identity_arn(),
sagemaker_session=get_sm_session(),
)

# uses ml.g5.2xlarge instance
predictor = model.deploy(
tags=[{"Key": JUMPSTART_TAG, "Value": os.environ[ENV_VAR_JUMPSTART_SDK_TEST_SUITE_ID]}],
)

payload = {
"inputs": "some-payload",
"parameters": {"max_new_tokens": 256, "top_p": 0.9, "temperature": 0.6},
}

response = predictor.predict(payload, custom_attributes="accept_eula=true")

assert response is not None


def test_instatiating_model_not_too_slow(setup):

model_id = "catboost-regression-model"
Expand Down
57 changes: 57 additions & 0 deletions tests/unit/sagemaker/jumpstart/constants.py
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Expand Up @@ -14,6 +14,63 @@


SPECIAL_MODEL_SPECS_DICT = {
"js-model-package-arn": {
"model_id": "meta-textgeneration-llama-2-7b-f",
"url": "https://ai.meta.com/resources/models-and-libraries/llama-downloads/",
"version": "1.0.0",
"min_sdk_version": "2.173.0",
"training_supported": False,
"incremental_training_supported": False,
"hosting_ecr_specs": {
"framework": "pytorch",
"framework_version": "1.12.0",
"py_version": "py38",
},
"hosting_artifact_key": "meta-infer/infer-meta-textgeneration-llama-2-7b-f.tar.gz",
"hosting_script_key": "source-directory-tarballs/meta/inference/textgeneration/v1.0.0/sourcedir.tar.gz",
"hosting_eula_key": "fmhMetadata/eula/llamaEula.txt",
"hosting_model_package_arns": {
"us-west-2": "arn:aws:sagemaker:us-west-2:594846645681:model-package/"
"llama2-7b-f-e46eb8a833643ed58aaccd81498972c3",
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Should be single line?

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I made this a multi-line string to shut-up flake8

"us-east-1": "arn:aws:sagemaker:us-east-1:865070037744:model-package/"
"llama2-7b-f-e46eb8a833643ed58aaccd81498972c3",
},
"inference_vulnerable": False,
"inference_dependencies": [],
"inference_vulnerabilities": [],
"training_vulnerable": False,
"training_dependencies": [],
"training_vulnerabilities": [],
"deprecated": False,
"inference_environment_variables": [],
"metrics": [],
"default_inference_instance_type": "ml.g5.2xlarge",
"supported_inference_instance_types": [
"ml.g5.2xlarge",
"ml.g5.4xlarge",
"ml.g5.8xlarge",
"ml.g5.12xlarge",
"ml.g5.24xlarge",
"ml.g5.48xlarge",
"ml.p4d.24xlarge",
],
"model_kwargs": {},
"deploy_kwargs": {
"model_data_download_timeout": 3600,
"container_startup_health_check_timeout": 3600,
},
"predictor_specs": {
"supported_content_types": ["application/json"],
"supported_accept_types": ["application/json"],
"default_content_type": "application/json",
"default_accept_type": "application/json",
},
"inference_volume_size": 256,
"inference_enable_network_isolation": True,
"validation_supported": False,
"fine_tuning_supported": False,
"resource_name_base": "meta-textgeneration-llama-2-7b-f",
},
"js-trainable-model-prepacked": {
"model_id": "huggingface-text2text-flan-t5-base",
"url": "https://huggingface.co/google/flan-t5-base",
Expand Down
74 changes: 74 additions & 0 deletions tests/unit/sagemaker/jumpstart/model/test_model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -15,6 +15,7 @@
from typing import Optional, Set
from unittest import mock
import unittest
from mock import MagicMock
import pytest
from sagemaker.async_inference.async_inference_config import AsyncInferenceConfig
from sagemaker.jumpstart.enums import JumpStartScriptScope
Expand Down Expand Up @@ -567,6 +568,79 @@ def test_model_id_not_found_refeshes_cach_inference(
]
)

@mock.patch("sagemaker.jumpstart.model.is_valid_model_id")
@mock.patch("sagemaker.jumpstart.factory.model.Session")
@mock.patch("sagemaker.jumpstart.accessors.JumpStartModelsAccessor.get_model_specs")
@mock.patch("sagemaker.jumpstart.factory.model.JUMPSTART_DEFAULT_REGION_NAME", region)
def test_jumpstart_model_package_arn(
self,
mock_get_model_specs: mock.Mock,
mock_session: mock.Mock,
mock_is_valid_model_id: mock.Mock,
):

mock_is_valid_model_id.return_value = True

model_id, _ = "js-model-package-arn", "*"

mock_get_model_specs.side_effect = get_special_model_spec

mock_session.return_value = MagicMock(sagemaker_config={})

model = JumpStartModel(model_id=model_id)

model.deploy()

self.assertEqual(
mock_session.return_value.create_model.call_args[0][2],
{
"ModelPackageName": "arn:aws:sagemaker:us-west-2:594846645681:model-package"
"/llama2-7b-f-e46eb8a833643ed58aaccd81498972c3"
},
)

@mock.patch("sagemaker.jumpstart.model.is_valid_model_id")
@mock.patch("sagemaker.jumpstart.factory.model.Session")
@mock.patch("sagemaker.jumpstart.accessors.JumpStartModelsAccessor.get_model_specs")
@mock.patch("sagemaker.jumpstart.factory.model.JUMPSTART_DEFAULT_REGION_NAME", region)
def test_jumpstart_model_package_arn_override(
self,
mock_get_model_specs: mock.Mock,
mock_session: mock.Mock,
mock_is_valid_model_id: mock.Mock,
):

mock_is_valid_model_id.return_value = True

# arbitrary model without model packarn arn
model_id, _ = "js-trainable-model", "*"

mock_get_model_specs.side_effect = get_special_model_spec

mock_session.return_value = MagicMock(sagemaker_config={})

model_package_arn = (
"arn:aws:sagemaker:us-west-2:867530986753:model-package/"
"llama2-ynnej-f-e46eb8a833643ed58aaccd81498972c3"
)
model = JumpStartModel(model_id=model_id, model_package_arn=model_package_arn)

model.deploy()

self.assertEqual(
mock_session.return_value.create_model.call_args[0][2],
{
"ModelPackageName": model_package_arn,
"Environment": {
"ENDPOINT_SERVER_TIMEOUT": "3600",
"MODEL_CACHE_ROOT": "/opt/ml/model",
"SAGEMAKER_ENV": "1",
"SAGEMAKER_MODEL_SERVER_WORKERS": "1",
"SAGEMAKER_PROGRAM": "inference.py",
},
},
)


def test_jumpstart_model_requires_model_id():
with pytest.raises(ValueError):
Expand Down