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"""Test the HuggingFace API.""" | |
import math | |
import os | |
from subprocess import PIPE, Popen | |
import numpy as np | |
import pytest | |
from manifest.api.models.huggingface import MODEL_REGISTRY, TextGenerationModel | |
from manifest.api.models.sentence_transformer import SentenceTransformerModel | |
NOCUDA = 0 | |
try: | |
p = Popen( | |
[ | |
"nvidia-smi", | |
( | |
"--query-gpu=index,utilization.gpu,memory.total,memory.used," | |
"memory.free,driver_version,name,gpu_serial,display_active," | |
"display_mode" | |
), | |
"--format=csv,noheader,nounits", | |
], | |
stdout=PIPE, | |
) | |
except OSError: | |
NOCUDA = 1 | |
MAXGPU = 0 | |
if NOCUDA == 0: | |
try: | |
p = os.popen( # type: ignore | |
"nvidia-smi --query-gpu=index --format=csv,noheader,nounits" | |
) | |
i = p.read().split("\n") # type: ignore | |
MAXGPU = int(i[-2]) + 1 | |
except OSError: | |
NOCUDA = 1 | |
def test_load_non_registry_model() -> None: | |
"""Test load model not in registry.""" | |
model_name = "NinedayWang/PolyCoder-160M" | |
assert model_name not in MODEL_REGISTRY | |
model = TextGenerationModel( | |
model_name_or_path=model_name, model_type="text-generation" | |
) | |
result = model.generate("Why is the sky green?", max_tokens=10) | |
assert result is not None | |
def test_gpt_generate() -> None: | |
"""Test pipeline generation from a gpt model.""" | |
model = TextGenerationModel( | |
model_name_or_path="gpt2", | |
use_accelerate=False, | |
use_parallelize=False, | |
use_bitsandbytes=False, | |
use_deepspeed=False, | |
use_fp16=False, | |
device=-1, | |
) | |
inputs = "Why is the sky green?" | |
result = model.generate(inputs, max_tokens=10) | |
assert result is not None | |
assert len(result) == 1 | |
assert result[0][0] == "\n\nThe sky is green.\n\nThe" | |
assert math.isclose(round(result[0][1], 3), -11.516) | |
result = model.generate("Cats are", max_tokens=10) | |
assert result is not None | |
assert len(result) == 1 | |
assert result[0][0] == " not the only ones who are being targeted by the" | |
assert math.isclose(round(result[0][1], 3), -21.069) | |
result = model.generate(inputs, max_tokens=5) | |
assert result is not None | |
assert len(result) == 1 | |
assert result[0][0] == "\n\nThe sky is" | |
assert math.isclose(round(result[0][1], 3), -6.046) | |
# Truncate max length | |
model.pipeline.max_length = 5 | |
result = model.generate(inputs, max_tokens=2) | |
assert result is not None | |
assert len(result) == 1 | |
assert result[0][0] == "\n\n" | |
assert math.isclose(round(result[0][1], 3), -1.414) | |
def test_encdec_generate() -> None: | |
"""Test pipeline generation from a gpt model.""" | |
model = TextGenerationModel( | |
model_name_or_path="google/t5-small-lm-adapt", | |
use_accelerate=False, | |
use_parallelize=False, | |
use_bitsandbytes=False, | |
use_deepspeed=False, | |
use_fp16=False, | |
device=-1, | |
) | |
inputs = "Why is the sky green?" | |
result = model.generate(inputs, max_tokens=10) | |
assert result is not None | |
assert len(result) == 1 | |
assert result[0][0] == "What is the sky green? What is the sky" | |
assert math.isclose(round(result[0][1], 3), -7.271) | |
result = model.generate("Cats are", max_tokens=10) | |
assert result is not None | |
assert len(result) == 1 | |
assert result[0][0] == "a great way to get out of the house" | |
assert math.isclose(round(result[0][1], 3), -13.868) | |
result = model.generate(inputs, max_tokens=5) | |
assert result is not None | |
assert len(result) == 1 | |
assert result[0][0] == "What is the sky green" | |
assert math.isclose(round(result[0][1], 3), -5.144) | |
# Truncate max length | |
model.pipeline.max_length = 5 | |
result = model.generate(inputs, max_tokens=2) | |
assert result is not None | |
assert len(result) == 1 | |
assert result[0][0] == "Is" | |
assert math.isclose(round(result[0][1], 3), -4.233) | |
def test_gpt_score() -> None: | |
"""Test pipeline generation from a gpt model.""" | |
model = TextGenerationModel( | |
model_name_or_path="gpt2", | |
use_accelerate=False, | |
use_parallelize=False, | |
use_bitsandbytes=False, | |
use_deepspeed=False, | |
use_fp16=False, | |
device=-1, | |
) | |
inputs = ["Why is the sky green?", "Cats are butterflies"] | |
result = model.score_sequence(inputs) | |
assert result is not None | |
assert len(result) == 2 | |
assert math.isclose(round(result[0][0], 3), -46.71) | |
assert math.isclose(round(result[1][0], 3), -12.752) | |
assert isinstance(result[0][1], list) | |
assert isinstance(result[1][1], list) | |
def test_embed() -> None: | |
"""Test embedding pipeline.""" | |
model = TextGenerationModel( | |
model_name_or_path="gpt2", | |
use_accelerate=False, | |
use_parallelize=False, | |
use_bitsandbytes=False, | |
use_deepspeed=False, | |
use_fp16=False, | |
device=-1, | |
) | |
inputs = ["Why is the sky green?", "Cats are butterflies"] | |
embeddings = model.embed(inputs) | |
assert isinstance(embeddings, np.ndarray) | |
assert embeddings.shape == (2, 768) | |
model2 = SentenceTransformerModel( | |
model_name_or_path="all-mpnet-base-v2", | |
use_accelerate=False, | |
use_parallelize=False, | |
use_bitsandbytes=False, | |
use_deepspeed=False, | |
use_fp16=False, | |
device=-1, | |
) | |
inputs = ["Why is the sky green?", "Cats are butterflies"] | |
embeddings = model2.embed(inputs) | |
assert isinstance(embeddings, np.ndarray) | |
assert embeddings.shape == (2, 768) | |
def test_batch_gpt_generate() -> None: | |
"""Test pipeline generation from a gpt model.""" | |
model = TextGenerationModel( | |
model_name_or_path="gpt2", | |
use_accelerate=False, | |
use_parallelize=False, | |
use_bitsandbytes=False, | |
use_deepspeed=False, | |
use_fp16=False, | |
device=-1, | |
) | |
inputs = ["Why is the sky green?", "Cats are"] | |
result = model.generate(inputs, max_tokens=10) | |
assert result is not None | |
assert len(result) == 2 | |
assert result[0][0] == "\n\nThe sky is green.\n\nThe" | |
assert math.isclose(round(result[0][1], 3), -11.516) | |
assert result[1][0] == " not the only ones who are being targeted by the" | |
assert math.isclose(round(result[1][1], 3), -21.069) | |
result = model.generate(inputs, max_tokens=5) | |
assert result is not None | |
assert len(result) == 2 | |
assert result[0][0] == "\n\nThe sky is" | |
assert math.isclose(round(result[0][1], 2), -6.05) | |
assert result[1][0] == " not the only ones who" | |
assert math.isclose(round(result[1][1], 3), -9.978) | |
# Truncate max length | |
model.pipeline.max_length = 5 | |
result = model.generate(inputs, max_tokens=2) | |
assert result is not None | |
assert len(result) == 2 | |
assert result[0][0] == "\n\n" | |
assert math.isclose(round(result[0][1], 3), -1.414) | |
assert result[1][0] == " not the" | |
assert math.isclose(round(result[1][1], 3), -6.246) | |
def test_batch_encdec_generate() -> None: | |
"""Test pipeline generation from a gpt model.""" | |
model = TextGenerationModel( | |
model_name_or_path="google/t5-small-lm-adapt", | |
use_accelerate=False, | |
use_parallelize=False, | |
use_bitsandbytes=False, | |
use_deepspeed=False, | |
use_fp16=False, | |
device=-1, | |
) | |
inputs = ["Why is the sky green?", "Cats are"] | |
result = model.generate(inputs, max_tokens=10) | |
assert result is not None | |
assert len(result) == 2 | |
assert result[0][0] == "What is the sky green? What is the sky" | |
assert math.isclose(round(result[0][1], 3), -7.271) | |
assert result[1][0] == "a great way to get out of the house" | |
assert math.isclose(round(result[1][1], 3), -13.868) | |
result = model.generate(inputs, max_tokens=5) | |
assert result is not None | |
assert len(result) == 2 | |
assert result[0][0] == "What is the sky green" | |
assert math.isclose(round(result[0][1], 3), -5.144) | |
assert result[1][0] == "a great way to" | |
assert math.isclose(round(result[1][1], 3), -6.353) | |
# Truncate max length | |
model.pipeline.max_length = 5 | |
result = model.generate(inputs, max_tokens=2) | |
assert result is not None | |
assert len(result) == 2 | |
assert result[0][0] == "Is" | |
assert math.isclose(round(result[0][1], 3), -4.233) | |
assert result[1][0] == "a" | |
assert math.isclose(round(result[1][1], 3), -1.840) | |
def test_gpt_deepspeed_generate() -> None: | |
"""Test deepspeed generation from a gpt model.""" | |
model = TextGenerationModel( | |
model_name_or_path="gpt2", | |
use_accelerate=False, | |
use_parallelize=False, | |
use_bitsandbytes=False, | |
use_deepspeed=True, | |
use_fp16=False, | |
device=0, | |
) | |
inputs = "Why is the sky green?" | |
result = model.generate(inputs, max_tokens=10) | |
assert result is not None | |
assert len(result) == 1 | |
assert result[0][0] == "\n\nThe sky is green.\n\nThe" | |
assert math.isclose(round(result[0][1], 3), -11.517) | |