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# Copyright (c) 2025, NVIDIA CORPORATION. All rights reserved.
#
# 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.
from unittest.mock import Mock, patch
import numpy as np
import pytest
@pytest.fixture
def model_dir(tmp_path):
return str(tmp_path / "model_dir")
@pytest.fixture
def mock_runner():
runner = Mock()
runner.model_type = "neva"
runner.load_test_media = Mock(return_value=np.zeros((1, 224, 224, 3)))
runner.run = Mock(return_value="Test response")
return runner
class TestTensorRTMMExporter:
@pytest.mark.run_only_on('GPU')
def test_init(self, model_dir):
# Test basic initialization
from nemo.export.tensorrt_mm_exporter import TensorRTMMExporter
exporter = TensorRTMMExporter(model_dir, load_model=False)
assert exporter.model_dir == model_dir
assert exporter.runner is None
assert exporter.modality == "vision"
@pytest.mark.run_only_on('GPU')
def test_init_invalid_modality(self, model_dir):
# Test initialization with invalid modality
from nemo.export.tensorrt_mm_exporter import TensorRTMMExporter
with pytest.raises(AssertionError):
TensorRTMMExporter(model_dir, modality="invalid")
@pytest.mark.run_only_on('GPU')
@patch("nemo.export.tensorrt_mm_exporter.build_mllama_engine")
def test_export_mllama(self, mock_build, model_dir):
from nemo.export.tensorrt_mm_exporter import TensorRTMMExporter
exporter = TensorRTMMExporter(model_dir, load_model=False)
exporter.export(
visual_checkpoint_path="dummy/path", model_type="mllama", tensor_parallel_size=1, load_model=False
)
mock_build.assert_called_once()
@pytest.mark.run_only_on('GPU')
@patch("nemo.export.tensorrt_mm_exporter.build_trtllm_engine")
@patch("nemo.export.tensorrt_mm_exporter.build_visual_engine")
def test_export_neva(self, mock_visual, mock_trtllm, model_dir):
from nemo.export.tensorrt_mm_exporter import TensorRTMMExporter
exporter = TensorRTMMExporter(model_dir, load_model=False)
exporter.export(
visual_checkpoint_path="dummy/path", model_type="neva", tensor_parallel_size=1, load_model=False
)
mock_trtllm.assert_called_once()
mock_visual.assert_called_once()
@pytest.mark.run_only_on('GPU')
def test_forward_without_loading(self, model_dir):
from nemo.export.tensorrt_mm_exporter import TensorRTMMExporter
exporter = TensorRTMMExporter(model_dir, load_model=False)
with pytest.raises(Exception) as exc_info:
exporter.forward("test prompt", "test_image.jpg")
assert "should be exported and" in str(exc_info.value)
@pytest.mark.run_only_on('GPU')
def test_forward(self, model_dir, mock_runner):
from nemo.export.tensorrt_mm_exporter import TensorRTMMExporter
exporter = TensorRTMMExporter(model_dir, load_model=False)
exporter.runner = mock_runner
result = exporter.forward(
input_text="What's in this image?", input_media="test_image.jpg", batch_size=1, max_output_len=30
)
assert result == "Test response"
mock_runner.load_test_media.assert_called_once()
mock_runner.run.assert_called_once()
@pytest.mark.run_only_on('GPU')
def test_get_triton_input(self, model_dir):
from nemo.export.tensorrt_mm_exporter import TensorRTMMExporter
exporter = TensorRTMMExporter(model_dir, load_model=False)
inputs = exporter.get_triton_input
# Verify we have the expected number of inputs
assert len(inputs) == 10 # 1 text input + 1 media input + 8 optional parameters
# Verify the first input is for text
assert inputs[0].name == "input_text"
assert inputs[0].dtype == bytes
@pytest.mark.run_only_on('GPU')
def test_get_triton_output(self, model_dir):
from nemo.export.tensorrt_mm_exporter import TensorRTMMExporter
exporter = TensorRTMMExporter(model_dir, load_model=False)
outputs = exporter.get_triton_output
assert len(outputs) == 1
assert outputs[0].name == "outputs"
assert outputs[0].dtype == bytes
@pytest.mark.run_only_on('GPU')
def test_forward_with_all_params(self, model_dir, mock_runner):
from nemo.export.tensorrt_mm_exporter import TensorRTMMExporter
exporter = TensorRTMMExporter(model_dir, load_model=False)
exporter.runner = mock_runner
result = exporter.forward(
input_text="What's in this image?",
input_media="test_image.jpg",
batch_size=2,
max_output_len=50,
top_k=5,
top_p=0.9,
temperature=0.7,
repetition_penalty=1.2,
num_beams=4,
lora_uids=["lora1", "lora2"],
)
assert result == "Test response"
mock_runner.load_test_media.assert_called_once()
mock_runner.run.assert_called_once_with(
"What's in this image?",
mock_runner.load_test_media.return_value,
50,
2,
5,
0.9,
0.7,
1.2,
4,
["lora1", "lora2"],
)
@pytest.mark.run_only_on('GPU')
def test_get_input_media_tensors_vision(self, model_dir):
from nemo.export.tensorrt_mm_exporter import TensorRTMMExporter
exporter = TensorRTMMExporter(model_dir, load_model=False, modality="vision")
tensors = exporter.get_input_media_tensors()
assert len(tensors) == 1
assert tensors[0].name == "input_media"
assert tensors[0].shape == (-1, -1, -1, 3)
assert tensors[0].dtype == np.uint8
@pytest.mark.run_only_on('GPU')
def test_get_input_media_tensors_audio(self, model_dir):
from nemo.export.tensorrt_mm_exporter import TensorRTMMExporter
exporter = TensorRTMMExporter(model_dir, load_model=False, modality="audio")
tensors = exporter.get_input_media_tensors()
assert len(tensors) == 2
assert tensors[0].name == "input_signal"
assert tensors[0].shape == (-1,)
assert tensors[0].dtype == np.single
assert tensors[1].name == "input_signal_length"
assert tensors[1].shape == (1,)
assert tensors[1].dtype == np.intc
@pytest.mark.run_only_on('GPU')
def test_export_with_invalid_model_type(self, model_dir):
from nemo.export.tensorrt_mm_exporter import TensorRTMMExporter
exporter = TensorRTMMExporter(model_dir, load_model=False)
with pytest.raises(Exception):
exporter.export(
visual_checkpoint_path="dummy/path",
model_type="invalid_model_type",
tensor_parallel_size=1,
load_model=False,
)
@pytest.mark.run_only_on('GPU')
def test_export_with_existing_files(self, model_dir):
import os
from nemo.export.tensorrt_mm_exporter import TensorRTMMExporter
# Create some files in the model directory
os.makedirs(model_dir, exist_ok=True)
with open(os.path.join(model_dir, "test.txt"), "w") as f:
f.write("test")
exporter = TensorRTMMExporter(model_dir, load_model=False)
with pytest.raises(Exception) as exc_info:
exporter.export(
visual_checkpoint_path="dummy/path",
model_type="neva",
tensor_parallel_size=1,
load_model=False,
delete_existing_files=False,
)
assert "There are files in this folder" in str(exc_info.value)
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