NeMo_Canary / tests /export /utils /test_model_loader.py
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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.
import json
import shutil
from pathlib import Path
from unittest.mock import MagicMock, patch
import numpy as np
import pytest
import torch
from nemo.export.utils.model_loader import (
TarFileSystemReader,
load_model_weights,
load_sharded_metadata_zarr,
nemo_to_path,
nemo_weights_directory,
)
@pytest.fixture
def mock_checkpoint_dir(tmp_path):
# Create a temporary directory structure mimicking a NeMo checkpoint
weights_dir = tmp_path / "model_weights"
weights_dir.mkdir()
# Create metadata.json
metadata = {"sharded_backend": "torch_dist"}
with open(weights_dir / "metadata.json", "w") as f:
json.dump(metadata, f)
return tmp_path
def test_nemo_to_path():
# Test directory path
dir_path = "/path/to/checkpoint"
with patch("os.path.isdir", return_value=True):
result = nemo_to_path(dir_path)
assert isinstance(result, Path)
assert str(result) == dir_path
def test_tar_file_system_reader():
path = Path("/some/path")
reader = TarFileSystemReader(path)
assert reader.path == path
@patch("zarr.open")
def test_load_sharded_metadata_zarr(mock_zarr_open):
checkpoint_dir = MagicMock()
# Mock directory structure
subdir = MagicMock()
subdir.name = "test_tensor"
subdir.is_dir.return_value = True
subdir.__truediv__.return_value.exists.return_value = True
checkpoint_dir.iterdir.return_value = [subdir]
# Mock zarr array
mock_array = MagicMock()
mock_array.dtype.name = "float32"
mock_array.__getitem__.return_value = np.array([1.0])
mock_zarr_open.return_value = mock_array
state_dict = load_sharded_metadata_zarr(checkpoint_dir)
assert "test_tensor" in state_dict
assert isinstance(state_dict["test_tensor"], torch.Tensor)
def test_nemo_weights_directory(mock_checkpoint_dir):
# Test model_weights directory
result = nemo_weights_directory(mock_checkpoint_dir)
assert result == mock_checkpoint_dir / "model_weights"
# Test weights directory
shutil.rmtree(mock_checkpoint_dir / "model_weights")
weights_dir = mock_checkpoint_dir / "weights"
weights_dir.mkdir()
result = nemo_weights_directory(mock_checkpoint_dir)
assert result == weights_dir
# Test fallback to checkpoint directory
weights_dir.rmdir()
result = nemo_weights_directory(mock_checkpoint_dir)
assert result == mock_checkpoint_dir
@patch("nemo.export.utils.model_loader.load_sharded_metadata_zarr")
@patch("nemo.export.utils.model_loader.load_sharded_metadata_torch_dist")
def test_load_model_weights(mock_torch_dist, mock_zarr, mock_checkpoint_dir):
# Test torch_dist backend
load_model_weights(mock_checkpoint_dir)
mock_torch_dist.assert_called_once()
mock_zarr.assert_not_called()
# Test zarr backend
mock_torch_dist.reset_mock()
metadata = {"sharded_backend": "zarr"}
with open(mock_checkpoint_dir / "model_weights" / "metadata.json", "w") as f:
json.dump(metadata, f)
load_model_weights(mock_checkpoint_dir)
mock_zarr.assert_called_once()
mock_torch_dist.assert_not_called()
# Test unsupported backend
metadata = {"sharded_backend": "unsupported"}
with open(mock_checkpoint_dir / "model_weights" / "metadata.json", "w") as f:
json.dump(metadata, f)
with pytest.raises(NotImplementedError):
load_model_weights(mock_checkpoint_dir)