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# SPDX-License-Identifier: Apache-2.0
"""
Unit tests for LazyWeight module.
"""
import tempfile
from pathlib import Path
from unittest.mock import MagicMock, patch
import pytest
import torch
import ttnn
from models.common.modules.lazy_weight import (
LazyWeight,
_auto_pad_for_sharded_tiles,
_from_torch_and_dump,
resolve_lazy_weight,
)
# ============================================================================
# Fixtures
# ============================================================================
@pytest.fixture
def mock_tensor():
"""Create a mock torch tensor for testing."""
return torch.randn(1, 32, 128)
@pytest.fixture
def mock_tensor_2d():
"""Create a 2D mock torch tensor for testing."""
return torch.randn(64, 128)
@pytest.fixture
def mock_mesh_device():
"""Create a mock MeshDevice for unit tests."""
device = MagicMock(spec=ttnn.MeshDevice)
device.get_num_devices.return_value = 8
device.id.return_value = "test_device_0"
return device
@pytest.fixture
def mock_memory_config():
"""Create a mock MemoryConfig."""
return ttnn.DRAM_MEMORY_CONFIG
@pytest.fixture
def mock_mesh_mapper_config():
"""Create a mock MeshMapperConfig for sharding."""
return ttnn.MeshMapperConfig(
placements=[ttnn.PlacementShard(-1)],
mesh_shape_override=ttnn.MeshShape([8]),
)
# ============================================================================
# Test LazyWeight Construction
# ============================================================================
class TestLazyWeightConstruction:
"""Tests for LazyWeight dataclass construction and __post_init__."""
def test_construction_with_tensor(self, mock_tensor):
"""Test basic construction with a tensor."""
lw = LazyWeight(source=mock_tensor)
assert lw.source is mock_tensor
assert lw.dtype == ttnn.bfloat16
assert lw.pad_value == 0.0
assert lw.device is None
assert lw.mesh_mapper_config is None
assert lw.memory_config is None
assert lw.layout is None
assert lw._value is None
def test_construction_with_all_parameters(
self, mock_tensor, mock_mesh_device, mock_memory_config, mock_mesh_mapper_config
):
"""Test construction with all parameters specified."""
cache_dir = Path("/tmp/cache")
lw = LazyWeight(
source=mock_tensor,
cache_dir_weight_name=(cache_dir, "test_weight"),
pad_value=1.0,
dtype=ttnn.bfloat4_b,
device=mock_mesh_device,
mesh_mapper_config=mock_mesh_mapper_config,
memory_config=mock_memory_config,
layout=ttnn.TILE_LAYOUT,
)
assert lw.source is mock_tensor
assert lw.cache_dir_weight_name == (cache_dir, "test_weight")
assert lw.pad_value == 1.0
assert lw.dtype == ttnn.bfloat4_b
assert lw.device is mock_mesh_device
assert lw.mesh_mapper_config is mock_mesh_mapper_config
assert lw.memory_config is mock_memory_config
assert lw.layout == ttnn.TILE_LAYOUT
def test_post_init_validates_shape(self):
"""Test that __post_init__ validates tensor shape."""
mock_source = MagicMock()
mock_source.shape = None
with pytest.raises(AssertionError, match="source must have a shape"):
LazyWeight(source=mock_source)
def test_post_init_validates_empty_shape(self):
"""Test that __post_init__ rejects empty shape."""
mock_source = MagicMock()
mock_source.shape = ()
with pytest.raises(AssertionError, match="source must have a shape"):
LazyWeight(source=mock_source)
# ============================================================================
# Test is_resolved Method
# ============================================================================
class TestIsResolved:
"""Tests for LazyWeight.is_resolved() method."""
def test_not_resolved_missing_device(self, mock_tensor, mock_memory_config, mock_mesh_mapper_config):
"""Test is_resolved returns False when device is missing."""
lw = LazyWeight(
source=mock_tensor,
memory_config=mock_memory_config,
mesh_mapper_config=mock_mesh_mapper_config,
layout=ttnn.TILE_LAYOUT,
)
assert not lw.is_resolved()
def test_not_resolved_missing_layout(self, mock_tensor, mock_mesh_device, mock_memory_config):
"""Test is_resolved returns False when layout is missing."""
lw = LazyWeight(
source=mock_tensor,
device=mock_mesh_device,
memory_config=mock_memory_config,
)
assert not lw.is_resolved()
def test_not_resolved_missing_memory_config(self, mock_tensor, mock_mesh_device):
"""Test is_resolved returns False when memory_config is missing."""
lw = LazyWeight(
source=mock_tensor,
device=mock_mesh_device,
layout=ttnn.TILE_LAYOUT,
)
assert not lw.is_resolved()
def test_is_resolved_with_all_required_fields(
self, mock_tensor, mock_mesh_device, mock_memory_config, mock_mesh_mapper_config
):
"""Test is_resolved returns True when all required fields are set."""
lw = LazyWeight(
source=mock_tensor,
device=mock_mesh_device,
memory_config=mock_memory_config,
mesh_mapper_config=mock_mesh_mapper_config,
layout=ttnn.TILE_LAYOUT,
)
assert lw.is_resolved()
def test_is_resolved_with_none_mesh_mapper_config(self, mock_tensor, mock_mesh_device, mock_memory_config):
"""Test is_resolved returns False when mesh_mapper_config is None (replicated case requires it to be explicitly set)."""
lw = LazyWeight(
source=mock_tensor,
device=mock_mesh_device,
memory_config=mock_memory_config,
layout=ttnn.TILE_LAYOUT,
mesh_mapper_config=None, # None means not resolved per is_resolved check
)
# mesh_mapper_config is in required_fields so None means not resolved
assert not lw.is_resolved()
# ============================================================================
# Test _get_fingerprint Method
# ============================================================================
class TestGetFingerprint:
"""Tests for LazyWeight._get_fingerprint() method."""
def test_fingerprint_includes_source_shape(self, mock_tensor, mock_mesh_device, mock_memory_config):
"""Test that fingerprint includes source shape."""
lw = LazyWeight(
source=mock_tensor,
device=mock_mesh_device,
memory_config=mock_memory_config,
layout=ttnn.TILE_LAYOUT,
)
fingerprint = lw._get_fingerprint()
assert "srcshape_1_32_128" in fingerprint
def test_fingerprint_includes_non_default_memory_config(self, mock_tensor, mock_mesh_device):
"""Test that fingerprint includes memory_config hash when non-default."""
# Use L1_MEMORY_CONFIG which is different from DRAM_MEMORY_CONFIG
lw = LazyWeight(
source=mock_tensor,
device=mock_mesh_device,
memory_config=ttnn.L1_MEMORY_CONFIG,
layout=ttnn.TILE_LAYOUT,
)
fingerprint = lw._get_fingerprint()
assert "memcfg_" in fingerprint
def test_fingerprint_includes_dtype(self, mock_tensor, mock_mesh_device, mock_memory_config):
"""Test that fingerprint includes dtype."""
lw = LazyWeight(
source=mock_tensor,
device=mock_mesh_device,
memory_config=mock_memory_config,
layout=ttnn.TILE_LAYOUT,
dtype=ttnn.bfloat16,
)
fingerprint = lw._get_fingerprint()
assert "dtype_BFLOAT16" in fingerprint
def test_fingerprint_includes_layout(self, mock_tensor, mock_mesh_device, mock_memory_config):
"""Test that fingerprint includes layout."""
lw = LazyWeight(
source=mock_tensor,
device=mock_mesh_device,
memory_config=mock_memory_config,
layout=ttnn.TILE_LAYOUT,
)
fingerprint = lw._get_fingerprint()
assert "layout_TILE" in fingerprint
def test_fingerprint_includes_pad_value_when_non_default(self, mock_tensor, mock_mesh_device, mock_memory_config):
"""Test that fingerprint includes pad_value when non-default."""
lw = LazyWeight(
source=mock_tensor,
device=mock_mesh_device,
memory_config=mock_memory_config,
layout=ttnn.TILE_LAYOUT,
pad_value=1.5,
)
fingerprint = lw._get_fingerprint()
assert "pad_1.5" in fingerprint
def test_fingerprint_excludes_pad_value_when_default(self, mock_tensor, mock_mesh_device, mock_memory_config):
"""Test that fingerprint excludes pad_value when default (0.0)."""
lw = LazyWeight(
source=mock_tensor,
device=mock_mesh_device,
memory_config=mock_memory_config,
layout=ttnn.TILE_LAYOUT,
pad_value=0.0,
)
fingerprint = lw._get_fingerprint()
assert "pad_" not in fingerprint
def test_fingerprint_includes_device_id(self, mock_tensor, mock_mesh_device, mock_memory_config):
"""Test that fingerprint includes device id."""
lw = LazyWeight(
source=mock_tensor,
device=mock_mesh_device,
memory_config=mock_memory_config,
layout=ttnn.TILE_LAYOUT,
)
fingerprint = lw._get_fingerprint()
assert "device_" in fingerprint
def test_fingerprint_device_without_id_method(self, mock_tensor, mock_memory_config):
"""Test fingerprint uses 'single' when device has no id() method."""
device = MagicMock()
del device.id # Remove id attribute
lw = LazyWeight(
source=mock_tensor,
device=device,
memory_config=mock_memory_config,
layout=ttnn.TILE_LAYOUT,
)
fingerprint = lw._get_fingerprint()
assert "device_single" in fingerprint
def test_fingerprint_changes_with_different_dtype(self, mock_tensor, mock_mesh_device, mock_memory_config):
"""Test that fingerprint changes with different dtype."""
lw1 = LazyWeight(
source=mock_tensor,
device=mock_mesh_device,
memory_config=mock_memory_config,
layout=ttnn.TILE_LAYOUT,
dtype=ttnn.bfloat16,
)
lw2 = LazyWeight(
source=mock_tensor,
device=mock_mesh_device,
memory_config=mock_memory_config,
layout=ttnn.TILE_LAYOUT,
dtype=ttnn.bfloat4_b,
)
assert lw1._get_fingerprint() != lw2._get_fingerprint()
# ============================================================================
# Test _get_mesh_mapper_fingerprint Method
# ============================================================================
class TestGetMeshMapperFingerprint:
"""Tests for LazyWeight._get_mesh_mapper_fingerprint() method."""
def test_fingerprint_replicated_when_none(self, mock_tensor, mock_mesh_device, mock_memory_config):
"""Test that fingerprint is 'replicated' when mesh_mapper_config is None."""
lw = LazyWeight(
source=mock_tensor,
device=mock_mesh_device,
memory_config=mock_memory_config,
layout=ttnn.TILE_LAYOUT,
mesh_mapper_config=None,
)
fingerprint = lw._get_mesh_mapper_fingerprint()
assert fingerprint == "replicated"
def test_fingerprint_with_mesh_mapper_config(
self, mock_tensor, mock_mesh_device, mock_memory_config, mock_mesh_mapper_config
):
"""Test that fingerprint includes mapper hash when config is set."""
lw = LazyWeight(
source=mock_tensor,
device=mock_mesh_device,
memory_config=mock_memory_config,
layout=ttnn.TILE_LAYOUT,
mesh_mapper_config=mock_mesh_mapper_config,
)
fingerprint = lw._get_mesh_mapper_fingerprint()
assert fingerprint.startswith("mapper_")
# Hash should be 12 characters
assert len(fingerprint) == len("mapper_") + 12
def test_different_configs_produce_different_fingerprints(self, mock_tensor, mock_mesh_device, mock_memory_config):
"""Test that different mesh_mapper_configs produce different fingerprints."""
config1 = ttnn.MeshMapperConfig(
placements=[ttnn.PlacementShard(-1)],
mesh_shape_override=ttnn.MeshShape([8]),
)
config2 = ttnn.MeshMapperConfig(
placements=[ttnn.PlacementShard(-2)],
mesh_shape_override=ttnn.MeshShape([8]),
)
lw1 = LazyWeight(
source=mock_tensor,
device=mock_mesh_device,
memory_config=mock_memory_config,
layout=ttnn.TILE_LAYOUT,
mesh_mapper_config=config1,
)
lw2 = LazyWeight(
source=mock_tensor,
device=mock_mesh_device,
memory_config=mock_memory_config,
layout=ttnn.TILE_LAYOUT,
mesh_mapper_config=config2,
)
assert lw1._get_mesh_mapper_fingerprint() != lw2._get_mesh_mapper_fingerprint()
# ============================================================================
# Test _get_cache_fill_path Method
# ============================================================================
class TestGetCacheFillPath:
"""Tests for LazyWeight._get_cache_fill_path() method."""
def test_returns_none_when_cache_dir_none(self, mock_tensor, mock_mesh_device, mock_memory_config):
"""Test that _get_cache_fill_path returns None when cache_dir is None."""
lw = LazyWeight(
source=mock_tensor,
device=mock_mesh_device,
memory_config=mock_memory_config,
layout=ttnn.TILE_LAYOUT,
)
result = lw._get_cache_fill_path(cache_dir=None, weight_name="test")
assert result is None
def test_returns_none_when_weight_name_none(self, mock_tensor, mock_mesh_device, mock_memory_config):
"""Test that _get_cache_fill_path returns None when weight_name is None."""
lw = LazyWeight(
source=mock_tensor,
device=mock_mesh_device,
memory_config=mock_memory_config,
layout=ttnn.TILE_LAYOUT,
)
result = lw._get_cache_fill_path(cache_dir=Path("/tmp/cache"), weight_name=None)
assert result is None
def test_returns_path_with_fingerprint(self, mock_tensor, mock_mesh_device, mock_memory_config):
"""Test that _get_cache_fill_path returns correct path with fingerprint."""
lw = LazyWeight(
source=mock_tensor,
device=mock_mesh_device,
memory_config=mock_memory_config,
layout=ttnn.TILE_LAYOUT,
)
cache_dir = Path("/tmp/cache")
result = lw._get_cache_fill_path(cache_dir=cache_dir, weight_name="my_weight")
assert result is not None
assert result.parent == cache_dir
assert result.name.startswith("my_weight_")
assert result.suffix == ".tensorbin"
# ============================================================================
# Test padded_shape Property
# ============================================================================
class TestPaddedShape:
"""Tests for LazyWeight.padded_shape property."""
def test_padded_shape_raises_when_not_resolved(self, mock_tensor, mock_mesh_device):
"""Test that padded_shape raises assertion when not resolved."""
lw = LazyWeight(
source=mock_tensor,
device=mock_mesh_device,
# Missing memory_config and layout
)
with pytest.raises(AssertionError, match="LazyWeight must be resolved"):
_ = lw.padded_shape
def test_padded_shape_raises_when_device_none(self, mock_tensor, mock_memory_config, mock_mesh_mapper_config):
"""Test that padded_shape raises ValueError when device is None."""
lw = LazyWeight(
source=mock_tensor,
device=None,
memory_config=mock_memory_config,
mesh_mapper_config=mock_mesh_mapper_config,
layout=ttnn.TILE_LAYOUT,
)
# First it will fail is_resolved check
with pytest.raises(AssertionError, match="LazyWeight must be resolved"):
_ = lw.padded_shape
def test_padded_shape_no_padding_when_replicated(self, mock_tensor, mock_mesh_device, mock_memory_config):
"""Test that padded_shape returns original shape when replicated (mesh_mapper_config is None)."""
# Need to set mesh_mapper_config to something to pass is_resolved - use a mock
lw = LazyWeight(
source=mock_tensor,
device=mock_mesh_device,
memory_config=mock_memory_config,
layout=ttnn.TILE_LAYOUT,
mesh_mapper_config=None,
)
# Override is_resolved to return True for this test
with patch.object(lw, "is_resolved", return_value=True):
result = lw.padded_shape
assert result == tuple(mock_tensor.shape)
def test_padded_shape_no_padding_single_device(self, mock_tensor, mock_memory_config, mock_mesh_mapper_config):
"""Test that padded_shape returns original shape for single device."""
single_device = MagicMock(spec=ttnn.MeshDevice)
single_device.get_num_devices.return_value = 1
lw = LazyWeight(
source=mock_tensor,
device=single_device,
memory_config=mock_memory_config,
mesh_mapper_config=mock_mesh_mapper_config,
layout=ttnn.TILE_LAYOUT,
)
result = lw.padded_shape
assert result == tuple(mock_tensor.shape)
def test_padded_shape_pads_for_sharding(self, mock_memory_config):
"""Test that padded_shape correctly pads for sharding across multiple devices."""
# Create tensor with shape that needs padding: dim -1 is 100
# With 8 devices, shard_dim = 100/8 = 12.5, needs to be tile aligned (32)
# padded_shard = ceil(12.5/32)*32 = 32
# padded_hidden = 32 * 8 = 256
tensor = torch.randn(1, 32, 100)
device = MagicMock(spec=ttnn.MeshDevice)
device.get_num_devices.return_value = 8
config = ttnn.MeshMapperConfig(
placements=[ttnn.PlacementShard(-1)],
mesh_shape_override=ttnn.MeshShape([8]),
)
lw = LazyWeight(
source=tensor,
device=device,
memory_config=mock_memory_config,
mesh_mapper_config=config,
layout=ttnn.TILE_LAYOUT,
)
result = lw.padded_shape
# Original: (1, 32, 100), padded dim -1 should be 256 (32*8 where 32 is tile-aligned shard)
assert result == (1, 32, 256)
def test_padded_shape_raises_valueerror_when_device_none_but_resolved(
self, mock_tensor, mock_memory_config, mock_mesh_mapper_config
):
"""Test that padded_shape raises ValueError when device is None but is_resolved mocked True."""
lw = LazyWeight(
source=mock_tensor,
device=None,
memory_config=mock_memory_config,
mesh_mapper_config=mock_mesh_mapper_config,
layout=ttnn.TILE_LAYOUT,
)
# Override is_resolved to return True to reach the ValueError branch
with patch.object(lw, "is_resolved", return_value=True):
with pytest.raises(ValueError, match="device must be set to compute padded_shape"):
_ = lw.padded_shape
# ============================================================================
# Test get_device_weight Method
# ============================================================================
class TestGetDeviceWeight:
"""Tests for LazyWeight.get_device_weight() method."""
def test_raises_when_device_none(self, mock_tensor, mock_memory_config):
"""Test that get_device_weight raises when device is None."""
lw = LazyWeight(
source=mock_tensor,
device=None,
memory_config=mock_memory_config,
layout=ttnn.TILE_LAYOUT,
)
with pytest.raises(ValueError, match="device must be provided"):
lw.get_device_weight()
def test_raises_when_layout_none(self, mock_tensor, mock_mesh_device, mock_memory_config):
"""Test that get_device_weight raises when layout is None."""
lw = LazyWeight(
source=mock_tensor,
device=mock_mesh_device,
memory_config=mock_memory_config,
layout=None,
)
with pytest.raises(ValueError, match="layout must be provided"):
lw.get_device_weight()
def test_raises_when_memory_config_none(self, mock_tensor, mock_mesh_device):
"""Test that get_device_weight raises when memory_config is None."""
lw = LazyWeight(
source=mock_tensor,
device=mock_mesh_device,
memory_config=None,
layout=ttnn.TILE_LAYOUT,
)
with pytest.raises(ValueError, match="memory_config must be provided"):
lw.get_device_weight()
def test_returns_cached_value_on_second_call(self, mock_tensor, mock_mesh_device, mock_memory_config):
"""Test that get_device_weight returns cached _value on second call."""
mock_ttnn_tensor = MagicMock()
lw = LazyWeight(
source=mock_tensor,
device=mock_mesh_device,
memory_config=mock_memory_config,
layout=ttnn.TILE_LAYOUT,
)
# Manually set _value to simulate previous call
lw._value = mock_ttnn_tensor
result = lw.get_device_weight()
assert result is mock_ttnn_tensor
def test_get_device_weight_replicated_flow(self, mock_tensor, mock_mesh_device, mock_memory_config):
"""Test get_device_weight with replicated tensor (no sharding) - mocked."""
mock_ttnn_tensor = MagicMock()
mock_mapper = MagicMock()
with patch("models.common.modules.lazy_weight.ttnn") as mock_ttnn:
mock_ttnn.replicate_tensor_to_mesh_mapper.return_value = mock_mapper
mock_ttnn.from_torch.return_value = mock_ttnn_tensor
lw = LazyWeight(
source=mock_tensor,
device=mock_mesh_device,
memory_config=mock_memory_config,
layout=ttnn.TILE_LAYOUT,
mesh_mapper_config=None, # Replicated
)
result = lw.get_device_weight()
# Verify replicate_tensor_to_mesh_mapper was called
mock_ttnn.replicate_tensor_to_mesh_mapper.assert_called_once_with(mock_mesh_device)
assert result is mock_ttnn_tensor
def test_get_device_weight_sharded_flow(
self, mock_tensor, mock_mesh_device, mock_memory_config, mock_mesh_mapper_config
):
"""Test get_device_weight with sharded tensor - mocked."""
mock_ttnn_tensor = MagicMock()
mock_mapper = MagicMock()
with patch("models.common.modules.lazy_weight.ttnn") as mock_ttnn:
mock_ttnn.create_mesh_mapper.return_value = mock_mapper
mock_ttnn.from_torch.return_value = mock_ttnn_tensor
lw = LazyWeight(
source=mock_tensor,
device=mock_mesh_device,
memory_config=mock_memory_config,
layout=ttnn.TILE_LAYOUT,
mesh_mapper_config=mock_mesh_mapper_config,
)
result = lw.get_device_weight()
# Verify create_mesh_mapper was called with the config
mock_ttnn.create_mesh_mapper.assert_called_once_with(mock_mesh_device, mock_mesh_mapper_config)
assert result is mock_ttnn_tensor
def test_get_device_weight_with_cache_dir_weight_name(self, mock_tensor, mock_mesh_device, mock_memory_config):
"""Test get_device_weight extracts cache_dir and weight_name from tuple."""
mock_ttnn_tensor = MagicMock()
mock_mapper = MagicMock()
with tempfile.TemporaryDirectory() as tmpdir:
cache_dir = Path(tmpdir)
with patch("models.common.modules.lazy_weight.ttnn") as mock_ttnn:
mock_ttnn.replicate_tensor_to_mesh_mapper.return_value = mock_mapper
mock_ttnn.from_torch.return_value = mock_ttnn_tensor
mock_ttnn.StorageType.HOST = ttnn.StorageType.HOST
mock_ttnn_tensor.storage_type.return_value = ttnn.StorageType.HOST
lw = LazyWeight(
source=mock_tensor,
cache_dir_weight_name=(cache_dir, "my_weight"),
device=mock_mesh_device,
memory_config=mock_memory_config,
layout=ttnn.TILE_LAYOUT,
mesh_mapper_config=None,
)
result = lw.get_device_weight()
assert result is not None
def test_get_device_weight_cache_hit(self, mock_tensor, mock_mesh_device, mock_memory_config):
"""Test get_device_weight loads from cache when file exists."""
mock_ttnn_tensor = MagicMock()
with tempfile.TemporaryDirectory() as tmpdir:
cache_dir = Path(tmpdir)
# Create LazyWeight and compute cache path WITHOUT mocking
lw = LazyWeight(
source=mock_tensor,
cache_dir_weight_name=(cache_dir, "cached_weight"),
device=mock_mesh_device,
memory_config=mock_memory_config,
layout=ttnn.TILE_LAYOUT,
mesh_mapper_config=None,
)
# Get expected cache path and create fake cache file
cache_path = lw._get_cache_fill_path(cache_dir, "cached_weight")
cache_path.parent.mkdir(parents=True, exist_ok=True)
cache_path.touch()
# Now patch ttnn.load_tensor for the get_device_weight call
with patch("models.common.modules.lazy_weight.ttnn.load_tensor") as mock_load:
mock_load.return_value = mock_ttnn_tensor
result = lw.get_device_weight()
# Verify load_tensor was called (cache hit)
mock_load.assert_called_once()
assert result is mock_ttnn_tensor
# ============================================================================
# Test _auto_pad_for_sharded_tiles Function
# ============================================================================
class TestAutoPadForSharding:
"""Tests for _auto_pad_for_sharded_tiles() function."""
def test_no_padding_when_shapes_match(self, mock_tensor):
"""Test that no padding is applied when shapes match."""
result = _auto_pad_for_sharded_tiles(mock_tensor, tuple(mock_tensor.shape))
assert result is mock_tensor
def test_padding_applied_when_shapes_differ(self):
"""Test that padding is applied when shapes differ."""
tensor = torch.randn(1, 32, 100)
padded_shape = (1, 32, 128)
result = _auto_pad_for_sharded_tiles(tensor, padded_shape)
assert result.shape == padded_shape
# Original data should be preserved
assert torch.equal(result[:, :, :100], tensor)
def test_padding_with_custom_pad_value(self):
"""Test padding with custom pad value."""
tensor = torch.zeros(1, 32, 100)
padded_shape = (1, 32, 128)
result = _auto_pad_for_sharded_tiles(tensor, padded_shape, pad_value=1.0)
assert result.shape == padded_shape
# Padded region should have pad_value
assert torch.allclose(result[:, :, 100:], torch.ones(1, 32, 28))
# ============================================================================
# Test _from_torch_and_dump Function
# ============================================================================
class TestFromTorchAndDump:
"""Tests for _from_torch_and_dump() function."""
def test_no_cache_when_cache_file_none(self, mock_tensor, mock_mesh_device, mock_memory_config):
"""Test that no caching occurs when cache_file_name is None."""
mock_ttnn_tensor = MagicMock()
mock_mapper = MagicMock()
with patch("models.common.modules.lazy_weight.ttnn") as mock_ttnn:
mock_ttnn.from_torch.return_value = mock_ttnn_tensor
result = _from_torch_and_dump(
tensor=mock_tensor,
device=mock_mesh_device,
dtype=ttnn.bfloat16,
layout=ttnn.TILE_LAYOUT,
memory_config=mock_memory_config,
mesh_mapper=mock_mapper,
is_replicated=False,
pad_value=0.0,
cache_file_name=None,
)
mock_ttnn.from_torch.assert_called_once()
assert result is mock_ttnn_tensor
def test_cache_dump_when_cache_file_provided(self, mock_tensor, mock_mesh_device, mock_memory_config):
"""Test that tensor is cached when cache_file_name is provided."""
mock_ttnn_tensor = MagicMock()
mock_ttnn_tensor.storage_type.return_value = ttnn.StorageType.HOST
with tempfile.TemporaryDirectory() as tmpdir:
cache_file = Path(tmpdir) / "test_cache.tensorbin"
with patch("models.common.modules.lazy_weight.ttnn") as mock_ttnn:
mock_ttnn.from_torch.return_value = mock_ttnn_tensor
mock_ttnn.StorageType.HOST = ttnn.StorageType.HOST
_from_torch_and_dump(
tensor=mock_tensor,
device=mock_mesh_device,
dtype=ttnn.bfloat16,
layout=ttnn.TILE_LAYOUT,
memory_config=mock_memory_config,
mesh_mapper=None,
is_replicated=True,
pad_value=0.0,
cache_file_name=cache_file,
)
# Verify from_torch was called with device=None for caching
call_kwargs = mock_ttnn.from_torch.call_args.kwargs
assert call_kwargs.get("device") is None
# Verify dump_tensor_flatbuffer was called
mock_ttnn._ttnn.tensor.dump_tensor_flatbuffer.assert_called_once()
def test_replicated_uses_none_mesh_mapper(self, mock_tensor, mock_mesh_device, mock_memory_config):
"""Test that replicated tensors use None mesh_mapper in from_torch."""
mock_ttnn_tensor = MagicMock()
mock_mapper = MagicMock()
with patch("models.common.modules.lazy_weight.ttnn") as mock_ttnn:
mock_ttnn.from_torch.return_value = mock_ttnn_tensor
_from_torch_and_dump(
tensor=mock_tensor,
device=mock_mesh_device,
dtype=ttnn.bfloat16,
layout=ttnn.TILE_LAYOUT,
memory_config=mock_memory_config,
mesh_mapper=mock_mapper,
is_replicated=True,
pad_value=0.0,
cache_file_name=None,
)
call_kwargs = mock_ttnn.from_torch.call_args.kwargs
assert call_kwargs.get("mesh_mapper") is None
def test_sharded_uses_mesh_mapper(self, mock_tensor, mock_mesh_device, mock_memory_config):
"""Test that sharded tensors use the provided mesh_mapper."""
mock_ttnn_tensor = MagicMock()
mock_mapper = MagicMock()
with patch("models.common.modules.lazy_weight.ttnn") as mock_ttnn:
mock_ttnn.from_torch.return_value = mock_ttnn_tensor
_from_torch_and_dump(
tensor=mock_tensor,
device=mock_mesh_device,
dtype=ttnn.bfloat16,
layout=ttnn.TILE_LAYOUT,
memory_config=mock_memory_config,
mesh_mapper=mock_mapper,
is_replicated=False,
pad_value=0.0,
cache_file_name=None,
)
call_kwargs = mock_ttnn.from_torch.call_args.kwargs
assert call_kwargs.get("mesh_mapper") is mock_mapper
# ============================================================================
# Test resolve_lazy_weight Function
# ============================================================================
class TestResolveLazyWeight:
"""Tests for resolve_lazy_weight() function."""
def test_resolves_none_fields(self, mock_tensor, mock_mesh_device, mock_memory_config):
"""Test that resolve_lazy_weight fills in None fields."""
lw = LazyWeight(source=mock_tensor)
resolved = resolve_lazy_weight(
lw,
device=mock_mesh_device,
memory_config=mock_memory_config,
layout=ttnn.TILE_LAYOUT,
)
assert resolved.device is mock_mesh_device
assert resolved.memory_config is mock_memory_config
assert resolved.layout == ttnn.TILE_LAYOUT
def test_does_not_override_existing_fields(self, mock_tensor, mock_mesh_device, mock_memory_config):
"""Test that resolve_lazy_weight does not override non-None fields."""
original_device = MagicMock(spec=ttnn.MeshDevice)
lw = LazyWeight(
source=mock_tensor,
device=original_device,
dtype=ttnn.bfloat4_b,
)
resolved = resolve_lazy_weight(
lw,
device=mock_mesh_device,
dtype=ttnn.bfloat16,
memory_config=mock_memory_config,
layout=ttnn.TILE_LAYOUT,
)
# Original non-None fields should be preserved
assert resolved.device is original_device
assert resolved.dtype == ttnn.bfloat4_b
# None fields should be filled
assert resolved.memory_config is mock_memory_config
assert resolved.layout == ttnn.TILE_LAYOUT
def test_returns_new_instance(self, mock_tensor, mock_mesh_device):
"""Test that resolve_lazy_weight returns a new LazyWeight instance."""
lw = LazyWeight(source=mock_tensor)
resolved = resolve_lazy_weight(lw, device=mock_mesh_device)
assert resolved is not lw
assert resolved.device is mock_mesh_device
assert lw.device is None # Original unchanged
def test_with_no_overrides(self, mock_tensor):
"""Test resolve_lazy_weight with no kwargs returns equivalent instance."""
lw = LazyWeight(source=mock_tensor, dtype=ttnn.bfloat16)
resolved = resolve_lazy_weight(lw)
assert resolved is not lw
assert resolved.source is lw.source
assert resolved.dtype == lw.dtype
# ============================================================================
# Integration Tests (require device - use parametrized fixture)
# ============================================================================
@pytest.mark.parametrize(
"ttnn_mesh_device",
[
(1, 1),
],
ids=[
"1x1",
],
indirect=True,
)
class TestLazyWeightIntegration:
"""Integration tests for LazyWeight that require actual TTNN device."""
def test_get_device_weight_replicated(self, ttnn_mesh_device: ttnn.MeshDevice):
"""Test get_device_weight with replicated tensor (no mesh_mapper_config)."""
tensor = torch.randn(1, 1, 32, 64, dtype=torch.bfloat16)
lw = LazyWeight(
source=tensor,
device=ttnn_mesh_device,
memory_config=ttnn.DRAM_MEMORY_CONFIG,
layout=ttnn.TILE_LAYOUT,
mesh_mapper_config=None, # Replicated
)
result = lw.get_device_weight()
assert result is not None
# Subsequent calls should return cached value
result2 = lw.get_device_weight()
assert result2 is result
def test_get_device_weight_with_cache(self, ttnn_mesh_device: ttnn.MeshDevice):
"""Test get_device_weight with caching enabled."""
tensor = torch.randn(1, 1, 32, 64, dtype=torch.bfloat16)
with tempfile.TemporaryDirectory() as tmpdir:
cache_dir = Path(tmpdir)
lw = LazyWeight(
source=tensor,
cache_dir_weight_name=(cache_dir, "test_weight"),
device=ttnn_mesh_device,
memory_config=ttnn.DRAM_MEMORY_CONFIG,
layout=ttnn.TILE_LAYOUT,
mesh_mapper_config=None,
)
# First call should create cache
result1 = lw.get_device_weight()
assert result1 is not None
# Verify cache file was created
cache_files = list(cache_dir.glob("*.tensorbin"))
assert len(cache_files) == 1
assert cache_files[0].name.startswith("test_weight_")
def test_get_device_weight_cache_hit(self, ttnn_mesh_device: ttnn.MeshDevice):
"""Test get_device_weight loads from cache on second instance."""
tensor = torch.randn(1, 1, 32, 64, dtype=torch.bfloat16)
with tempfile.TemporaryDirectory() as tmpdir:
cache_dir = Path(tmpdir)
# First LazyWeight creates cache
lw1 = LazyWeight(
source=tensor,
cache_dir_weight_name=(cache_dir, "test_weight"),
device=ttnn_mesh_device,
memory_config=ttnn.DRAM_MEMORY_CONFIG,
layout=ttnn.TILE_LAYOUT,
mesh_mapper_config=None,
)
lw1.get_device_weight()
# Second LazyWeight should load from cache
lw2 = LazyWeight(
source=tensor,
cache_dir_weight_name=(cache_dir, "test_weight"),
device=ttnn_mesh_device,
memory_config=ttnn.DRAM_MEMORY_CONFIG,
layout=ttnn.TILE_LAYOUT,
mesh_mapper_config=None,
)
result2 = lw2.get_device_weight()
assert result2 is not None
if __name__ == "__main__":
# Run unit tests that don't require device
pytest.main([__file__, "-v", "-k", "not Integration"])
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