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Rename ConcatenatedLoRALayer to MergedLayerPatch. And other minor cleanup.

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This commit is contained in:
Ryan Dick
2025-01-24 19:14:23 +00:00
parent 7fef569e38
commit 5357d6e08e
4 changed files with 9 additions and 9 deletions
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8
tests/backend/model_manager/load/model_cache/torch_module_autocast/custom_modules/test_all_custom_modules.py
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@@ -13,10 +13,10 @@ from invokeai.backend.model_manager.load.model_cache.torch_module_autocast.torch
)
from invokeai.backend.patches.layer_patcher import LayerPatcher
from invokeai.backend.patches.layers.base_layer_patch import BaseLayerPatch
from invokeai.backend.patches.layers.concatenated_lora_layer import ConcatenatedLoRALayer, Range
from invokeai.backend.patches.layers.flux_control_lora_layer import FluxControlLoRALayer
from invokeai.backend.patches.layers.lokr_layer import LoKRLayer
from invokeai.backend.patches.layers.lora_layer import LoRALayer
from invokeai.backend.patches.layers.merged_layer_patch import MergedLayerPatch, Range
from invokeai.backend.util.original_weights_storage import OriginalWeightsStorage
from tests.backend.model_manager.load.model_cache.torch_module_autocast.custom_modules.test_custom_invoke_linear_8_bit_lt import (
build_linear_8bit_lt_layer,
@@ -328,7 +328,7 @@ def patch_under_test(request: pytest.FixtureRequest) -> PatchUnderTest:
elif layer_type == "concatenated_lora":
sub_layer_out_features = [16, 16, 32]
# Create a ConcatenatedLoRA layer.
# Create a MergedLayerPatch.
sub_layers: list[LoRALayer] = []
sub_layer_ranges: list[Range] = []
dim_0_offset = 0
@@ -339,10 +339,10 @@ def patch_under_test(request: pytest.FixtureRequest) -> PatchUnderTest:
sub_layers.append(LoRALayer(up=up, mid=None, down=down, alpha=1.0, bias=bias))
sub_layer_ranges.append(Range(dim_0_offset, dim_0_offset + out_features))
dim_0_offset += out_features
concatenated_lora_layer = ConcatenatedLoRALayer(sub_layers, sub_layer_ranges)
merged_layer_patch = MergedLayerPatch(sub_layers, sub_layer_ranges)
input = torch.randn(1, in_features)
return ([(concatenated_lora_layer, 0.7)], input)
return ([(merged_layer_patch, 0.7)], input)
elif layer_type == "flux_control_lora":
# Create a FluxControlLoRALayer.
patched_in_features = 40