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Enforce IR version for older onnxruntime

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henryruhs
2025-02-13 12:52:59 +01:00
parent 3fe32d7832
commit f05ff6cdb1
6 changed files with 12 additions and 4 deletions
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embedding_converter/README.md
+1
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@@ -69,6 +69,7 @@ file_pattern = arcface_converter_simswap_{epoch:02d}_{val_loss:.4f}
directory_path = .exports
source_path = .outputs/last.ckpt
target_path = .exports/arcface_converter_simswap.onnx
ir_version = 10
opset_version = 15
```
embedding_converter/config.ini
+1
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@@ -29,6 +29,7 @@ file_pattern =
directory_path =
source_path =
target_path =
ir_version =
opset_version =
[execution]
embedding_converter/src/exporting.py
+5 -3
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@@ -13,10 +13,12 @@ def export() -> None:
directory_path = CONFIG.get('exporting', 'directory_path')
source_path = CONFIG.get('exporting', 'source_path')
target_path = CONFIG.get('exporting', 'target_path')
ir_version = CONFIG.getint('exporting', 'ir_version')
opset_version = CONFIG.getint('exporting', 'opset_version')
makedirs(directory_path, exist_ok = True)
embedding_converter_trainer = EmbeddingConverterTrainer.load_from_checkpoint(source_path, map_location = 'cpu')
embedding_converter_trainer.eval()
model = EmbeddingConverterTrainer.load_from_checkpoint(source_path, map_location = 'cpu')
model.eval()
model.ir_version = ir_version
input_tensor = torch.randn(1, 512)
torch.onnx.export(embedding_converter_trainer, input_tensor, target_path, input_names = [ 'input' ], output_names = [ 'output' ], opset_version = opset_version)
torch.onnx.export(model, input_tensor, target_path, input_names = [ 'input' ], output_names = [ 'output' ], opset_version = opset_version)
face_swapper/README.md
+1
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@@ -92,6 +92,7 @@ validation_frequency = 1000
directory_path = .exports
source_path = .outputs/last.ckpt
target_path = .exports/face_swapper.onnx
ir_version = 10
opset_version = 15
```
face_swapper/config.ini
+1
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@@ -48,6 +48,7 @@ validation_frequency =
directory_path =
source_path =
target_path =
ir_version =
opset_version =
[inferencing]
face_swapper/src/exporting.py
+3 -1
View File
@@ -13,6 +13,7 @@ def export() -> None:
directory_path = CONFIG.get('exporting', 'directory_path')
source_path = CONFIG.get('exporting', 'source_path')
target_path = CONFIG.get('exporting', 'target_path')
ir_version = CONFIG.getint('exporting', 'ir_version')
opset_version = CONFIG.getint('exporting', 'opset_version')
makedirs(directory_path, exist_ok = True)
@@ -20,6 +21,7 @@ def export() -> None:
model = AdaptiveEmbeddingIntegrationNetwork()
model.load_state_dict(state_dict)
model.eval()
model.ir_version = ir_version
source_tensor = torch.randn(1, 512)
target_tensor = torch.randn(1, 3, 256, 256)
torch.onnx.export(model, (target_tensor, source_tensor), target_path, input_names = [ 'target', 'source' ], output_names = [ 'output' ], opset_version = opset_version)
torch.onnx.export(model, (source_tensor, target_tensor), target_path, input_names = [ 'source', 'target' ], output_names = [ 'output' ], opset_version = opset_version)