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https://github.com/vladmandic/automatic
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Override CPU to use FP32 by default
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+11
-7
@@ -2,15 +2,19 @@
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## Update for 2025-06-06
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- **Torch**:
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- set default to `torch==2.7.1`
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- **Changes**
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- Increase the medvram mode threshold from 8GB to 12GB
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- Set CPU backend to use FP32 by default
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- **Torch**
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- set default to `torch==2.7.1`
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- **SDNQ Quantization**
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- Add group size support for convolutional layers
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- Add quantized matmul support for for convolutional layers
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- Fix forced FP32 with tensorwise FP8 matmul
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- Fix PyTorch <= 2.4 compatibility with FP8 matmul
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- Fix VAE with conv quant
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- Add group size support for convolutional layers
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- Add quantized matmul support for for convolutional layers
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- Fix forced FP32 with tensorwise FP8 matmul
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- Fix PyTorch <= 2.4 compatibility with FP8 matmul
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- Fix VAE with conv quant
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## Update for 2025-06-02
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+2
-2
@@ -331,7 +331,7 @@ def test_fp16():
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if fp16_ok is not None:
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return fp16_ok
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if opts.cuda_dtype != 'FP16': # don't override if the user sets it
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if sys.platform == "darwin" or backend == 'openvino': # override
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if sys.platform == "darwin" or backend in {'openvino', 'cpu'}: # override
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fp16_ok = False
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return fp16_ok
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elif backend == 'rocm':
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@@ -362,7 +362,7 @@ def test_bf16():
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if bf16_ok is not None:
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return bf16_ok
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if opts.cuda_dtype != 'BF16': # don't override if the user sets it
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if sys.platform == "darwin" or backend == 'openvino' or backend == 'directml': # override
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if sys.platform == "darwin" or backend in {'openvino', 'directml', 'cpu'}: # override
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bf16_ok = False
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return bf16_ok
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elif backend == 'rocm' or backend == 'zluda':
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