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Intel ARC Support

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Disty0
2023-04-30 15:13:56 +03:00
parent 67c392027b
commit b075d3c8fd
11 changed files with 153 additions and 41 deletions
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modules/shared.py
+2 -2
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@@ -238,7 +238,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), {
"comma_padding_backtrack": OptionInfo(20, "Increase coherency by padding from the last comma within n tokens when using more than 75 tokens", gr.Slider, {"minimum": 0, "maximum": 74, "step": 1 }),
"CLIP_stop_at_last_layers": OptionInfo(1, "Clip skip", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1, "visible": False}),
"upcast_attn": OptionInfo(False, "Upcast cross attention layer to float32"),
"cross_attention_optimization": OptionInfo("Sub-quadratic" if is_device_dml else "Scaled-Dot-Product", "Cross-attention optimization method", gr.Radio, lambda: {"choices": shared_items.list_crossattention() }),
"cross_attention_optimization": OptionInfo("Sub-quadratic" if is_device_dml else "Split attention" if cmd_opts.use_ipex else "Scaled-Dot-Product", "Cross-attention optimization method", gr.Radio, lambda: {"choices": shared_items.list_crossattention() }),
"cross_attention_options": OptionInfo([], "Cross-attention advanced options", gr.CheckboxGroup, lambda: {"choices": ['xFormers enable flash Attention', 'SDP disable memory attention']}),
"sub_quad_q_chunk_size": OptionInfo(512, "Sub-quadratic cross-attention query chunk size for the layer optimization to use", gr.Slider, {"minimum": 16, "maximum": 8192, "step": 8}),
"sub_quad_kv_chunk_size": OptionInfo(512, "Sub-quadratic cross-attentionkv chunk size for the sub-quadratic cross-attention layer optimization to use", gr.Slider, {"minimum": 0, "maximum": 8192, "step": 8}),
@@ -318,7 +318,7 @@ options_templates.update(options_section(('cuda', "CUDA Settings"), {
"cuda_dtype": OptionInfo("FP32" if sys.platform == "darwin" else "FP16", "Device precision type", gr.Radio, lambda: {"choices": ["FP32", "FP16", "BF16"]}),
"no_half": OptionInfo(True if is_device_dml else False, "Use full precision for model (--no-half)", None, None, lambda: print("Warning: Most of DirectML devices do not fully support half mode. Recommend to use full precision to model.") if is_device_dml else None),
"no_half_vae": OptionInfo(True if is_device_dml else False, "Use full precision for VAE (--no-half-vae)"),
"upcast_sampling": OptionInfo(True if sys.platform == "darwin" else False, "Enable upcast sampling. Usually produces similar results to --no-half with better performance while using less memory"),
"upcast_sampling": OptionInfo(True if sys.platform == "darwin" or cmd_opts.use_ipex else False, "Enable upcast sampling. Usually produces similar results to --no-half with better performance while using less memory"),
"disable_nan_check": OptionInfo(True, "Do not check if produced images/latent spaces have NaN values"),
"rollback_vae": OptionInfo(False, "Attempt to roll back VAE when produced NaN values, requires NaN check (experimental)"),
"opt_channelslast": OptionInfo(False, "Use channels last as torch memory format "),