xinyun/ComfyUI-CogVideoXWrapper
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update vae tile defaults

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kijai 2024-09-21 00:27:52 +03:00
parent d22c0b866b
commit c11d00b94c
4 changed files with 16 additions and 16 deletions
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8
examples/cogvideox_5b_example_01.json
View File

@ -392,10 +392,10 @@
}, },
"widgets_values": [ "widgets_values": [
false, false,
96, 240,
96, 360,
0.083, 0.2,
0.083, 0.2,
true true
] ]
} }

8
examples/cogvideox_I2V_example_01.json
View File

@ -401,10 +401,10 @@
}, },
"widgets_values": [ "widgets_values": [
false, false,
96, 240,
96, 360,
0.083, 0.2,
0.083, 0.2,
true true
] ]
}, },

8
examples/cogvidex_fun_i2v_example_01.json
View File

@ -158,10 +158,10 @@
}, },
"widgets_values": [ "widgets_values": [
false, false,
96, 240,
96, 360,
0.083, 0.2,
0.083, 0.2,
true true
] ]
}, },

8
nodes.py
View File

@ -628,10 +628,10 @@ class CogVideoDecode:
"enable_vae_tiling": ("BOOLEAN", {"default": False, "tooltip": "Drastically reduces memory use but may introduce seams"}), "enable_vae_tiling": ("BOOLEAN", {"default": False, "tooltip": "Drastically reduces memory use but may introduce seams"}),
}, },
"optional": { "optional": {
"tile_sample_min_height": ("INT", {"default": 96, "min": 16, "max": 2048, "step": 8}), "tile_sample_min_height": ("INT", {"default": 240, "min": 16, "max": 2048, "step": 8}),
"tile_sample_min_width": ("INT", {"default": 96, "min": 16, "max": 2048, "step": 8}), "tile_sample_min_width": ("INT", {"default": 360, "min": 16, "max": 2048, "step": 8}),
"tile_overlap_factor_height": ("FLOAT", {"default": 0.083, "min": 0.0, "max": 1.0, "step": 0.001}), "tile_overlap_factor_height": ("FLOAT", {"default": 0.2, "min": 0.0, "max": 1.0, "step": 0.001}),
"tile_overlap_factor_width": ("FLOAT", {"default": 0.083, "min": 0.0, "max": 1.0, "step": 0.001}), "tile_overlap_factor_width": ("FLOAT", {"default": 0.2, "min": 0.0, "max": 1.0, "step": 0.001}),
"enable_vae_slicing": ("BOOLEAN", {"default": True, "tooltip": "VAE will split the input tensor in slices to compute decoding in several steps. This is useful to save some memory and allow larger batch sizes."}), "enable_vae_slicing": ("BOOLEAN", {"default": True, "tooltip": "VAE will split the input tensor in slices to compute decoding in several steps. This is useful to save some memory and allow larger batch sizes."}),
} }
} }