55 lines
2.1 KiB
Markdown
55 lines
2.1 KiB
Markdown
# Empty Latent Image (Big Batch) 🎭🅐🅓
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## Documentation
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- Class name: ADE_EmptyLatentImageLarge
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- Category: Animate Diff 🎭🅐🅓/extras
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- Output node: False
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- Repo Ref: https://github.com/Kosinkadink/ComfyUI-AnimateDiff-Evolved.git
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ADE_EmptyLatentImageLarge节点旨在初始化一个用零填充的大型潜在图像张量。此张量作为进一步生成过程的空白画布，允许在潜在层面上创建和操作图像。
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## Input types
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### Required
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- width
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- 指定要生成的潜在图像的宽度。它决定了生成张量的水平维度。
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- Comfy dtype: INT
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- Python dtype: int
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- height
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- 确定潜在图像的高度。它影响生成张量的垂直维度。
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- Comfy dtype: INT
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- Python dtype: int
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- batch_size
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- 控制一次生成的潜在图像的数量。它影响生成张量的第一个维度，允许批处理多个图像。
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- Comfy dtype: INT
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- Python dtype: int
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## Output types
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- latent
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- Comfy dtype: LATENT
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- 输出是一个表示一批空白潜在图像的张量。每个图像都用零初始化，准备进行后续生成修改。
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- Python dtype: torch.Tensor
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## Usage tips
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- Infra type: GPU
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<!-- - Common nodes:
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- [BatchPromptScheduleLatentInput](../../ComfyUI_FizzNodes/Nodes/BatchPromptScheduleLatentInput.md)
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- [KSampler](../../Comfy/Nodes/KSampler.md) -->
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## Source code
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```python
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class EmptyLatentImageLarge:
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def __init__(self, device="cpu"):
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self.device = device
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@classmethod
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def INPUT_TYPES(s):
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return {"required": { "width": ("INT", {"default": 512, "min": 64, "max": comfy_nodes.MAX_RESOLUTION, "step": 8}),
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"height": ("INT", {"default": 512, "min": 64, "max": comfy_nodes.MAX_RESOLUTION, "step": 8}),
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"batch_size": ("INT", {"default": 1, "min": 1, "max": 262144})}}
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RETURN_TYPES = ("LATENT",)
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FUNCTION = "generate"
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CATEGORY = "Animate Diff 🎭🅐🅓/extras"
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def generate(self, width, height, batch_size=1):
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latent = torch.zeros([batch_size, 4, height // 8, width // 8])
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return ({"samples":latent}, ) |