33 lines
1.4 KiB
Markdown
33 lines
1.4 KiB
Markdown
# Ptn Layer Norm
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A normalization model to normalize elements over specified axes.
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Args:
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normalized_shape (list): Specifies the shape of elements to normalize.
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- For an input of shape `[8, 1024, 768]` (where axes represent `[batch_size, sequence_length, hidden_dim]`):
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- `normalize_shape=[768]` normalizes within each token (across the hidden dimension).
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- `normalize_shape=[1024, 768]` normalizes within each sample (across both sequence and token dimensions).
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- For an image input of shape `[8, 4, 256, 256]` (where axes represent `[batch_size, channel, height, width]`):
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- `normalize_shape=[256, 256]` normalizes within each channel (across spatial dimensions).
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- `normalize_shape=[4, 256, 256]` normalizes within each sample (across channels and spatial dimensions).
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elementwise_affine (bool): If `True`, applies a learnable scaling factor to the normalized elements.
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bias (bool): If `True` and elementwise_affine is also `True`, applies a learnable bias to the normalized elements.
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## Input
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| Name | Data type |
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| normalized_shape | String |
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| elementwise_affine | Boolean |
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| bias | Boolean |
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## Output
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| Data type |
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| Ptmodel |
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<HR>
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Category: PyTorch wrapper - Model
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ComfyUI Pt Wrapper Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.
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