41 lines
1.2 KiB
Python
41 lines
1.2 KiB
Python
"""Custom activation functions."""
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import torch
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import torch.nn as nn
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from cacheflow import activation_ops
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_ACTIVATION_REGISTRY = {
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"gelu": nn.GELU(),
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"gelu_new": nn.GELU(approximate="tanh"), # NOTE: This may introduce small rounding errors.
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"gelu_fast": nn.GELU(approximate="tanh"), # NOTE: This may introduce small rounding errors.
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"relu": nn.ReLU(),
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}
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def get_act_fn(act_fn: str) -> nn.Module:
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"""Get an activation function by name."""
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act_fn = act_fn.lower()
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if act_fn in _ACTIVATION_REGISTRY:
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return _ACTIVATION_REGISTRY[act_fn]
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raise ValueError(f"Activation function {act_fn!r} is not supported.")
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class SiluAndMul(nn.Module):
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"""An activation function for SwiGLU.
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The function computes x -> silu(x[:d]) * x[d:] where d = x.shape[1] // 2.
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"""
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def __init__(self):
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super().__init__()
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def forward(
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self,
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x: torch.Tensor, # (num_tokens, 2 * d)
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) -> torch.Tensor: # (num_tokens, d)
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num_tokens = x.shape[0]
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d = x.shape[1] // 2
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out = torch.empty(num_tokens, d, dtype=x.dtype, device=x.device)
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activation_ops.silu_and_mul(out, x)
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return out
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