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import torch |
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import torch.nn as nn |
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import torch.nn.functional as F |
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from annotator.mmpkg.mmcv.utils import TORCH_VERSION, build_from_cfg, digit_version |
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from .registry import ACTIVATION_LAYERS |
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for module in [ |
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nn.ReLU, nn.LeakyReLU, nn.PReLU, nn.RReLU, nn.ReLU6, nn.ELU, |
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nn.Sigmoid, nn.Tanh |
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]: |
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ACTIVATION_LAYERS.register_module(module=module) |
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@ACTIVATION_LAYERS.register_module(name='Clip') |
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@ACTIVATION_LAYERS.register_module() |
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class Clamp(nn.Module): |
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"""Clamp activation layer. |
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This activation function is to clamp the feature map value within |
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:math:`[min, max]`. More details can be found in ``torch.clamp()``. |
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Args: |
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min (Number | optional): Lower-bound of the range to be clamped to. |
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Default to -1. |
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max (Number | optional): Upper-bound of the range to be clamped to. |
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Default to 1. |
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""" |
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def __init__(self, min=-1., max=1.): |
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super(Clamp, self).__init__() |
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self.min = min |
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self.max = max |
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def forward(self, x): |
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"""Forward function. |
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Args: |
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x (torch.Tensor): The input tensor. |
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Returns: |
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torch.Tensor: Clamped tensor. |
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""" |
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return torch.clamp(x, min=self.min, max=self.max) |
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class GELU(nn.Module): |
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r"""Applies the Gaussian Error Linear Units function: |
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.. math:: |
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\text{GELU}(x) = x * \Phi(x) |
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where :math:`\Phi(x)` is the Cumulative Distribution Function for |
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Gaussian Distribution. |
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Shape: |
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- Input: :math:`(N, *)` where `*` means, any number of additional |
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dimensions |
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- Output: :math:`(N, *)`, same shape as the input |
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.. image:: scripts/activation_images/GELU.png |
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Examples:: |
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>>> m = nn.GELU() |
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>>> input = torch.randn(2) |
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>>> output = m(input) |
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""" |
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def forward(self, input): |
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return F.gelu(input) |
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if (TORCH_VERSION == 'parrots' |
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or digit_version(TORCH_VERSION) < digit_version('1.4')): |
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ACTIVATION_LAYERS.register_module(module=GELU) |
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else: |
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ACTIVATION_LAYERS.register_module(module=nn.GELU) |
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def build_activation_layer(cfg): |
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"""Build activation layer. |
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Args: |
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cfg (dict): The activation layer config, which should contain: |
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- type (str): Layer type. |
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- layer args: Args needed to instantiate an activation layer. |
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Returns: |
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nn.Module: Created activation layer. |
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""" |
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return build_from_cfg(cfg, ACTIVATION_LAYERS) |
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