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| from caffe2.python import core |
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| def prelu(model, blob_in, blob_out, num_channels=1, slope_init=None, |
| **kwargs): |
| """PRelu""" |
| slope_init = ( |
| slope_init if slope_init else ('ConstantFill', {'value': 0.25})) |
| if model.init_params: |
| slope = model.param_init_net.__getattr__(slope_init[0])( |
| [], |
| blob_out + '_slope', |
| shape=[num_channels], |
| **slope_init[1] |
| ) |
| else: |
| slope = core.ScopedBlobReference( |
| blob_out + '_slope', model.param_init_net) |
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| model.AddParameter(slope) |
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| return model.net.PRelu([blob_in, slope], [blob_out]) |
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| def relu(model, blob_in, blob_out, use_cudnn=False, order="NCHW", **kwargs): |
| """Relu.""" |
| if use_cudnn: |
| kwargs['engine'] = 'CUDNN' |
| return model.net.Relu(blob_in, blob_out, order=order, **kwargs) |
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| def tanh(model, blob_in, blob_out, use_cudnn=False, order="NCHW", **kwargs): |
| """Tanh.""" |
| if use_cudnn: |
| kwargs['engine'] = 'CUDNN' |
| return model.net.Tanh(blob_in, blob_out, order=order, **kwargs) |
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|
