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ff61ed358e
Summary: This diff is the first step in the effort for refactoring all paramters. As a first step - I'm merging concept of params and computed_params, that is going to be based on tags instead (in the first version it's still using old data structs to store all the BlobReferences). Renaming computed_params to non-trainable/non-backprop params should be done is some other diff. Reviewed By: salexspb Differential Revision: D5119830 fbshipit-source-id: 2001090a37346eb12abbb234e13e727c288eb8a7
37 lines
1.0 KiB
Python
37 lines
1.0 KiB
Python
## @package nonlinearity
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# Module caffe2.python.helpers.nonlinearity
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from __future__ import unicode_literals
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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,
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**kwargs):
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"""PRelu"""
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slope_init = (
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slope_init if slope_init else ('ConstantFill', {'value': 0.25}))
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if model.init_params:
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slope = model.param_init_net.__getattr__(slope_init[0])(
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[],
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blob_out + '_slope',
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shape=[num_channels],
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**slope_init[1]
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)
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else:
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slope = core.ScopedBlobReference(
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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):
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"""Relu."""
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if use_cudnn:
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kwargs['engine'] = 'CUDNN'
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return model.net.Relu(blob_in, blob_out, order=order, **kwargs)
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