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93571306c3
* Add generic layer specification for using in presets * Modify presets to use the generic scheme
79 lines
2.4 KiB
Python
79 lines
2.4 KiB
Python
#
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# Copyright (c) 2017 Intel Corporation
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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"""
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Module implementing base classes for common network layers used by preset schemes
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"""
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class Conv2d(object):
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"""
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Base class for framework specfic Conv2d layer
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"""
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def __init__(self, num_filters: int, kernel_size: int, strides: int):
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self.num_filters = num_filters
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self.kernel_size = kernel_size
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self.strides = strides
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def __str__(self):
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return "Convolution (num filters = {}, kernel size = {}, stride = {})"\
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.format(self.num_filters, self.kernel_size, self.strides)
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class BatchnormActivationDropout(object):
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"""
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Base class for framework specific batchnorm->activation->dropout layer group
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"""
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def __init__(self, batchnorm: bool=False, activation_function: str=None, dropout_rate: float=0):
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self.batchnorm = batchnorm
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self.activation_function = activation_function
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self.dropout_rate = dropout_rate
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def __str__(self):
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result = []
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if self.batchnorm:
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result += ["Batch Normalization"]
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if self.activation_function:
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result += ["Activation (type = {})".format(self.activation_function)]
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if self.dropout_rate > 0:
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result += ["Dropout (rate = {})".format(self.dropout_rate)]
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return "\n".join(result)
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class Dense(object):
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"""
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Base class for framework specific Dense layer
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"""
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def __init__(self, units: int):
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self.units = units
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def __str__(self):
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return "Dense (num outputs = {})".format(self.units)
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class NoisyNetDense(object):
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"""
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Base class for framework specific factorized Noisy Net layer
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https://arxiv.org/abs/1706.10295.
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"""
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def __init__(self, units: int):
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self.units = units
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self.sigma0 = 0.5
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def __str__(self):
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return "Noisy Dense (num outputs = {})".format(self.units)
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