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#!/usr/bin/env python |
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# -*- coding: utf-8 -*- |
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from layer import NeuralLayer |
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class Block(NeuralLayer): |
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""" |
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Create a block, which contains the parameters of many connected layers. |
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""" |
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def __init__(self): |
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super(Block, self).__init__("block") |
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self.layers = [] |
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self.fixed = False |
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def fix(self): |
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""" |
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Fix the block, register all the parameters of sub layers. |
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:return: |
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""" |
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if not self.fixed: |
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for layer in self.layers: |
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if not layer.initialized: |
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raise Exception("All sub layers in a block must be initialized when fixing it.") |
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self.register_inner_layers(layer) |
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self.fixed = True |
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def register(self, *layers): |
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""" |
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Register many connected layers. |
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:type layers: list of NeuralLayer |
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""" |
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for layer in layers: |
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self.register_layer(layer) |
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def register_layer(self, layer): |
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""" |
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Register one connected layer. |
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:type layer: NeuralLayer |
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""" |
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if self.fixed: |
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raise Exception("After a block is fixed, no more layers can be registered.") |
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self.layers.append(layer) |
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def compute_tensor(self, x): |
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return x |
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def compute_test_tesnor(self, x): |
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return x |
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def load_params(self, path, exclude_free_params=False): |
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""" |
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Load parameters to the block. |
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""" |
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from deepy.networks.comp_graph import ComputationalGraph |
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model = ComputationalGraph(blocks=[self]) |
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model.load_params(path, exclude_free_params=exclude_free_params) |
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@property |
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def all_parameters(self): |
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return self.parameters |
zomux /
deepy
