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Adding specific parameters interface on fc_ layer (#213)

This commit is contained in:
Lucas Clemente Vella 2016-09-10 15:31:01 -03:00 committed by Davis E. King
parent 48df23a0e0
commit 6168781ab9
2 changed files with 80 additions and 0 deletions
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24
dlib/dnn/layers.h
View File

@ -1086,6 +1086,30 @@ namespace dlib
tt::gemm(1,sub.get_gradient_input(), 1,gradient_input,false, w,true);
}
alias_tensor_instance get_weights()
{
return weights(params, 0);
}
alias_tensor_const_instance get_weights() const
{
return weights(params, 0);
}
alias_tensor_instance get_biases()
{
static_assert(bias_mode == FC_HAS_BIAS, "This fc_ layer doesn't have a bias vector "
"to be retrieved, as per template parameter 'bias_mode'.");
return biases(params, weights.size());
}
alias_tensor_const_instance get_biases() const
{
static_assert(bias_mode == FC_HAS_BIAS, "This fc_ layer doesn't have a bias vector "
"to be retrieved, as per template parameter 'bias_mode'.");
return biases(params, weights.size());
}
const tensor& get_layer_params() const { return params; }
tensor& get_layer_params() { return params; }

56
dlib/dnn/layers_abstract.h
View File

@ -539,6 +539,62 @@ namespace dlib
- #get_bias_weight_decay_multiplier() == val
!*/
alias_tensor_const_instance get_weights(
) const;
/*!
ensures
- returns an alias of get_layer_params(), containing the weights matrix of
the fully connected layer.
- #get_weights().num_samples() is the number of elements in input sample,
i.e. sublayer's output's k * nc * nr.
- #get_bias().k() == #get_num_outputs()
- if get_bias_mode() == FC_HAS_BIAS:
- #get_layer_params().size() == (#get_weights().size() + #get_biases().size())
- else:
- #get_layer_params().size() == #get_weights().size()
!*/
alias_tensor_instance get_weights(
);
/*!
ensures
- returns an alias of get_layer_params(), containing the weights matrix of
the fully connected layer.
- #get_weights().num_samples() is the number of elements in input sample,
i.e. sublayer's output's k * nc * nr.
- #get_bias().k() == #get_num_outputs()
- if get_bias_mode() == FC_HAS_BIAS:
- #get_layer_params().size() == (#get_weights().size() + #get_biases().size())
- else:
- #get_layer_params().size() == #get_weights().size()
!*/
alias_tensor_const_instance get_biases(
) const;
/*!
requires
- #get_bias_mode() == FC_HAS_BIAS
ensures
- returns an alias of get_layer_params(), containing the bias vector of
the fully connected layer.
- #get_bias().num_samples() == 1
- #get_bias().k() == #get_num_outputs()
- #get_layer_params().size() == (#get_weights().size() + #get_biases().size())
!*/
alias_tensor_instance get_biases(
);
/*!
requires
- #get_bias_mode() == FC_HAS_BIAS
ensures
- returns an alias of get_layer_params(), containing the bias vector of
the fully connected layer.
- #get_bias().num_samples() == 1
- #get_bias().k() == #get_num_outputs()
- #get_layer_params().size() == (#get_weights().size() + #get_biases().size())
!*/
template <typename SUBNET> void setup (const SUBNET& sub);
template <typename SUBNET> void forward(const SUBNET& sub, resizable_tensor& output);
template <typename SUBNET> void backward(const tensor& gradient_input, SUBNET& sub, tensor& params_grad);