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Commit bb7d2ef5 authored by Davis King's avatar Davis King
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Added input_tensor_to_output_tensor() and output_tensor_to_input_tensor() along 

with the mapping functions necessary at each layer to support these routines.
parent d7c003d1
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dlib/dnn/layers.h
View file @ bb7d2ef5
......@@ -69,6 +69,23 @@ namespace dlib
void set_bias_learning_rate_multiplier(double val) { bias_learning_rate_multiplier = val; }
void set_bias_weight_decay_multiplier(double val) { bias_weight_decay_multiplier = val; }
inline point map_input_to_output (
point p
) const
{
p.x() = (p.x()+padding_x()-nc()/2)/stride_x();
p.y() = (p.y()+padding_y()-nr()/2)/stride_y();
return p;
}
inline point map_output_to_input (
point p
) const
{
p.x() = p.x()*stride_x() - padding_x() + nc()/2;
p.y() = p.y()*stride_y() - padding_y() + nr()/2;
return p;
}
con_ (
const con_& item
......@@ -317,6 +334,24 @@ namespace dlib
long padding_y() const { return padding_y_; }
long padding_x() const { return padding_x_; }
inline point map_input_to_output (
point p
) const
{
p.x() = (p.x()+padding_x()-nc()/2)/stride_x();
p.y() = (p.y()+padding_y()-nr()/2)/stride_y();
return p;
}
inline point map_output_to_input (
point p
) const
{
p.x() = p.x()*stride_x() - padding_x() + nc()/2;
p.y() = p.y()*stride_y() - padding_y() + nr()/2;
return p;
}
max_pool_ (
const max_pool_& item
) :
......@@ -496,6 +531,24 @@ namespace dlib
long padding_y() const { return padding_y_; }
long padding_x() const { return padding_x_; }
inline point map_input_to_output (
point p
) const
{
p.x() = (p.x()+padding_x()-nc()/2)/stride_x();
p.y() = (p.y()+padding_y()-nr()/2)/stride_y();
return p;
}
inline point map_output_to_input (
point p
) const
{
p.x() = p.x()*stride_x() - padding_x() + nc()/2;
p.y() = p.y()*stride_y() - padding_y() + nr()/2;
return p;
}
avg_pool_ (
const avg_pool_& item
) :
......@@ -683,6 +736,9 @@ namespace dlib
void set_bias_learning_rate_multiplier(double val) { bias_learning_rate_multiplier = val; }
void set_bias_weight_decay_multiplier(double val) { bias_weight_decay_multiplier = val; }
inline point map_input_to_output (const point& p) const { return p; }
inline point map_output_to_input (const point& p) const { return p; }
template <typename SUBNET>
void setup (const SUBNET& sub)
......@@ -1143,6 +1199,9 @@ namespace dlib
tt::multiply(true, data_grad, mask, gradient_input);
}
inline point map_input_to_output (const point& p) const { return p; }
inline point map_output_to_input (const point& p) const { return p; }
const tensor& get_layer_params() const { return params; }
tensor& get_layer_params() { return params; }
......@@ -1219,6 +1278,9 @@ namespace dlib
tt::affine_transform(output, input, val);
}
inline point map_input_to_output (const point& p) const { return p; }
inline point map_output_to_input (const point& p) const { return p; }
void backward_inplace(
const tensor& gradient_input,
tensor& data_grad,
......@@ -1324,6 +1386,9 @@ namespace dlib
layer_mode get_mode() const { return mode; }
inline point map_input_to_output (const point& p) const { return p; }
inline point map_output_to_input (const point& p) const { return p; }
template <typename SUBNET>
void setup (const SUBNET& sub)
{
......@@ -1584,6 +1649,9 @@ namespace dlib
tt::relu_gradient(data_grad, computed_output, gradient_input);
}
inline point map_input_to_output (const point& p) const { return p; }
inline point map_output_to_input (const point& p) const { return p; }
const tensor& get_layer_params() const { return params; }
tensor& get_layer_params() { return params; }
......@@ -1661,6 +1729,9 @@ namespace dlib
gradient_input, params, params_grad);
}
inline point map_input_to_output (const point& p) const { return p; }
inline point map_output_to_input (const point& p) const { return p; }
const tensor& get_layer_params() const { return params; }
tensor& get_layer_params() { return params; }
......@@ -1733,6 +1804,9 @@ namespace dlib
tt::sigmoid_gradient(data_grad, computed_output, gradient_input);
}
inline point map_input_to_output (const point& p) const { return p; }
inline point map_output_to_input (const point& p) const { return p; }
const tensor& get_layer_params() const { return params; }
tensor& get_layer_params() { return params; }
......@@ -1783,6 +1857,9 @@ namespace dlib
{
}
inline point map_input_to_output (const point& p) const { return p; }
inline point map_output_to_input (const point& p) const { return p; }
void forward_inplace(const tensor& input, tensor& output)
{
tt::tanh(output, input);
......@@ -1994,6 +2071,9 @@ namespace dlib
impl::concat_helper_impl<TAG_TYPES...>::split(gradient_input, sub, 0);
}
point map_input_to_output(point p) const;
point map_output_to_input(point p) const;
const tensor& get_layer_params() const { return params; }
tensor& get_layer_params() { return params; }
......
dlib/dnn/layers_abstract.h
View file @ bb7d2ef5
......@@ -348,6 +348,16 @@ namespace dlib
- returns the parameters that define the behavior of forward().
!*/
point map_input_to_output(point p) const;
point map_output_to_input(point p) const;
/*!
These two functions are optional. If provided, they should map between
(column,row) coordinates in input and output tensors of forward(). Providing
these functions allows you to use global utility functions like
input_tensor_to_output_tensor().
!*/
};
std::ostream& operator<<(std::ostream& out, const EXAMPLE_COMPUTATIONAL_LAYER_& item);
......@@ -740,6 +750,8 @@ namespace dlib
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);
point map_input_to_output(point p) const;
point map_output_to_input(point p) const;
const tensor& get_layer_params() const;
tensor& get_layer_params();
/*!
......@@ -798,6 +810,8 @@ namespace dlib
template <typename SUBNET> void setup (const SUBNET& sub);
void forward_inplace(const tensor& input, tensor& output);
void backward_inplace(const tensor& gradient_input, tensor& data_grad, tensor& params_grad);
point map_input_to_output(point p) const;
point map_output_to_input(point p) const;
const tensor& get_layer_params() const;
tensor& get_layer_params();
/*!
......@@ -850,6 +864,8 @@ namespace dlib
template <typename SUBNET> void setup (const SUBNET& sub);
void forward_inplace(const tensor& input, tensor& output);
void backward_inplace(const tensor& gradient_input, tensor& data_grad, tensor& params_grad);
point map_input_to_output(point p) const;
point map_output_to_input(point p) const;
const tensor& get_layer_params() const;
tensor& get_layer_params();
/*!
......@@ -1048,6 +1064,8 @@ namespace dlib
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);
point map_input_to_output(point p) const;
point map_output_to_input(point p) const;
const tensor& get_layer_params() const;
tensor& get_layer_params();
/*!
......@@ -1139,6 +1157,8 @@ namespace dlib
template <typename SUBNET> void setup (const SUBNET& sub);
void forward_inplace(const tensor& input, tensor& output);
void backward_inplace(const tensor& computed_output, const tensor& gradient_input, tensor& data_grad, tensor& params_grad);
point map_input_to_output(point p) const;
point map_output_to_input(point p) const;
const tensor& get_layer_params() const;
tensor& get_layer_params();
/*!
......@@ -1273,6 +1293,8 @@ namespace dlib
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& computed_output, const tensor& gradient_input, SUBNET& sub, tensor& params_grad);
point map_input_to_output(point p) const;
point map_output_to_input(point p) const;
const tensor& get_layer_params() const;
tensor& get_layer_params();
/*!
......@@ -1416,6 +1438,8 @@ namespace dlib
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& computed_output, const tensor& gradient_input, SUBNET& sub, tensor& params_grad);
point map_input_to_output(point p) const;
point map_output_to_input(point p) const;
const tensor& get_layer_params() const;
tensor& get_layer_params();
/*!
......@@ -1461,6 +1485,8 @@ namespace dlib
template <typename SUBNET> void setup (const SUBNET& sub);
void forward_inplace(const tensor& input, tensor& output);
void backward_inplace(const tensor& computed_output, const tensor& gradient_input, tensor& data_grad, tensor& params_grad);
point map_input_to_output(point p) const;
point map_output_to_input(point p) const;
const tensor& get_layer_params() const;
tensor& get_layer_params();
/*!
......@@ -1514,6 +1540,8 @@ namespace dlib
template <typename SUBNET> void setup (const SUBNET& sub);
void forward_inplace(const tensor& input, tensor& output);
void backward_inplace(const tensor& computed_output, const tensor& gradient_input, tensor& data_grad, tensor& params_grad);
point map_input_to_output(point p) const;
point map_output_to_input(point p) const;
const tensor& get_layer_params() const;
tensor& get_layer_params();
/*!
......@@ -1545,6 +1573,8 @@ namespace dlib
template <typename SUBNET> void setup (const SUBNET& sub);
void forward_inplace(const tensor& input, tensor& output);
void backward_inplace(const tensor& computed_output, const tensor& gradient_input, tensor& data_grad, tensor& params_grad);
point map_input_to_output(point p) const;
point map_output_to_input(point p) const;
const tensor& get_layer_params() const;
tensor& get_layer_params();
/*!
......@@ -1578,6 +1608,8 @@ namespace dlib
template <typename SUBNET> void setup (const SUBNET& sub);
void forward_inplace(const tensor& input, tensor& output);
void backward_inplace(const tensor& computed_output, const tensor& gradient_input, tensor& data_grad, tensor& params_grad);
point map_input_to_output(point p) const;
point map_output_to_input(point p) const;
const tensor& get_layer_params() const;
tensor& get_layer_params();
/*!
......@@ -1729,6 +1761,8 @@ namespace dlib
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);
point map_input_to_output(point p) const;
point map_output_to_input(point p) const;
const tensor& get_layer_params() const;
tensor& get_layer_params();
/*!
......
dlib/dnn/utilities.h
View file @ bb7d2ef5
......@@ -5,6 +5,7 @@
#include "core.h"
#include "utilities_abstract.h"
#include "../geometry.h"
namespace dlib
{
......@@ -107,6 +108,63 @@ namespace dlib
out << "</net>\n";
}
// ----------------------------------------------------------------------------------------
namespace impl
{
class visitor_net_map_input_to_output
{
public:
visitor_net_map_input_to_output(point& p_) : p(p_) {}
point& p;
template<typename layer_type>
void operator()(size_t idx, const layer_type& net)
{
p = net.layer_details().map_input_to_output(p);
}
};
class visitor_net_map_output_to_input
{
public:
visitor_net_map_output_to_input(point& p_) : p(p_) {}
point& p;
template<typename layer_type>
void operator()(size_t idx, const layer_type& net)
{
p = net.layer_details().map_output_to_input(p);
}
};
}
template <typename net_type>
inline point input_tensor_to_output_tensor(
const net_type& net,
point p
)
{
impl::visitor_net_map_input_to_output temp(p);
visit_layers_backwards_range<0,net_type::num_layers-1>(net, temp);
return p;
}
template <typename net_type>
inline point output_tensor_to_input_tensor(
const net_type& net,
point p
)
{
impl::visitor_net_map_output_to_input temp(p);
visit_layers_range<0,net_type::num_layers-1>(net, temp);
return p;
}
// ----------------------------------------------------------------------------------------
}
......
dlib/dnn/utilities_abstract.h
View file @ bb7d2ef5
......@@ -4,6 +4,7 @@
#ifdef DLIB_DNn_UTILITIES_ABSTRACT_H_
#include "core_abstract.h"
#include "../geometry/vector_abstract.h"
namespace dlib
{
......@@ -55,6 +56,42 @@ namespace dlib
stream.
!*/
// ----------------------------------------------------------------------------------------
template <typename net_type>
point input_tensor_to_output_tensor(
const net_type& net,
point p
);
/*!
requires
- net_type is an object of type add_layer, add_skip_layer, or add_tag_layer.
- All layers in the net must provide map_input_to_output() functions.
ensures
- Given a point (i.e. a row,column coordinate) in the input tensor given to
net, this function returns the corresponding point in the output tensor
net.get_output(). This kind of mapping is useful when working with fully
convolutional networks as you will often want to know what parts of the
output feature maps correspond to what parts of the input.
!*/
// ----------------------------------------------------------------------------------------
template <typename net_type>
point output_tensor_to_input_tensor(
const net_type& net,
point p
);
/*!
requires
- net_type is an object of type add_layer, add_skip_layer, or add_tag_layer.
- All layers in the net must provide map_output_to_input() functions.
ensures
- This function provides the reverse mapping of input_tensor_to_output_tensor().
That is, given a point in net.get_output(), what is the corresponding point
in the input tensor?
!*/
// ----------------------------------------------------------------------------------------
}
......
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