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Commit ea5f89c6 authored by Davis King's avatar Davis King
Browse files

Renamed variable to make things more clear.

parent 030f5a0a
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Showing with 25 additions and 25 deletions
dlib/dnn/core.h
View file @ ea5f89c6
......@@ -1344,7 +1344,7 @@ namespace dlib
template <
size_t num,
template<typename> class LAYER,
template<typename> class REPEATED_LAYER,
typename SUBNET
>
class repeat
......@@ -1353,10 +1353,10 @@ namespace dlib
public:
typedef SUBNET subnet_type;
typedef typename SUBNET::input_type input_type;
const static size_t num_layers = (LAYER<SUBNET>::num_layers-SUBNET::num_layers)*num + SUBNET::num_layers;
const static size_t num_layers = (REPEATED_LAYER<SUBNET>::num_layers-SUBNET::num_layers)*num + SUBNET::num_layers;
const static unsigned int sample_expansion_factor = SUBNET::sample_expansion_factor;
typedef LAYER<impl::repeat_input_layer> repeated_layer_type;
typedef REPEATED_LAYER<impl::repeat_input_layer> repeated_layer_type;
repeat(
) :
......@@ -1481,7 +1481,7 @@ namespace dlib
template <typename solver_type>
void update(const tensor& x, const tensor& gradient_input, sstack<solver_type> solvers, double step_size)
{
const auto cnt = (LAYER<SUBNET>::num_layers-SUBNET::num_layers);
const auto cnt = (REPEATED_LAYER<SUBNET>::num_layers-SUBNET::num_layers);
if (details.size() > 1)
{
details[0].update(details[1].get_output(), gradient_input, solvers,step_size);
......@@ -1565,10 +1565,10 @@ namespace dlib
template <
size_t num,
template<typename> class LAYER,
template<typename> class REPEATED_LAYER,
typename SUBNET
>
struct is_nonloss_layer_type<repeat<num,LAYER,SUBNET>> : std::true_type {};
struct is_nonloss_layer_type<repeat<num,REPEATED_LAYER,SUBNET>> : std::true_type {};
// ----------------------------------------------------------------------------------------
......
dlib/dnn/core_abstract.h
View file @ ea5f89c6
......@@ -927,7 +927,7 @@ namespace dlib
template <
size_t num,
template<typename> class LAYER,
template<typename> class REPEATED_LAYER,
typename SUBNET
>
class repeat
......@@ -936,11 +936,11 @@ namespace dlib
REQUIREMENTS ON num
- num > 0
REQUIREMENTS ON LAYER
- LAYER must be a template that stacks more layers onto a deep neural
REQUIREMENTS ON REPEATED_LAYER
- REPEATED_LAYER must be a template that stacks more layers onto a deep neural
network. For example, if net_type were a network without a loss layer,
then it should be legal to create a deeper network with a type of
LAYER<net_type>.
REPEATED_LAYER<net_type>.
REQUIREMENTS ON SUBNET
- One of the following must be true:
......@@ -951,8 +951,8 @@ namespace dlib
WHAT THIS OBJECT REPRESENTS
This object adds more layers to a deep neural network. In particular, it
adds LAYER on top of SUBNET num times. So for example, if num were 2 then
repeat<2,LAYER,SUBNET> would create a network equivalent to LAYER<LAYER<SUBNET>>.
adds REPEATED_LAYER on top of SUBNET num times. So for example, if num were 2 then
repeat<2,REPEATED_LAYER,SUBNET> would create a network equivalent to REPEATED_LAYER<REPEATED_LAYER<SUBNET>>.
Also, this object provides an interface identical to the one defined by the
add_layer object except that we add the num_repetitions() and
......@@ -964,9 +964,9 @@ namespace dlib
typedef SUBNET subnet_type;
typedef typename SUBNET::input_type input_type;
const static size_t num_layers = (LAYER<SUBNET>::num_layers-SUBNET::num_layers)*num + SUBNET::num_layers;
const static size_t num_layers = (REPEATED_LAYER<SUBNET>::num_layers-SUBNET::num_layers)*num + SUBNET::num_layers;
const static unsigned int sample_expansion_factor = SUBNET::sample_expansion_factor;
typedef LAYER<an_unspecified_input_type> repeated_layer_type;
typedef REPEATED_LAYER<an_unspecified_input_type> repeated_layer_type;
template <typename T, typename ...U>
repeat(
......@@ -975,8 +975,8 @@ namespace dlib
);
/*!
ensures
- arg1 is used to initialize the num_repetitions() copies of LAYER inside
this object. That is, all the LAYER elements are initialized identically
- arg1 is used to initialize the num_repetitions() copies of REPEATED_LAYER inside
this object. That is, all the REPEATED_LAYER elements are initialized identically
by being given copies of arg1.
- The rest of the arguments to the constructor, i.e. args2, are passed to
SUBNET's constructor.
......@@ -986,7 +986,7 @@ namespace dlib
) const;
/*!
ensures
- returns num (i.e. the number of times LAYER was stacked on top of SUBNET)
- returns num (i.e. the number of times REPEATED_LAYER was stacked on top of SUBNET)
!*/
const repeated_layer_type& get_repeated_layer (
......@@ -996,10 +996,10 @@ namespace dlib
requires
- i < num_repetitions()
ensures
- returns a reference to the i-th instance of LAYER. For example,
get_repeated_layer(0) returns the instance of LAYER that is on the top of
- returns a reference to the i-th instance of REPEATED_LAYER. For example,
get_repeated_layer(0) returns the instance of REPEATED_LAYER that is on the top of
the network while get_repeated_layer(num_repetitions()-1) returns the
instance of LAYER that is stacked immediately on top of SUBNET.
instance of REPEATED_LAYER that is stacked immediately on top of SUBNET.
!*/
repeated_layer_type& get_repeated_layer (
......@@ -1009,10 +1009,10 @@ namespace dlib
requires
- i < num_repetitions()
ensures
- returns a reference to the i-th instance of LAYER. For example,
get_repeated_layer(0) returns the instance of LAYER that is on the top of
- returns a reference to the i-th instance of REPEATED_LAYER. For example,
get_repeated_layer(0) returns the instance of REPEATED_LAYER that is on the top of
the network while get_repeated_layer(num_repetitions()-1) returns the
instance of LAYER that is stacked immediately on top of SUBNET.
instance of REPEATED_LAYER that is stacked immediately on top of SUBNET.
!*/
const subnet_type& subnet(
......@@ -1020,7 +1020,7 @@ namespace dlib
/*!
ensures
- returns the SUBNET base network that repeat sits on top of. If you want
to access the LAYER components then you must use get_repeated_layer().
to access the REPEATED_LAYER components then you must use get_repeated_layer().
!*/
subnet_type& subnet(
......@@ -1028,7 +1028,7 @@ namespace dlib
/*!
ensures
- returns the SUBNET base network that repeat sits on top of. If you want
to access the LAYER components then you must use get_repeated_layer().
to access the REPEATED_LAYER components then you must use get_repeated_layer().
!*/
};
......
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