std::vector<const_cuda_linear_buffer_device_smart_ptr> local_contrast_subtractive_layer_updater_schema::get_schema_buffers() const
{
std::vector<const_cuda_linear_buffer_device_smart_ptr> res;
std::tr1::shared_ptr<const local_contrast_subtractive_layer> layer_derived = std::tr1::dynamic_pointer_cast<const local_contrast_subtractive_layer>(layer_schema);
res.push_back(
cuda_linear_buffer_device_smart_ptr(new cuda_linear_buffer_device(
&(*layer_derived->feature_maps_affected.begin()),
layer_derived->feature_maps_affected.size() * sizeof(unsigned int)))
);
for(std::vector<std::vector<float> >::const_iterator it = layer_derived->window_weights_list.begin(); it != layer_derived->window_weights_list.end(); ++it)
{
const std::vector<float>& current_weights = *it;
res.push_back(
cuda_linear_buffer_device_smart_ptr(new cuda_linear_buffer_device(
&(*current_weights.begin()),
current_weights.size() * sizeof(float)))
);
}
if (!layer_derived->feature_maps_unaffected.empty())
{
res.push_back(
cuda_linear_buffer_device_smart_ptr(new cuda_linear_buffer_device(
&(*layer_derived->feature_maps_unaffected.begin()),
layer_derived->feature_maps_unaffected.size() * sizeof(unsigned int)))
);
}
return res;
}
layer_hessian_cuda::buffer_set layer_hessian_cuda::allocate_all_buffers(unsigned int max_entry_count) const
{
buffer_set res;
std::vector<size_t> sizes = get_sizes_of_additional_buffers_per_entry();
for(std::vector<size_t>::const_iterator it = sizes.begin(); it != sizes.end(); ++it)
{
size_t sz = *it * max_entry_count;
res.additional_buffers.push_back(cuda_linear_buffer_device_smart_ptr(new cuda_linear_buffer_device(sz)));
}
std::vector<size_t> fixed_sizes = get_sizes_of_additional_buffers_fixed();
for(std::vector<size_t>::const_iterator it = fixed_sizes.begin(); it != fixed_sizes.end(); ++it)
{
res.additional_buffers.push_back(cuda_linear_buffer_device_smart_ptr(new cuda_linear_buffer_device(*it)));
}
{
size_t sz = output_elem_count_per_entry * sizeof(float) * max_entry_count;
res.output_neurons_buffer = cuda_linear_buffer_device_smart_ptr(new cuda_linear_buffer_device(sz));
}
if (backprop_required && !is_in_place_backprop())
{
size_t sz = input_elem_count_per_entry * sizeof(float) * max_entry_count;
res.input_errors_buffer = cuda_linear_buffer_device_smart_ptr(new cuda_linear_buffer_device(sz));
}
fill_additional_buffers(res.additional_buffers);
return res;
}
std::vector<cuda_linear_buffer_device_smart_ptr> weight_vector_bound_cuda::allocate_additional_buffers(unsigned int max_entry_count)
{
std::vector<cuda_linear_buffer_device_smart_ptr> res;
std::vector<size_t> per_entry_sizes = get_sizes_of_additional_buffers_per_entry();
for(std::vector<size_t>::const_iterator it = per_entry_sizes.begin(); it != per_entry_sizes.end(); ++it)
res.push_back(cuda_linear_buffer_device_smart_ptr(new cuda_linear_buffer_device(*it * max_entry_count)));
return res;
}
std::vector<const_cuda_linear_buffer_device_smart_ptr> sigmoid_layer_updater_schema::get_schema_buffers() const
{
std::vector<const_cuda_linear_buffer_device_smart_ptr> res;
nnforge_shared_ptr<const sigmoid_layer> layer_derived = nnforge_dynamic_pointer_cast<const sigmoid_layer>(layer_schema);
if (!layer_derived->affected_feature_map_id_list.empty())
{
res.push_back(
cuda_linear_buffer_device_smart_ptr(new cuda_linear_buffer_device(
&(layer_derived->affected_feature_map_id_list.front()),
layer_derived->affected_feature_map_id_list.size() * sizeof(unsigned int)))
);
}
return res;
}
