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tiny_dnn 1.0.0
A header only, dependency-free deep learning framework in C++11
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| ▼ tiny_dnn | |
| ▼ activations | |
| activation_function.h | |
| ▼ core | |
| ► framework | |
| ► kernels | |
| ► params | |
| backend.h | |
| backend_avx.h | |
| backend_dnn.h | |
| backend_nnp.h | |
| backend_tiny.h | |
| session.h | |
| ▼ io | |
| ► caffe | |
| cifar10_parser.h | |
| display.h | |
| layer_factory.h | |
| mnist_parser.h | |
| ▼ layers | |
| arithmetic_layer.h | |
| average_pooling_layer.h | |
| average_unpooling_layer.h | |
| batch_normalization_layer.h | |
| concat_layer.h | |
| convolutional_layer.h | |
| deconvolutional_layer.h | |
| dropout_layer.h | |
| feedforward_layer.h | |
| fully_connected_layer.h | |
| input_layer.h | |
| layer.h | |
| layers.h | |
| linear_layer.h | |
| lrn_layer.h | |
| max_pooling_layer.h | |
| max_unpooling_layer.h | |
| partial_connected_layer.h | |
| power_layer.h | |
| quantized_convolutional_layer.h | |
| quantized_deconvolutional_layer.h | |
| quantized_fully_connected_layer.h | |
| slice_layer.h | |
| ▼ lossfunctions | |
| loss_function.h | |
| ▼ models | |
| alexnet.h | |
| ▼ optimizers | |
| optimizer.h | |
| ▼ util | |
| aligned_allocator.h | |
| colored_print.h | |
| deform.h | |
| deserialization_helper.h | |
| graph_visualizer.h | |
| image.h | |
| macro.h | |
| math_functions.h | |
| nn_error.h | |
| parallel_for.h | |
| product.h | |
| random.h | |
| serialization_helper.h | |
| serialization_layer_list.h | |
| target_cost.h | |
| util.h | |
| weight_init.h | |
| config.h | |
| network.h | |
| node.h | |
| nodes.h | |
| tiny_dnn.h |