tiny-dnn/cci.20201023

tiny-dnn is a C++14 implementation of deep learning.
Recipe info
2023-07-17

Available packages
Header Only

Install
Add the following line to your conanfile.txt:
[requires]
tiny-dnn/cci.20201023

Using tiny-dnn

Note

If you are a new Conan user, we recommend reading the how to consume packages tutorial.

If you need additional assistance, please ask a question in the Conan Center Index repository.

Simplest use case consuming this recipe and assuming CMake as your local build tool:

[requires]
tiny-dnn/cci.20201023
[generators]
CMakeDeps
CMakeToolchain
[layout]
cmake_layout
from conan import ConanFile
from conan.tools.cmake import cmake_layout


class ExampleRecipe(ConanFile):
    settings = "os", "compiler", "build_type", "arch"
    generators = "CMakeDeps", "CMakeToolchain"

    def requirements(self):
        self.requires("tiny-dnn/cci.20201023")

    def layout(self):
        cmake_layout(self)

Now, you can run this Conan command to locally install (and build if necessary) this recipe and its dependencies (if any):

$ conan install conanfile.txt --build=missing

Useful information to take into account to consume this library:


These are the main declared targets:

  • CMake package name(s): tinydnn
  • CMake target name(s): TinyDNN::tiny_dnn
  • tinydnn => TinyDNN::tiny_dnn
    
  • pkg-config file name(s): tiny-dnn.pc
  • tinydnn => tiny-dnn-tinydnn.pc
    

A simple use case using the CMake file name and the global target:

# ...
find_package(tinydnn REQUIRED)
# ...
target_link_libraries(YOUR_TARGET TinyDNN::tiny_dnn)

These are all the available headers. Some of these ones might be non-public; make sure of it by visiting the tiny-dnn homepage listed above:

#include "tiny_dnn/activations/activation_layer.h"
#include "tiny_dnn/activations/asinh_layer.h"
#include "tiny_dnn/activations/elu_layer.h"
#include "tiny_dnn/activations/leaky_relu_layer.h"
#include "tiny_dnn/activations/relu_layer.h"
#include "tiny_dnn/activations/selu_layer.h"
#include "tiny_dnn/activations/sigmoid_layer.h"
#include "tiny_dnn/activations/softmax_layer.h"
#include "tiny_dnn/activations/softplus_layer.h"
#include "tiny_dnn/activations/softsign_layer.h"
#include "tiny_dnn/activations/tanh_layer.h"
#include "tiny_dnn/activations/tanh_p1m2_layer.h"
#include "tiny_dnn/config.h"
#include "tiny_dnn/core/backend.h"
#include "tiny_dnn/core/backend_avx.h"
#include "tiny_dnn/core/backend_tiny.h"
#include "tiny_dnn/core/framework/device.fwd.h"
#include "tiny_dnn/core/framework/device.h"
#include "tiny_dnn/core/framework/op_kernel.h"
#include "tiny_dnn/core/framework/program.h"
#include "tiny_dnn/core/framework/program_manager.h"
#include "tiny_dnn/core/framework/tensor.h"
#include "tiny_dnn/core/framework/tensor_utils.h"
#include "tiny_dnn/core/kernels/avx_deconv2d_back_kernel.h"
#include "tiny_dnn/core/kernels/avx_deconv2d_kernel.h"
#include "tiny_dnn/core/kernels/avx_kernel_common.h"
#include "tiny_dnn/core/kernels/conv2d_grad_op.h"
#include "tiny_dnn/core/kernels/conv2d_grad_op_avx.h"
#include "tiny_dnn/core/kernels/conv2d_op.h"
#include "tiny_dnn/core/kernels/conv2d_op_avx.h"
#include "tiny_dnn/core/kernels/conv2d_op_internal.h"
#include "tiny_dnn/core/kernels/conv2d_op_libdnn.h"
#include "tiny_dnn/core/kernels/conv2d_op_nnpack.h"
#include "tiny_dnn/core/kernels/conv2d_op_opencl.h"
#include "tiny_dnn/core/kernels/fully_connected_grad_op.h"
#include "tiny_dnn/core/kernels/fully_connected_op.h"
#include "tiny_dnn/core/kernels/fully_connected_op_avx.h"
#include "tiny_dnn/core/kernels/fully_connected_op_cblas.h"
#include "tiny_dnn/core/kernels/fully_connected_op_intel_mkl.h"
#include "tiny_dnn/core/kernels/fully_connected_op_internal.h"
#include "tiny_dnn/core/kernels/fully_connected_op_nnpack.h"
#include "tiny_dnn/core/kernels/global_avepool_grad_op.h"
#include "tiny_dnn/core/kernels/global_avepool_op.h"
#include "tiny_dnn/core/kernels/global_avepool_op_avx.h"
#include "tiny_dnn/core/kernels/global_avepool_op_internal.h"
#include "tiny_dnn/core/kernels/gru_cell_grad_op.h"
#include "tiny_dnn/core/kernels/gru_cell_op.h"
#include "tiny_dnn/core/kernels/gru_cell_op_internal.h"
#include "tiny_dnn/core/kernels/lstm_cell_grad_op.h"
#include "tiny_dnn/core/kernels/lstm_cell_op.h"
#include "tiny_dnn/core/kernels/lstm_cell_op_internal.h"
#include "tiny_dnn/core/kernels/maxpool_grad_op.h"
#include "tiny_dnn/core/kernels/maxpool_op.h"
#include "tiny_dnn/core/kernels/maxpool_op_avx.h"
#include "tiny_dnn/core/kernels/maxpool_op_internal.h"
#include "tiny_dnn/core/kernels/maxpool_op_nnpack.h"
#include "tiny_dnn/core/kernels/nnp_deconv2d_kernel.h"
#include "tiny_dnn/core/kernels/rnn_cell_grad_op.h"
#include "tiny_dnn/core/kernels/rnn_cell_op.h"
#include "tiny_dnn/core/kernels/rnn_cell_op_internal.h"
#include "tiny_dnn/core/kernels/tiny_deconv2d_back_kernel.h"
#include "tiny_dnn/core/kernels/tiny_deconv2d_kernel.h"
#include "tiny_dnn/core/kernels/tiny_quantization_kernel.h"
#include "tiny_dnn/core/kernels/tiny_quantized_conv2d_kernel.h"
#include "tiny_dnn/core/kernels/tiny_quantized_deconv2d_kernel.h"
#include "tiny_dnn/core/kernels/tiny_quantized_fully_connected_kernel.h"
#include "tiny_dnn/core/kernels/tiny_quantized_matmul_kernel.h"
#include "tiny_dnn/core/params/conv_params.h"
#include "tiny_dnn/core/params/deconv_params.h"
#include "tiny_dnn/core/params/fully_params.h"
#include "tiny_dnn/core/params/global_avepool_params.h"
#include "tiny_dnn/core/params/gru_cell_params.h"
#include "tiny_dnn/core/params/lstm_cell_params.h"
#include "tiny_dnn/core/params/maxpool_params.h"
#include "tiny_dnn/core/params/params.h"
#include "tiny_dnn/core/params/rnn_cell_params.h"
#include "tiny_dnn/core/session.h"
#include "tiny_dnn/io/caffe/CPPLINT.cfg"
#include "tiny_dnn/io/caffe/caffe.proto"
#include "tiny_dnn/io/caffe/layer_factory.h"
#include "tiny_dnn/io/caffe/layer_factory_impl.h"
#include "tiny_dnn/io/cifar10_parser.h"
#include "tiny_dnn/io/display.h"
#include "tiny_dnn/io/layer_factory.h"
#include "tiny_dnn/io/mnist_parser.h"
#include "tiny_dnn/layers/arithmetic_layer.h"
#include "tiny_dnn/layers/average_pooling_layer.h"
#include "tiny_dnn/layers/average_unpooling_layer.h"
#include "tiny_dnn/layers/batch_normalization_layer.h"
#include "tiny_dnn/layers/cell.h"
#include "tiny_dnn/layers/cells.h"
#include "tiny_dnn/layers/concat_layer.h"
#include "tiny_dnn/layers/convolutional_layer.h"
#include "tiny_dnn/layers/deconvolutional_layer.h"
#include "tiny_dnn/layers/dropout_layer.h"
#include "tiny_dnn/layers/fully_connected_layer.h"
#include "tiny_dnn/layers/global_average_pooling_layer.h"
#include "tiny_dnn/layers/gru_cell.h"
#include "tiny_dnn/layers/input_layer.h"
#include "tiny_dnn/layers/l2_normalization_layer.h"
#include "tiny_dnn/layers/layer.h"
#include "tiny_dnn/layers/layers.h"
#include "tiny_dnn/layers/linear_layer.h"
#include "tiny_dnn/layers/lrn_layer.h"
#include "tiny_dnn/layers/lstm_cell.h"
#include "tiny_dnn/layers/max_pooling_layer.h"
#include "tiny_dnn/layers/max_unpooling_layer.h"
#include "tiny_dnn/layers/partial_connected_layer.h"
#include "tiny_dnn/layers/power_layer.h"
#include "tiny_dnn/layers/quantized_convolutional_layer.h"
#include "tiny_dnn/layers/quantized_deconvolutional_layer.h"
#include "tiny_dnn/layers/quantized_fully_connected_layer.h"
#include "tiny_dnn/layers/recurrent_layer.h"
#include "tiny_dnn/layers/rnn_cell.h"
#include "tiny_dnn/layers/slice_layer.h"
#include "tiny_dnn/layers/zero_pad_layer.h"
#include "tiny_dnn/lossfunctions/loss_function.h"
#include "tiny_dnn/models/alexnet.h"
#include "tiny_dnn/network.h"
#include "tiny_dnn/node.h"
#include "tiny_dnn/nodes.h"
#include "tiny_dnn/optimizers/optimizer.h"
#include "tiny_dnn/tiny_dnn.h"
#include "tiny_dnn/util/aligned_allocator.h"
#include "tiny_dnn/util/colored_print.h"
#include "tiny_dnn/util/deform.h"
#include "tiny_dnn/util/deserialization_helper.h"
#include "tiny_dnn/util/gradient_check.h"
#include "tiny_dnn/util/graph_visualizer.h"
#include "tiny_dnn/util/image.h"
#include "tiny_dnn/util/macro.h"
#include "tiny_dnn/util/math_functions.h"
#include "tiny_dnn/util/nms.h"
#include "tiny_dnn/util/nn_error.h"
#include "tiny_dnn/util/parallel_for.h"
#include "tiny_dnn/util/product.h"
#include "tiny_dnn/util/random.h"
#include "tiny_dnn/util/serialization_functions.h"
#include "tiny_dnn/util/serialization_helper.h"
#include "tiny_dnn/util/serialization_layer_list.h"
#include "tiny_dnn/util/target_cost.h"
#include "tiny_dnn/util/util.h"
#include "tiny_dnn/util/weight_init.h"
#include "tiny_dnn/xtensor/xadapt.hpp"
#include "tiny_dnn/xtensor/xarray.hpp"
#include "tiny_dnn/xtensor/xassign.hpp"
#include "tiny_dnn/xtensor/xaxis_iterator.hpp"
#include "tiny_dnn/xtensor/xbroadcast.hpp"
#include "tiny_dnn/xtensor/xbuffer_adaptor.hpp"
#include "tiny_dnn/xtensor/xbuilder.hpp"
#include "tiny_dnn/xtensor/xcomplex.hpp"
#include "tiny_dnn/xtensor/xcontainer.hpp"
#include "tiny_dnn/xtensor/xcsv.hpp"
#include "tiny_dnn/xtensor/xeval.hpp"
#include "tiny_dnn/xtensor/xexception.hpp"
#include "tiny_dnn/xtensor/xexpression.hpp"
#include "tiny_dnn/xtensor/xfunction.hpp"
#include "tiny_dnn/xtensor/xfunctorview.hpp"
#include "tiny_dnn/xtensor/xgenerator.hpp"
#include "tiny_dnn/xtensor/xindexview.hpp"
#include "tiny_dnn/xtensor/xinfo.hpp"
#include "tiny_dnn/xtensor/xio.hpp"
#include "tiny_dnn/xtensor/xiterable.hpp"
#include "tiny_dnn/xtensor/xiterator.hpp"
#include "tiny_dnn/xtensor/xlayout.hpp"
#include "tiny_dnn/xtensor/xmath.hpp"
#include "tiny_dnn/xtensor/xmissing.hpp"
#include "tiny_dnn/xtensor/xnoalias.hpp"
#include "tiny_dnn/xtensor/xoffsetview.hpp"
#include "tiny_dnn/xtensor/xoperation.hpp"
#include "tiny_dnn/xtensor/xoptional.hpp"
#include "tiny_dnn/xtensor/xrandom.hpp"
#include "tiny_dnn/xtensor/xreducer.hpp"
#include "tiny_dnn/xtensor/xscalar.hpp"
#include "tiny_dnn/xtensor/xsemantic.hpp"
#include "tiny_dnn/xtensor/xslice.hpp"
#include "tiny_dnn/xtensor/xstorage.hpp"
#include "tiny_dnn/xtensor/xstridedview.hpp"
#include "tiny_dnn/xtensor/xstrides.hpp"
#include "tiny_dnn/xtensor/xtensor.hpp"
#include "tiny_dnn/xtensor/xtensor_config.hpp"
#include "tiny_dnn/xtensor/xtensor_forward.hpp"
#include "tiny_dnn/xtensor/xutils.hpp"
#include "tiny_dnn/xtensor/xvectorize.hpp"
#include "tiny_dnn/xtensor/xview.hpp"
#include "tiny_dnn/xtensor/xview_utils.hpp"