josephjaspers / blackcat_tensors

Matrix-Vector Library Designed for Neural Network Construction. cuda (gpu) support, openmp (multithreaded cpu) support, partial support of BLAS, expression template based implementation PTX code generation identical to hand written kernels, and support for auto-differentiation
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how to use GPU train? #69

Open xinsuinizhuan opened 2 years ago

xinsuinizhuan commented 2 years ago

nvcc: NVIDIA (R) Cuda compiler driver Copyright (c) 2005-2020 NVIDIA Corporation Built on Wed_Jul_22_19:09:35_Pacific_Daylight_Time_2020 Cuda compilation tools, release 11.0, V11.0.221 Build cuda_11.0_bu.relgpu_drvr445TC445_37.28845127_0

VS2019 i set: auto make_lstm_network() { return bc::nn::neuralnetwork( bc::nn::lstm(bc::device_tag(), 96 * 10, 1536, bc::nn::adam), bc::nn::lstm(bc::device_tag(), 1536, 768, bc::nn::adam), bc::nn::lstm(bc::device_tag(), 768, 384, bc::nn::adam), bc::nn::feedforward(bc::device_tag(), 384, 192), bc::nn::logistic(bc::device_tag(), 192), bc::nn::logging_output_layer(bc::device_tag(), 192, bc::nn::RMSE).skip_every(100) ); } using network_type = decltype(make_lstm_network()); but many compile errors: 图片