Created
June 25, 2017 20:48
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#include "tensorflow/cc/client/client_session.h" | |
#include "tensorflow/cc/ops/standard_ops.h" | |
#include "tensorflow/core/framework/tensor.h" | |
namespace tf = tensorflow; | |
namespace to = tf::ops; | |
int main() { | |
tf::Scope r = tf::Scope::NewRootScope(); | |
tf::Scope s = r.ExitOnError(); | |
tf::ClientSession Session(s); | |
tf::Output RandW = to::RandomUniform(s, {10}, tf::DT_DOUBLE); | |
tf::Output W = to::Variable(s.WithOpName("W"), {10}, tf::DT_DOUBLE); | |
tf::Output AssignToW = to::Assign(s, W, RandW); | |
tf::Output RandB = to::RandomUniform(s, {10}, tf::DT_DOUBLE); | |
tf::Output b = to::Variable(s.WithOpName("b"), {10}, tf::DT_DOUBLE); | |
tf::Output AssignToB = to::Assign(s, b, RandB); | |
{ | |
std::vector<tf::Tensor> OutputsOfAssigning; | |
TF_CHECK_OK(Session.Run({AssignToW}, &OutputsOfAssigning)); | |
LOG(INFO) << OutputsOfAssigning[0].vec<double>(); | |
} | |
{ | |
std::vector<tf::Tensor> OutputsOfAssigning; | |
TF_CHECK_OK(Session.Run({AssignToB}, &OutputsOfAssigning)); | |
LOG(INFO) << OutputsOfAssigning[0].vec<double>(); | |
} | |
tf::Output x = to::Placeholder(s.WithOpName("xInput"), tf::DT_DOUBLE); | |
tf::Output Wx = to::MatMul(s.WithOpName("Wx"), W, x, to::MatMul::TransposeB(true)); | |
tf::Output Model = to::AddN(s.WithOpName("Wxb"), {b, Wx}); | |
std::vector<tf::Tensor> Outputs; | |
TF_CHECK_OK(Session.Run({{x, {1., 2., 3., 4., 5., 6., 7., 8., 9., 0.}}}, {Model}, &Outputs)); | |
LOG(INFO) << Outputs[0].matrix<double>(); | |
return 0; | |
// tf::Scope root = tf::Scope::NewRootScope(); | |
// // Matrix A = [3 2; -1 0] | |
// auto A = to::Const(root, {{3.f, 2.f}, {-1.f, 0.f}}); | |
// // Vector b = [3 5] | |
// auto b = to::Const(root, {{3.f, 5.f}}); | |
// // v = Ab^T | |
// auto v = to::MatMul(root.WithOpName("v"), A, b, to::MatMul::TransposeB(true)); | |
// std::vector<tf::Tensor> outputs; | |
// tf::ClientSession session(root); | |
// // Run and fetch v | |
// TF_CHECK_OK(session.Run({v}, &outputs)); | |
// // Expect outputs[0] == [19; -3] | |
// LOG(INFO) << outputs[0].matrix<float>(); | |
// return 0; | |
} |
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