| /external/eigen/Eigen/src/plugins/ |
| D | MatrixCwiseBinaryOps.h | 104 cwiseMax(const EIGEN_CURRENT_STORAGE_BASE_CLASS<OtherDerived> &other) const in cwiseMax() function
115 cwiseMax(const Scalar &other) const in cwiseMax() function
117 return cwiseMax(Derived::Constant(rows(), cols(), other)); in cwiseMax()
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| /external/tensorflow/tensorflow/core/kernels/image/ |
| D | colorspace_op.h | 76 auto dr = ((dh - T(3)).abs() - T(1)).cwiseMax(T(0)).cwiseMin(T(1)); in operator()
77 auto dg = (-(dh - T(2)).abs() + T(2)).cwiseMax(T(0)).cwiseMin(T(1)); in operator()
78 auto db = (-(dh - T(4)).abs() + T(2)).cwiseMax(T(0)).cwiseMin(T(1)); in operator()
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| D | adjust_contrast_op.h | 85 output.device(d) = adjusted.cwiseMin(max_bcast).cwiseMax(min_bcast); in operator()
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| /external/eigen/Eigen/src/Geometry/ |
| D | AlignedBox.h | 204 m_max = m_max.cwiseMax(p_n); in extend()
213 m_max = m_max.cwiseMax(b.m_max); in extend()
222 m_min = m_min.cwiseMax(b.m_min); in clamp()
231 {return AlignedBox(m_min.cwiseMax(b.m_min), m_max.cwiseMin(b.m_max)); } in intersection()
237 { return AlignedBox(m_min.cwiseMin(b.m_min), m_max.cwiseMax(b.m_max)); } in merged()
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| /external/tensorflow/tensorflow/core/kernels/ |
| D | quantize_op.cc | 248 ((input.cwiseMin(max_range).cwiseMax(min_range) - min_range) * in QuantizeSlice()
257 ((input.cwiseMin(max_range).cwiseMax(min_range) - min_range) * in QuantizeSlice()
280 (input.cwiseMin(max_range).cwiseMax(min_range) * scale_factor) in QuantizeSlice()
286 (input.cwiseMin(max_range).cwiseMax(min_range) * scale_factor) in QuantizeSlice()
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| D | quantized_activation_ops.cc | 48 input.flat<T>().cwiseMax(min_as_quantized).template cast<T>(); in Compute()
84 .cwiseMax(min_as_quantized) in Compute()
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| D | fused_eigen_output_kernels.h | 86 -> decltype(expr.cwiseMax(std::declval<typename XprType::Scalar>())) {
87 return expr.cwiseMax(static_cast<typename XprType::Scalar>(0));
95 -> decltype(expr.cwiseMax(std::declval<typename XprType::Scalar>())
97 return expr.cwiseMax(static_cast<typename XprType::Scalar>(0))
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| D | fake_quant_ops_functor.h | 92 auto clamped = inputs.cwiseMin(nudged_max).cwiseMax(nudged_min); in operator()
143 const auto clamped = inputs.cwiseMin(nudged_max).cwiseMax(nudged_min); in operator()
216 inputs.chip<1>(i).cwiseMin(nudged_max).cwiseMax(nudged_min); in operator()
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| D | relu_op_functor.h | 36 features.template cwiseMax<Eigen::PropagateNaN>(static_cast<T>(0)); in operator()
70 features.template cwiseMax<Eigen::PropagateNaN>(static_cast<T>(0)) in operator()
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| D | sdca_internal.h | 100 .cwiseMax(weights.constant(0.0))); in EigenShrinkVector()
108 .cwiseMax(weights.constant(0.0))); in EigenShrinkMatrix()
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| D | histogram_op.cc | 62 ((values.cwiseMax(value_range(0)) - values.constant(value_range(0))) in Compute()
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| D | quantized_pooling_ops.cc | 95 .cwiseMax(lowest) in Compute()
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| D | cwise_op_clip_gpu.cu.cc | 119 out_flat.device(d) = in0_flat.cwiseMin(in2_flat).cwiseMax(in1_flat); in operator ()()
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| D | cwise_op_clip.cc | 147 out_flat.device(d) = in0_flat.cwiseMin(in2_flat).cwiseMax(in1_flat); in operator ()()
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| D | scatter_functor.h | 117 p = p.cwiseMax(u);
121 p = p.cwiseMax(u);
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| D | scatter_nd_op_cpu_impl.h | 97 output.device(device) = output.cwiseMax(update); in Execute()
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| /external/eigen/test/ |
| D | array_for_matrix.cpp | 119 VERIFY_IS_APPROX( (m1.array()>m2.array()).select(m1,m2), m1.cwiseMax(m2) ); in comparisons()
190 …VERIFY_IS_APPROX(MatrixType::Constant(rows,cols, maxM1), m1.cwiseMax(MatrixType::Constant(rows,col… in cwise_min_max()
191 VERIFY_IS_APPROX(m1, m1.cwiseMax(MatrixType::Constant(rows,cols, minM1))); in cwise_min_max()
199 VERIFY_IS_APPROX(MatrixType::Constant(rows,cols, maxM1), m1.cwiseMax( maxM1)); in cwise_min_max()
200 VERIFY_IS_APPROX(m1, m1.cwiseMax(minM1)); in cwise_min_max()
201 VERIFY_IS_APPROX(-m1, (-m1).cwiseMax(-maxM1)); in cwise_min_max()
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| D | block.cpp | 17 VERIFY_IS_APPROX(m1.row(r1).cwiseMax(s1), m1.cwiseMax(s1).row(r1)); in block_real_only()
21 …VERIFY_IS_APPROX(m1.block(r1,c1,r2-r1+1,c2-c1+1).cwiseMax(s1), m1.cwiseMax(s1).block(r1,c1,r2-r1+1… in block_real_only()
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| /external/eigen/doc/snippets/ |
| D | MatrixBase_cwiseMax.cpp | 2 cout << v.cwiseMax(w) << endl;
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| /external/tensorflow/tensorflow/lite/kernels/ |
| D | cpu_backend_gemm_eigen.cc | 73 eigen_dst = eigen_dst.cwiseMin(params.clamp_max).cwiseMax(params.clamp_min); in Run()
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| /external/eigen/unsupported/test/ |
| D | cxx11_tensor_expr.cpp | 135 mat7 = mat1.cwiseMax(mat5 * 2.0f).exp(); in test_3d()
180 mat3 = mat1.cwiseMax(7.3f).exp(); in test_constants()
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| /external/eigen/bench/ |
| D | BenchTimer.h | 88 m_worsts = m_worsts.cwiseMax(m_times); in stop()
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| /external/eigen/unsupported/Eigen/CXX11/src/Tensor/ |
| D | TensorCostModel.h | 106 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost cwiseMax( in cwiseMax() function
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| /external/eigen/unsupported/Eigen/src/LevenbergMarquardt/ |
| D | LMonestep.h | 88 m_diag = m_diag.cwiseMax(m_wa2); in minimizeOneStep()
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| /external/eigen/unsupported/Eigen/src/NonLinearOptimization/ |
| D | HybridNonLinearSolver.h | 233 diag = diag.cwiseMax(wa2); in solveOneStep()
476 diag = diag.cwiseMax(wa2); in solveNumericalDiffOneStep()
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