| /external/eigen/bench/btl/libs/gmm/ |
| gmm_interface.hh | 21 #include <gmm/gmm.h>
24 using namespace gmm;
36 typedef gmm::dense_matrix<real> gene_matrix;
41 return "gmm";
82 gmm::mult(A,B, X);
86 gmm::mult(gmm::transposed(A),gmm::transposed(B), X);
90 gmm::mult(gmm::transposed(A),A, X)
[all...] |
| /external/tensorflow/tensorflow/contrib/factorization/python/ops/ |
| gmm_test.py | 15 """Tests for ops.gmm."""
23 from tensorflow.contrib.factorization.python.ops import gmm as gmm_lib
88 gmm = gmm_lib.GMM(self.num_centers,
92 gmm.fit(input_fn=self.input_fn(), steps=0)
93 weights = gmm.weights()
98 gmm = gmm_lib.GMM(self.num_centers,
102 gmm.fit(input_fn=self.input_fn(), steps=0)
103 clusters = gmm.clusters(
[all...] |
| gmm.py | 15 """Implementation of Gaussian mixture model (GMM) clustering using tf.Learn."""
69 class GMM(estimator.Estimator):
70 """An estimator for GMM clustering."""
83 """Creates a model for running GMM training and inference.
93 See gmm_ops.gmm for the possible values.
103 super(GMM, self).__init__(
112 yield result[GMM.ASSIGNMENTS]
127 return np.log(np.sum(np.exp(results[GMM.SCORES])))
162 is_initialized) = gmm_ops.gmm(self._parse_tensor_or_dict(features),
172 GMM.ASSIGNMENTS: model_predictions[0][0]
[all...] |
| gmm_ops_test.py | 125 loss_op, scores, assignments, training_op, init_op, _ = gmm_ops.gmm(
|
| gmm_ops.py | 155 """Initializes GMM algorithm."""
462 def gmm(inp, function
468 """Creates the graph for Gaussian mixture model (GMM) clustering.
498 # Implementation of GMM.
|
| /external/tensorflow/tensorflow/contrib/factorization/ |
| __init__.py | 24 from tensorflow.contrib.factorization.python.ops.gmm import *
34 'GMM',
35 'gmm',
|
| /external/eigen/bench/ |
| BenchUtil.h | 47 #include <gmm/gmm.h>
|
| sparse_transpose.cpp | 78 // GMM++
84 BENCH(for (int k=0; k<REPEAT; ++k) gmm::copy(gmm::transposed(m1),m3);)
85 std::cout << " GMM:\t\t" << timer.value() << endl;
|
| BenchSparseUtil.h | 71 #include "gmm/gmm.h"
72 typedef gmm::csc_matrix<Scalar> GmmSparse;
73 typedef gmm::col_matrix< gmm::wsvector<Scalar> > GmmDynSparse;
80 gmm::copy(tmp, dst);
|
| sparse_trisolver.cpp | 134 // GMM++
137 std::cout << "GMM++ sparse\t" << density*100 << "%\n";
139 gmm::csr_matrix<Scalar> m2;
141 gmm::copy(m1,m2);
147 BENCH(gmm::upper_tri_solve(m1, gmmX, false);)
152 BENCH(gmm::upper_tri_solve(m2, gmmX, false);)
|
| benchEigenSolver.cpp | 95 gmm::dense_matrix<Scalar> gmmCovMat(covMat.rows(),covMat.cols());
96 gmm::dense_matrix<Scalar> eigvect(covMat.rows(),covMat.cols());
104 gmm::symmetric_qr_algorithm(gmmCovMat, eigval, eigvect);
115 // gmm::implicit_qr_algorithm(gmmCovMat, eigval, eigvect);
194 std::cout << " GMM++ ";
|
| sparse_dense_product.cpp | 115 // GMM++
118 std::cout << "GMM++ sparse\t" << density*100 << "%\n";
127 BENCH( asm("#myx"); gmm::mult(m1, gmmV1, gmmV2); asm("#myy"); )
130 BENCH( gmm::mult(gmm::transposed(m1), gmmV1, gmmV2); )
152 // BENCH( boost::ublas::prod(gmm::transposed(m1), gmmV1, gmmV2); )
|
| spmv.cpp | 188 // GMM++
198 SPMV_BENCH(gmm::mult(gm, gv, gres));
199 std::cout << "GMM++ " << t.value()/repeats << "\t";
201 SPMV_BENCH(gmm::mult(gmm::transposed(gm), gv, gres));
|
| sparse_product.cpp | 263 // GMM++
266 std::cout << "GMM++ sparse\t" << nnzPerCol << "%\n";
272 BENCH(gmm::mult(m1, m2, gmmT3););
275 // BENCH(gmm::mult(gmm::transposed(m1), m2, gmmT3););
280 // BENCH(gmm::mult(gmm::transposed(m1), gmm::transposed(m2), gmmT3););
283 // BENCH(gmm::mult(m1, gmm::transposed(m2), gmmT3);)
[all...] |
