/dports/math/py-keras/Keras-2.4.3/tests/integration_tests/ |
H A D | test_datasets.py | 19 (x_train, y_train), (x_test, y_test) = cifar10.load_data() 21 assert len(x_test) == len(y_test) == 10000 24 assert len(x_test) == len(y_test) == 10000 27 assert len(x_test) == len(y_test) == 10000 37 assert len(x_test) == len(y_test) 38 assert len(x_train) + len(x_test) == 11228 41 assert len(x_test) == len(y_test) 53 assert len(x_test) == len(y_test) == 10000 64 assert len(x_test) == len(y_test) 76 assert len(x_test) == len(y_test) [all …]
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/dports/math/py-keras/Keras-2.4.3/examples/ |
H A D | mnist_cnn.py | 24 (x_train, y_train), (x_test, y_test) = mnist.load_data() 28 x_test = x_test.reshape(x_test.shape[0], 1, img_rows, img_cols) variable 32 x_test = x_test.reshape(x_test.shape[0], img_rows, img_cols, 1) variable 36 x_test = x_test.astype('float32') variable 38 x_test /= 255 41 print(x_test.shape[0], 'test samples') 67 validation_data=(x_test, y_test)) 68 score = model.evaluate(x_test, y_test, verbose=0)
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H A D | mnist_swwae.py | 104 (x_train, _), (x_test, _) = mnist.load_data() 107 x_test = x_test.reshape(x_test.shape[0], 1, img_rows, img_cols) variable 109 x_test = x_test.astype('float32') variable 111 x_test /= 255 114 print(x_test.shape[0], 'test samples') 133 x_test = np.pad(x_test, [[0, 0], [0, 0], [2, 2], [2, 2]], mode='constant') variable 138 x_test = x_test[:, :, :-1, :-1] variable 179 validation_data=(x_test, x_test)) 182 x_recon = model.predict(x_test[:25]) 183 x_plot = np.concatenate((x_test[:25], x_recon), axis=1)
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H A D | mnist_hierarchical_rnn.py | 53 (x_train, y_train), (x_test, y_test) = mnist.load_data() 57 x_test = x_test.reshape(x_test.shape[0], 28, 28, 1) variable 59 x_test = x_test.astype('float32') variable 61 x_test /= 255 64 print(x_test.shape[0], 'test samples') 93 validation_data=(x_test, y_test)) 96 scores = model.evaluate(x_test, y_test, verbose=0)
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H A D | mnist_irnn.py | 35 (x_train, y_train), (x_test, y_test) = mnist.load_data() 38 x_test = x_test.reshape(x_test.shape[0], -1, 1) variable 40 x_test = x_test.astype('float32') variable 42 x_test /= 255 45 print(x_test.shape[0], 'test samples') 69 validation_data=(x_test, y_test)) 71 scores = model.evaluate(x_test, y_test, verbose=0)
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H A D | mnist_mlp.py | 21 (x_train, y_train), (x_test, y_test) = mnist.load_data() 24 x_test = x_test.reshape(10000, 784) variable 26 x_test = x_test.astype('float32') variable 28 x_test /= 255 30 print(x_test.shape[0], 'test samples') 53 validation_data=(x_test, y_test)) 54 score = model.evaluate(x_test, y_test, verbose=0)
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H A D | mnist_sklearn_wrapper.py | 24 (x_train, y_train), (x_test, y_test) = mnist.load_data() 28 x_test = x_test.reshape(x_test.shape[0], 1, img_rows, img_cols) variable 32 x_test = x_test.reshape(x_test.shape[0], img_rows, img_cols, 1) variable 36 x_test = x_test.astype('float32') variable 38 x_test /= 255 100 metric_values = best_model.evaluate(x_test, y_test)
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H A D | mnist_transfer_cnn.py | 45 x_test = test[0].reshape((test[0].shape[0],) + input_shape) 47 x_test = x_test.astype('float32') 49 x_test /= 255 52 print(x_test.shape[0], 'test samples') 67 validation_data=(x_test, y_test)) 69 score = model.evaluate(x_test, y_test, verbose=0) 75 (x_train, y_train), (x_test, y_test) = mnist.load_data() 80 x_test_lt5 = x_test[y_test < 5] 85 x_test_gte5 = x_test[y_test >= 5]
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H A D | lstm_stateful.py | 166 x_test = x[to_train:] 172 x_test = x_test[:-1 * to_drop] 178 x_test = reshape_3(x_test) 184 return (x_train, y_train), (x_test, y_test) 187 (x_train, y_train), (x_test, y_test) = split_data(data_input, expected_output) 190 print('x_test.shape: ', x_test.shape) 207 validation_data=(x_test, y_test), 212 predicted_stateful = model_stateful.predict(x_test, batch_size=batch_size) 223 validation_data=(x_test, y_test), 227 predicted_stateless = model_stateless.predict(x_test, batch_size=batch_size)
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H A D | imdb_fasttext.py | 80 (x_train, y_train), (x_test, y_test) = imdb.load_data(num_words=max_features) 82 print(len(x_test), 'test sequences') 86 np.mean(list(map(len, x_test)), dtype=int))) 109 x_test = add_ngram(x_test, token_indice, ngram_range) variable 113 np.mean(list(map(len, x_test)), dtype=int))) 117 x_test = sequence.pad_sequences(x_test, maxlen=maxlen) variable 119 print('x_test shape:', x_test.shape) 144 validation_data=(x_test, y_test))
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/dports/science/py-dipy/dipy-1.4.1/dipy/nn/tests/ |
H A D | test_tf.py | 23 (x_train, y_train), (x_test, y_test) = mnist.load_data() 24 x_train, x_test = x_train / 255.0, x_test / 255.0 38 model.evaluate(x_test, y_test, verbose=2) 49 (x_train, y_train), (x_test, y_test) = mnist.load_data() 50 x_train, x_test = x_train / 255.0, x_test / 255.0 54 slp.evaluate(x_test, y_test, verbose=2) 55 x_test_prob = slp.predict(x_test) 69 (x_train, y_train), (x_test, y_test) = mnist.load_data() 70 x_train, x_test = x_train / 255.0, x_test / 255.0 74 mlp.evaluate(x_test, y_test, verbose=2) [all …]
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/dports/biology/ncbi-blast+/ncbi-blast-2.12.0+-src/c++/scripts/common/check/ |
H A D | check_add.sh | 29 x_test=$2 51 if test ! -f "$x_srcdir/Makefile.$x_test.app"; then 52 echo "Warning: File \"$x_srcdir/Makefile.$x_test.app\" not found." 57 x_app=`grep '^ *APP[ =]' "$x_srcdir/Makefile.$x_test.app"` 60 x_tpath=$x_srcdir_rel/$x_test 61 if grep -c '^ *CHECK_CMD' $x_srcdir/Makefile.$x_test.app > /dev/null ; then 90 x_run=`grep '^ *CHECK_CMD' "$x_srcdir/Makefile.$x_test.app"` 98 x_files=`grep '^ *CHECK_COPY' "$x_srcdir/Makefile.$x_test.app" | sed -e 's/^.*=//' -e 's/^[ ]*//'` 100 x_timeout=`grep '^ *CHECK_TIMEOUT' "$x_srcdir/Makefile.$x_test.app" | sed -e 's/^.*=//' -e 's/^[ ]*… 103 x_requires=`grep '^ *CHECK_REQUIRES' "$x_srcdir/Makefile.$x_test.app" | sed -e 's/^.*=//' -e 's/^[ … [all …]
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/dports/biology/ncbi-cxx-toolkit/ncbi_cxx--25_2_0/scripts/common/check/ |
H A D | check_add.sh | 29 x_test=$2 51 if test ! -f "$x_srcdir/Makefile.$x_test.app"; then 52 echo "Warning: File \"$x_srcdir/Makefile.$x_test.app\" not found." 57 x_app=`grep '^ *APP[ =]' "$x_srcdir/Makefile.$x_test.app"` 60 x_tpath=$x_srcdir_rel/$x_test 61 if grep -c '^ *CHECK_CMD' $x_srcdir/Makefile.$x_test.app > /dev/null ; then 90 x_run=`grep '^ *CHECK_CMD' "$x_srcdir/Makefile.$x_test.app"` 98 x_files=`grep '^ *CHECK_COPY' "$x_srcdir/Makefile.$x_test.app" | sed -e 's/^.*=//' -e 's/^[ ]*//'` 100 x_timeout=`grep '^ *CHECK_TIMEOUT' "$x_srcdir/Makefile.$x_test.app" | sed -e 's/^.*=//' -e 's/^[ ]*… 103 x_requires=`grep '^ *CHECK_REQUIRES' "$x_srcdir/Makefile.$x_test.app" | sed -e 's/^.*=//' -e 's/^[ … [all …]
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/dports/math/openturns/openturns-1.18/python/doc/examples/meta_modeling/kriging_metamodel/ |
H A D | plot_kriging_chose_trend.py | 76 y_test = model(x_test) 138 y_test = metamodel(x_test) 139 curve = ot.Curve(x_test, y_test) 170 y_test = myTrend(myTransform(x_test)) 171 curve = ot.Curve(x_test, y_test) 233 y_test = metamodel(x_test) 234 curve = ot.Curve(x_test, y_test) 265 curve = ot.Curve(x_test, y_test) 311 y_test = metamodel(x_test) 312 curve = ot.Curve(x_test, y_test) [all …]
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H A D | plot_kriging_simulate.py | 73 y_test = g(x_test) 89 def plot_data_test(x_test, y_test): argument 91 graphF = ot.Curve(x_test, y_test) 100 graph.add(plot_data_test(x_test, y_test)) 125 y_test_MM = krigeageMM(x_test) 132 def plot_data_kriging(x_test, y_test_MM): argument 134 graphK = ot.Curve(x_test, y_test_MM) 142 graph.add(plot_data_test(x_test, y_test)) 176 def deleteCommonValues(x_train, x_test): argument 181 x_test_filtered = x_test # Initialize [all …]
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H A D | plot_kriging_1d.py | 75 x_test = myRegularGrid.getVertices() variable 76 y_test = g(x_test) 92 def plot_data_test(x_test, y_test): argument 94 graphF = ot.Curve(x_test, y_test) 103 graph.add(plot_data_test(x_test, y_test)) 130 y_test_MM = krigeageMM(x_test) 137 def plot_data_kriging(x_test, y_test_MM): argument 139 graphK = ot.Curve(x_test, y_test_MM) 147 graph.add(plot_data_test(x_test, y_test)) 203 curve = ot.Curve(x_test, conditionalSigma) [all …]
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/dports/science/py-dlib/dlib-19.22/dlib/svm/ |
H A D | cross_validate_regression_trainer.h | 24 const std::vector<sample_type>& x_test, in test_regression_function() argument 30 DLIB_ASSERT( is_learning_problem(x_test,y_test) == true, in test_regression_function() 34 << is_learning_problem(x_test,y_test)); in test_regression_function() 39 for (unsigned long i = 0; i < x_test.size(); ++i) in test_regression_function() 42 const double output = reg_funct(x_test[i]); in test_regression_function() 89 std::vector<sample_type> x_test, x_train; in cross_validate_regression_trainer() local 98 x_test.clear(); in cross_validate_regression_trainer() 106 x_test.push_back(x[next_test_idx]); in cross_validate_regression_trainer() 126 for (unsigned long j = 0; j < x_test.size(); ++j) in cross_validate_regression_trainer() 129 const double output = df(x_test[j]); in cross_validate_regression_trainer()
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/dports/science/dlib-cpp/dlib-19.22/dlib/svm/ |
H A D | cross_validate_regression_trainer.h | 24 const std::vector<sample_type>& x_test, in test_regression_function() argument 30 DLIB_ASSERT( is_learning_problem(x_test,y_test) == true, in test_regression_function() 34 << is_learning_problem(x_test,y_test)); in test_regression_function() 39 for (unsigned long i = 0; i < x_test.size(); ++i) in test_regression_function() 42 const double output = reg_funct(x_test[i]); in test_regression_function() 89 std::vector<sample_type> x_test, x_train; in cross_validate_regression_trainer() local 98 x_test.clear(); in cross_validate_regression_trainer() 106 x_test.push_back(x[next_test_idx]); in cross_validate_regression_trainer() 126 for (unsigned long j = 0; j < x_test.size(); ++j) in cross_validate_regression_trainer() 129 const double output = df(x_test[j]); in cross_validate_regression_trainer()
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/dports/lang/gcc10/gcc-10.3.0/libgo/go/cmd/internal/test2json/testdata/ |
H A D | bench.test | 5 x_test.go:8: My benchmark 6 x_test.go:8: My benchmark 7 x_test.go:8: My benchmark 8 x_test.go:8: My benchmark 9 x_test.go:8: My benchmark 10 x_test.go:8: My benchmark
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/dports/lang/go-devel/go-becaeea1199b875bc24800fa88f2f4fea119bf78/src/cmd/internal/test2json/testdata/ |
H A D | bench.test | 5 x_test.go:8: My benchmark 6 x_test.go:8: My benchmark 7 x_test.go:8: My benchmark 8 x_test.go:8: My benchmark 9 x_test.go:8: My benchmark 10 x_test.go:8: My benchmark
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/dports/lang/gcc11/gcc-11.2.0/libgo/go/cmd/internal/test2json/testdata/ |
H A D | bench.test | 5 x_test.go:8: My benchmark 6 x_test.go:8: My benchmark 7 x_test.go:8: My benchmark 8 x_test.go:8: My benchmark 9 x_test.go:8: My benchmark 10 x_test.go:8: My benchmark
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/dports/lang/gcc12-devel/gcc-12-20211205/libgo/go/cmd/internal/test2json/testdata/ |
H A D | bench.test | 5 x_test.go:8: My benchmark 6 x_test.go:8: My benchmark 7 x_test.go:8: My benchmark 8 x_test.go:8: My benchmark 9 x_test.go:8: My benchmark 10 x_test.go:8: My benchmark
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/dports/lang/gcc11-devel/gcc-11-20211009/libgo/go/cmd/internal/test2json/testdata/ |
H A D | bench.test | 5 x_test.go:8: My benchmark 6 x_test.go:8: My benchmark 7 x_test.go:8: My benchmark 8 x_test.go:8: My benchmark 9 x_test.go:8: My benchmark 10 x_test.go:8: My benchmark
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/dports/lang/gcc9-devel/gcc-9-20211007/libgo/go/cmd/internal/test2json/testdata/ |
H A D | bench.test | 5 x_test.go:8: My benchmark 6 x_test.go:8: My benchmark 7 x_test.go:8: My benchmark 8 x_test.go:8: My benchmark 9 x_test.go:8: My benchmark 10 x_test.go:8: My benchmark
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/dports/misc/cxx_atomics_pic/gcc-11.2.0/libgo/go/cmd/internal/test2json/testdata/ |
H A D | bench.test | 5 x_test.go:8: My benchmark 6 x_test.go:8: My benchmark 7 x_test.go:8: My benchmark 8 x_test.go:8: My benchmark 9 x_test.go:8: My benchmark 10 x_test.go:8: My benchmark
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