| /external/tensorflow/tensorflow/contrib/learn/python/learn/datasets/ |
| synthetic_test.py | 48 - returned `data` shape is (n_samples, n_features)
49 - returned `target` shape is (n_samples,)
55 n_samples = 100
58 n_samples=n_samples, noise=None, n_classes=n_classes)
60 self.assertTupleEqual(circ.data.shape, (n_samples, 2))
61 self.assertTupleEqual(circ.target.shape, (n_samples,))
74 n_samples=100, noise=noise, n_classes=2, seed=seed)
76 n_samples=100, noise=noise, n_classes=2, seed=seed)
81 n_samples=100, noise=noise, n_classes=2, seed=seed + 1
[all...] |
| synthetic.py | 26 def circles(n_samples=100,
36 n_samples: int, number of datapoints to generate
65 linspace = np.linspace(0, 2 * np.pi, n_samples // n_classes)
77 y = np.append(y, label * np.ones(n_samples // n_classes, dtype=np.int32))
79 # Add more points if n_samples is not divisible by n_classes (unbalanced!)
80 extras = n_samples % n_classes
90 indices = np.random.permutation(range(n_samples))
96 def spirals(n_samples=100,
108 n_samples: int, number of datapoints to generate
140 linspace = np.linspace(0, 2 * n_loops * np.pi, n_samples // n_classes
[all...] |
| __init__.py | 76 def make_dataset(name, n_samples=100, noise=None, seed=42, *args, **kwargs):
81 n_samples: int, number of datapoints to generate
110 n_samples=n_samples, noise=noise, seed=seed, *args, **kwargs)
|
| base.py | 45 n_samples = int(header[0])
47 data = np.zeros((n_samples, n_features), dtype=features_dtype)
48 target = np.zeros((n_samples,), dtype=target_dtype)
|
| /external/strace/ |
| ptp.c | 90 tprintf("{n_samples=%u", sysoff.n_samples);
93 unsigned int n_samples, i; local
107 n_samples = sysoff.n_samples > PTP_MAX_SAMPLES ?
108 PTP_MAX_SAMPLES : sysoff.n_samples;
109 for (i = 0; i < 2 * n_samples + 1; ++i) {
116 if (sysoff.n_samples > PTP_MAX_SAMPLES)
|
| /external/tensorflow/tensorflow/python/keras/_impl/keras/wrappers/ |
| scikit_learn.py | 137 x : array-like, shape `(n_samples, n_features)`
138 Training samples where `n_samples` is the number of samples
140 y : array-like, shape `(n_samples,)` or `(n_samples, n_outputs)`
200 x : array-like, shape `(n_samples, n_features)`
201 Training samples where `n_samples` is the number of samples
203 y : array-like, shape `(n_samples,)` or `(n_samples, n_outputs)`
230 x: array-like, shape `(n_samples, n_features)`
231 Test samples where `n_samples` is the number of sample
[all...] |
| /external/tensorflow/tensorflow/contrib/learn/python/learn/ |
| trainable.py | 41 x: Matrix of shape [n_samples, n_features...] or the dictionary of
47 y: Vector or matrix [n_samples] or [n_samples, n_outputs] or the
|
| evaluable.py | 61 x: Matrix of shape [n_samples, n_features...] or dictionary of many
68 y: Vector or matrix [n_samples] or [n_samples, n_outputs] containing the
|
| /external/linux-kselftest/tools/testing/selftests/ptp/ |
| testptp.c | 177 int n_samples = 0; local
218 n_samples = atoi(optarg);
481 if (n_samples <= 0 || n_samples > 25) {
482 puts("n_samples should be between 1 and 25");
492 sysoff->n_samples = n_samples;
500 for (i = 0; i < sysoff->n_samples; i++) {
|
| /bionic/libc/kernel/uapi/linux/ |
| ptp_clock.h | 55 unsigned int n_samples; member in struct:ptp_sys_offset
|
| /external/kernel-headers/original/uapi/linux/ |
| ptp_clock.h | 77 unsigned int n_samples; /* Desired number of measurements. */ member in struct:ptp_sys_offset
81 * will provide 2*n_samples + 1 time stamps, with the last
|
| /external/tensorflow/tensorflow/contrib/learn/python/learn/preprocessing/ |
| categorical.py | 104 x: iterable, [n_samples]. Category-id matrix.
119 x: iterable, [n_samples]. Category-id matrix.
|
| text.py | 166 x: iterable, [n_samples, max_document_length]. Word-id matrix.
181 x: iterable, [n_samples, max_document_length]. Word-id matrix.
|
| /external/tensorflow/tensorflow/contrib/losses/python/metric_learning/ |
| metric_loss_ops_test.py | 519 def _genClusters(self, n_samples, n_clusters):
521 n_samples=n_samples, centers=n_clusters)
532 embeddings, labels = self._genClusters(n_samples=128, n_clusters=64)
549 embeddings, labels = self._genClusters(n_samples=128, n_clusters=64)
|
| /external/tensorflow/tensorflow/contrib/bayesflow/python/kernel_tests/ |
| mcmc_diagnostics_test.py | 254 n_samples = 1000
257 state_0 = rng.randn(n_samples, 2)
263 state_1 = rng.randn(n_samples, 3, 4) + offset
|
| /external/tensorflow/tensorflow/contrib/distributions/python/kernel_tests/ |
| quantized_distribution_test.py | 228 # Standard error should be less than 1 / (2 * sqrt(n_samples))
229 n_samples = 10000
230 stddev_err_bound = 1 / (2 * np.sqrt(n_samples))
231 samps = qdist.sample((n_samples,), seed=42).eval()
|
| /external/deqp/external/openglcts/modules/gles31/ |
| es31cTextureStorageMultisampleTexStorage3DMultisampleTests.cpp | [all...] |
| es31cTextureStorageMultisampleTexStorage2DMultisampleTests.cpp | [all...] |
| /external/deqp/external/openglcts/modules/gl/ |
| gl4cTextureViewTests.cpp | 5680 const unsigned int n_samples = local
[all...] |
| gl4cTextureViewTests.hpp | 522 unsigned int n_samples; member in struct:gl4cts::TextureViewTestViewSampling::_reference_color_storage
546 n_samples = in_n_samples;
583 unsigned int n_samples);
[all...] |
| gl4cCopyImageTests.cpp | 108 static glw::GLuint prepareMultisampleTex(deqp::Context& context, glw::GLenum target, glw::GLsizei n_samples);
1273 * @param n_samples Number of samples
1277 GLuint Utils::prepareMultisampleTex(deqp::Context& context, GLenum target, GLsizei n_samples)
1296 gl.texImage2DMultisample(target, n_samples, internal_format, width, height, GL_FALSE /* fixedsamplelocation */);
1305 gl.texImage3DMultisample(target, n_samples, internal_format, width, height, depth,
4839 static const GLsizei n_samples[2] = { 1, 4 }; local
[all...] |
| /external/tensorflow/tensorflow/contrib/learn/python/learn/estimators/ |
| estimator.py | 167 x: Real-valued matrix of shape [n_samples, n_features...]. Can be
521 x: Matrix of shape [n_samples, n_features...]. Can be iterator that
524 y: Vector or matrix [n_samples] or [n_samples, n_outputs]. Can be
608 x: Matrix of shape [n_samples, n_features...]. Can be iterator that
[all...] |
| /external/tensorflow/tensorflow/python/keras/_impl/keras/engine/ |
| training_test.py | 879 n_samples = 50
881 batch_index = np.random.randint(0, n_samples - batch_size)
[all...] |
| /external/tensorflow/tensorflow/contrib/seq2seq/python/kernel_tests/ |
| attention_wrapper_test.py | 534 n_samples = 100000
536 [sample(p_choose_i) for _ in range(n_samples)], axis=0)
[all...] |
| /external/tensorflow/tensorflow/contrib/learn/python/learn/learn_io/ |
| data_feeder.py | 292 `[n_samples, n_features, ...]` or dictionary of Nd numpy matrix.
|
