| /external/tensorflow/tensorflow/contrib/kernel_methods/python/ |
| kernel_estimators_test.py | 253 input_dim=4, output_dim=50, stddev=1.0, name='rffm')
|
| /external/tensorflow/tensorflow/contrib/opt/python/training/ |
| model_average_optimizer.py | 58 stddev=1.0 / IMAGE_PIXELS),
|
| /external/tensorflow/tensorflow/core/lib/histogram/ |
| histogram.cc | 173 snprintf(buf, sizeof(buf), "Count: %.0f Average: %.4f StdDev: %.2f\n", num_,
|
| /external/tensorflow/tensorflow/python/kernel_tests/distributions/ |
| dirichlet_test.py | 186 dist.stddev(),
|
| uniform_test.py | 228 self.assertAllClose(uniform.stddev().eval(), s_uniform.std())
|
| dirichlet_multinomial_test.py | 216 # We will test mean, cov, var, stddev on a DirichletMultinomial constructed
251 dist.stddev(),
|
| normal_test.py | 376 self.assertAllEqual((3,), normal.stddev().get_shape())
377 self.assertAllEqual([7., 7, 7], normal.stddev().eval())
|
| /external/webrtc/webrtc/base/ |
| virtualsocketserver.h | 108 uint32_t stddev,
|
| /system/netd/tests/benchmarks/ |
| connect_benchmark.cpp | 63 * custom 'label' output for graphing. Stddev isn't appropriate because the latency
|
| /external/harfbuzz_ng/test/shaping/ |
| hb_test_tools.py | 265 def stddev (self): member in class:Stats
276 return (self.mean () - population.mean ()) / population.stddev ()
|
| /external/tensorflow/tensorflow/contrib/layers/python/layers/ |
| feature_column.py | [all...] |
| /external/tensorflow/tensorflow/contrib/slim/python/slim/nets/ |
| inception_v2.py | 32 trunc_normal = lambda stddev: init_ops.truncated_normal_initializer(0.0, stddev)
|
| /external/tensorflow/tensorflow/python/training/ |
| checkpoint_ops.py | 467 # TODO(b/25671353): This should be kept in sync with the stddev used by
470 stddev=1.0 / math.sqrt(embedding_dim))
|
| saver_test.py | [all...] |
| /external/tensorflow/tensorflow/tools/api/golden/ |
| tensorflow.keras.backend.pbtxt | 353 argspec: "args=[\'shape\', \'mean\', \'stddev\', \'dtype\', \'seed\'], varargs=None, keywords=None, defaults=[\'0.0\', \'1.0\', \'None\', \'None\'], "
525 argspec: "args=[\'shape\', \'mean\', \'stddev\', \'dtype\', \'seed\'], varargs=None, keywords=None, defaults=[\'0.0\', \'1.0\', \'None\', \'None\'], "
|
| /external/tensorflow/tensorflow/examples/image_retraining/ |
| retrain.py | 740 with tf.name_scope('stddev'):
741 stddev = tf.sqrt(tf.reduce_mean(tf.square(var - mean)))
742 tf.summary.scalar('stddev', stddev)
[all...] |
| /device/linaro/bootloader/edk2/AppPkg/Applications/Python/Python-2.7.10/Lib/ |
| random.py | 856 stddev = _sqrt(sqsum/n - avg*avg)
857 print 'avg %g, stddev %g, min %g, max %g' % \
858 (avg, stddev, smallest, largest)
[all...] |
| /device/linaro/bootloader/edk2/AppPkg/Applications/Python/Python-2.7.2/Lib/ |
| random.py | 854 stddev = _sqrt(sqsum/n - avg*avg)
855 print 'avg %g, stddev %g, min %g, max %g' % \
856 (avg, stddev, smallest, largest)
[all...] |
| /external/python/cpython2/Lib/ |
| random.py | 856 stddev = _sqrt(sqsum/n - avg*avg)
857 print 'avg %g, stddev %g, min %g, max %g' % \
858 (avg, stddev, smallest, largest)
|
| /prebuilts/gdb/darwin-x86/lib/python2.7/ |
| random.py | 850 stddev = _sqrt(sqsum/n - avg*avg)
851 print 'avg %g, stddev %g, min %g, max %g' % \
852 (avg, stddev, smallest, largest)
|
| /prebuilts/gdb/linux-x86/lib/python2.7/ |
| random.py | 850 stddev = _sqrt(sqsum/n - avg*avg)
851 print 'avg %g, stddev %g, min %g, max %g' % \
852 (avg, stddev, smallest, largest)
|
| /prebuilts/python/darwin-x86/2.7.5/lib/python2.7/ |
| random.py | 850 stddev = _sqrt(sqsum/n - avg*avg)
851 print 'avg %g, stddev %g, min %g, max %g' % \
852 (avg, stddev, smallest, largest)
|
| /prebuilts/python/linux-x86/2.7.5/lib/python2.7/ |
| random.py | 850 stddev = _sqrt(sqsum/n - avg*avg)
851 print 'avg %g, stddev %g, min %g, max %g' % \
852 (avg, stddev, smallest, largest)
|
| /external/autotest/client/common_lib/cros/network/ |
| ping_runner.py | 101 round-trip min/avg/max/stddev = 3.770/4.279/4.901/0.469 ms
|
| /external/fio/ |
| idletime.c | 474 log_buf(out, " stddev=%3.2f\n", ipc.cali_stddev);
|
