| /external/skqp/infra/bots/recipes/test.expected/ |
| Test-Android-Clang-NexusPlayer-CPU-Moorefield-x86-Release-All-Android.json | 566 "\nimport contextlib\nimport math\nimport socket\nimport sys\nimport time\nimport urllib2\n\nHASHES_URL = 'https://storage.googleapis.com/skia-infra-gm/hash_files/gold-prod-hashes.txt'\nRETRIES = 5\nTIMEOUT = 60\nWAIT_BASE = 15\n\nsocket.setdefaulttimeout(TIMEOUT)\nfor retry in range(RETRIES):\n try:\n with contextlib.closing(\n urllib2.urlopen(HASHES_URL, timeout=TIMEOUT)) as w:\n hashes = w.read()\n with open(sys.argv[1], 'w') as f:\n f.write(hashes)\n break\n except Exception as e:\n print 'Failed to get uninteresting hashes from %s:' % HASHES_URL\n print e\n if retry == RETRIES:\n raise\n waittime = WAIT_BASE * math.pow(2, retry)\n print 'Retry in %d seconds.' % waittime\n time.sleep(waittime)\n",
586 "@@@STEP_LOG_LINE@python.inline@HASHES_URL = 'https://storage.googleapis.com/skia-infra-gm/hash_files/gold-prod-hashes.txt'@@@",
[all...] |
| Test-Android-Clang-NexusPlayer-GPU-PowerVR-x86-Release-All-Android_Vulkan.json | 566 "\nimport contextlib\nimport math\nimport socket\nimport sys\nimport time\nimport urllib2\n\nHASHES_URL = 'https://storage.googleapis.com/skia-infra-gm/hash_files/gold-prod-hashes.txt'\nRETRIES = 5\nTIMEOUT = 60\nWAIT_BASE = 15\n\nsocket.setdefaulttimeout(TIMEOUT)\nfor retry in range(RETRIES):\n try:\n with contextlib.closing(\n urllib2.urlopen(HASHES_URL, timeout=TIMEOUT)) as w:\n hashes = w.read()\n with open(sys.argv[1], 'w') as f:\n f.write(hashes)\n break\n except Exception as e:\n print 'Failed to get uninteresting hashes from %s:' % HASHES_URL\n print e\n if retry == RETRIES:\n raise\n waittime = WAIT_BASE * math.pow(2, retry)\n print 'Retry in %d seconds.' % waittime\n time.sleep(waittime)\n",
586 "@@@STEP_LOG_LINE@python.inline@HASHES_URL = 'https://storage.googleapis.com/skia-infra-gm/hash_files/gold-prod-hashes.txt'@@@",
[all...] |
| failed_get_hashes.json | 566 "\nimport contextlib\nimport math\nimport socket\nimport sys\nimport time\nimport urllib2\n\nHASHES_URL = 'https://storage.googleapis.com/skia-infra-gm/hash_files/gold-prod-hashes.txt'\nRETRIES = 5\nTIMEOUT = 60\nWAIT_BASE = 15\n\nsocket.setdefaulttimeout(TIMEOUT)\nfor retry in range(RETRIES):\n try:\n with contextlib.closing(\n urllib2.urlopen(HASHES_URL, timeout=TIMEOUT)) as w:\n hashes = w.read()\n with open(sys.argv[1], 'w') as f:\n f.write(hashes)\n break\n except Exception as e:\n print 'Failed to get uninteresting hashes from %s:' % HASHES_URL\n print e\n if retry == RETRIES:\n raise\n waittime = WAIT_BASE * math.pow(2, retry)\n print 'Retry in %d seconds.' % waittime\n time.sleep(waittime)\n",
587 "@@@STEP_LOG_LINE@python.inline@HASHES_URL = 'https://storage.googleapis.com/skia-infra-gm/hash_files/gold-prod-hashes.txt'@@@",
[all...] |
| failed_pull.json | 566 "\nimport contextlib\nimport math\nimport socket\nimport sys\nimport time\nimport urllib2\n\nHASHES_URL = 'https://storage.googleapis.com/skia-infra-gm/hash_files/gold-prod-hashes.txt'\nRETRIES = 5\nTIMEOUT = 60\nWAIT_BASE = 15\n\nsocket.setdefaulttimeout(TIMEOUT)\nfor retry in range(RETRIES):\n try:\n with contextlib.closing(\n urllib2.urlopen(HASHES_URL, timeout=TIMEOUT)) as w:\n hashes = w.read()\n with open(sys.argv[1], 'w') as f:\n f.write(hashes)\n break\n except Exception as e:\n print 'Failed to get uninteresting hashes from %s:' % HASHES_URL\n print e\n if retry == RETRIES:\n raise\n waittime = WAIT_BASE * math.pow(2, retry)\n print 'Retry in %d seconds.' % waittime\n time.sleep(waittime)\n",
586 "@@@STEP_LOG_LINE@python.inline@HASHES_URL = 'https://storage.googleapis.com/skia-infra-gm/hash_files/gold-prod-hashes.txt'@@@",
[all...] |
| /external/tensorflow/tensorflow/contrib/bayesflow/python/ops/ |
| csiszar_divergence_impl.py | 950 `O(num_draws * num_batch_draws * prod(batch_shape) * prod(event_shape))`.
[all...] |
| /external/tensorflow/tensorflow/contrib/layers/python/layers/ |
| feature_column_test.py | 49 values = np.random.randint(0, vocab_size + 1, size=np.prod(shape))
559 [np.prod(input_shape[output_rank - 1:])])
[all...] |
| /external/tensorflow/tensorflow/python/keras/_impl/keras/ |
| backend_test.py | 331 (keras.backend.prod, np.prod),
[all...] |
| /external/webp/src/dsp/ |
| enc_neon.c | 797 const uint16x8_t prod = vmull_u8(abs_diff, abs_diff); local
798 sum = vpadalq_u16(sum, prod);
[all...] |
| /device/linaro/bootloader/edk2/AppPkg/Applications/Python/Python-2.7.2/Lib/ |
| htmlentitydefs.py | 195 'prod': 0x220f, # n-ary product = product sign, U+220F ISOamsb
|
| /external/autotest/client/common_lib/cros/ |
| cr50_utils.py | 15 CR50_PROD = '/opt/google/cr50/firmware/cr50.bin.prod'
|
| /external/autotest/ |
| global_config.ini | 191 # Set to True to upload results to prod Sponge server.
|
| /external/autotest/server/cros/dynamic_suite/ |
| suite.py | 495 code that lives in prod aka the test code
[all...] |
| /external/eigen/Eigen/src/Core/ |
| DenseBase.h | 444 EIGEN_DEVICE_FUNC Scalar prod() const;
|
| /external/eigen/Eigen/src/LU/ |
| PartialPivLU.h | 542 return Scalar(m_det_p) * m_lu.diagonal().prod();
|
| /external/eigen/Eigen/src/QR/ |
| ColPivHouseholderQR.h | 453 return abs(m_qr.diagonal().prod());
|
| FullPivHouseholderQR.h | 430 return abs(m_qr.diagonal().prod());
|
| /external/google-breakpad/src/client/mac/sender/ |
| uploader.mm | 423 [googleDictionary_ setObject:@"prod" forKey:@BREAKPAD_PRODUCT];
|
| /external/libusb/libusb/os/ |
| windows_winusb.h | 197 uint8_t string_index[3]; // man, prod, ser
|
| /external/libxml2/test/schemas/ |
| nvdcve_0.xsd | 384 <xs:element name="prod" maxOccurs="unbounded">
|
| /external/owasp/sanitizer/src/main/org/owasp/html/ |
| HtmlEntities.java | 424 .put("prod", Integer.valueOf('\u220f'))
|
| /external/python/cpython2/Lib/ |
| htmlentitydefs.py | 195 'prod': 0x220f, # n-ary product = product sign, U+220F ISOamsb
|
| /external/tensorflow/tensorflow/compiler/xla/tests/ |
| params_test.cc | 145 auto prod = builder.Mul(sum, param1); local
|
| /external/tensorflow/tensorflow/contrib/distributions/python/kernel_tests/ |
| distribution_util_test.py | 49 d = np.reshape(d, (int(np.prod(d.shape[:-1])), d.shape[-1]))
|
| /external/tensorflow/tensorflow/contrib/distributions/python/ops/bijectors/ |
| masked_autoregressive.py | 58 decomposition, `p(x) = prod{ p(x[i] | x[0:i]) : i=0, ..., d }`. The provided
|
| /external/tensorflow/tensorflow/contrib/distributions/python/ops/ |
| sample_stats.py | 510 end_shape = [np.prod([x_shape[i] for i in axis])]
|
