| /device/linaro/bootloader/edk2/AppPkg/Applications/Python/Python-2.7.2/Lib/test/ |
| test_socketserver.py | 139 name='%s serving' % svrcls,
263 name='MyServer serving',
|
| /external/autotest/site_utils/stats/ |
| apache_access_log_metrics.py | 40 %p: The canonical Port of the server serving the request
47 %v: The canonical ServerName of the server serving the request.
|
| /external/libmicrohttpd/doc/chapters/ |
| responseheaders.inc | 8 This will lead to an application capable of correctly serving different types of files.
157 Serving dynamically created responses will be a topic of a future chapter.
|
| /external/tensorflow/tensorflow/examples/saved_model/ |
| saved_model_half_plus_two.py | 204 sess, [tf.saved_model.tag_constants.SERVING],
211 sess, [tf.saved_model.tag_constants.SERVING],
|
| /external/tensorflow/tensorflow/cc/saved_model/testdata/half_plus_two_pbtxt/00000123/ |
| saved_model.pbtxt | [all...] |
| /external/tensorflow/tensorflow/core/kernels/batching_util/ |
| shared_batch_scheduler.h | 39 namespace serving { namespace in namespace:tensorflow
44 } // namespace serving
48 namespace serving { namespace in namespace:tensorflow
78 // maximum number of batches worth of enqueued tasks). For online serving, it is
702 } // namespace serving
|
| basic_batch_scheduler.h | 28 namespace serving { namespace in namespace:tensorflow
50 // For online serving, it is recommended to set the maximum number of enqueued
265 } // namespace serving
|
| basic_batch_scheduler_benchmark_test.cc | 28 namespace serving { namespace in namespace:tensorflow
421 } // namespace serving
429 tensorflow::serving::RunLatencyBenchmarks();
|
| batch_scheduler.h | 45 namespace serving { namespace in namespace:tensorflow
278 } // namespace serving
|
| /external/nanohttpd/ |
| README.md | 100 * `/webserver` ? Standalone file server. Run & enjoy. A popular use seems to be serving files out off an Android device.
125 * Supports both dynamic content and file serving.
205 For a more classic aproach, perhaps to just create a HTTP server serving mostly service files from your disk, you can use the module with artifactId *nanohttpd-webserver*.
|
| /external/nanohttpd/src/site/markdown/ |
| index.md | 100 * `/webserver` ? Standalone file server. Run & enjoy. A popular use seems to be serving files out off an Android device.
125 * Supports both dynamic content and file serving.
201 For a more classic aproach, perhaps to just create a HTTP server serving mostly service files from your disk, you can use the module with artifactId *nanohttpd-webserver*.
|
| /external/tensorflow/tensorflow/core/kernels/ |
| batch_kernels.cc | 270 struct BatchTask : public serving::BatchTask {
281 using Batcher = serving::SharedBatchScheduler<BatchTask>;
282 using BatcherQueue = serving::BatchScheduler<BatchTask>;
283 using Batch = serving::Batch<BatchTask>;
595 timeout_enforcer_(new serving::PeriodicFunction(
774 std::unique_ptr<serving::PeriodicFunction> timeout_enforcer_;
[all...] |
| /external/libchrome/base/memory/ |
| singleton.h | 150 // singletons having the same memory allocation functions but serving a
151 // different purpose. This is mainly used for Locks serving different purposes.
|
| /external/python/cpython2/Lib/test/ |
| test_socketserver.py | 146 name='%s serving' % svrcls,
307 name='MyServer serving',
|
| /external/tensorflow/tensorflow/contrib/learn/python/learn/estimators/ |
| model_fn.py | 83 of all of the heads. However: at serving time, requests will be made
94 type is communicated for export and serving. If output_alternatives is not
|
| /external/tensorflow/tensorflow/core/util/ |
| example_proto_helper.h | 100 // Example protos in memory (such as a serving use-case) and we do not wish
103 // ExampleParserOp. In a serving setting, this method could be used to produce
|
| /external/tensorflow/tensorflow/python/saved_model/ |
| saved_model_test.py | 216 builder.add_meta_graph([tag_constants.SERVING])
223 builder.add_meta_graph([tag_constants.SERVING, tag_constants.GPU])
227 # - multiple tags (from predefined constants for serving on TPU).
230 builder.add_meta_graph([tag_constants.SERVING, tag_constants.TPU])
251 loader.load(sess, [tag_constants.SERVING], export_dir)
258 loader.load(sess, [tag_constants.SERVING, tag_constants.GPU], export_dir)
262 # Restore the graph with multiple predefined tags (for serving on TPU)
265 loader.load(sess, [tag_constants.SERVING, tag_constants.TPU], export_dir)
[all...] |
| /external/tensorflow/tensorflow/python/tools/ |
| freeze_graph_test.py | 153 [tag_constants.SERVING],
235 saved_model_tags = tag_constants.SERVING
|
| /prebuilts/gdb/darwin-x86/lib/python2.7/test/ |
| test_socketserver.py | 143 name='%s serving' % svrcls,
299 name='MyServer serving',
|
| /prebuilts/gdb/linux-x86/lib/python2.7/test/ |
| test_socketserver.py | 143 name='%s serving' % svrcls,
299 name='MyServer serving',
|
| /prebuilts/python/darwin-x86/2.7.5/lib/python2.7/test/ |
| test_socketserver.py | 143 name='%s serving' % svrcls,
299 name='MyServer serving',
|
| /prebuilts/python/linux-x86/2.7.5/lib/python2.7/test/ |
| test_socketserver.py | 143 name='%s serving' % svrcls,
299 name='MyServer serving',
|
| /test/vti/dashboard/ |
| README.md | 176 "testPlanName": "vts-serving-staging-fuzz",
181 "testPlanName": "vts-serving-staging-hal-conventional",
|
| /art/test/008-exceptions/src/ |
| Main.java | 53 // A class that throws BadError during static initialization, serving as a super class.
|
| /bootable/recovery/ |
| adb_install.cpp | 92 // FUSE_SIDELOAD_HOST_PATHNAME will start to exist once the host connects and starts serving a
|
