| /external/tensorflow/tensorflow/contrib/opt/python/training/ |
| D | drop_stale_gradient_optimizer_test.py | 49 graphs = []
106 graphs.append(graph)
109 return sessions, graphs, train_ops
119 sessions, graphs, train_ops = _get_workers(num_workers, 0)
120 with graphs[0].as_default():
122 global_step = training_util.get_global_step(graphs[0])
123 var_0 = graphs[0].get_tensor_by_name('v0:0')
124 var_1 = graphs[0].get_tensor_by_name('v1:0')
125 stale_counter = graphs[0].get_tensor_by_name('stale_counter:0')
142 sessions, graphs, train_ops = _get_workers(num_workers, -1)
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| D | agn_optimizer_test.py | 66 graphs = []
127 graphs.append(graph)
130 return sessions, graphs, train_ops
144 sessions, graphs, train_ops = _get_workers(num_workers,
147 var_0 = graphs[0].get_tensor_by_name("v0:0")
148 var_1 = graphs[0].get_tensor_by_name("v1:0")
149 global_step = training_util.get_global_step(graphs[0])
150 var_0_g = graphs[0].get_tensor_by_name(
152 var_1_g = graphs[0].get_tensor_by_name(
156 with graphs[0].as_default():
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| D | elastic_average_optimizer_test.py | 69 graphs = []
138 graphs.append(graph)
142 return sessions, graphs, train_ops, savers
157 sessions, graphs, train_ops, savers = _get_workers(
160 var_0 = graphs[0].get_tensor_by_name("v0:0")
161 var_1 = graphs[0].get_tensor_by_name("v1:0")
162 global_step = training_util.get_global_step(graphs[0])
163 var_0_g = graphs[0].get_tensor_by_name(GLOBAL_VARIABLE_NAME + "/v0:0")
164 var_1_g = graphs[0].get_tensor_by_name(GLOBAL_VARIABLE_NAME + "/v1:0")
220 sessions, graphs, train_ops, savers = _get_workers(
[all …]
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| D | model_average_optimizer_test.py | 63 graphs = []
107 graphs.append(graph)
109 return sessions, graphs, train_ops
124 sessions, graphs, train_ops = _get_workers(num_workers, steps, workers)
126 var_0 = graphs[0].get_tensor_by_name("v0:0")
127 var_1 = graphs[0].get_tensor_by_name("v1:0")
128 global_step = training_util.get_global_step(graphs[0])
129 global_var_0 = graphs[0].get_tensor_by_name(
131 global_var_1 = graphs[0].get_tensor_by_name(
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| /external/tensorflow/tensorflow/python/tools/ |
| D | print_selective_registration_header_test.py | 88 def WriteGraphFiles(self, graphs): argument
90 for i, graph in enumerate(graphs):
99 graphs = [
105 'rawproto', self.WriteGraphFiles(graphs), default_ops)
124 graphs[0].node[0].ClearField('device')
125 graphs[0].node[2].ClearField('device')
127 'rawproto', self.WriteGraphFiles(graphs), default_ops)
144 graphs = [
149 'rawproto', self.WriteGraphFiles(graphs), default_ops)
168 self.WriteGraphFiles(graphs), 'rawproto', default_ops).split('\n'))
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| D | print_selective_registration_header.py | 48 graphs = FLAGS.graphs.split(',')
50 graphs, FLAGS.proto_fileformat, FLAGS.default_ops))
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| D | selective_registration_header_lib.py | 170 def get_header(graphs, argument
185 ops_and_kernels = get_ops_and_kernels(proto_fileformat, graphs, default_ops)
|
| /external/tensorflow/tensorflow/python/training/ |
| D | sync_replicas_optimizer_test.py | 37 graphs = []
81 graphs.append(graph)
84 return sessions, graphs, train_ops
100 sessions, graphs, train_ops = get_workers(num_workers,
104 var_0_g_0 = graphs[0].get_tensor_by_name("v0:0")
105 var_1_g_0 = graphs[0].get_tensor_by_name("v1:0")
106 local_step_0 = graphs[0].get_tensor_by_name("sync_rep_local_step:0")
112 var_0_g_1 = graphs[1].get_tensor_by_name("v0:0")
113 var_1_g_1 = graphs[1].get_tensor_by_name("v1:0")
114 var_sparse_g_1 = graphs[1].get_tensor_by_name("v_sparse:0")
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| /external/syzkaller/tools/syz-benchcmp/ |
| D | benchcmp.go | 46 graphs := []*Graph{
55 for _, g := range graphs {
67 for _, g := range graphs {
75 printFinalStats(graphs)
76 display(graphs)
163 func printFinalStats(graphs []*Graph) {
164 for i := 1; i < len(graphs[0].Headers); i++ {
165 fmt.Printf("%-12v%16v%16v%16v\n", "", graphs[0].Headers[0], graphs[0].Headers[i], "diff")
166 for _, g := range graphs {
183 func display(graphs []*Graph) {
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| /external/tensorflow/tensorflow/python/autograph/pyct/static_analysis/ |
| D | liveness.py | 104 def __init__(self, source_info, graphs): argument
106 self.graphs = graphs
112 subgraph = self.graphs[node]
227 def resolve(node, source_info, graphs): argument
237 cross_function_analyzer = WholeTreeAnalyzer(source_info, graphs)
|
| D | reaching_definitions.py | 181 def __init__(self, source_info, graphs, definition_factory): argument
184 self.graphs = graphs
190 subgraph = self.graphs[node]
295 def resolve(node, source_info, graphs, definition_factory): argument
306 visitor = TreeAnnotator(source_info, graphs, definition_factory)
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| D | live_values_test.py | 52 graphs = cfg.build(node)
55 node = reaching_definitions.resolve(node, ctx, graphs,
|
| /external/v8/tools/ |
| D | run_perf.py | 167 def __init__(self, graphs, units, results_regexp, stddev_regexp): argument
168 self.name = '/'.join(graphs)
169 self.graphs = graphs
201 "graphs": self.graphs,
366 self.graphs = []
397 self.graphs = parent.graphs[:] + [suite["name"]]
448 self.graphs,
507 self.graphs,
514 self.graphs,
549 AccumulateGenericResults(self.graphs, self.units, stdout),
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| /external/tensorflow/tensorflow/lite/toco/ |
| D | README.md | 3 The TensorFlow Lite Converter converts TensorFlow graphs into
4 TensorFlow Lite graphs. There are additional usages that are also detailed in
22 frozen graphs (models generated via
|
| /external/conscrypt/ |
| D | settings.gradle | 8 include ":conscrypt-benchmark-graphs"
23 project(':conscrypt-benchmark-graphs').projectDir = "$rootDir/benchmark-graphs" as File
|
| /external/tensorflow/tensorflow/contrib/makefile/ |
| D | README.md | 68 mkdir -p ~/graphs
69 curl -o ~/graphs/inception.zip \
71 && unzip ~/graphs/inception.zip -d ~/graphs/inception
78 --graph=$HOME/graphs/inception/tensorflow_inception_graph.pb
96 mkdir -p ~/graphs
97 curl -o ~/graphs/inception.zip \
99 && unzip ~/graphs/inception.zip -d ~/graphs/inception
120 adb push ~/graphs/inception/tensorflow_inception_graph.pb /data/local/tmp/
261 mkdir -p ~/graphs
262 curl -o ~/graphs/inception.zip \
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| /external/v8/tools/perf/ |
| D | statistics-for-json.R | 40 testName <- patch$traces[[i]]$graphs[[2]]
65 xlab(patch$traces[[i]]$graphs[[2]])
73 xlab(patch$traces[[i]]$graphs[[2]])
|
| /external/tensorflow/ |
| D | SECURITY.md | 14 [**graphs**](https://developers.google.com/machine-learning/glossary/#graph).
41 Python code that generates TensorFlow graphs.
51 It is easily possible to create computation graphs in which malicious
58 In other words, graphs can contain vulnerabilities of their own. To allow users
92 from anywhere, and executes the graphs it is sent without performing any checks.
108 graphs known to the `ModelServer`. This means that an attacker may run
109 graphs using untrusted inputs as described above, but they would not be able to
110 execute arbitrary graphs. It is possible to safely expose a `ModelServer`
111 directly to an untrusted network, **but only if the graphs it is configured to
131 Given TensorFlow's flexibility, it is possible to specify computation graphs
|
| /external/tensorflow/tensorflow/examples/ios/ |
| D | README.md | 19 mkdir -p ~/graphs
20 curl -o ~/graphs/inception5h.zip \
22 && unzip ~/graphs/inception5h.zip -d ~/graphs/inception5h
23 cp ~/graphs/inception5h/* tensorflow/examples/ios/benchmark/data/
24 cp ~/graphs/inception5h/* tensorflow/examples/ios/camera/data/
25 cp ~/graphs/inception5h/* tensorflow/examples/ios/simple/data/
|
| /external/tensorflow/tensorflow/python/autograph/core/ |
| D | converter.py | 359 graphs = cfg.build(node)
362 node = reaching_definitions.resolve(node, context, graphs, AnnotatedDef)
363 node = liveness.resolve(node, context, graphs)
|
| /external/tensorflow/tensorflow/core/protobuf/ |
| D | worker_service.proto | 28 // graphs on a set of local devices, on behalf of a MasterService.
30 // A worker service keeps track of multiple "registered graphs". Each
|
| /external/tensorflow/tensorflow/python/autograph/pyct/ |
| D | cfg_test.py | 56 graphs, node = self._build_cfg(test_fn)
57 graph, = graphs.values()
78 graphs, node = self._build_cfg(test_fn)
79 graph, = graphs.values()
|
| /external/tensorflow/tensorflow/python/saved_model/ |
| D | README.md | 17 * Multiple graphs sharing a single set of variables and assets can be added to a
24 to allow generic support for signatures that may need to be saved with the graphs.
46 as the canonical way to export TensorFlow graphs for serving.
87 Subsequent meta graphs will simply be saved with their graph definitions. If
192 SavedModel offers the flexibility to build and load TensorFlow graphs for a
|
| /external/tensorflow/tensorflow/python/debug/ |
| D | README.md | 6 graphs. It provides access to internal graph structures and tensor values at
37 * Association of nodes and tensors in graphs with Python source lines
|
| /external/mockito/src/main/java/org/mockito/internal/creation/bytebuddy/ |
| D | MockMethodAdvice.java | 44 private final WeakConcurrentMap<Class<?>, SoftReference<MethodGraph>> graphs field in MockMethodAdvice
130 SoftReference<MethodGraph> reference = graphs.get(instance.getClass()); in isOverridden()
134 graphs.put(instance.getClass(), new SoftReference<MethodGraph>(methodGraph)); in isOverridden()
|