| /external/tensorflow/tensorflow/tools/api/golden/v2/ |
| D | tensorflow.losses.-poisson.pbtxt | 1 path: "tensorflow.losses.Poisson"
3 is_instance: "<class \'tensorflow.python.keras.losses.Poisson\'>"
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| D | tensorflow.keras.losses.-poisson.pbtxt | 1 path: "tensorflow.keras.losses.Poisson"
3 is_instance: "<class \'tensorflow.python.keras.losses.Poisson\'>"
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| D | tensorflow.metrics.-poisson.pbtxt | 1 path: "tensorflow.metrics.Poisson"
3 is_instance: "<class \'tensorflow.python.keras.metrics.Poisson\'>"
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| D | tensorflow.keras.metrics.-poisson.pbtxt | 1 path: "tensorflow.keras.metrics.Poisson"
3 is_instance: "<class \'tensorflow.python.keras.metrics.Poisson\'>"
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| D | tensorflow.keras.losses.pbtxt | 56 name: "Poisson"
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| D | tensorflow.losses.pbtxt | 56 name: "Poisson"
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| D | tensorflow.metrics.pbtxt | 92 name: "Poisson"
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| D | tensorflow.keras.metrics.pbtxt | 92 name: "Poisson"
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| /external/tensorflow/tensorflow/tools/api/golden/v1/ |
| D | tensorflow.keras.losses.-poisson.pbtxt | 1 path: "tensorflow.keras.losses.Poisson"
3 is_instance: "<class \'tensorflow.python.keras.losses.Poisson\'>"
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| D | tensorflow.keras.metrics.-poisson.pbtxt | 1 path: "tensorflow.keras.metrics.Poisson"
3 is_instance: "<class \'tensorflow.python.keras.metrics.Poisson\'>"
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| D | tensorflow.keras.losses.pbtxt | 56 name: "Poisson"
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| D | tensorflow.keras.metrics.pbtxt | 92 name: "Poisson"
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| /external/grpc-grpc/src/ruby/qps/ |
| D | client.rb | 28 class Poisson class
89 waiter = Poisson.new(config.load_params.poisson.offered_load /
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| /external/tensorflow/tensorflow/contrib/distributions/python/ops/ |
| D | poisson.py | 51 class Poisson(distribution.Distribution): class
125 super(Poisson, self).__init__(
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| D | poisson_lognormal.py | 300 self._distribution = poisson_lib.Poisson(
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| /external/grpc-grpc/src/csharp/Grpc.IntegrationTesting/ |
| D | Control.cs | 436 case LoadOneofCase.Poisson: in LoadParams()
437 Poisson = other.Poisson.Clone(); in LoadParams()
463 public global::Grpc.Testing.PoissonParams Poisson { property in Grpc.Testing.LoadParams
464 …get { return loadCase_ == LoadOneofCase.Poisson ? (global::Grpc.Testing.PoissonParams) load_ : nul…
467 loadCase_ = value == null ? LoadOneofCase.None : LoadOneofCase.Poisson;
476 Poisson = 2, enumerator
504 if (!object.Equals(Poisson, other.Poisson)) return false; in Equals()
513 if (loadCase_ == LoadOneofCase.Poisson) hash ^= Poisson.GetHashCode(); in GetHashCode()
532 if (loadCase_ == LoadOneofCase.Poisson) { in WriteTo()
534 output.WriteMessage(Poisson); in WriteTo()
[all …]
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| D | ClientRunners.cs | 357 case LoadParams.LoadOneofCase.Poisson: in CreateTimer()
358 … return new PoissonInterarrivalTimer(loadParams.Poisson.OfferedLoad * loadMultiplier); in CreateTimer()
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| /external/tensorflow/tensorflow/contrib/boosted_trees/lib/utils/ |
| D | random_test.cc | 23 TEST(RandomTest, Poisson) { in TEST() argument
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| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| D | api_def_RandomPoissonV2.pbtxt | 39 summary: "Outputs random values from the Poisson distribution(s) described by rate."
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| /external/tensorflow/tensorflow/contrib/distributions/python/kernel_tests/ |
| D | poisson_test.py | 35 return poisson_lib.Poisson(rate=rate, validate_args=validate_args)
254 return poisson_lib.Poisson(
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| /external/tensorflow/tensorflow/python/keras/ |
| D | losses.py | 536 class Poisson(LossFunctionWrapper): class
560 super(Poisson, self).__init__(poisson, name=name, reduction=reduction)
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| D | losses_test.py | 1292 poisson_obj = keras.losses.Poisson(
1299 poisson_obj = keras.losses.Poisson()
1307 poisson_obj = keras.losses.Poisson()
1322 poisson_obj = keras.losses.Poisson()
1335 poisson_obj = keras.losses.Poisson()
1353 poisson_obj = keras.losses.Poisson()
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| D | metrics_test.py | 996 poisson_obj = metrics.Poisson(name='poisson', dtype=dtypes.int32)
1000 poisson_obj2 = metrics.Poisson.from_config(poisson_obj.get_config())
1006 poisson_obj = metrics.Poisson()
1017 poisson_obj = metrics.Poisson()
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| /external/tensorflow/tensorflow/contrib/linear_optimizer/kernels/g3doc/ |
| D | readme.md | 202 ### Poisson log loss
204 Poisson log loss is defined as $$ \l(u) = e^u - uy $$ for label $$y \geq 0.$$
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| /external/eigen/doc/ |
| D | SparseLinearSystems.dox | 24 <td>Recommended for very sparse and not too large problems (e.g., 2D Poisson eq.)</td></tr>
46 <td>Recommended for large symmetric problems (e.g., 3D Poisson eq.)</td></tr>
|