| /aosp_15_r20/external/tensorflow/tensorflow/python/distribute/ |
| H A D | mirrored_strategy_test.py | 67 distribution=[
78 def testMinimizeLoss(self, distribution): argument
80 self._test_minimize_loss_eager(distribution)
82 self._test_minimize_loss_graph(distribution)
84 def testReplicaId(self, distribution): argument
85 self._test_replica_id(distribution)
87 def testNumReplicasInSync(self, distribution): argument
88 self.assertEqual(2, distribution.num_replicas_in_sync)
90 def testCallAndMergeExceptions(self, distribution): argument
91 self._test_call_and_merge_exceptions(distribution)
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| H A D | custom_training_loop_input_test.py | 79 distribution=strategy_combinations.all_strategies,
82 def testConstantNumpyInput(self, distribution): argument
90 outputs = distribution.experimental_local_results(
91 distribution.run(computation, args=(x,)))
95 constant_op.constant(4., shape=(distribution.num_replicas_in_sync)),
100 distribution=strategy_combinations.all_strategies,
103 def testStatefulExperimentalRunAlwaysExecute(self, distribution): argument
104 with distribution.scope():
114 distribution.run(assign_add)
122 distribution=strategy_combinations.strategies_minus_tpu,
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| H A D | vars_test.py | 52 # distribution=[
59 distribution=[
70 distribution=[
85 def testAssign(self, distribution, experimental_run_tf_function): argument
94 return test_util.gather(distribution, distribution.run(update_fn))
112 with distribution.scope():
124 def testAssignOnWriteVar(self, distribution, experimental_run_tf_function): argument
126 with distribution.scope():
139 return test_util.gather(distribution, distribution.run(update_fn))
157 with distribution.scope():
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| H A D | mirrored_variable_test.py | 63 distribution=[
103 def testVariableInFuncGraph(self, distribution): argument
110 with func_graph.FuncGraph("fg").as_default(), distribution.scope():
112 v2 = distribution.extended.call_for_each_replica(model_fn)
114 self._test_mv_properties(v1, "foo:0", distribution)
115 self._test_mv_properties(v2, "bar:0", distribution)
117 def testVariableWithTensorInitialValueInFunction(self, distribution): argument
132 return distribution.experimental_local_results(
133 distribution.extended.call_for_each_replica(model_fn))
137 def testSingleVariable(self, distribution): argument
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| H A D | values_test.py | 58 distribution=[
72 distribution=(strategy_combinations.all_strategies_minus_default +
76 def testMakeDistributedValueFromTensor(self, distribution): argument
85 distribution.experimental_distribute_values_from_function(value_fn))
87 ds_test_util.gather(distribution, distributed_values),
88 constant_op.constant(1., shape=(distribution.num_replicas_in_sync)))
92 distribution=(strategy_combinations.all_strategies_minus_default +
96 def testMakeDistributedValueSingleNumpyArrayConstant(self, distribution): argument
105 distribution.experimental_distribute_values_from_function(value_fn))
107 ds_test_util.gather(distribution, distributed_values).numpy(),
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| H A D | input_lib_test.py | 287 distribution=[
290 def testMultiDeviceIterInitialize(self, distribution): argument
300 dataset_fn(distribute_lib.InputContext()), input_workers, distribution)
316 distribution=[
321 def testOneDeviceCPU(self, input_type, api_type, iteration_type, distribution, argument
330 distribution.extended.experimental_enable_get_next_as_optional = (
334 expected_values, distribution)
342 distribution=[strategy_combinations.multi_worker_mirrored_2x1_cpu],
345 distribution, enable_get_next_as_optional): argument
353 distribution.extended.experimental_enable_get_next_as_optional = (
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| H A D | one_device_strategy_test.py | 31 distribution=[
40 def testMinimizeLoss(self, distribution): argument
42 self._test_minimize_loss_eager(distribution)
44 self._test_minimize_loss_graph(distribution)
46 def testReplicaId(self, distribution): argument
47 self._test_replica_id(distribution)
49 def testCallAndMergeExceptions(self, distribution): argument
50 self._test_call_and_merge_exceptions(distribution)
52 def testReplicateDataset(self, distribution): argument
62 self._test_input_fn_iterable(distribution, input_fn, expected_values)
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| H A D | input_lib_type_spec_test.py | 51 distribution=[
56 def testTypeSpec(self, input_type, distribution, argument
63 distribution.extended.experimental_enable_get_next_as_optional = (
66 dist_dataset = distribution.experimental_distribute_dataset(dataset)
67 with distribution.scope():
83 distribution=[
89 distribution, enable_get_next_as_optional): argument
96 distribution.extended.experimental_enable_get_next_as_optional = (
99 dist_dataset = distribution.experimental_distribute_dataset(dataset)
100 with distribution.scope():
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| H A D | metrics_v1_test.py | 73 distribution=[
84 distribution=[
95 def _test_metric(self, distribution, dataset_fn, metric_fn, expected_fn): argument
96 with ops.Graph().as_default(), distribution.scope():
97 iterator = distribution.make_input_fn_iterator(lambda _: dataset_fn())
98 if strategy_test_lib.is_tpu_strategy(distribution):
100 value, update = distribution.extended.call_for_each_replica(
103 return distribution.group(update)
105 ctx = distribution.extended.experimental_run_steps_on_iterator(
106 step_fn, iterator, iterations=distribution.extended.steps_per_run)
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| H A D | moving_averages_test.py | 44 distribution=all_distributions, mode=["graph"])
47 distribution=all_distributions, mode=["eager"], use_function=[True, False])
53 def testReplicaModeWithoutZeroDebias(self, distribution): argument
65 with distribution.scope():
66 var, assign = distribution.extended.call_for_each_replica(replica_fn)
69 self.evaluate(distribution.experimental_local_results(assign))
80 def testReplicaMode(self, distribution): argument
91 with distribution.scope():
92 var, assign_op = distribution.extended.call_for_each_replica(replica_fn)
95 self.evaluate(distribution.experimental_local_results(assign_op))
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| /aosp_15_r20/external/sdk-platform-java/java-common-protos/proto-google-common-protos/src/main/java/com/google/api/ |
| H A D | Distribution.java | 17 // source: google/api/distribution.proto
25 * `Distribution` contains summary statistics for a population of values. It
26 * optionally contains a histogram representing the distribution of those values
39 * Protobuf type {@code google.api.Distribution}
41 public final class Distribution extends com.google.protobuf.GeneratedMessageV3 class
43 // @@protoc_insertion_point(message_implements:google.api.Distribution)
46 // Use Distribution.newBuilder() to construct.
47 private Distribution(com.google.protobuf.GeneratedMessageV3.Builder<?> builder) { in Distribution() method in Distribution
51 private Distribution() { in Distribution() method in Distribution
59 return new Distribution(); in newInstance()
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| /aosp_15_r20/external/google-cloud-java/java-service-control/proto-google-cloud-service-control-v1/src/main/java/com/google/api/servicecontrol/v1/ |
| H A D | Distribution.java | 17 // source: google/api/servicecontrol/v1/distribution.proto
25 * Distribution represents a frequency distribution of double-valued sample
34 * Protobuf type {@code google.api.servicecontrol.v1.Distribution}
36 public final class Distribution extends com.google.protobuf.GeneratedMessageV3 class
38 // @@protoc_insertion_point(message_implements:google.api.servicecontrol.v1.Distribution)
41 // Use Distribution.newBuilder() to construct.
42 private Distribution(com.google.protobuf.GeneratedMessageV3.Builder<?> builder) { in Distribution() method in Distribution
46 private Distribution() { in Distribution() method in Distribution
54 return new Distribution(); in newInstance()
73 com.google.api.servicecontrol.v1.Distribution.class, in internalGetFieldAccessorTable()
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| /aosp_15_r20/prebuilts/clang/host/linux-x86/clang-r522817/lib/cmake/llvm/ |
| D | LLVMDistributionSupport.cmake | 1 # Utility functions for packaging an LLVM distribution. See the
10 # - The ${PROJECT}${distribution}_HAS_EXPORTS global property holds whether a
11 # project has any exports for a particular ${distribution} (where ${PROJECT}
31 # distribution for a target later. The distribution for ${target} is stored in
38 # denote the default (unnamed) distribution.
42 foreach(distribution ${LLVM_DISTRIBUTIONS})
43 foreach(target ${LLVM_${distribution}_DISTRIBUTION_COMPONENTS})
49 if(current_distribution AND NOT current_distribution STREQUAL distribution)
52 ${distribution} and ${current_distribution}\n"
56 set_property(GLOBAL PROPERTY LLVM_DISTRIBUTION_FOR_${target} ${distribution})
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| /aosp_15_r20/prebuilts/clang/host/linux-x86/clang-r530567/lib/cmake/llvm/ |
| D | LLVMDistributionSupport.cmake | 1 # Utility functions for packaging an LLVM distribution. See the
10 # - The ${PROJECT}${distribution}_HAS_EXPORTS global property holds whether a
11 # project has any exports for a particular ${distribution} (where ${PROJECT}
31 # distribution for a target later. The distribution for ${target} is stored in
38 # denote the default (unnamed) distribution.
42 foreach(distribution ${LLVM_DISTRIBUTIONS})
43 foreach(target ${LLVM_${distribution}_DISTRIBUTION_COMPONENTS})
49 if(current_distribution AND NOT current_distribution STREQUAL distribution)
52 ${distribution} and ${current_distribution}\n"
56 set_property(GLOBAL PROPERTY LLVM_DISTRIBUTION_FOR_${target} ${distribution})
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| /aosp_15_r20/prebuilts/clang/host/linux-x86/clang-r536225/lib/cmake/llvm/ |
| D | LLVMDistributionSupport.cmake | 1 # Utility functions for packaging an LLVM distribution. See the
10 # - The ${PROJECT}${distribution}_HAS_EXPORTS global property holds whether a
11 # project has any exports for a particular ${distribution} (where ${PROJECT}
31 # distribution for a target later. The distribution for ${target} is stored in
38 # denote the default (unnamed) distribution.
42 foreach(distribution ${LLVM_DISTRIBUTIONS})
43 foreach(target ${LLVM_${distribution}_DISTRIBUTION_COMPONENTS})
49 if(current_distribution AND NOT current_distribution STREQUAL distribution)
52 ${distribution} and ${current_distribution}\n"
56 set_property(GLOBAL PROPERTY LLVM_DISTRIBUTION_FOR_${target} ${distribution})
[all …]
|
| /aosp_15_r20/prebuilts/clang/host/linux-x86/clang-r530567b/lib/cmake/llvm/ |
| D | LLVMDistributionSupport.cmake | 1 # Utility functions for packaging an LLVM distribution. See the
10 # - The ${PROJECT}${distribution}_HAS_EXPORTS global property holds whether a
11 # project has any exports for a particular ${distribution} (where ${PROJECT}
31 # distribution for a target later. The distribution for ${target} is stored in
38 # denote the default (unnamed) distribution.
42 foreach(distribution ${LLVM_DISTRIBUTIONS})
43 foreach(target ${LLVM_${distribution}_DISTRIBUTION_COMPONENTS})
49 if(current_distribution AND NOT current_distribution STREQUAL distribution)
52 ${distribution} and ${current_distribution}\n"
56 set_property(GLOBAL PROPERTY LLVM_DISTRIBUTION_FOR_${target} ${distribution})
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| /aosp_15_r20/external/python/setuptools/docs/ |
| D | pkg_resources.rst | 33 Eggs are a distribution format for Python modules, similar in concept to
35 However, unlike a pure distribution format, eggs can also be installed and
42 a distribution to co-exist in the same Python installation, with individual
60 distribution
63 importable distribution
67 pluggable distribution
68 An importable distribution whose filename unambiguously identifies its
82 necessarily active. More than one distribution (i.e. release version) for
87 ``sys.path``. At most one distribution (release version) of a given
99 default version of a distribution that is available to software that
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| /aosp_15_r20/external/apache-commons-math/src/main/java/org/apache/commons/math3/random/ |
| H A D | RandomDataImpl.java | 20 import org.apache.commons.math3.distribution.IntegerDistribution;
21 import org.apache.commons.math3.distribution.RealDistribution;
243 * org.apache.commons.math3.distribution.BetaDistribution Beta Distribution}. This
247 * @param alpha first distribution shape parameter
248 * @param beta second distribution shape parameter
249 * @return random value sampled from the beta(alpha, beta) distribution
258 * org.apache.commons.math3.distribution.BinomialDistribution Binomial Distribution}. This
262 * @param numberOfTrials number of trials of the Binomial distribution
263 * @param probabilityOfSuccess probability of success of the Binomial distribution
265 * distribution
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| /aosp_15_r20/external/rust/android-crates-io/crates/criterion/src/stats/ |
| D | tuple.rs | 3 use crate::stats::Distribution;
14 /// A tuple of distributions: `(Distribution<A>, Distribution<B>, ..)`
42 type Distributions = (Distribution<A>,);
46 impl<A> TupledDistributions for (Distribution<A>,) implementation
70 fn complete(self) -> (Distribution<A>,) { in complete()
71 (Distribution(self.0.into_boxed_slice()),) in complete()
80 type Distributions = (Distribution<A>, Distribution<B>);
84 impl<A, B> TupledDistributions for (Distribution<A>, Distribution<B>) implementation
112 fn complete(self) -> (Distribution<A>, Distribution<B>) { in complete()
114 Distribution(self.0.into_boxed_slice()), in complete()
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| /aosp_15_r20/external/tensorflow/tensorflow/python/ops/distributions/ |
| H A D | transformed_distribution.py | 15 """A Transformed Distribution class."""
26 from tensorflow.python.ops.distributions import distribution as distribution_lib
118 class TransformedDistribution(distribution_lib.Distribution):
119 """A Transformed Distribution.
121 A `TransformedDistribution` models `p(y)` given a base distribution `p(x)`,
124 distribution is typically an instance of the `Distribution` class.
133 `Distribution` associated with a random variable (rv) `X`.
135 Write `cdf(Y=y)` for an absolutely continuous cumulative distribution function
147 Programmatically: `bijector.forward(distribution.sample(...))`
152 Programmatically: `(distribution.log_prob(bijector.inverse(y))
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| /aosp_15_r20/prebuilts/gcc/linux-x86/host/x86_64-w64-mingw32-4.8/x86_64-w64-mingw32/include/c++/4.8.3/bits/ |
| D | random.h | 162 * the input for a specific Distribution. in _GLIBCXX_VISIBILITY()
183 * distribution. in _GLIBCXX_VISIBILITY()
1661 * @brief Uniform discrete distribution for random numbers. in _GLIBCXX_VISIBILITY()
1662 * A discrete random distribution on the range @f$[min, max]@f$ with equal in _GLIBCXX_VISIBILITY()
1672 /** The type of the range of the distribution. */ in _GLIBCXX_VISIBILITY()
1706 * @brief Constructs a uniform distribution object. in _GLIBCXX_VISIBILITY()
1720 * @brief Resets the distribution state. in _GLIBCXX_VISIBILITY()
1722 * Does nothing for the uniform integer distribution. in _GLIBCXX_VISIBILITY()
1736 * @brief Returns the parameter set of the distribution. in _GLIBCXX_VISIBILITY()
1743 * @brief Sets the parameter set of the distribution. in _GLIBCXX_VISIBILITY()
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| /aosp_15_r20/prebuilts/gcc/linux-x86/host/x86_64-linux-glibc2.17-4.8/x86_64-linux/include/c++/4.8.3/bits/ |
| D | random.h | 162 * the input for a specific Distribution. in _GLIBCXX_VISIBILITY()
183 * distribution. in _GLIBCXX_VISIBILITY()
1661 * @brief Uniform discrete distribution for random numbers. in _GLIBCXX_VISIBILITY()
1662 * A discrete random distribution on the range @f$[min, max]@f$ with equal in _GLIBCXX_VISIBILITY()
1672 /** The type of the range of the distribution. */ in _GLIBCXX_VISIBILITY()
1706 * @brief Constructs a uniform distribution object. in _GLIBCXX_VISIBILITY()
1720 * @brief Resets the distribution state. in _GLIBCXX_VISIBILITY()
1722 * Does nothing for the uniform integer distribution. in _GLIBCXX_VISIBILITY()
1736 * @brief Returns the parameter set of the distribution. in _GLIBCXX_VISIBILITY()
1743 * @brief Sets the parameter set of the distribution. in _GLIBCXX_VISIBILITY()
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| /aosp_15_r20/external/python/cpython3/Doc/library/ |
| D | importlib.metadata.rst | 17 the metadata of an installed `Distribution Package <https://packaging.python.org/en/latest/glossary…
27 ``importlib_metadata`` operates on third-party *distribution packages*
39 One *distribution package* can contain multiple *import packages*
42 may map to multiple *distribution packages*
47 By default, distribution metadata can live on the file system
70 `Distribution Package <https://packaging.python.org/en/latest/glossary/#term-Distribution-Package>`…
93 You can get the :ref:`metadata for a distribution <metadata>`::
98 You can also get a :ref:`distribution's version number <version>`, list its
99 :ref:`constituent files <files>`, and get a list of the distribution's
188 Distribution metadata
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| /aosp_15_r20/external/google-cloud-java/java-containeranalysis/proto-google-cloud-containeranalysis-v1beta1/src/main/java/io/grafeas/v1beta1/pkg/ |
| H A D | Package.java | 87 distribution_ = new java.util.ArrayList<io.grafeas.v1beta1.pkg.Distribution>(); in Package()
92 io.grafeas.v1beta1.pkg.Distribution.parser(), extensionRegistry)); in Package()
181 private java.util.List<io.grafeas.v1beta1.pkg.Distribution> distribution_;
189 * <code>repeated .grafeas.v1beta1.package.Distribution distribution = 10;</code>
192 public java.util.List<io.grafeas.v1beta1.pkg.Distribution> getDistributionList() { in getDistributionList()
202 * <code>repeated .grafeas.v1beta1.package.Distribution distribution = 10;</code>
216 * <code>repeated .grafeas.v1beta1.package.Distribution distribution = 10;</code>
229 * <code>repeated .grafeas.v1beta1.package.Distribution distribution = 10;</code>
232 public io.grafeas.v1beta1.pkg.Distribution getDistribution(int index) { in getDistribution()
242 * <code>repeated .grafeas.v1beta1.package.Distribution distribution = 10;</code>
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| H A D | Distribution.java | 25 * This represents a particular channel of distribution for a given package.
29 * Protobuf type {@code grafeas.v1beta1.package.Distribution}
31 public final class Distribution extends com.google.protobuf.GeneratedMessageV3 class
33 // @@protoc_insertion_point(message_implements:grafeas.v1beta1.package.Distribution)
36 // Use Distribution.newBuilder() to construct.
37 private Distribution(com.google.protobuf.GeneratedMessageV3.Builder<?> builder) { in Distribution() method in Distribution
41 private Distribution() { in Distribution() method in Distribution
52 return new Distribution(); in newInstance()
60 private Distribution( in Distribution() method in Distribution
158 io.grafeas.v1beta1.pkg.Distribution.class, in internalGetFieldAccessorTable()
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