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Searched refs:num_updates (Results 1 – 19 of 19) sorted by relevance

/external/tensorflow/tensorflow/python/kernel_tests/v1_compat_tests/
Dscatter_nd_ops_test.py51 num_updates = indices.size // ixdim
57 flat_updates = updates.reshape((num_updates, slice_size))
87 num_updates = indices_shape[0]
98 indices = np.array(all_indices[:num_updates])
100 if num_updates > 1 and repeat_indices:
101 indices = indices[:num_updates // 2]
102 for _ in range(num_updates - num_updates // 2):
104 indices, [indices[np.random.randint(num_updates // 2)]], axis=0)
106 indices = _AsType(indices[:num_updates], itype)
108 updates_shape = (num_updates,)
/external/webrtc/modules/audio_processing/agc/
Dloudness_histogram_unittest.cc48 EXPECT_EQ(hist_->num_updates(), 0); in TestClean()
65 int num_updates = 0; in RunTest() local
72 num_updates = 0; in RunTest()
79 num_updates++; in RunTest()
80 EXPECT_EQ(hist_->num_updates(), num_updates); in RunTest()
Dloudness_histogram.h46 int num_updates() const { return num_updates_; } in num_updates() function
Dagc.cc55 if (histogram_->num_updates() < kNumAnalysisFrames) { in GetRmsErrorDb()
/external/tensorflow/tensorflow/compiler/tests/
Dscatter_nd_op_test.py52 num_updates = indices.size // ixdim
58 flat_updates = updates.reshape((num_updates, slice_size))
84 num_updates = indices_shape[0]
95 indices = np.array(all_indices[:num_updates])
97 if num_updates > 1 and repeat_indices:
98 indices = indices[:num_updates // 2]
99 for _ in range(num_updates - num_updates // 2):
101 indices, [indices[np.random.randint(num_updates // 2)]], axis=0)
103 indices = _AsType(indices[:num_updates], itype)
105 updates_shape = (num_updates,)
Dadadelta_test.py34 num_updates = 4 # number of ADADELTA steps to perform
98 update = [None] * num_updates
100 for step in range(num_updates):
/external/tensorflow/tensorflow/python/training/
Dmoving_averages.py368 num_updates=None, argument
393 self._num_updates = num_updates
483 num_updates = math_ops.cast(
486 (1.0 + num_updates) / (10.0 + num_updates))
Dadadelta_test.py38 num_updates = 4 # number of ADADELTA steps to perform
108 update = [None] * num_updates
110 for step in range(num_updates):
Dmoving_averages_test.py260 ema = moving_averages.ExponentialMovingAverage(0.25, num_updates=1)
267 0.25, num_updates=1, zero_debias=True)
273 ema = moving_averages.ExponentialMovingAverage(0.25, num_updates=1)
280 0.25, num_updates=1, zero_debias=True)
/external/tensorflow/tensorflow/python/kernel_tests/array_ops/
Dscatter_nd_ops_test.py65 num_updates = indices.size // ixdim
71 flat_updates = updates.reshape((num_updates, slice_size))
121 num_updates = indices_shape[0]
133 indices = np.array(all_indices[:num_updates])
135 if num_updates > 1 and repeat_indices:
136 indices = indices[:num_updates // 2]
137 for _ in range(num_updates - num_updates // 2):
139 indices, [indices[np.random.randint(num_updates // 2)]], axis=0)
141 indices = _AsType(indices[:num_updates], itype)
143 updates_shape = (num_updates,)
[all …]
/external/tensorflow/tensorflow/python/keras/optimizer_v2/
Dadadelta_test.py45 num_updates = 4 # number of ADADELTA steps to perform
98 update = [None] * num_updates
100 for step in range(num_updates):
/external/tensorflow/tensorflow/core/kernels/
Dscatter_nd_op.cc52 int64 num_updates) { in ValidEmptyOutputShape() argument
53 if (num_indices == 0 && num_updates == 0) { in ValidEmptyOutputShape()
57 return (num_inputs != 0 && num_indices != 0 && num_updates != 0); in ValidEmptyOutputShape()
820 int64* slice_dim, Index* num_updates, in PrepareAndValidateInputs() argument
885 *num_updates = indices_shape.num_elements() / safe_slice_dim; in PrepareAndValidateInputs()
906 Index num_updates; in DoScatterNd() local
909 shape, indices, updates, &slice_dim, &num_updates, &slice_size)); in DoScatterNd()
913 auto updates_flat = updates.shaped<T, 2>({num_updates, slice_size}); in DoScatterNd()
Drange_sampler.cc194 int num_updates = std::min(static_cast<int>(values.size()), in Update() local
196 for (int i = 0; i < num_updates; i++) { in Update()
Dresource_variable_ops.cc918 int64 num_updates = updates.NumElements(); in DoCompute() local
919 OP_REQUIRES(c, num_updates % N == 0, in DoCompute()
924 auto updates_flat = updates.shaped<T, 2>({N, num_updates / N}); in DoCompute()
/external/tensorflow/tensorflow/tools/api/golden/v2/
Dtensorflow.train.-exponential-moving-average.pbtxt11 …argspec: "args=[\'self\', \'decay\', \'num_updates\', \'zero_debias\', \'name\'], varargs=None, ke…
/external/tensorflow/tensorflow/tools/api/golden/v1/
Dtensorflow.train.-exponential-moving-average.pbtxt11 …argspec: "args=[\'self\', \'decay\', \'num_updates\', \'zero_debias\', \'name\'], varargs=None, ke…
/external/libchrome/dbus/
Dproperty_unittest.cc128 void WaitForUpdates(size_t num_updates) { in WaitForUpdates() argument
129 while (updated_properties_.size() < num_updates) { in WaitForUpdates()
133 for (size_t i = 0; i < num_updates; ++i) in WaitForUpdates()
/external/tensorflow/tensorflow/core/api_def/base_api/
Dapi_def_TensorScatterUpdate.pbtxt48 * `indices` must have at least 2 axes: `(num_updates, index_depth)`.
/external/tensorflow/tensorflow/compiler/mlir/tensorflow/ir/
Dtf_generated_ops.td16729 * `indices` must have at least 2 axes: `(num_updates, index_depth)`.