Searched refs:result_t (Results 1 – 8 of 8) sorted by relevance
/external/tensorflow/tensorflow/python/keras/ |
D | metrics_test.py | 81 result_t = m(100, sample_weight=0.5) 82 self.assertEqual(self.evaluate(result_t), 50) 86 result_t = m([1, 5], sample_weight=[1, 0.2]) 87 result = self.evaluate(result_t) 92 result_t = m([1, 2], sample_weight=0.5) 93 self.assertAlmostEqual(self.evaluate(result_t), 53.5, 1) # 52 + 0.5 + 1 97 result_t = m([1, 5], sample_weight=[[1], [0.2]]) 98 self.assertAlmostEqual(self.evaluate(result_t), 55.5, 1) # 53.5 + 1 + 1 102 result_t = m([[1], [5]], sample_weight=[1, 0.2]) 103 self.assertAlmostEqual(self.evaluate(result_t), 57.5, 2) # 55.5 + 1 + 1 [all …]
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D | metrics.py | 172 result_t = self.result() # pylint: disable=not-callable 183 result_t._metric_obj = self # pylint: disable=protected-access 184 return result_t
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/external/v8/src/base/ |
D | template-utils.h | 88 using result_t = typename std::remove_reference<T>::type; 98 using result_t = typename next_fold_helper::result_t; 99 static constexpr result_t fold(Func func, T1&& first, T2&& second, 112 typename detail::fold_helper<Func, Ts...>::result_t {
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/external/tensorflow/tensorflow/python/keras/utils/ |
D | metrics_utils.py | 102 result_t = array_ops.identity(result_fn(*args)) 122 result_t = replica_context.merge_call( 124 return result_t
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/external/google-fruit/include/fruit/impl/normalized_component_storage/ |
D | binding_normalization.templates.h | 562 using result_t = std::vector<ComponentStorageEntry, ArenaAllocator<ComponentStorageEntry>>; in performBindingCompression() local 563 result_t result = result_t(ArenaAllocator<ComponentStorageEntry>(memory_pool)); in performBindingCompression()
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/external/tensorflow/tensorflow/core/kernels/ |
D | list_kernels.h | 998 auto result_t = result->vec<Variant>(); in Compute() local 1002 result_t(b) = *tl_batch[b]; in Compute() 1004 TensorList* output = result_t(b).get<TensorList>(); in Compute()
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/external/tensorflow/tensorflow/python/kernel_tests/ |
D | functional_ops_test.py | 397 result_t = functional_ops.scan(lambda a, x: a + x, x_t, infer_shape=False) 400 result_t_grad = gradients_impl.gradients(result_t, [x_t])[0] 403 sess.run([result, result_t, result_grad, result_t_grad],
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D | list_ops_test.py | 1182 result_t = list_ops.tensor_list_stack(result, element_dtype=dtypes.float32) 1183 self.assertAllEqual(self.evaluate(result_t), [9., 12.])
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