/external/icu/icu4c/source/data/rbnf/ |
D | pl.txt | 59 "1000: tysi\u0105c[ >%%spellout-cardinal-masculine-genitive-ones>];", 60 …(cardinal,few{tysi\u0105ce}other{tysi\u0119cy})$[ >%%spellout-cardinal-masculine-genitive-ones>];", 63 "1000000000: miliard[ >%%spellout-cardinal-masculine-genitive-ones>];", 65 "1000000000000: bilion[ >%%spellout-cardinal-masculine-genitive-ones>];", 67 "1000000000000000: biliard[ >%%spellout-cardinal-masculine-genitive-ones>];", 93 "20: <%%spellout-cardinal-tens<[ >%%spellout-cardinal-feminine-ones>];", 94 "100: sto[ >%%spellout-cardinal-feminine-ones>];", 95 "200: dwie\u015Bcie[ >%%spellout-cardinal-feminine-ones>];", 96 "300: <%spellout-cardinal-feminine<sta[ >%%spellout-cardinal-feminine-ones>];", 97 "500: <%spellout-cardinal-feminine<set[ >%%spellout-cardinal-feminine-ones>];", [all …]
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D | lo.txt | 29 "10: \u0EAA\u0EB4\u0E9A[\u200B>%%alt-ones>];", 30 "20: \u0E8A\u0EB2\u0EA7[\u200B>%%alt-ones>];", 31 "30: <<\u200B\u0EAA\u0EB4\u0E9A[\u200B>%%alt-ones>];", 38 "%%alt-ones:",
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D | th.txt | 29 "10: \u0E2A\u0E34\u0E1A[\u200B>%%alt-ones>];", 30 "20: \u0E22\u0E35\u0E48\u200B\u0E2A\u0E34\u0E1A[\u200B>%%alt-ones>];", 31 "30: <<\u200B\u0E2A\u0E34\u0E1A[\u200B>%%alt-ones>];", 38 "%%alt-ones:",
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/external/mesa3d/src/util/ |
D | u_atomic_test.c | 46 #define test_atomic_assign(type, ones) \ argument 50 p_atomic_set(&v, ones); \ 51 assert(v == ones && "p_atomic_set"); \ 54 assert(r == ones && "p_atomic_read"); \ 56 v = ones; \ 58 assert(v == ones && "p_atomic_cmpxchg"); \ 59 assert(r == ones && "p_atomic_cmpxchg"); \ 60 r = p_atomic_cmpxchg(&v, ones, 0); \ 62 assert(r == ones && "p_atomic_cmpxchg"); \ 69 #define test_atomic_8bits(type, ones) \ argument [all …]
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/external/tensorflow/tensorflow/contrib/learn/python/learn/learn_io/ |
D | generator_io_test.py | 36 'a': np.ones(1) * index, 37 'b': np.ones(1) * index + 32, 38 'label': np.ones(1) * index - 32 69 yield {'a': np.ones(1) * index} 94 'a': np.ones(1) * index, 95 'b': np.ones(1) * index + 32, 96 'label': np.ones(1) * index - 32, 97 'label2': np.ones(1) * index - 64, 132 'a': np.ones((10, 10)) * index, 133 'b': np.ones((5, 5)) * index + 32, [all …]
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/external/tensorflow/tensorflow/python/estimator/inputs/queues/ |
D | feeding_functions_test.py | 294 a = (np.ones(shape=[32, 32], dtype=np.int32).tolist() + 295 np.ones(shape=[32, 36], dtype=np.int32).tolist()) 296 actual = np.ones(shape=[64, 36], dtype=np.int32) 298 expected = np.ones(shape=[64, 36], dtype=np.int32) 303 a = (np.ones(shape=[8, 8, 8, 8, 32], dtype=np.int32).tolist() + 304 np.ones(shape=[8, 8, 8, 8, 36], dtype=np.int32).tolist()) 305 actual = np.ones(shape=[16, 8, 8, 8, 36], dtype=np.int32) 307 expected = np.ones(shape=[16, 8, 8, 8, 36], dtype=np.int32) 313 a = (np.ones(shape=[32, 32], dtype=np.int32).tolist() + 314 np.ones(shape=[32, 36], dtype=np.int32).tolist()) [all …]
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/external/libvpx/libvpx/vpx_dsp/mips/ |
D | loopfilter_masks_dspr2.h | 35 uint32_t ones = 0xFFFFFFFF; in filter_hev_mask_dspr2() local 122 [ones] "r"(ones), [flimit] "r"(flimit)); in filter_hev_mask_dspr2() 134 uint32_t ones = 0xFFFFFFFF; in filter_hev_mask_flatmask4_dspr2() local 233 [thresh] "r"(thresh), [flat_thresh] "r"(flat_thresh), [ones] "r"(ones)); in filter_hev_mask_flatmask4_dspr2() 262 [ones] "r"(ones), [flimit] "r"(flimit)); in filter_hev_mask_flatmask4_dspr2() 273 uint32_t ones = 0xFFFFFFFF; in flatmask5() local 346 [flat_thresh] "r"(flat_thresh), [ones] "r"(ones)); in flatmask5()
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/external/tensorflow/tensorflow/python/kernel_tests/ |
D | reduction_ops_test_big.py | 52 arr_ = np.ones([4097, 4097], dtype=np.float32) 62 col_sum = np.ones([size_y], dtype=np.float32) * size_x 63 row_sum = np.ones([size_x], dtype=np.float32) * size_y 64 full_sum = np.ones([], dtype=np.float32) * size_x * size_y 76 arr_ = np.ones([130, 130, 130], dtype=np.float32) 81 sum_y = np.ones([size_x, size_z], dtype=np.float32) 82 sum_xz = np.ones([size_y], dtype=np.float32) 138 arr_ = np.ones([4097, 4097], dtype=np.bool) 148 col_sum = np.ones([size_y], dtype=np.bool) 149 row_sum = np.ones([size_x], dtype=np.bool) [all …]
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D | metrics_test.py | 170 return np.reshape(np.cumsum(np.ones(shape)), newshape=shape) 179 metrics.mean(array_ops.ones([4, 3])) 185 array_ops.ones([4, 3]), metrics_collections=[my_collection_name]) 191 array_ops.ones([4, 3]), updates_collections=[my_collection_name]) 237 metrics.mean(values, weights=np.ones((1, 1, 1))), 238 metrics.mean(values, weights=np.ones((1, 1, 1, 1))), 239 metrics.mean(values, weights=np.ones((1, 1, 1, 1, 1))), 240 metrics.mean(values, weights=np.ones((1, 1, 4))), 241 metrics.mean(values, weights=np.ones((1, 1, 4, 1))), 242 metrics.mean(values, weights=np.ones((1, 2, 1))), [all …]
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D | dense_update_ops_no_tsan_test.py | 58 ones = np.ones((1024, 1024)).astype(np.float32) 59 self.assertTrue((vals >= ones).all()) 60 self.assertTrue((vals <= ones * 20).all()) 118 ones = np.ones((1024, 1024)).astype(np.float32) 119 self.assertAllEqual(vals, ones * 20) 150 self.assertAllEqual(vals, np.ones([1024, 1024]) * vals[0, 0])
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/external/tensorflow/tensorflow/python/keras/_impl/keras/ |
D | model_subclassing_test.py | 185 x = np.ones((num_samples, input_dim)) 205 x1 = np.ones((num_samples, input_dim)) 206 x2 = np.ones((num_samples, input_dim)) 225 x = array_ops.ones((num_samples, input_dim)) 243 x1 = array_ops.ones((num_samples, input_dim)) 244 x2 = array_ops.ones((num_samples, input_dim)) 263 x1 = np.ones((num_samples, input_dim)) 264 x2 = np.ones((num_samples, input_dim)) 285 x1 = np.ones((num_samples, input_dim)) 286 x2 = np.ones((num_samples, input_dim)) [all …]
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/external/tensorflow/tensorflow/contrib/boosted_trees/python/utils/ |
D | losses_test.py | 38 labels_positive = array_ops.ones([10, 1], dtypes.float32) 39 weights = array_ops.ones([10, 1], dtypes.float32) 61 self.assertAllClose(np.exp(np.ones([2, 1])), pos_loss[:2], atol=1e-4) 62 self.assertAllClose(np.exp(-np.ones([2, 1])), neg_loss[:2], atol=1e-4) 67 self.assertAllClose(np.exp(-np.ones([4, 1])), pos_loss[6:10], atol=1e-4) 68 self.assertAllClose(np.exp(np.ones([4, 1])), neg_loss[6:10], atol=1e-4) 83 weights = array_ops.ones([5, 1], dtypes.float32)
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/external/tensorflow/tensorflow/python/keras/_impl/keras/layers/ |
D | gru_test.py | 101 out1 = model.predict(np.ones((num_samples, timesteps))) 106 np.ones((num_samples, timesteps)), np.ones((num_samples, units))) 107 out2 = model.predict(np.ones((num_samples, timesteps))) 115 out3 = model.predict(np.ones((num_samples, timesteps))) 120 out4 = model.predict(np.ones((num_samples, timesteps))) 124 out5 = model.predict(np.ones((num_samples, timesteps))) 130 left_padded_input = np.ones((num_samples, timesteps)) 137 right_padded_input = np.ones((num_samples, timesteps)) 160 x = keras.backend.variable(np.ones((2, 3, 2)))
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D | simplernn_test.py | 101 out1 = model.predict(np.ones((num_samples, timesteps))) 106 np.ones((num_samples, timesteps)), np.ones((num_samples, units))) 107 out2 = model.predict(np.ones((num_samples, timesteps))) 115 out3 = model.predict(np.ones((num_samples, timesteps))) 120 out4 = model.predict(np.ones((num_samples, timesteps))) 124 out5 = model.predict(np.ones((num_samples, timesteps))) 130 left_padded_input = np.ones((num_samples, timesteps)) 137 right_padded_input = np.ones((num_samples, timesteps)) 160 x = keras.backend.variable(np.ones((2, 3, 2)))
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D | convolutional_recurrent.py | 486 ones = K.zeros_like(inputs) 487 ones = K.sum(ones, axis=1) 488 ones += 1 491 return K.dropout(ones, self.dropout) 494 K.in_train_phase(dropped_inputs, ones, training=training) 504 ones = K.zeros_like(inputs) 505 ones = K.sum(ones, axis=1) 506 ones = self.input_conv(ones, K.zeros(shape), padding=self.padding) 507 ones += 1. 510 return K.dropout(ones, self.recurrent_dropout) [all …]
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D | lstm_test.py | 117 out1 = model.predict(np.ones((num_samples, timesteps))) 122 np.ones((num_samples, timesteps)), np.ones((num_samples, units))) 123 out2 = model.predict(np.ones((num_samples, timesteps))) 131 out3 = model.predict(np.ones((num_samples, timesteps))) 136 out4 = model.predict(np.ones((num_samples, timesteps))) 140 out5 = model.predict(np.ones((num_samples, timesteps))) 146 left_padded_input = np.ones((num_samples, timesteps)) 153 right_padded_input = np.ones((num_samples, timesteps)) 175 x = keras.backend.variable(np.ones((2, 3, 2))) 286 values = [np.ones(shape) for shape in state_shapes] [all …]
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/external/tensorflow/tensorflow/contrib/metrics/python/ops/ |
D | metric_ops_test.py | 165 metrics.streaming_mean(array_ops.ones([4, 3])) 171 array_ops.ones([4, 3]), metrics_collections=[my_collection_name]) 177 array_ops.ones([4, 3]), updates_collections=[my_collection_name]) 323 metrics.streaming_mean_tensor(array_ops.ones([4, 3])) 330 array_ops.ones([4, 3]), metrics_collections=[my_collection_name]) 336 array_ops.ones([4, 3]), updates_collections=[my_collection_name]) 487 predictions=array_ops.ones((10, 1)), 488 labels=array_ops.ones((10, 1)), 496 predictions=array_ops.ones((10, 1)), 497 labels=array_ops.ones((10, 1)), [all …]
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/external/tensorflow/tensorflow/contrib/distributions/python/kernel_tests/ |
D | vector_exponential_diag_test.py | 98 diag = np.ones([3]) 122 loc=array_ops.ones([2, 3], dtype=dtypes.float32)) 124 np.diag(np.ones([3], dtype=np.float32)), 128 loc=array_ops.ones([3], dtype=dtypes.float32), 142 loc=array_ops.ones([3], dtype=dtypes.float32), 160 np.ones([3], dtype=np.float32), 164 loc=array_ops.ones([3], dtype=dtypes.float32), 172 loc=array_ops.ones([3], dtype=dtypes.float32), 185 np.ones([3], dtype=np.float32),
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D | distribution_util_test.py | 68 scale_identity_multiplier * _matrix_diag(np.ones( 93 return scale_identity_multiplier * np.diag(np.ones(shape_hint)) 225 scale = linear_operator_diag.LinearOperatorDiag(np.ones((5, 1, 3))) 231 scale = linear_operator_diag.LinearOperatorDiag(np.ones((5, 1, 3))) 245 feed_dict={diag: np.ones((5, 1, 3))}) 251 diag = constant_op.constant(np.ones((5, 2, 3))) 270 feed_dict={diag: np.ones((5, 2, 3)), loc: np.zeros((2, 3))}) 276 scale = linear_operator_diag.LinearOperatorDiag(np.ones((5, 1, 3))) 290 feed_dict={diag: np.ones((5, 1, 3))}) 298 x = array_ops.ones((2, 1, 3)) [all …]
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/external/tensorflow/tensorflow/contrib/kfac/python/kernel_tests/ |
D | optimizer_test.py | 53 inputs = array_ops.ones((2, 1)) * 2 54 weights_val = np.ones((1, 1), dtype=np.float32) * 3. 130 x = variable_scope.get_variable('x', initializer=array_ops.ones((2, 2))) 132 'y', initializer=array_ops.ones((2, 2)) * 2) 133 vec1 = array_ops.ones((2, 2)) * 3 134 vec2 = array_ops.ones((2, 2)) * 4 165 inputs = array_ops.ones((2, 1)) * 2 166 weights_val = np.ones((1, 1), dtype=np.float32) * 3.
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/external/tensorflow/tensorflow/contrib/model_pruning/python/layers/ |
D | layers_test.py | 35 input_tensor = array_ops.ones((self.height, self.width, 3)) 40 input_tensor = array_ops.ones((8, 8, self.height, self.width, 3)) 47 input_tensor = array_ops.ones((8, self.height, self.width, input_depth)) 67 input_tensor = array_ops.ones((8, self.height, self.width, base_depth)) 96 input_tensor = array_ops.ones((5, input_depth)) 115 input_tensor = array_ops.ones((8, base_depth))
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/external/tensorflow/tensorflow/contrib/timeseries/python/timeseries/state_space_models/ |
D | periodic.py | 49 return self.transition_to_powers(array_ops.ones([], dtype=dtypes.int32)) 57 array_ops.ones([1], dtype=self.dtype), 79 array_ops.ones([array_ops.rank(powers)], dtype=dtypes.int32), 85 negative_row_indicator = array_ops.where(is_row_negative, -array_ops.ones( 95 array_ops.ones( 144 array_ops.ones([array_ops.rank(num_steps)], dtype=dtypes.int32), 192 array_ops.ones([1], dtype=self.dtype), array_ops.zeros( 306 array_ops.ones( 381 array_ops.ones(
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/external/tensorflow/tensorflow/python/ops/distributions/ |
D | student_t.py | 227 df = self.df * array_ops.ones(self.batch_shape_tensor(), dtype=self.dtype) 262 v = array_ops.ones(self.batch_shape_tensor(), 278 mean = self.loc * array_ops.ones(self.batch_shape_tensor(), 285 array_ops.ones(self.batch_shape_tensor(), dtype=self.dtype)), 292 array_ops.ones([], dtype=self.dtype), 314 var = (array_ops.ones(self.batch_shape_tensor(), dtype=self.dtype) * 328 array_ops.ones(self.batch_shape_tensor(), dtype=self.dtype)), 335 array_ops.ones([], dtype=self.dtype),
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/external/libvpx/libvpx/vpx_dsp/ppc/ |
D | hadamard_vsx.c | 77 const uint16x8_t ones = vec_splat_u16(1); in vpx_hadamard_16x16_vsx() local 97 const int16x8_t b0 = vec_sra(a0, ones); in vpx_hadamard_16x16_vsx() 98 const int16x8_t b1 = vec_sra(a1, ones); in vpx_hadamard_16x16_vsx() 99 const int16x8_t b2 = vec_sra(a2, ones); in vpx_hadamard_16x16_vsx() 100 const int16x8_t b3 = vec_sra(a3, ones); in vpx_hadamard_16x16_vsx()
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/external/tensorflow/tensorflow/compiler/xla/tests/ |
D | pad_test.cc | 303 auto ones = MakeUnique<Array4D<int32>>(2, 3, 3, 2); in XLA_TEST_F() local 305 ones->Fill(1); in XLA_TEST_F() 306 b.Select(padded, AddParam(*ones, &b), AddParam(*zeros, &b)); in XLA_TEST_F() 322 auto ones = MakeUnique<Array2D<float>>(4, 4); in XLA_TEST_P() local 323 ones->Fill(1.0f); in XLA_TEST_P() 324 auto input = AddParam(*ones, &b); in XLA_TEST_P() 335 auto expected = ReferenceUtil::PadArray2D(*ones, padding_config, 0.0f); in XLA_TEST_P() 448 auto ones = MakeUnique<Array4D<float>>(2, 2, 2, 2); in XLA_TEST_P() local 449 ones->Fill(1.0); in XLA_TEST_P() 450 auto input = AddParam(*ones, &b); in XLA_TEST_P()
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