/third_party/grpc/src/core/lib/iomgr/ |
D | timer_generic.cc | 252 static grpc_millis compute_min_deadline(timer_shard* shard) { in compute_min_deadline() argument 253 return grpc_timer_heap_is_empty(&shard->heap) in compute_min_deadline() 254 ? saturating_add(shard->queue_deadline_cap, 1) in compute_min_deadline() 255 : grpc_timer_heap_top(&shard->heap)->deadline; in compute_min_deadline() 278 timer_shard* shard = &g_shards[i]; in timer_list_init() local 279 gpr_mu_init(&shard->mu); in timer_list_init() 280 grpc_time_averaged_stats_init(&shard->stats, 1.0 / ADD_DEADLINE_SCALE, 0.1, in timer_list_init() 282 shard->queue_deadline_cap = g_shared_mutables.min_timer; in timer_list_init() 283 shard->shard_queue_index = i; in timer_list_init() 284 grpc_timer_heap_init(&shard->heap); in timer_list_init() [all …]
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/third_party/grpc/src/core/lib/slice/ |
D | slice_intern.cc | 71 slice_shard* shard = &g_shards[SHARD_IDX(this->hash)]; in ~InternedSliceRefcount() local 72 MutexLockForGprMu lock(&shard->mu); in ~InternedSliceRefcount() 75 for (prev_next = &shard->strs[TABLE_IDX(this->hash, shard->capacity)], in ~InternedSliceRefcount() 80 shard->count--; in ~InternedSliceRefcount() 85 static void grow_shard(slice_shard* shard) { in grow_shard() argument 88 size_t capacity = shard->capacity * 2; in grow_shard() 96 for (i = 0; i < shard->capacity; i++) { in grow_shard() 97 for (s = shard->strs[i]; s; s = next) { in grow_shard() 104 gpr_free(shard->strs); in grow_shard() 105 shard->strs = strtab; in grow_shard() [all …]
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/third_party/grpc/src/core/lib/transport/ |
D | metadata.cc | 232 static void gc_mdtab(mdtab_shard* shard); 237 mdtab_shard* shard = &g_shards[i]; in grpc_mdctx_global_init() local 238 gpr_mu_init(&shard->mu); in grpc_mdctx_global_init() 239 shard->count = 0; in grpc_mdctx_global_init() 240 gpr_atm_no_barrier_store(&shard->free_estimate, 0); in grpc_mdctx_global_init() 241 shard->capacity = INITIAL_SHARD_CAPACITY; in grpc_mdctx_global_init() 242 shard->elems = static_cast<InternedMetadata::BucketLink*>( in grpc_mdctx_global_init() 243 gpr_zalloc(sizeof(*shard->elems) * shard->capacity)); in grpc_mdctx_global_init() 249 mdtab_shard* shard = &g_shards[i]; in grpc_mdctx_global_shutdown() local 250 gpr_mu_destroy(&shard->mu); in grpc_mdctx_global_shutdown() [all …]
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/third_party/mindspore/mindspore/parallel/nn/ |
D | moe.py | 115 self.transpose = P.Transpose().shard(((self.dp, 1, 1),)) 116 self.transpose2 = P.Transpose().shard(((self.dp, 1, 1, 1),)) 117 self.transpose3 = P.Transpose().shard(((self.dp, 1, 1, 1),)) 118 self.transpose4 = P.Transpose().shard(((self.dp, 1, 1),)) 119 self.transpose5 = P.Transpose().shard(((self.dp, 1, 1),)) 120 self.batch_mm = P.BatchMatMul().shard(((self.dp, 1, 1), (self.dp, 1, 1))) 121 self.batch_mm2 = P.BatchMatMul().shard(((self.dp, 1, 1), (self.dp, 1, 1))) 122 self.mul = P.Mul().shard(((), ())) 195 self.range = P.Range().shard(((1,),)) 197 self.matmul = P.MatMul().shard(((dp, 1), (1, 1))) [all …]
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D | layers.py | 243 def shard(self, strategy): member in _LayerNorm 259 self.mean.shard(strategy) 260 self.square.shard(strategy) 261 self.sqrt.shard(strategy) 262 self.sub1.shard((strategy[0], strategy[0])) 263 self.sub2.shard((strategy[0], strategy[0])) 264 self.add.shard((strategy[0], ())) 265 self.mul.shard((strategy[0], (1,))) 266 self.add2.shard((strategy[0], (1,))) 267 self.real_div.shard((strategy[0], strategy[0])) [all …]
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D | loss.py | 72 self.sum = P.ReduceSum().shard(((dp, mp),)) 73 self.onehot = P.OneHot().shard(((dp, mp), (), ())) 77 self.max = P.ArgMaxWithValue(axis=-1, keep_dims=True).shard( 80 self.sub = P.Sub().shard(((dp, mp), (dp, 1))) 81 self.exp = P.Exp().shard(((dp, mp),)) 82 self.div = P.RealDiv().shard(((dp, mp), (dp, 1))) 83 self.log = P.Log().shard(((dp, mp),)) 84 self.add = P.Add().shard(((dp, mp), ())) 85 self.mul = P.Mul().shard( 87 self.neg = P.Neg().shard(((dp, mp),)) [all …]
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D | transformer.py | 351 self.mapping.shard(strategy_matmul=((ep, 1, 1), (ep, 1, mp)), 355 self.mapping.shard(strategy_matmul=((dp, 1), (1, mp)), 365 self.projection.shard(strategy_matmul=((ep, 1, mp), (ep, mp, 1)), 368 self.projection.shard(strategy_matmul=((dp, mp), (mp, 1)), 372 self.dropout.dropout.shard(((dp, 1),)) 374 self.dropout_3d.dropout.shard(((dp, 1, 1),)) 437 self.not_equal = P.NotEqual().shard(((parallel_config.data_parallel, 1), ())) 439 self.mul = P.BatchMatMul().shard( 441 self.expand_dim = P.ExpandDims().shard(((1, 1),)) 445 self.multiply = P.Mul().shard(((parallel_config.data_parallel, 1, 1), (1, 1, 1))) [all …]
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/third_party/mindspore/tests/ut/python/parallel/ |
D | test_hybird_parallel_activation.py | 60 self.matmul1 = P.MatMul().shard(strategy1) 61 self.matmul2 = P.MatMul().shard(strategy2) 62 self.tanh = P.Tanh().shard(strategy3) 86 self.matmul1 = P.MatMul().shard(strategy1) 87 self.matmul2 = P.MatMul().shard(strategy2) 88 self.activation = P.ReLU().shard(strategy3) 112 self.matmul1 = P.MatMul().shard(strategy1) 113 self.matmul2 = P.MatMul().shard(strategy2) 114 self.softmax = P.Softmax().shard(strategy3) 138 self.matmul1 = P.MatMul().shard(strategy1) [all …]
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D | test_element_wise_function.py | 60 self.matmul = P.MatMul().shard(strategy1) 61 self.pow = P.Pow().shard(strategy2) 62 self.matmul2 = P.MatMul().shard(strategy1) 86 self.matmul = P.MatMul().shard(strategy1) 87 self.exp = P.Exp().shard(strategy2) 88 self.matmul2 = P.MatMul().shard(strategy1) 112 self.matmul = P.MatMul().shard(strategy1) 113 self.log = P.Log().shard(strategy2) 114 self.matmul2 = P.MatMul().shard(strategy1) 137 self.matmul = P.MatMul().shard(strategy1) [all …]
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D | test_one_hot_net.py | 88 self.cast.shard(strategy=strategy.twod_strategy) 90 self.cast1.shard(strategy=strategy.twod_strategy) 92 self.cast2.shard(strategy=strategy.twod_strategy) 94 self.cast3.shard(strategy=strategy.scalar_strategy) 96 self.cast4.shard(strategy=strategy.scalar_strategy) 105 self.onehot.shard(strategy=strategy.onehot_strategy) 107 self.exp.shard(strategy=strategy.twod_strategy) 109 self.exp2.shard(strategy=strategy.twod_strategy) 111 self.exp3.shard(strategy=strategy.twod_strategy) 113 self.mul_const.shard(strategy=strategy.scalar_twod_strategy) [all …]
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D | test_reduce_method_info.py | 87 self.mul1 = P.Mul().shard(strategy1) 88 self.reduce_sum = P.ReduceSum(keep_dims=False).shard(strategy2) 89 self.mul2 = P.Mul().shard(strategy3) 114 self.mul1 = P.Mul().shard(strategy1) 115 self.reduce_sum = P.ReduceSum(keep_dims=False).shard(strategy2) 116 self.mul2 = P.Mul().shard(strategy3) 141 self.mul1 = P.Mul().shard(strategy1) 142 self.reduce_sum = P.ReduceSum(keep_dims=False).shard(strategy2) 143 self.mul2 = P.Mul().shard(strategy3) 168 self.mul1 = P.Mul().shard(strategy1) [all …]
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D | test_comparison_function_info.py | 60 self.matmul = P.MatMul().shard(strategy1) 61 self.equal = P.Equal().shard(strategy2) 83 self.matmul = P.MatMul().shard(strategy1) 84 self.notequal = P.NotEqual().shard(strategy2) 106 self.matmul = P.MatMul().shard(strategy1) 107 self.approximateEqual = P.ApproximateEqual(tolerance=0.5).shard(strategy2) 130 self.matmul = P.MatMul().shard(strategy1) 131 self.greater = P.Greater().shard(strategy2) 154 self.matmul = P.MatMul().shard(strategy1) 155 self.greaterEqual = P.GreaterEqual().shard(strategy2) [all …]
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D | test_arithmetic.py | 59 self.matmul = P.MatMul().shard(strategy1) 60 self.sub = P.Sub().shard(strategy2) 83 self.matmul = P.MatMul().shard(strategy1) 84 self.add = P.Add().shard(strategy2) 107 self.matmul = P.MatMul().shard(strategy1) 108 self.mul = P.Mul().shard(strategy2) 130 self.matmul = P.MatMul().shard(strategy1) 131 self.mod = P.Mod().shard(strategy2) 153 self.matmul = P.MatMul().shard(strategy1) 154 self.floormod = P.FloorMod().shard(strategy2) [all …]
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D | test_operator_model_parallel.py | 54 shard=None): argument 72 self.matmul = P.MatMul(transpose_b=True).shard(matmul_strategy) 73 self.bias_add = P.Add().shard(shard) 111 conv.conv2d.shard(strategy_weight) 122 conv.conv2d.shard(strategy_weight) 133 conv.conv2d.shard(strategy_weight) 155 bn.bn_train.shard(strategy_bn) 167 bn.bn_train.shard(strategy_bn) 178 matmul_strategy=strategy_fc_weight_nobias, shard=strategy_tensor_add) 200 self.relu1 = P.ReLU().shard(strategy_no_weight) [all …]
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D | test_dsd_matmul.py | 46 def __init__(self, batch_size, num_heads, dp, mp, shard=True): argument 66 if shard: 67 … self.dsd_matmul.shard(((dp, mp, 1, 1, 1, 1, 1), (dp, mp, 1, 1, 1, 1, 1), (dp, mp, 1, 1))) 68 self.dense1.matmul.shard(((dp, 1), (mp, 1))) 69 self.dense2.matmul.shard(((dp, 1), (mp, 1))) 70 self.dense2.matmul.shard(((dp, 1), (mp, 1))) 71 self.transpose.shard(((dp, 1, mp, 1),)) 72 self.transpose1.shard(((dp, mp, 1, 1, 1, 1),)) 118 def compile_graph(batch_size, num_heads, dp, mp, auto=False, shard=True): argument 124 net = GradWrap(NetWithLoss(Net(batch_size, num_heads, dp, mp, shard=shard))) [all …]
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D | test_cus_matmul_dds.py | 41 def __init__(self, batch_size, num_heads, dp, mp, shard=True): argument 61 if shard: 62 self.cus_matmul.shard(((mp, dp, 1, 1), (mp, dp, 1, 1), (1, dp, 1, 1), (dp, 1, 1, 1))) 63 self.dense1.matmul.shard(((dp, 1), (mp, 1))) 64 self.dense2.matmul.shard(((dp, 1), (mp, 1))) 65 self.transpose.shard(((dp, 1, mp, 1),)) 102 def compile_graph(batch_size, num_heads, dp, mp, auto=False, shard=True): argument 108 net = GradWrap(NetWithLoss(Net(batch_size, num_heads, dp, mp, shard=shard))) 169 compile_graph(batch_size, num_heads, dp, mp, auto=True, shard=False) 178 compile_graph(batch_size, num_heads, dp, mp, auto=True, shard=False) [all …]
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D | test_matmul_tensor.py | 63 self.matmul1 = P.MatMul().shard(strategy1) 64 self.matmul2 = P.MatMul().shard(strategy2) 65 self.matmul3 = P.MatMul().shard(strategy3) 93 self.matmul = P.MatMul().shard(strategy1) 94 self.mul = P.Mul().shard(strategy2) 117 self.matmul1 = P.MatMul().shard(strategy1) 118 self.matmul2 = P.MatMul().shard(strategy2) 119 self.matmul3 = P.MatMul().shard(strategy3) 147 self.matmul = P.MatMul().shard(strategy1) 148 self.add = P.Add().shard(strategy2)
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D | test_two_matmul.py | 61 self.matmul1 = P.MatMul().shard(strategy1) 62 self.matmul2 = P.MatMul().shard(strategy2) 86 self.matmul1 = P.MatMul().shard(strategy1) 87 self.matmul2 = P.MatMul().shard(strategy2) 110 self.matmul1 = P.MatMul().shard(strategy1) 111 self.matmul2 = P.MatMul().shard(strategy2) 134 self.matmul = P.MatMul().shard(strategy1) 136 self.mul = P.Mul().shard(strategy2) 158 self.matmul = P.MatMul(transpose_b=True).shard(strategy1) 160 self.mul = P.Mul().shard(strategy2)
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D | test_reshape_unexpand.py | 55 self.mul = P.Mul().shard(((1, 8), (1, 1, 8))) 78 self.mul = P.Mul().shard(((1, 1, 8), (1, 8))) 101 self.mul = P.Mul().shard(((1, 4, 2), (4, 2))) 124 self.relu1 = P.ReLU().shard(((4, 1),)) 125 self.relu2 = P.ReLU().shard(((1, 4),)) 148 self.relu1 = P.ReLU().shard(((4, 1),)) 149 self.relu2 = P.ReLU().shard(((1, 2, 2),)) 172 self.relu1 = P.ReLU().shard(((2, 2, 1),)) 173 self.relu2 = P.ReLU().shard(((1, 4),)) 196 self.relu1 = P.ReLU().shard(((2, 1),)) [all …]
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D | test_loss_and_optimizer.py | 30 self.loss = P.SoftmaxCrossEntropyWithLogits().shard(strategy3) 49 self.matmul = P.MatMul(transpose_a=False, transpose_b=True).shard(strategy1) 50 self.relu = P.ReLU().shard(strategy2) 83 self.matmul = P.MatMul(transpose_a=False, transpose_b=True).shard(strategy1) 84 self.relu = P.ReLU().shard(strategy2) 117 self.matmul = P.MatMul(transpose_a=False, transpose_b=True).shard(strategy1) 118 self.relu = P.ReLU().shard(strategy2) 152 self.matmul = P.MatMul(transpose_a=False, transpose_b=True).shard(strategy1) 153 self.relu = P.ReLU().shard(strategy2) 188 self.matmul = P.MatMul(transpose_a=False, transpose_b=True).shard(strategy1) [all …]
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D | test_strategy_checkpoint.py | 54 self.matmul1 = P.MatMul().shard(strategy1) 55 self.matmul2 = P.MatMul().shard(strategy2) 56 self.matmul3 = P.MatMul().shard(strategy3) 57 self.matmul4 = P.MatMul().shard(strategy4) 58 self.matmul5 = P.MatMul().shard(strategy5) 59 self.matmul6 = P.MatMul().shard(strategy6) 118 self.matmul1 = P.MatMul().shard(strategy1) 119 self.matmul3 = P.MatMul().shard(strategy3) 120 self.matmul4 = P.MatMul().shard(strategy4) 121 self.matmul5 = P.MatMul().shard(strategy5) [all …]
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D | test_split.py | 28 self.split = P.Split(axis, out_nums).shard(strategy1) 29 self.mul = P.Mul().shard(strategy2) 30 self.matmul = P.MatMul(transpose_b=True).shard(strategy2) 31 self.matmul2 = P.MatMul().shard(strategy3) 45 self.split = P.Split(axis, out_nums).shard(strategy1) 46 self.mul = P.Mul().shard(strategy2) 59 self.split = P.Split(axis, out_nums).shard(strategy1) 60 self.mul = P.Mul().shard(strategy2)
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D | test_batchmm.py | 28 self.relu = P.ReLU().shard(stra1) 29 self.transpose = P.Transpose().shard(stra2) 31 self.batch_mm = P.BatchMatMul().shard(stra3) 33 self.batch_mm2 = P.BatchMatMul().shard(stra4) 34 self.transpose2 = P.Transpose().shard(stra5) 35 self.relu2 = P.ReLU().shard(stra6)
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D | test_layer_norm_further.py | 32 self.mul = P.Mul().shard(strategy1) 34 self.begin_norm_axis, self.begin_params_axis).shard(strategy2) 35 self.relu = P.ReLU().shard(strategy3) 56 self.mul = P.Mul().shard(strategy1) 58 self.begin_norm_axis, self.begin_params_axis).shard(strategy2) 59 self.relu = P.ReLU().shard(strategy3) 80 self.mul = P.Mul().shard(strategy1) 82 self.begin_norm_axis, self.begin_params_axis).shard(strategy2) 83 self.relu = P.ReLU().shard(strategy3) 104 self.mul = P.Mul().shard(strategy1) [all …]
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/third_party/mindspore/mindspore/nn/layer/ |
D | embedding.py | 258 self.unique = P.Unique().shard(((1,),)) 275 self.gatherv2.shard(((get_group_size(), 1), (1, get_group_size()))) 276 self.embeddinglookup.shard(((get_group_size(), 1), (1, get_group_size()))) 281 self.gather_revert.shard(((1, 1), (get_group_size(),))) 284 self.gatherv2.shard(((get_group_size(), 1), indices_strategy)) 285 self.embeddinglookup.shard(((get_group_size(), 1), indices_strategy)) 289 self.gather_revert.shard(((1, get_group_size()), (1,))) 292 self.gatherv2.shard(((1, get_group_size()), indices_strategy)) 293 self.embeddinglookup.shard(((1, get_group_size()), indices_strategy)) 298 self.gatherv2.shard(((1, 1), indices_strategy)) [all …]
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