/third_party/mindspore/mindspore/lite/src/delegate/npu/op/ |
D | reduce_npu.cc | 47 auto reduce_mean = new (std::nothrow) hiai::op::ReduceMean(name_); in Init() local 48 if (reduce_mean == nullptr) { in Init() 52 reduce_mean->set_attr_keep_dims(reduce_prim->keep_dims()); in Init() 53 reduce_ = reduce_mean; in Init() 65 auto reduce_mean = reinterpret_cast<hiai::op::ReduceMean *>(reduce_); in SetNPUInputs() local 66 reduce_mean->set_input_x(*npu_inputs[0]).set_input_axes(*npu_inputs[1]); in SetNPUInputs()
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/third_party/mindspore/mindspore/nn/probability/zhusuan/variational/ |
D | elbo.py | 29 self.reduce_mean = P.ReduceMean(keep_dims=False) 45 …elbo = self.reduce_mean(log_prob_x_) + self.reduce_mean(log_prob_z_) - self.reduce_mean(log_prob_z)
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/third_party/mindspore/tests/ut/python/parallel/ |
D | test_bias_add.py | 28 self.reduce_mean = P.ReduceMean() 35 loss = self.reduce_mean(loss, (-1,)) 74 self.reduce_mean = P.ReduceMean(keep_dims=False).shard(((1, 1, 1, 8),)) 79 x = self.reduce_mean(x, -1)
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D | test_reduce_method_info.py | 319 self.reduce_mean = P.ReduceMean(keep_dims=False).shard(strategy2) 324 out = self.reduce_mean(out, 0) 493 …self.reduce_mean = P.ReduceMean(keep_dims=False).shard(strategy3).add_prim_attr("cross_batch", Tru… 498 out = self.reduce_mean(out, 0) 518 self.reduce_mean = P.ReduceMean(keep_dims=False).shard(strategy2) 523 out = self.reduce_mean(out, -1) 544 self.reduce_mean = P.ReduceMean(keep_dims=False) 549 out = self.reduce_mean(out, -1)
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D | test_auto_parallel_flag.py | 90 self.reduce_mean = P.ReduceMean() 94 return self.reduce_mean(self.square(diff), get_axis(diff))
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D | test_reshape.py | 539 self.reduce_mean = P.ReduceMean(keep_dims=reducemean_keep_dims) 543 self.reduce_mean.shard(strategy) 547 x = self.reduce_mean(x, self.reducemean_axis) 556 self.reduce_mean = P.ReduceMean() 563 loss = self.reduce_mean(loss, (-1,))
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/third_party/mindspore/tests/st/ops/cpu/ |
D | test_reduce_op.py | 37 self.reduce_mean = P.ReduceMean(False) 44 return (self.reduce_mean(indice, self.axis0), 45 self.reduce_mean(indice, self.axis1), 46 self.reduce_mean(indice, self.axis2), 47 self.reduce_mean(indice, self.axis3), 48 self.reduce_mean(indice, self.axis4),
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/third_party/mindspore/tests/st/ops/ascend/test_tbe_ops/ |
D | test_ReduceMean.py | 29 self.reduce_mean = P.ReduceMean(keep_dims=keep_dims) 34 return self.reduce_mean(inputs, self.axis)
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/third_party/mindspore/tests/st/fusion/ |
D | test_add_relu_buffer_fusion.py | 33 self.reduce_mean = P.ReduceMean() 40 x = self.reduce_mean(x)
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/third_party/mindspore/mindspore/nn/layer/ |
D | pooling.py | 216 self.reduce_mean = P.ReduceMean(keep_dims=True) 381 self.reduce_mean = P.ReduceMean(keep_dims=True) 390 x = self.reduce_mean(x, 2) 393 x = self.reduce_mean(x, 2)
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D | image.py | 271 self.reduce_mean = P.ReduceMean() 287 …nnel, _ = _compute_multi_channel_loss(c1, c2, img1, img2, self.conv, self.concat, self.reduce_mean) 288 loss = self.reduce_mean(ssim_ave_channel, -1) 375 self.reduce_mean = P.ReduceMean() 401 … self.multi_convs_list[i], self.concat, self.reduce_mean) 409 loss = self.reduce_mean(ms_ssim, -1)
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D | normalization.py | 124 self.reduce_mean = P.ReduceMean(keep_dims=True) 1126 self.reduce_mean = P.ReduceMean(keep_dims=True) 1136 mean = self.reduce_mean(x, 2)
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/third_party/mindspore/tests/st/ops/graph_kernel/ |
D | test_reduce_mean.py | 27 self.reduce_mean = P.ReduceMean(keep_dims=False) 30 return self.reduce_mean(x)
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/third_party/mindspore/tests/st/auto_monad/ |
D | test_auto_monad_momentum_loss.py | 57 self.reduce_mean = P.ReduceMean() 61 return self.reduce_mean(self.square(diff), get_axis(diff))
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/third_party/mindspore/mindspore/_extends/graph_kernel/expanders/ |
D | __init__.py | 46 from .reduce_mean import ReduceMean
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/third_party/mindspore/tests/ut/python/optimizer/ |
D | test_debug_location.py | 115 self.reduce_mean = P.ReduceMean() 120 return self.reduce_mean(self.square(diff), get_axis(diff))
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D | test_optimizer_with_loss_scale.py | 93 self.reduce_mean = P.ReduceMean() 97 return self.reduce_mean(self.square(diff), get_axis(diff))
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/third_party/mindspore/mindspore/ops/_op_impl/cpu/ |
D | __init__.py | 54 from .reduce_mean import _reduce_mean_cpu
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/third_party/mindspore/tests/st/gnn/ |
D | aggregator.py | 213 self.reduce_mean = P.ReduceMean(keep_dims=False) 222 output_feature = self.reduce_mean(input_feature, 1)
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/third_party/mindspore/tests/st/networks/models/deeplabv3/src/ |
D | deeplabv3.py | 383 self.reduce_mean = P.ReduceMean() 405 logits = self.reduce_mean(logits, 2) 421 logits = self.reduce_mean(logits, 2)
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/third_party/mindspore/tests/st/pynative/loss_scale/ |
D | test_loss_scale.py | 142 self.reduce_mean = P.ReduceMean() 146 return self.reduce_mean(self.square(diff), get_axis(diff))
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/third_party/mindspore/tests/st/export_and_load/ |
D | test_bgcf.py | 48 self.reduce_mean = P.ReduceMean(keep_dims=False) 52 neigh_matrix = self.reduce_mean(neigh_feature, 1)
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/third_party/mindspore/tests/st/auto_parallel/ |
D | soft_entropy_loss_expand_parallel.py | 153 self.reduce_mean = P.ReduceMean(keep_dims=False).shard(strategy=stra_list[8]) 168 loss = self.reduce_mean(loss, -1)
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/third_party/mindspore/tests/st/fl/albert/src/ |
D | cell_wrapper.py | 148 self.reduce_mean = P.ReduceMean() 159 loss = self.reduce_mean(per_example_loss, self.last_idx)
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/third_party/mindspore/tests/ut/python/dtype/ |
D | test_list.py | 224 self.reduce_mean = P.ReduceMean() 232 ret_mean = self.reduce_mean(x, self.axis)
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