| /third_party/mindspore/tests/ut/python/parallel/ |
| D | test_different_type_for_div_op.py | 46 def __init__(self, strategy0, strategy1): argument
48 self.fc_nobias = P.MatMul(transpose_b=True).shard(strategy0)
57 strategy0 = ((4, 1), (4, 1))
59 net = GradWrap(Net(strategy0, strategy1))
69 def __init__(self, strategy0, strategy1): argument
71 self.fc_nobias = P.MatMul(transpose_b=True).shard(strategy0)
80 strategy0 = ((4, 1), (4, 1))
82 net = GradWrap(Net(strategy0, strategy1))
92 def __init__(self, strategy0, strategy1): argument
94 self.fc_nobias = P.MatMul(transpose_b=True).shard(strategy0)
[all …]
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| D | test_reshape.py | 67 def __init__(self, strategy0, strategy1, strategy2): argument
69 self.relu = P.ReLU().shard(strategy0)
81 def reshape_net(strategy0, strategy1, strategy2): argument
82 return ReshapeNet(strategy0=strategy0, strategy1=strategy1, strategy2=strategy2)
85 def reshape_common(parallel_mode, strategy0, strategy1, strategy2, strategy_loss): argument
95 net = reshape_net(strategy0, strategy1, strategy2)
106 strategy0 = ((8, 1, 1, 1),)
110 reshape_common(ParallelMode.SEMI_AUTO_PARALLEL, strategy0, strategy1, strategy2, strategy_loss)
114 strategy0 = ((8, 1, 1, 1),)
119 … reshape_common(ParallelMode.SEMI_AUTO_PARALLEL, strategy0, strategy1, strategy2, strategy_loss)
[all …]
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| D | test_sum_as_loss.py | 46 def __init__(self, strategy0, strategy1): argument
48 self.fc_nobias = P.MatMul(transpose_b=True).shard(strategy0)
57 strategy0 = ((4, 1), (4, 1))
59 net = GradWrap(Net(strategy0, strategy1))
69 def __init__(self, strategy0, strategy1): argument
71 self.fc_nobias = P.MatMul(transpose_b=True).shard(strategy0)
80 strategy0 = ((4, 1), (4, 1))
82 net = GradWrap(Net(strategy0, strategy1))
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| D | test_virtual_dataset_with_strategy.py | 87 strategy0 = ((1, 8), (1, 8), (1, 8))
88 context.set_auto_parallel_context(dataset_strategy=strategy0)
101 strategy0 = ((1, 8), (1, 8), (1, 8))
102 context.set_auto_parallel_context(dataset_strategy=strategy0)
115 strategy0 = ((1, 8), (1, 8), (8,))
116 context.set_auto_parallel_context(dataset_strategy=strategy0)
129 strategy0 = ((1, 8), (1, 8), (8,))
130 context.set_auto_parallel_context(dataset_strategy=strategy0)
143 strategy0 = ((1, 8), (1, 8), (1,))
144 context.set_auto_parallel_context(dataset_strategy=strategy0)
[all …]
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| D | test_add_relu_redistribution.py | 30 def __init__(self, strategy0=None, strategy1=None): argument
32 self.add = P.Add().shard(strategy=strategy0)
70 strategy0 = ((1, 1), (1, 1))
72 net = Grad(NetWithLoss(AddRelu(strategy0, strategy1)))
83 strategy0 = ((8, 1), (8, 1))
85 net = Grad(NetWithLoss(AddRelu(strategy0, strategy1)))
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| D | test_scalar_loss.py | 41 def __init__(self, strategy0, strategy1): argument
43 self.fc_nobias = P.MatMul(transpose_b=True).shard(strategy0)
55 strategy0 = ((4, 1), (4, 1))
57 net = GradWrap(Net(strategy0, strategy1))
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| D | test_linear.py | 51 def __init__(self, strategy0, strategy1, strategy2): argument
53 self.fc_nobias = P.MatMul(transpose_b=True).shard(strategy0)
65 strategy0 = ((2, 4), (2, 4))
69 net = GradWrap(NetWithLoss(Net(strategy0, strategy1, strategy2), strategy3))
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| D | test_split_grad_sens.py | 162 def __init__(self, strategy0, strategy1): argument
164 self.fc_nobias = P.MatMul(transpose_b=True).shard(strategy0)
173 strategy0 = ((4, 1), (4, 1))
175 net = GradWrap4(Net(strategy0, strategy1))
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| /third_party/mindspore/mindspore/ccsrc/frontend/parallel/auto_parallel/ |
| D | operator_costmodel.cc | 1089 auto strategy0 = shape[0] / slice_shape[0]; in IsDataParallel() local
1091 return (total_device_num == LongToSize(strategy0)); in IsDataParallel()
|