| /third_party/mindspore/mindspore-src/source/tests/st/backend_opt_pass/ |
| D | test_backend_common_unify.py | 33 class Net(nn.Cell): class
43 net = WrapNet(Net())
45 net(x)
47 patterns = ['Default/net-Net/BroadcastTo-op',
48 'Default/net-Net/Mul-op']
64 class Net(nn.Cell): class
74 net = WrapNet(Net())
76 net(x)
78 patterns = ['Default/net-Net/ReduceMean-op']
94 class Net(nn.Cell): class
[all …]
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| /third_party/mindspore/mindspore-src/source/tests/ut/python/graph_syntax/python_builtin_functions/ |
| D | test_enumerate.py | 27 class Net(nn.Cell): class
29 super(Net, self).__init__()
40 net = Net()
41 assert net() == (6, 110)
45 class Net(nn.Cell): class
47 super(Net, self).__init__()
58 net = Net()
59 assert net() == (6, 110)
63 class Net(nn.Cell): class
65 super(Net, self).__init__()
[all …]
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| /third_party/mindspore/mindspore-src/source/tests/st/pi_jit/one_stage/ |
| D | test_base_op.py | 43 class Net(nn.Cell): class
48 net = Net()
50 jit(net.construct, mode="PIJit", jit_config=cfg)
51 ret = net(a)
68 class Net(nn.Cell): class
73 net = Net()
75 jit(net.construct, mode="PIJit", jit_config=cfg)
76 ret = net(a)
93 class Net(nn.Cell): class
98 net = Net()
[all …]
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| /third_party/mindspore/mindspore-src/source/tests/ut/python/pipeline/parse/ |
| D | test_use_undefined_name_or_unsupported_builtin_function.py | 27 class Net(nn.Cell): class
32 net = Net()
34 net(Tensor([1, 2, 3], mstype.float32))
42 class Net(nn.Cell): class
48 net = Net()
50 net(Tensor([1, 2, 3], mstype.float32))
57 class Net(nn.Cell): class
63 net = Net()
65 net(Tensor([1, 2, 3], mstype.float32))
73 class Net(nn.Cell): class
[all …]
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| D | test_structure_output.py | 31 class Net(Cell): class
33 super(Net, self).__init__()
40 net = Net()
41 assert net() == x
45 class Net(Cell): class
47 super(Net, self).__init__()
55 net = Net()
56 assert net() == (1, 2, 3, 4, 5, 6)
60 class Net(Cell): class
62 super(Net, self).__init__()
[all …]
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| /third_party/mindspore/mindspore-src/source/tests/st/pi_jit/operation/ |
| D | test_dtype.py | 22 net = DType()
24 jit(net.construct, mode="PIJit")(Tensor(input_np))
26 fact.forward_cmp(net)
27 fact.grad_cmp(net)
45 net = DType()
47 jit(net.construct, mode="PIJit")(Tensor(input_np))
49 fact.forward_cmp(net)
50 fact.grad_cmp(net)
68 net = DType()
70 jit(net.construct, mode="PIJit")(Tensor(input_np))
[all …]
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| /third_party/mindspore/mindspore-src/source/tests/ut/python/graph_syntax/tensor/tensor_methods/ |
| D | test_tensor_view.py | 28 class Net(nn.Cell): class
30 super(Net, self).__init__()
36 net = Net()
37 net()
41 class Net(nn.Cell): class
43 super(Net, self).__init__()
49 net = Net()
50 net()
54 class Net(nn.Cell): class
56 super(Net, self).__init__()
[all …]
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| /third_party/mindspore/mindspore-src/source/tests/st/pynative/ops/view/ |
| D | test_view_slice.py | 42 class Net(nn.Cell): class
47 net = Net()
48 expect_output = net(x).asnumpy()
50 expect_grad = grad_op(net)(x)
53 net = Net()
54 output = net(x).asnumpy()
55 grad = grad_op(net)(x)
76 class Net(nn.Cell): class
83 net = Net()
84 expect_output = net(x).asnumpy()
[all …]
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| /third_party/mindspore/mindspore-src/source/tests/ut/python/parameter_feature/ |
| D | test_var_grad.py | 48 net = AddNet()
49 _ = grad_all_with_sens(net, net.trainable_params())(x, y, sens)
53 def __init__(self, net): argument
59 self.net = net
62 return self.net(*args) * self.w + self.b
108 def __init__(self, net): argument
110 self.weights = ParameterTuple(net.trainable_params())
111 self.net = net
114 return grad_by_list_with_sens(self.net, self.weights)(*inputs)
119 net = VarNet(SecondNet())
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| D | test_parameter.py | 50 net = NetOut()
51 assert np.all(net(tensor1, tensor2).asnumpy() == tensor1.asnumpy())
59 self.net = SecondNet()
62 c = self.net(22, 33, x, y, z, 2, 3, 4, 5, key1=10, key2=20, key3=30, key4=40)
74 net = FirstNet()
75 net()
83 self.net = SecondNet()
86 c = self.net(22, 33, x, y, z, 2, 3, 4, 5, key1=10, key2=20, key3=30, key4=40)
99 net = FirstNet()
100 net(x, x, x)
[all …]
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| /third_party/mindspore/mindspore-src/source/tests/ut/python/parallel/ |
| D | test_neighborexchangev2.py | 29 def compile_net(net, x1, x2): argument
31 optimizer = Momentum(net.trainable_params(), learning_rate=0.1, momentum=0.9)
32 train_net = TrainOneStepCell(net, optimizer)
45 class Net(nn.Cell): class
47 super(Net, self).__init__()
60 net = Net()
61 compile_net(net, _x1, _x2)
72 class Net(nn.Cell): class
74 super(Net, self).__init__()
87 net = Net()
[all …]
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| D | test_neighborexchange.py | 36 def compile_net(net): argument
38 optimizer = Momentum(net.trainable_params(), learning_rate=0.1, momentum=0.9)
39 train_net = TrainOneStepCell(net, optimizer)
68 net = MatMulNet(_w1)
69 compile_net(net)
95 net = MatMulNet2(_w1)
96 compile_net(net)
107 class Net(nn.Cell): class
109 super(Net, self).__init__()
117 net = Net()
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| D | test_conv2d.py | 30 class Net(Cell): class
59 def compile_net(net, input_x=_x): argument
60 optimizer = Momentum(net.trainable_params(), learning_rate=0.1, momentum=0.9)
61 train_net = TrainOneStepCell(net, optimizer)
76 …net = Net(_w1, out_channel=8, kernel_size=2, pad_mode="same", stride=1, strategy1=strategy1, strat…
77 compile_net(net)
89 net = Net(_w5, out_channel=8, kernel_size=4, pad_mode="pad", stride=5, pad=(3, 0, 3, 0),
92 compile_net(net, _x3)
104 net = Net(_w2, out_channel=8, kernel_size=3, pad_mode="pad", stride=1, pad=(3, 3, 3, 3),
106 compile_net(net, _x3)
[all …]
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| /third_party/mindspore/mindspore-src/source/tests/ut/python/nn/optim/ |
| D | test_adafactor.py | 29 class Net(nn.Cell): class
30 """ Net definition """
33 super(Net, self).__init__()
72 net = Net()
73 net.set_train()
76 …optimizer = AdaFactor(net.trainable_params(), learning_rate=0.1, weight_decay=0.9, relative_step=F…
78 net_with_loss = WithLossCell(net, loss)
87 net = Net()
88 net.set_train()
91 optimizer = AdaFactor(net.trainable_params(), learning_rate=None, weight_decay=0.9)
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| D | test_adam.py | 30 class Net(nn.Cell): class
31 """ Net definition """
34 super(Net, self).__init__()
69 net = NetWithoutWeight()
70 net.set_train()
72 AdamWeightDecay(net.trainable_params(), learning_rate=0.1)
79 net = Net()
80 net.set_train()
83 optimizer = AdamWeightDecay(net.trainable_params(), learning_rate=0.1)
85 net_with_loss = WithLossCell(net, loss)
[all …]
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| /third_party/mindspore/mindspore-src/source/tests/st/mutable/ |
| D | test_mutable_in_graph.py | 86 class Net(nn.Cell): class
88 super(Net, self).__init__()
99 net = Net()
100 output = net(x, y)
117 class Net(nn.Cell): class
119 super(Net, self).__init__()
130 net = Net()
131 output = net(x, y)
145 class Net(nn.Cell): class
147 super(Net, self).__init__()
[all …]
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| /third_party/mindspore/mindspore-src/source/tests/ut/python/ops/ |
| D | test_control_ops.py | 39 class Net(nn.Cell): class
42 super(Net, self).__init__()
62 net = Net()
63 output = net(x, y)
78 class Net(nn.Cell): class
81 super(Net, self).__init__()
101 net = Net()
102 output = net(x, y)
107 class Net(nn.Cell): class
110 super(Net, self).__init__()
[all …]
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| /third_party/mindspore/mindspore-src/source/tests/st/ops/ |
| D | test_constexpr_modfied.py | 34 class Net(nn.Cell): class
36 super(Net, self).__init__()
45 net = Net()
46 output = net(x)
62 class Net(nn.Cell): class
64 super(Net, self).__init__()
74 net = Net()
75 output = net(input_x1, input_x2)
90 class Net(nn.Cell): class
92 super(Net, self).__init__()
[all …]
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| /third_party/mindspore/mindspore-src/source/tests/ut/python/graph_syntax/ |
| D | test_jit_class.py | 37 class Net(nn.Cell): class
39 super(Net, self).__init__()
46 net = Net()
47 out = net()
62 class Net(nn.Cell): class
63 def __init__(self, net): argument
64 super(Net, self).__init__()
65 self.inner_net = net()
71 net = Net(InnerNet)
72 out = net()
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| /third_party/rust/crates/rustix/tests/net/ |
| D | connect_bind_send.rs | 1 use rustix::net::{
5 use std::net::{IpAddr, Ipv4Addr, SocketAddr};
13 rustix::net::socket(AddressFamily::INET, SocketType::STREAM, Protocol::default())?; in net_v4_connect_any()
14 rustix::net::bind(&listener, &addr).expect("bind"); in net_v4_connect_any()
15 rustix::net::listen(&listener, 1).expect("listen"); in net_v4_connect_any()
17 let local_addr = rustix::net::getsockname(&listener)?; in net_v4_connect_any()
18 let sender = rustix::net::socket(AddressFamily::INET, SocketType::STREAM, Protocol::default())?; in net_v4_connect_any()
19 rustix::net::connect_any(&sender, &local_addr).expect("connect"); in net_v4_connect_any()
21 let n = rustix::net::send(&sender, request, SendFlags::empty()).expect("send"); in net_v4_connect_any()
27 let accepted = rustix::net::accept(&listener).expect("accept"); in net_v4_connect_any()
[all …]
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| /third_party/mindspore/mindspore-src/source/tests/ut/python/nn/ |
| D | test_conv.py | 24 class Net(nn.Cell): class
25 """ Net definition """
39 super(Net, self).__init__()
58 net = Net(3, 64, 3, bias_init='zeros')
60 net(input_data)
64 net = Net(3, 64, 4, has_bias=False, weight_init='normal')
66 net(input_data)
70 net = Net(3, 64, (3, 5), has_bias=False, weight_init='normal')
72 net(input_data)
76 net = Net(3, 64, (3, 5), pad_mode="same", padding=0, has_bias=False, weight_init='normal')
[all …]
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| /third_party/mindspore/mindspore-src/source/tests/st/ops/ascend/test_aicpu_ops/ |
| D | test_squeeze.py | 25 class Net(nn.Cell): class
27 super(Net, self).__init__()
36 net = Net()
37 output = net(Tensor(x))
44 net = Net()
45 output = net(Tensor(x))
52 net = Net()
53 output = net(Tensor(x))
60 net = Net()
61 output = net(Tensor(x))
[all …]
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| D | test_is_finite.py | 25 class Net(nn.Cell): class
27 super(Net, self).__init__()
36 net = Net()
37 output = net(Tensor(x))
44 net = Net()
45 output = net(Tensor(x))
52 net = Net()
53 output = net(Tensor(x))
60 net = Net()
61 output = net(Tensor(x))
[all …]
|
| /third_party/mindspore/mindspore-src/source/tests/st/gradient/ |
| D | test_dict_grad_graph.py | 39 class Net(nn.Cell): class
41 super(Net, self).__init__()
49 def __init__(self, net): argument
51 self.net = net
55 grad_func = self.grad_op(self.net)
59 net = Net()
60 grad_net = GradNetWrtX(net)
80 class Net(nn.Cell): class
82 super(Net, self).__init__()
92 def __init__(self, net): argument
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| /third_party/mindspore/mindspore-src/source/tests/st/pi_jit/gradient/ |
| D | test_dict_grad_graph_pijit.py | 35 class Net(nn.Cell): class
37 super(Net, self).__init__()
46 def __init__(self, net): argument
48 self.net = net
52 grad_func = self.grad_op(self.net)
57 net = Net()
58 grad_net = GradNetWrtX(net)
76 class Net(nn.Cell): class
78 super(Net, self).__init__()
89 def __init__(self, net): argument
[all …]
|