| /third_party/mindspore/tests/ut/python/pynative_mode/nn/ |
| D | test_dense.py | 28 dense = nn.Dense(3, 2, weight)
29 assert dense.activation is None
32 output = dense(input_data)
39 dense = nn.Dense(3, 2, bias_init=bias)
42 output = dense(input_data)
50 dense = nn.Dense(3, 2, weight, bias)
53 output = dense(input_data)
60 dense = nn.Dense(3, 2, weight, has_bias=False)
63 output = dense(input_data)
74 dense = nn.Dense(1, 1, activation='relu')
[all …]
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| /third_party/mindspore/tests/st/ops/cpu/ |
| D | test_sparse_tensor_dense_matmul_op.py | 32 def construct(self, indices, values, dens_shape, dense): argument
33 return self.matmul(indices, values, dens_shape, dense)
42 def construct(self, indices, values, dens_shape, dense): argument
43 return self.grad(self.network)(indices, values, dens_shape, dense)
65 dense = Tensor(dense_np)
66 out_ms = sparse_dense_matmul_net(indices, values, dense_shape, dense)
71 grad_ms = grad_net(indices, values, dense_shape, dense)
94 dense = Tensor(dense_np)
95 out_ms = sparse_dense_matmul_net(indices, values, dense_shape, dense)
101 grad_ms = grad_net(indices, values, dense_shape, dense)
[all …]
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| D | test_time_distributed_op.py | 71 dense = nn.Dense(10, 6)
72 output_expect = dense(Tensor(inputs, mindspore.float32)).asnumpy()
74 time_distributed = TestTimeDistributed(dense, time_axis=1, reshape_with_axis=0)
87 dense = nn.Dense(10, 6)
88 output_expect = dense(Tensor(inputs, mindspore.float32)).asnumpy()
90 time_distributed = TestTimeDistributed(dense, time_axis=1, reshape_with_axis=0)
102 dense = nn.Dense(10, 6)
103 output_expect = dense(Tensor(inputs, mindspore.float32)).asnumpy()
105 time_distributed = TestTimeDistributed(dense, time_axis=0, reshape_with_axis=1)
177 dense = nn.Dense(10, 6)
[all …]
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| /third_party/mindspore/tests/ut/python/nn/ |
| D | test_dense.py | 34 dense = nn.Dense(1, 1, activation='relu')
35 assert isinstance(dense.activation, nn.ReLU)
38 dense(input_data)
43 dense = nn.Dense(1, 1, activation=nn.ReLU())
44 assert isinstance(dense.activation, nn.ReLU)
47 dense(input_data)
52 dense = nn.Dense(1, 1, activation=P.ReLU())
53 assert isinstance(dense.activation, P.ReLU)
56 dense(input_data)
100 self.dense = nn.Dense(input_channels,
[all …]
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| /third_party/flutter/flutter/packages/flutter/lib/src/material/ |
| D | typography.dart | 19 /// [ScriptCategory.dense] scripts - for text styles that are smaller than the
33 dense,
48 /// and a geometry text theme, one of [englishLike], [dense],
76 /// dense: Typography.dense2018,
96 /// The default values for [englishLike], [dense], and [tall] are
103 TextTheme dense,
118 dense ??= dense2014;
120 return Typography._(black, white, englishLike, dense, tall);
123 const Typography._(this.black, this.white, this.englishLike, this.dense, this.tall)
127 assert(dense != null),
[all …]
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| /third_party/flutter/flutter/packages/flutter/test/material/ |
| D | list_tile_test.dart | 59 …Widget buildFrame({ bool dense = false, bool isTwoLine = false, bool isThreeLine = false, double t…
75 dense: dense,
133 await tester.pumpWidget(buildFrame(dense: true));
143 await tester.pumpWidget(buildFrame(isTwoLine: true, dense: true));
153 await tester.pumpWidget(buildFrame(isThreeLine: true, dense: true));
163 await tester.pumpWidget(buildFrame(dense: true, textScaleFactor: 4.0));
179 await tester.pumpWidget(buildFrame(isTwoLine: true, dense: true, textScaleFactor: 4.0));
189 await tester.pumpWidget(buildFrame(isThreeLine: true, dense: true, textScaleFactor: 4.0));
260 bool dense = false,
270 dense: dense,
[all …]
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| /third_party/mindspore/tests/ut/python/communication/ |
| D | test_comm.py | 50 self.dense = Dense(input_channel, out_channel)
55 x = self.dense(x)
65 self.dense = Dense(input_channel, out_channel)
70 x = self.dense(x)
79 self.dense = Dense(input_channel, out_channel)
90 x = self.dense(x)
100 self.dense = Dense(input_channel, out_channel)
105 x = self.dense(x)
115 self.dense = Dense(input_channel, out_channel)
120 x = self.dense(x)
[all …]
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| /third_party/ffmpeg/tests/fate/ |
| D | dnn.mak | 11 FATE_DNN += fate-dnn-layer-dense
12 fate-dnn-layer-dense: $(DNNTESTSDIR)/dnn-layer-dense-test$(EXESUF)
13 fate-dnn-layer-dense: CMD = run $(DNNTESTSDIR)/dnn-layer-dense-test$(EXESUF)
14 fate-dnn-layer-dense: CMP = null
|
| /third_party/mindspore/tests/st/ops/gpu/ |
| D | test_time_distributed_op.py | 71 dense = nn.Dense(10, 6)
72 output_expect = dense(Tensor(inputs, mindspore.float32)).asnumpy()
74 time_distributed = TestTimeDistributed(dense, time_axis=1, reshape_with_axis=0)
86 dense = nn.Dense(10, 6)
87 output_expect = dense(Tensor(inputs, mindspore.float32)).asnumpy()
89 time_distributed = TestTimeDistributed(dense, time_axis=0, reshape_with_axis=1)
161 dense = nn.Dense(10, 6)
162 output_expect = dense(Tensor(inputs, mindspore.float32)).asnumpy()
164 time_distributed = TestTimeDistributed(dense, time_axis=1)
|
| D | test_dense.py | 27 self.dense = nn.Dense(2048, 1001)
30 return self.dense(x)
|
| /third_party/flutter/flutter/examples/flutter_gallery/lib/demo/material/ |
| D | list_demo.dart | 65 dense: true,
76 dense: true,
87 dense: true,
98 dense: true,
113 dense: true,
128 dense: true,
143 dense: true,
186 dense: _dense,
|
| /third_party/mindspore/tests/st/fusion/ |
| D | test_conv_bn1_fusion.py | 69 self.dense = nn.Dense(output_channel, num_class)
78 output = self.dense(output)
97 self.dense = nn.Dense(output_channel, num_class)
105 output = self.dense(output)
123 self.dense = nn.Dense(output_channel, num_class)
130 output = self.dense(output)
|
| /third_party/mindspore/mindspore/ops/operations/ |
| D | sparse_ops.py | 153 def __infer__(self, indices, values, sparse_shape, dense): argument
156 args = {'values': values['dtype'], 'dense': dense['dtype']}
168 b_shape = dense['shape'][::-1] if self.adjoint_dt else dense['shape']
|
| /third_party/mindspore/mindspore/ops/_grad/ |
| D | grad_sparse.py | 69 def bprop(indices, values, dense_shape, dense, out, dout): argument
77 parts_b = F.gather(F.transpose(dense, perm) if adj_d else dense, rows if adj_s else cols, 0)
|
| /third_party/mindspore/mindspore/compression/quant/ |
| D | qat.py | 484 subcell_weight_para = subcell.dense.weight.data.asnumpy()
493 dense_inner = subcell.dense
500 dense_inner.weight = subcell.dense.weight
501 if subcell.dense.has_bias:
502 dense_inner.bias = subcell.dense.bias
503 subcell.dense = dense_inner
609 subcell_weight_para = cell.dense.weight.data.asnumpy()
610 if hasattr(cell.dense, 'gamma'):
611 scale_factor = (cell.dense.gamma.data.asnumpy() /
612 … np.sqrt(cell.dense.moving_variance.data.asnumpy() + self.eps))
[all …]
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| /third_party/mindspore/tests/st/quantization/mobilenetv2_quant/ |
| D | mobilenetV2.py | 259 m.dense.weight.set_data(
260 Tensor(np.random.normal(0, 0.01, m.dense.weight.data.shape).astype("float32")))
261 if m.dense.bias is not None:
262 m.dense.bias.set_data(
263 Tensor(np.zeros(m.dense.bias.data.shape, dtype="float32")))
|
| /third_party/boost/libs/numeric/odeint/doc/ |
| D | stepper_table.qbk | 20 …system] [5] [Yes (4)] [Yes] [Yes] [Standard method with error control and dense output, to be used…
29 …Dense output for __stepper and __error_stepper from above if they provide dense output functionali…
32 …tepper with step size and order control as well as dense output. Very good if high precision and d…
37 …r] [__implicit_system] [4] [Yes] [Yes] [No] [Controlled Rosenbrock 4 with dense output. Works only…
|
| /third_party/mindspore/mindspore/nn/sparse/ |
| D | sparse.py | 129 def construct(self, indices, values, sparse_shape, dense): argument
130 return self.sparse_dense_matmul(indices, values, sparse_shape, dense)
|
| /third_party/typescript/src/services/ |
| D | classifier2020.ts | 22 const dense = classifications.spans; constant
24 for (let i = 0; i < dense.length; i += 3) {
26 textSpan: createTextSpan(dense[i], dense[i + 1]),
27 classificationType: dense[i + 2]
|
| /third_party/mindspore/tests/ut/python/train/ |
| D | test_amp.py | 38 self.dense = nn.Dense(in_features, out_features)
42 output = self.dense(input_x)
50 self.dense = nn.Dense(in_features, out_features)
53 return self.dense(input_x)
|
| /third_party/mindspore/tests/ut/python/exec/ |
| D | test_train.py | 134 self.dense = nn.Dense(64, 12)
143 output = self.dense(output)
167 self.dense = nn.Dense(cin, cout)
173 output = self.dense(output)
|
| /third_party/mindspore/tests/ut/python/parallel/ |
| D | test_auto_parallel_inference.py | 28 self.dense = nn.Dense(input_ch, out_ch)
32 x = self.dense(x)
|
| /third_party/mindspore/tests/st/ops/ascend/ |
| D | test_dense.py | 28 self.dense = nn.Dense(2048, 1001)
32 return self.dense(x)
|
| D | test_dense_grad.py | 40 self.dense = nn.Dense(2048, 1001)
43 return self.dense(x)
|
| /third_party/boost/libs/numeric/odeint/examples/ |
| D | stepper_details.cpp | 178 … dense_output_runge_kutta< controlled_runge_kutta< runge_kutta_dopri5< state_type > > > dense; in main() local
179 dense.initialize( in , t , dt ); in main()
180 pair< double , double > times = dense.do_step( sys ); in main()
|