| /third_party/mindspore/tests/ut/python/parallel/ |
| D | test_broadcast_to.py | 26 def __init__(self, weight1, strategy1=None, strategy2=None, is_parameter=True): argument
32 self.weight1 = Parameter(weight1, "w1")
34 self.weight1 = weight1
37 out = self.broadcast(self.weight1)
43 def __init__(self, weight1, strategy1=None, strategy2=None, strategy3=None, is_parameter=True): argument
50 self.weight1 = Parameter(weight1, "w1")
52 self.weight1 = weight1
57 out = self.mul(out, self.weight1)
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| D | test_neighborexchange.py | 48 def __init__(self, weight1): argument
55 self.weight1 = Parameter(weight1, "w1")
59 out = self.mul(out, self.weight1)
76 def __init__(self, weight1): argument
82 self.weight1 = Parameter(weight1, "w1")
86 out = self.mul(out, self.weight1)
169 def __init__(self, weight1): argument
175 self.weight1 = Parameter(weight1, "w1")
179 out = self.mul(out, self.weight1)
197 def __init__(self, weight1): argument
[all …]
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| D | test_pack.py | 27 def __init__(self, weight1, weight2, axis=0, strategy1=None, strategy2=None, is_parameter=True): argument
32 self.weight1 = Parameter(weight1, "w1")
34 self.weight1 = weight1
38 out = self.pack([self.weight1, self.weight2])
44 def __init__(self, weight1, weight2, axis=0, strategy1=None, strategy2=None): argument
48 self.weight1 = Parameter(weight1, "w1")
52 out = self.mul(x, self.weight1)
58 …def __init__(self, weight1, weight2, weight3, axis=0, strategy1=None, strategy2=None, is_parameter… argument
63 self.weight1 = Parameter(weight1, "w1")
65 self.weight1 = weight1
[all …]
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| D | test_auto_parallel_parameter_cast.py | 48 …self.weight1 = Parameter(Tensor(np.ones([64, 64]).astype(np.float16) * 0.01), "w", requires_grad=T…
53 m1_result = self.matmul1(x, self.cast1(self.weight1, mstype.float32))
54 m2_result = self.matmul2(y, self.cast2(self.weight1, mstype.float32))
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| D | test_strategy_checkpoint.py | 60 self.weight1 = Parameter(Tensor(np.ones([32, 64]), dtype=ms.float32), name="weight1")
68 out = self.matmul1(x1, self.weight1)
124 self.weight1 = Parameter(Tensor(np.ones([32, 64]), dtype=ms.float32), name="weight1")
131 out = self.matmul1(x1, self.weight1)
188 self.weight1 = Parameter(Tensor(np.ones([32, 64]), dtype=ms.float32), name="weight1")
196 out = self.matmul1(x1, self.weight1)
245 self.weight1 = Parameter(Tensor(np.ones([32, 64]), dtype=ms.float32), name="weight1")
252 out = self.matmul1(x1, self.weight1)
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| D | test_auto_parallel_rhombus.py | 91 …self.weight1 = Parameter(Tensor(np.ones([128, 128]).astype(np.float32) * 0.01), "w", requires_grad…
95 mm1_out = self.matmul1(x, self.weight1)
122 …self.weight1 = Parameter(Tensor(np.ones([128, 128]).astype(np.float32) * 0.01), "w", requires_grad…
126 mm1_out = self.matmul1(x, self.weight1)
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| D | test_optimizer.py | 34 self.weight1 = Parameter(Tensor(weight_init1), "loss_weight1", layerwise_parallel=True)
41 x = self.fc(x, self.weight1)
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| /third_party/ffmpeg/libavcodec/mips/ |
| D | hevc_mc_biw_msa.c | 90 int32_t weight1, in hevc_biwgt_copy_4w_msa() argument
107 weight = weight0 | (weight1 << 16); in hevc_biwgt_copy_4w_msa()
179 int32_t weight1, in hevc_biwgt_copy_6w_msa() argument
196 weight = weight0 | (weight1 << 16); in hevc_biwgt_copy_6w_msa()
233 int32_t weight1, in hevc_biwgt_copy_8w_msa() argument
249 weight = weight0 | (weight1 << 16); in hevc_biwgt_copy_8w_msa()
321 int32_t weight1, in hevc_biwgt_copy_12w_msa() argument
337 weight = weight0 | (weight1 << 16); in hevc_biwgt_copy_12w_msa()
380 int32_t weight1, in hevc_biwgt_copy_16w_msa() argument
396 weight = weight0 | (weight1 << 16); in hevc_biwgt_copy_16w_msa()
[all …]
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| /third_party/mindspore/tests/st/dynamic_shape/ |
| D | test_ftrl.py | 30 self.weight1 = Parameter(Tensor(np.ones([3, 1, 2]).astype(np.float32)), name="weight1")
36 return self.gather(self.weight1, indices, self.axis) + self.weight2
52 np.allclose(net.weight1.asnumpy(), np.array([[[0.7884067, 0.7884067]],
73 np.allclose(net.weight1.asnumpy(), np.array([[[0.9, 0.9]], [[0.9, 0.9]], [[1.0, 1.0]]]))
92 np.allclose(net.weight1.asnumpy(), np.array([[[0.9, 0.9]], [[0.9, 0.9]], [[1.0, 1.0]]]))
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| /third_party/mindspore/tests/st/pynative/dynamic_shape/ |
| D | test_pynative_ftrl.py | 30 self.weight1 = Parameter(Tensor(np.ones([3, 1, 2]).astype(np.float32)), name="weight1")
36 return self.gather(self.weight1, indices, self.axis) + self.weight2
52 np.allclose(net.weight1.asnumpy(), np.array([[[0.7884067, 0.7884067]],
73 np.allclose(net.weight1.asnumpy(), np.array([[[0.9, 0.9]], [[0.9, 0.9]], [[1.0, 1.0]]]))
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| /third_party/skia/third_party/externals/dng_sdk/source/ |
| D | dng_hue_sat_map.cpp | 263 real64 weight1) in Interpolate() argument
266 if (weight1 >= 1.0) in Interpolate()
282 if (weight1 <= 0.0) in Interpolate()
331 real32 w1 = (real32) weight1; in Interpolate()
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| D | dng_hue_sat_map.h | 228 real64 weight1);
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| /third_party/mindspore/tests/st/nccl/ |
| D | test_nccl_lenet.py | 42 weight1 = Tensor(np.ones([6, 3, 5, 5]).astype(np.float32) * 0.01)
44 … self.conv1 = nn.Conv2d(3, 6, (5, 5), weight_init=weight1, stride=1, padding=0, pad_mode='valid')
49 weight1 = Tensor(np.ones([120, 400]).astype(np.float32) * 0.01)
50 self.fc1 = nn.Dense(400, 120, weight_init=weight1)
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| /third_party/pixman/pixman/ |
| D | pixman-inlines.h | 954 int weight1, weight2; \
970 weight1 = BILINEAR_INTERPOLATION_RANGE - weight2; \
976 weight1 = weight2 = BILINEAR_INTERPOLATION_RANGE / 2; \
994 buf1, buf2, left_pad, weight1, weight2, 0, 0, 0, FALSE); \
1002 src1, src2, width, weight1, weight2, vx, unit_x, 0, FALSE); \
1012 buf1, buf2, right_pad, weight1, weight2, 0, 0, 0, FALSE); \
1023 weight1 = 0; \
1028 weight1 = 0; \
1049 buf1, buf2, left_pad, weight1, weight2, 0, 0, 0, TRUE); \
1061 buf1, buf2, left_tz, weight1, weight2, \
[all …]
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| /third_party/skia/third_party/externals/swiftshader/src/Shader/ |
| D | VertexPipeline.cpp | 88 Float4 weight1; in transformBlend() local
95 case 3: weight1 = v[BlendWeight].y; in transformBlend()
107 weight1 = Float4(1.0f) - weight0; in transformBlend()
115 dst.x = pos0.x * weight0 + pos1.x * weight1; // FIXME: Vector4f operators in transformBlend()
116 dst.y = pos0.y * weight0 + pos1.y * weight1; in transformBlend()
117 dst.z = pos0.z * weight0 + pos1.z * weight1; in transformBlend()
118 dst.w = pos0.w * weight0 + pos1.w * weight1; in transformBlend()
122 weight2 = Float4(1.0f) - (weight0 + weight1); in transformBlend()
132 dst.x = pos0.x * weight0 + pos1.x * weight1 + pos2.x * weight2; in transformBlend()
133 dst.y = pos0.y * weight0 + pos1.y * weight1 + pos2.y * weight2; in transformBlend()
[all …]
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| /third_party/mindspore/tests/st/networks/models/ |
| D | lenet.py | 26 weight1 = Tensor(np.ones([6, 3, 5, 5]).astype(np.float32) * 0.01)
28 … self.conv1 = nn.Conv2d(3, 6, (5, 5), weight_init=weight1, stride=1, padding=0, pad_mode='valid')
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| /third_party/mindspore/mindspore/lite/src/runtime/kernel/opencl/cl/ |
| D | winograd.cl | 150 FLT16 weight0 = weight_ptr[0], weight1 = weight_ptr[1];
163 out10 += in0.x * weight1.s0123;
164 out10 += in0.y * weight1.s4567;
165 out10 += in0.z * weight1.s89ab;
166 out10 += in0.w * weight1.scdef;
168 out11 += in1.x * weight1.s0123;
169 out11 += in1.y * weight1.s4567;
170 out11 += in1.z * weight1.s89ab;
171 out11 += in1.w * weight1.scdef;
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| D | fullconnection.cl | 71 FLT4 weight1 = READ_IMAGE(weight, smp_zero, (int2)(i, gidx * 4 + 1));
72 result.y += dot(v, weight1);
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| /third_party/mindspore/tests/ut/python/nn/optim/ |
| D | test_ftrl.py | 50 self.weight1 = Parameter(Tensor(np.ones([3, 1, 2]).astype(np.float32)), name="weight1")
56 return self.gather(self.weight1, indices, self.axis) + self.weight2
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| D | test_proximal_ada_grad.py | 50 self.weight1 = Parameter(Tensor(np.ones([3, 1, 2]).astype(np.float32)), name="weight1")
56 return self.gather(self.weight1, indices, self.axis) + self.weight2
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| D | test_adam.py | 61 self.weight1 = Parameter(Tensor(np.ones([3, 1, 2]).astype(np.float32)), name="weight1")
67 return self.gather(self.weight1, indices, self.axis) + self.weight2
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| /third_party/mindspore/tests/ut/cpp/pipeline/static_analysis/ |
| D | data_test.cc | 116 tensor::TensorPtr weight1 = std::make_shared<tensor::Tensor>(kNumberTypeInt64, weight1_dims); in TEST_F() local
119 AbstractBasePtr abstract_weight1 = FromValue(weight1, true); in TEST_F()
125 std::vector<ValuePtr> vec({weight1, weight2}); in TEST_F()
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| /third_party/mindspore/tests/ut/python/transform/ |
| D | test_transform.py | 125 weight1 = Tensor(np.ones([6, 1, 5, 5]).astype(np.float32) * 0.01)
127 … self.conv1 = nn.Conv2d(1, 6, (5, 5), weight_init=weight1, stride=1, padding=0, pad_mode='valid')
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| /third_party/ffmpeg/libavcodec/ |
| D | rv34.h | 111 int weight1, weight2; ///< B-frame distance fractions (0.14) used in motion compensation member
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| /third_party/mindspore/tests/ut/python/optimizer/ |
| D | test_auto_grad.py | 187 self.weight1 = Parameter(Tensor(np.array([1.0], dtype=np.float32)), name="weight1")
193 out = out + self.weight1 * self.weight2
195 out = out + self.weight1
224 self.weight1 = Parameter(Tensor(np.array([1.0], dtype=np.float32)), name="weight1")
230 out = inner_add(x, y) + self.weight1
|