| /third_party/skia/third_party/externals/swiftshader/third_party/astc-encoder/Source/ |
| D | astc_color_unquantize.cpp | 29 uint4* output0, in rgb_delta_unpack() argument
128 output0->x = r0e; in rgb_delta_unpack()
129 output0->y = g0e; in rgb_delta_unpack()
130 output0->z = b0e; in rgb_delta_unpack()
131 output0->w = 0xFF; in rgb_delta_unpack()
144 uint4* output0, in rgb_unpack() argument
162 output0->x = ri1b; in rgb_unpack()
163 output0->y = gi1b; in rgb_unpack()
164 output0->z = bi1b; in rgb_unpack()
165 output0->w = 255; in rgb_unpack()
[all …]
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| /third_party/mindspore/tests/st/ops/cpu/ |
| D | test_argminwithvalue_op.py | 46 output0, output1 = argmin_a0(Tensor(x))
50 assert np.all(output0.asnumpy() == expect0)
55 output0, output1 = argmin_a0k(Tensor(x))
59 assert np.all(output0.asnumpy() == expect0)
64 output0, output1 = argmin_a1(Tensor(x))
68 assert np.all(output0.asnumpy() == expect0)
73 output0, output1 = argmin_a1k(Tensor(x))
77 assert np.all(output0.asnumpy() == expect0)
91 output0, output1 = argmin_a0(Tensor(x))
95 assert np.all(output0.asnumpy() == expect0)
[all …]
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| /third_party/mindspore/mindspore/ccsrc/backend/kernel_compiler/cpu/nnacl/infer/control/ |
| D | tensorlist_setitem_infer.c | 47 TensorListC *output0 = (TensorListC *)(outputs[0]); in TensorListSetItemInferShape() local
48 output0->data_type_ = input0->data_type_; in TensorListSetItemInferShape()
49 output0->format_ = input0->format_; in TensorListSetItemInferShape()
50 output0->tensors_data_type_ = value_tensor->data_type_; in TensorListSetItemInferShape()
62 output0->max_elements_num_ = input0->max_elements_num_; in TensorListSetItemInferShape()
66 …ShapeSet(output0->element_shape_, &(output0->element_shape_size_), value_tensor->shape_, value_ten… in TensorListSetItemInferShape()
68 ShapeSet(output0->element_shape_, &(output0->element_shape_size_), input0->element_shape_, in TensorListSetItemInferShape()
88 output0->element_num_ = 1; in TensorListSetItemInferShape()
90 output0->element_num_ = input0->element_num_; in TensorListSetItemInferShape()
116 int ret = MallocTensorListData(output0, input0->tensors_data_type_, &out_shape); in TensorListSetItemInferShape()
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| /third_party/mindspore/tests/ut/cpp/python_input/gtest_input/pre_activate/ |
| D | layer_norm_beta_gamma_backprop_fusion_test.py | 42 output0 = Cast(tuple_getitem(layer, 0))
44 add = Add(output0, output1)
50 output0 = Cast(tuple_getitem(layer, 0))
52 add = Add(output0, output1)
58 output0 = Cast(layer)
59 return output0
64 output0 = tuple_getitem(layer, 0)
66 add = Add(output0, output1)
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| /third_party/mindspore/tests/st/ops/gpu/ |
| D | test_matrix_inverse_op.py | 47 output0 = matrix_inverse(x0)
48 diff0 = output0.asnumpy() - expect0
50 assert output0.shape == expect0.shape
54 output0 = matrix_inverse(x0)
55 diff0 = output0.asnumpy() - expect0
57 assert output0.shape == expect0.shape
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| D | test_reciprocal_op.py | 49 output0 = reciprocal(x0)
50 diff0 = output0.asnumpy() - expect0
52 assert output0.shape == expect0.shape
60 output0 = reciprocal(x0)
61 diff0 = output0.asnumpy() - expect0
63 assert output0.shape == expect0.shape
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| D | test_exp_op.py | 49 output0 = exp(x0)
50 diff0 = output0.asnumpy() - expect0
52 assert output0.shape == expect0.shape
60 output0 = exp(x0)
61 diff0 = output0.asnumpy() - expect0
63 assert output0.shape == expect0.shape
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| D | test_log_op.py | 49 output0 = log(x0)
51 diff0 = output0.asnumpy() - expect0
53 assert output0.shape == expect0.shape
60 output0 = log(x0)
62 diff0 = output0.asnumpy() - expect0
64 assert output0.shape == expect0.shape
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| D | test_neg_op.py | 46 output0 = neg_net(x0)
47 diff0 = output0.asnumpy() - expect0
49 assert output0.shape == expect0.shape
57 output0 = neg_net(x0)
58 diff0 = output0.asnumpy() - expect0
60 assert output0.shape == expect0.shape
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| D | test_oneslike_op.py | 50 output0 = ones_like(x0)
52 diff0 = output0.asnumpy() - expect0
55 assert output0.shape == expect0.shape
66 output0 = ones_like(x0)
68 diff0 = output0.asnumpy() - expect0
71 assert output0.shape == expect0.shape
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| D | test_sub_op.py | 81 output0 = sub_net(x0, y0)
86 diff0 = output0.asnumpy() - expect0
88 assert output0.shape == expect0.shape
104 output0 = sub_net(x0, y0)
109 diff0 = output0.asnumpy() - expect0
111 assert output0.shape == expect0.shape
129 output0 = d_sub_net(x0, y0)
133 diff0 = output0.asnumpy() - expect0
135 assert output0.shape == expect0.shape
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| /third_party/mindspore/mindspore/ccsrc/backend/kernel_compiler/cpu/nnacl/infer/string/ |
| D | custom_predict_infer.c | 28 TensorC *output0 = outputs[0]; in CustomPredictInferShape() local
32 output0->shape_size_ = 1; in CustomPredictInferShape()
33 output0->shape_[0] = param->output_num; in CustomPredictInferShape()
34 output0->data_type_ = kNumberTypeInt32; in CustomPredictInferShape()
35 output0->format_ = input->format_; in CustomPredictInferShape()
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| D | custom_extract_features_infer.c | 28 TensorC *output0 = outputs[0]; in CustomExtractFeaturesInferShape() local
31 output0->data_type_ = kNumberTypeInt32; in CustomExtractFeaturesInferShape()
32 output0->format_ = input->format_; in CustomExtractFeaturesInferShape()
42 output0->shape_size_ = 1; in CustomExtractFeaturesInferShape()
43 output0->shape_[0] = res; in CustomExtractFeaturesInferShape()
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| /third_party/mindspore/mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/ |
| D | batchnorm_fp32_tests.cc | 111 lite::Tensor output0(kNumberTypeFloat32, {1, 2, 2, 3}); in TEST_F() local
112 output0.set_data(output.data()); in TEST_F()
113 std::vector<lite::Tensor *> outputs_tensor = {&output0}; in TEST_F()
129 for (int i = 0; i < output0.ElementsNum(); i++) { in TEST_F()
133 ASSERT_EQ(0, CompareOutputData(output.data(), corr_out.data(), output0.ElementsNum(), 0.001)); in TEST_F()
140 output0.set_data(nullptr); in TEST_F()
165 lite::Tensor output0(kNumberTypeFloat32, {1, 1, 6, 2}); in TEST_F() local
166 output0.set_data(output.data()); in TEST_F()
167 std::vector<lite::Tensor *> outputs_tensor = {&output0}; in TEST_F()
183 for (int i = 0; i < output0.ElementsNum(); i++) { in TEST_F()
[all …]
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| /third_party/mindspore/mindspore/lite/src/runtime/kernel/arm/control/ |
| D | tensorlist_fromtensor.cc | 86 auto output0 = reinterpret_cast<lite::TensorList *>(output0_); in Run() local
87 CHECK_NULL_RETURN(output0); in Run()
88 if (dim0 != output0->ElementsNum()) { in Run()
89 …MS_LOG(ERROR) << "output0_->ElementsNum():" << output0->ElementsNum() << " must be equal to dim0:"… in Run()
102 auto out_ptr = output0->GetTensor(i); in Run()
115 output0->set_own_data(true); in Run()
116 output0->set_tensors_data_type(dtype_); in Run()
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| /third_party/mindspore/mindspore/ccsrc/backend/kernel_compiler/cpu/nnacl/fp32_grad/ |
| D | arithmetic_grad.c | 43 … const int *input1_dims, const int *dy_dims, float *output0, float *output1, int num_dims) { in MaximumByAxes() argument
61 output0[offset] = input0[offset] > input1[offset] ? dy[offset] : 0.; in MaximumByAxes()
65 memset(output0, 0, num_output0 * sizeof(float)); // zero output in MaximumByAxes()
86 output0[offset0] += input0[offset0] > input1[offset1] ? dy[yt_offset] : 0.; in MaximumByAxes()
93 … const int *input1_dims, const int *dy_dims, float *output0, float *output1, int num_dims) { in MinimumByAxes() argument
111 output0[offset] = input0[offset] < input1[offset] ? dy[offset] : 0.; in MinimumByAxes()
115 memset(output0, 0, num_output0 * sizeof(float)); // zero output in MinimumByAxes()
136 output0[offset0] += input0[offset0] < input1[offset1] ? dy[yt_offset] : 0.; in MinimumByAxes()
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| /third_party/mindspore/mindspore/ccsrc/backend/kernel_compiler/cpu/nnacl/fp16_grad/ |
| D | arithmetic_grad.c | 44 … const int *input1_dims, const int *dy_dims, float16_t *output0, float16_t *output1, in MaximumByAxesFp16() argument
63 output0[offset] = input0[offset] > input1[offset] ? dy[offset] : 0.; in MaximumByAxesFp16()
67 memset(output0, 0, num_output0 * sizeof(float16_t)); // zero output in MaximumByAxesFp16()
88 output0[offset0] += input0[offset0] > input1[offset1] ? dy[yt_offset] : 0.; in MaximumByAxesFp16()
95 … const int *input1_dims, const int *dy_dims, float16_t *output0, float16_t *output1, in MinimumByAxesFp16() argument
114 output0[offset] = input0[offset] < input1[offset] ? dy[offset] : 0.; in MinimumByAxesFp16()
118 memset(output0, 0, num_output0 * sizeof(float16_t)); // zero output in MinimumByAxesFp16()
139 output0[offset0] += input0[offset0] < input1[offset1] ? dy[yt_offset] : 0.; in MinimumByAxesFp16()
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| /third_party/mindspore/mindspore/ccsrc/backend/kernel_compiler/cpu/nnacl/fp32/ |
| D | transpose_fp32.c | 23 const int output0 = output_shape[0]; in TransposeDim2Fp32() local
25 for (int i = 0; i < output0; ++i) { in TransposeDim2Fp32()
41 const int output0 = output_shape[0]; in TransposeDim3Fp32() local
44 for (int i = 0; i < output0; ++i) { in TransposeDim3Fp32()
66 const int output0 = output_shape[0]; in TransposeDim4Fp32() local
71 for (int i = 0; i < output0; ++i) { in TransposeDim4Fp32()
100 const int output0 = output_shape[0]; in TransposeDim5Fp32() local
106 for (int i = 0; i < output0; ++i) { in TransposeDim5Fp32()
141 const int output0 = output_shape[0]; in TransposeDim6Fp32() local
148 for (int i = 0; i < output0; ++i) { in TransposeDim6Fp32()
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| D | unique_fp32.c | 28 void Unique(const float *input, int input_len, float *output0, int *output0_len, int *output1) { in Unique() argument
31 int idx = Find(output0, *output0_len, input[i]); in Unique()
35 output0[(*output0_len)++] = input[i]; in Unique()
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| /third_party/mindspore/mindspore/ccsrc/backend/kernel_compiler/cpu/nnacl/fp16/ |
| D | transpose_fp16.c | 25 const int output0 = output_shape[0]; in Fp16TransposeDim2() local
27 for (int i = 0; i < output0; ++i) { in Fp16TransposeDim2()
43 const int output0 = output_shape[0]; in Fp16TransposeDim3() local
46 for (int i = 0; i < output0; ++i) { in Fp16TransposeDim3()
68 const int output0 = output_shape[0]; in Fp16TransposeDim4() local
73 for (int i = 0; i < output0; ++i) { in Fp16TransposeDim4()
102 const int output0 = output_shape[0]; in Fp16TransposeDim5() local
108 for (int i = 0; i < output0; ++i) { in Fp16TransposeDim5()
143 const int output0 = output_shape[0]; in Fp16TransposeDim6() local
150 for (int i = 0; i < output0; ++i) { in Fp16TransposeDim6()
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| /third_party/mindspore/mindspore/ccsrc/backend/kernel_compiler/cpu/nnacl/int8/ |
| D | transpose_int8.c | 22 const int output0 = output_shape[0]; in TransposeDim2Int8() local
24 for (int i = 0; i < output0; ++i) { in TransposeDim2Int8()
41 const int output0 = output_shape[0]; in TransposeDim3Int8() local
44 for (int i = 0; i < output0; ++i) { in TransposeDim3Int8()
66 const int output0 = output_shape[0]; in TransposeDim4Int8() local
71 for (int i = 0; i < output0; ++i) { in TransposeDim4Int8()
100 const int output0 = output_shape[0]; in TransposeDim5Int8() local
106 for (int i = 0; i < output0; ++i) { in TransposeDim5Int8()
142 const int output0 = output_shape[0]; in TransposeDim6Int8() local
149 for (int i = 0; i < output0; ++i) { in TransposeDim6Int8()
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| /third_party/mindspore/mindspore/ccsrc/backend/kernel_compiler/cpu/nnacl/base/ |
| D | transpose_base.c | 25 …const int output0 = output_shape[0]; …
27 …for (int i = 0; i < output0; ++i) { …
44 …const int output0 = output_shape[0]; …
47 …for (int i = 0; i < output0; ++i) { …
70 …const int output0 = output_shape[0]; …
74 …for (int i = 0; i < output0; ++i) { …
104 …const int output0 = output_shape[0]; …
109 …for (int i = 0; i < output0; ++i) { …
145 …const int output0 = output_shape[0]; …
151 …for (int i = 0; i < output0; ++i) { …
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| /third_party/mindspore/mindspore/ccsrc/backend/kernel_compiler/cpu/nnacl/infer/ |
| D | dropout_infer.c | 28 TensorC *output0 = outputs[0]; in DropoutInferShape() local
29 SetDataTypeFormat(output0, input); in DropoutInferShape()
33 SetShapeTensor(output0, input); in DropoutInferShape()
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| D | unique_infer.c | 28 TensorC *output0 = outputs[0]; in UniqueInferShape() local
31 SetDataTypeFormat(output0, input); in UniqueInferShape()
37 SetShapeTensor(output0, input); in UniqueInferShape()
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| /third_party/mindspore/mindspore/lite/src/runtime/kernel/arm/fp32/ |
| D | unique_fp32.cc | 38 auto output0 = reinterpret_cast<float *>(out_tensors_.at(0)->MutableData()); in Run() local
39 CHECK_NULL_RETURN(output0); in Run()
44 Unique(input, in_tensors_.at(0)->ElementsNum(), output0, &output0_len, output1); in Run()
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