/third_party/mindspore/mindspore/ccsrc/minddata/dataset/kernels/image/ |
D | image_utils.h | 71 bool CheckTensorShape(const std::shared_ptr<Tensor> &tensor, const int &channel); 77 Status Flip(std::shared_ptr<Tensor> input, std::shared_ptr<Tensor> *output, int flip_code); 82 Status HorizontalFlip(std::shared_ptr<Tensor> input, std::shared_ptr<Tensor> *output); 87 Status VerticalFlip(std::shared_ptr<Tensor> input, std::shared_ptr<Tensor> *output); 98 Status Resize(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output, int32_t output… 108 Status Decode(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output); 110 Status DecodeCv(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output); 112 bool IsNonEmptyJPEG(const std::shared_ptr<Tensor> &input); 114 bool IsNonEmptyPNG(const std::shared_ptr<Tensor> &input); 118 Status JpegCropAndDecode(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output, int… [all …]
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D | lite_image_utils.h | 50 bool IsNonEmptyJPEG(const std::shared_ptr<Tensor> &input); 54 Status JpegCropAndDecode(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output, int… 64 Status Crop(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output, int x, int y, in… 72 Status Decode(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output); 78 Status GetJpegImageInfo(const std::shared_ptr<Tensor> &input, int *img_width, int *img_height); 85 Status Normalize(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output, std::vector… 97 Status Resize(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output, int32_t output… 114 Status RgbToBgr(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output); 120 Status RgbToGray(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output); 133 Status Pad(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output, const int32_t &pa… [all …]
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/third_party/mindspore/tests/ut/python/ops/ |
D | test_math_ops_check.py | 20 from mindspore import Tensor 34 …self.inputdata = Parameter(Tensor(np.zeros([1]).astype(np.bool_), mstype.bool_), name="assign_add1… 45 …self.inputdata = Parameter(Tensor(np.zeros([1]).astype(np.bool_), mstype.bool_), name="assign_sub1… 85 …'desc_inputs': [Tensor(np.ones([3, 5]).astype(np.float32)), Tensor(np.ones([3, 4]).astype(np.float… 91 'desc_inputs': [Tensor(np.ones([1]).astype(np.bool_), mstype.bool_)], 97 'desc_inputs': [Tensor(np.ones([1]).astype(np.bool_), mstype.bool_)], 104 'desc_inputs': [Tensor(np.ones([2, 3, 5]).astype(np.float32))], 110 'desc_inputs': [Tensor(np.ones([2, 3, 5]).astype(np.float32))], 117 'desc_inputs': [Tensor(np.ones([2, 3, 5]).astype(np.float32))], 123 'desc_inputs': [Tensor(np.ones([2, 3, 5]).astype(np.float32))], [all …]
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D | test_nn_ops_check.py | 19 from mindspore import Tensor 67 'desc_inputs': [Tensor(np.ones([3, 4]).astype(np.float32))], 72 'desc_inputs': [Tensor(np.ones([3, 4]).astype(np.float32))], 83 'desc_inputs': [Tensor(np.ones([3, 4]).astype(np.float32))], 94 'desc_inputs': [Tensor(np.ones([3, 4]).astype(np.bool_))], 105 'desc_inputs': [Tensor(np.ones([3, 4]).astype(np.int32))], 116 'desc_inputs': [Tensor(np.ones([3, 4]).astype(np.int32))], 127 'desc_inputs': [Tensor(np.ones([3, 4]).astype(np.int32))], 144 …'desc_inputs': [Tensor(np.ones([5, 3]).astype(np.float32)), Tensor(np.ones([5, 3]).astype(np.float… 145 Tensor(np.ones([5, 3]).astype(np.float32)), None, None], [all …]
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D | test_tensor_slice.py | 19 from mindspore import Tensor, Parameter 32 self.tensor_ret0 = Tensor(np.ones([1, 2, 2], np.int32)) 33 self.tensor_ret1 = Tensor(np.ones([4, 7, 4], np.int32)) 34 self.tensor_ret2 = Tensor(np.ones([6, 8, 10], np.int32)) 35 self.tensor_ret3 = Tensor(np.ones([3, 8, 10], np.int32)) 48 self.tensor_ret0 = Tensor(np.ones([2, 7, 8], np.int32)) 49 self.tensor_ret1 = Tensor(np.ones([6, 7, 8, 9], np.int32)) 50 self.tensor_ret2 = Tensor(np.ones([1, 6, 7, 8, 9], np.int32)) 63 self.tensor_ret0 = Tensor(np.ones([2, 4, 1], np.int32)) 64 self.tensor_ret1 = Tensor(np.ones([3, 4], np.int32)) [all …]
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D | test_ops.py | 23 from mindspore import Tensor 78 x = Tensor(3, mstype.float32) 79 y = Tensor(1, mstype.float32) 92 … self.input_x = Parameter(Tensor(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]).astype(np.float32))) 419 self.ref = Parameter(Tensor(np.ones(ref_shape, dtype)), name="ref") 432 … self.ref = Parameter(Tensor(np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]], dtype)), name="ref") 445 … self.ref = Parameter(Tensor(np.array([[-1.0, 2.0, 3.0], [-4.0, 1.0, 6.0]], dtype)), name="ref") 458 self.ref = Parameter(Tensor(np.ones(ref_shape, dtype)), name="ref") 471 self.ref = Parameter(Tensor(np.ones(ref_shape, dtype)), name="ref") 484 self.ref = Parameter(Tensor(np.ones(ref_shape, dtype)), name="ref") [all …]
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D | test_ops_check.py | 22 from mindspore import Tensor 65 inp = Tensor(np.ones([1, 1, 32, 32]).astype(np.float32)) 84 inp = Tensor(np.ones([1, 1, 32, 32]).astype(np.float32)) 126 'desc_inputs': [Tensor(np.ones(shape=[1, 1, 6, 5]).astype(np.float32))]}), 129 'desc_inputs': [Tensor(np.ones(shape=[1, 1, 6, 5]).astype(np.float32))]}), 132 'desc_inputs': [Tensor(np.ones(shape=[1, 1, 6, 5]).astype(np.float32))]}), 135 'desc_inputs': [Tensor(np.ones(shape=[1, 1, 6, 5]).astype(np.float32))]}), 137 … 'block': nn.Conv2d(1, 6, 5, has_bias=True, bias_init=Tensor(np.ones([6]).astype(np.float32))), 138 'desc_inputs': [Tensor(np.ones(shape=[1, 1, 6, 5]).astype(np.float32))]}), 141 'desc_inputs': [Tensor(np.ones(shape=[1, 1, 6, 5]).astype(np.float32))]}), [all …]
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D | test_tuple_slice.py | 19 from mindspore import Tensor 34 self.index_0 = Tensor(3) 35 self.index_1 = Tensor([5]) 36 self.index_3 = Tensor([True]) 57 self.step = Tensor([-1]) 58 self.index_0 = Tensor(-6) 101 self.index_0 = Tensor([2, 3]) 112 self.index_0 = Tensor([2.1]) 121 'desc_inputs': [(Tensor(np.ones([2, 3, 4], np.int32)), 122 Tensor(np.zeros([2, 3, 4], np.int32)), [all …]
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/third_party/mindspore/mindspore/ccsrc/minddata/dataset/kernels/data/ |
D | data_utils.h | 42 Status OneHotEncoding(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output, dsize_… 44 Status OneHotEncodingUnsigned(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output, 47 Status OneHotEncodingSigned(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output, … 55 Status Fill(const std::shared_ptr<Tensor> input, std::shared_ptr<Tensor> *output, std::shared_ptr<T… 65 void CastFrom(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output); 68 void Cast(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output); 70 Status ToFloat16(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output); 72 Status TypeCast(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output, const DataTy… 81 Status PadEnd(const std::shared_ptr<Tensor> &src, std::shared_ptr<Tensor> *dst, const std::vector<d… 82 const std::shared_ptr<Tensor> &pad_val); [all …]
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/third_party/mindspore/tests/st/ops/gpu/ |
D | test_broadcast_op.py | 20 from mindspore.common.tensor import Tensor 36 output_ms = P.Minimum()(Tensor(x1_np), Tensor(x2_np)) 40 output_ms = P.Maximum()(Tensor(x1_np), Tensor(x2_np)) 44 output_ms = P.Greater()(Tensor(x1_np), Tensor(x2_np)) 47 output_ms = P.Greater()(Tensor(x1_np_int32), Tensor(x2_np_int32)) 51 output_ms = P.Less()(Tensor(x1_np), Tensor(x2_np)) 54 output_ms = P.Less()(Tensor(x1_np_int32), Tensor(x2_np_int32)) 58 output_ms = P.Pow()(Tensor(x1_np), Tensor(x2_np)) 62 output_ms = P.RealDiv()(Tensor(x1_np), Tensor(x2_np)) 66 output_ms = P.Mul()(Tensor(x1_np), Tensor(x2_np)) [all …]
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D | test_range_op.py | 21 from mindspore import Tensor 41 ms_out = range_net(Tensor(1000.04, mstype.float32), 42 Tensor(1001.04, mstype.float32), 43 Tensor(0.01, mstype.float32)).asnumpy() 48 ms_out = range_net(Tensor(100, mstype.float32), 49 Tensor(101, mstype.float32), 50 Tensor(0.001, mstype.float32)).asnumpy() 55 ms_out = range_net(Tensor(1, mstype.float32), 56 Tensor(8000, mstype.float32), 57 Tensor(0.01, mstype.float32)).asnumpy() [all …]
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/third_party/mindspore/mindspore/explainer/ |
D | _operators.py | 51 _Idx = Union[int, mindspore.Tensor, Tuple[int, ...], Tuple[mindspore.Tensor, ...]] 54 Tensor = mindspore.Tensor variable 57 def absolute(inputs: Tensor) -> Tensor: argument 68 dtype: mindspore.dtype = None) -> Tensor: 71 nums = mindspore.Tensor(nums, dtype=dtype) 75 def argmax(inputs: Tensor, axis: int = -1, keep_dims: bool = False) -> Tensor: argument 83 return mindspore.Tensor(outputs, mindspore.int32) 86 def argmin(inputs: Tensor, axis: int = -1, keep_dims: bool = False) -> Tensor: argument 94 return mindspore.Tensor(outputs, mindspore.int32) 97 def argsort(inputs: Tensor, axis: int = -1, descending: bool = False) -> Tensor: argument [all …]
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/third_party/mindspore/tests/st/ops/cpu/ |
D | test_cast_op.py | 21 from mindspore.common.tensor import Tensor 41 tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.bool))) 42 tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float16))) 43 tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float32))) 44 tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float64))) 45 tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int8))) 46 tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int16))) 47 tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int32))) 48 tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int64))) 49 tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint8))) [all …]
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/third_party/mindspore/tests/ut/python/ir/ |
D | test_tensor.py | 27 from mindspore import Tensor, context 40 tensor_list = ms.Tensor(lst, ms.float32) 47 tensor_list = ms.Tensor(lst, ms.float32) 53 t1 = ms.Tensor(ndarr) 54 assert isinstance(t1, ms.Tensor) 57 t2 = ms.Tensor(np.zeros([1, 2, 3]), ms.float32) 58 assert isinstance(t2, ms.Tensor) 62 t3 = ms.Tensor(0.1) 63 assert isinstance(t3, ms.Tensor) 66 t4 = ms.Tensor(1) [all …]
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/third_party/mindspore/tests/ut/python/nn/ |
D | test_loss.py | 20 from mindspore import Tensor 26 input_data = Tensor(np.array([[1, 2, 3], [2, 3, 4]]).astype(np.float32)) 27 target_data = Tensor(np.array([[0, 2, 5], [3, 1, 1]]).astype(np.float32)) 33 input_data = Tensor(np.array([[1, 2, 3], [2, 3, 2]]).astype(np.float32)) 34 target_data = Tensor(np.array([[0, 0, 5], [1, 2, 3]]).astype(np.float32)) 43 logits = Tensor(np.random.randint(0, 9, [100, 10]).astype(np.float32)) 44 labels = Tensor(np.random.randint(0, 9, [100, 10]).astype(np.float32)) 52 logits = Tensor(np.random.randint(0, 9, [100, 10]).astype(np.float32)) 53 labels = Tensor(np.random.randint(0, 9, [100, 10]).astype(np.float32)) 61 inputs_data = Tensor(np.array([[0.1, 0.2, 0.3], [0.5, 0.7, 0.9]]).astype(np.float32)) [all …]
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D | test_transformer.py | 18 from mindspore import Tensor 34 encoder_input_value = Tensor(np.ones((2, 20, 64)), dtype.float32) 35 encoder_input_mask = Tensor(np.ones((2, 20, 20)), dtype.float16) 51 encoder_input_value = Tensor(np.ones((2, 20, 64)), dtype.float32) 52 encoder_input_mask = Tensor(np.ones((2, 20, 20)), dtype.float16) 67 encoder_input_value = Tensor(np.ones((2, 20, 64)), dtype.float32) 68 encoder_input_mask = Tensor(np.ones((2, 20, 20)), dtype.float16) 83 encoder_input_value = Tensor(np.ones((2, 20, 64)), dtype.float32) 84 encoder_input_mask = Tensor(np.ones((2, 20, 20)), dtype.float16) 98 encoder_input_value = Tensor(np.ones((2, 20, 64)), dtype.float32) [all …]
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/third_party/mindspore/mindspore/lite/test/ut/src/runtime/ |
D | runtime_pass_tests.cc | 24 extern void Nc4hw4PassAct(std::vector<kernel::LiteKernel *> *kernels, std::vector<Tensor *> *tensor… 33 void Nc4hw4PassConstruct(std::vector<kernel::LiteKernel *> *kernels, std::vector<lite::Tensor *> *t… in Nc4hw4PassConstruct() 37 lite::Tensor *conv_in_tensor = new lite::Tensor(kNumberTypeFloat32, {1, 1, 1, 1}, NHWC); in Nc4hw4PassConstruct() 39 lite::Tensor *conv_weight = new lite::Tensor(kNumberTypeFloat32, {1, 1, 1, 1}, NHWC); in Nc4hw4PassConstruct() 41 lite::Tensor *conv_out_tensor = new lite::Tensor(kNumberTypeFloat32, {1, 1, 1, 1}, NHWC); in Nc4hw4PassConstruct() 43 std::vector<lite::Tensor *> conv_in = {conv_in_tensor, conv_weight}; in Nc4hw4PassConstruct() 44 std::vector<lite::Tensor *> conv_out = {conv_out_tensor}; in Nc4hw4PassConstruct() 54 lite::Tensor *trans_param_tensor = new lite::Tensor(kNumberTypeFloat32, {1, 1, 1, 1}, NHWC); in Nc4hw4PassConstruct() 56 lite::Tensor *trans_out_tensor = new lite::Tensor(kNumberTypeFloat32, {1, 1, 1, 1}, NHWC); in Nc4hw4PassConstruct() 62 std::vector<lite::Tensor *> trans_in = {conv_out_tensor, trans_param_tensor}; in Nc4hw4PassConstruct() [all …]
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/third_party/mindspore/tests/ut/cpp/dataset/ |
D | fill_op_test.cc | 33 std::shared_ptr<Tensor> input; in TEST_F() 34 Tensor::CreateFromVector(labels, &input); in TEST_F() 36 std::shared_ptr<Tensor> fill_tensor; in TEST_F() 37 Tensor::CreateScalar<uint64_t>(4, &fill_tensor); in TEST_F() 39 std::shared_ptr<Tensor> output; in TEST_F() 44 std::shared_ptr<Tensor> expected; in TEST_F() 45 Tensor::CreateFromVector(out, &expected); in TEST_F() 60 std::shared_ptr<Tensor> input; in TEST_F() 61 Tensor::CreateFromVector(labels, &input); in TEST_F() 63 std::shared_ptr<Tensor> fill_tensor; in TEST_F() [all …]
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D | slice_op_test.cc | 33 std::shared_ptr<Tensor> input; in TEST_F() 34 Tensor::CreateFromVector(labels, &input); in TEST_F() 36 std::shared_ptr<Tensor> output; in TEST_F() 42 std::shared_ptr<Tensor> expected; in TEST_F() 43 Tensor::CreateFromVector(out, &expected); in TEST_F() 60 std::shared_ptr<Tensor> input; in TEST_F() 61 Tensor::CreateFromVector(labels, &input); in TEST_F() 63 std::shared_ptr<Tensor> output; in TEST_F() 69 std::shared_ptr<Tensor> expected; in TEST_F() 70 Tensor::CreateFromVector(out, &expected); in TEST_F() [all …]
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/third_party/mindspore/tests/syntax/simple_expression/ |
D | test_assignment_ops.py | 19 from mindspore import Tensor, Parameter 39 x = Tensor(np.ones([3, 3]).astype(np.bool_)) 40 y = Tensor(np.zeros([3, 3]).astype(np.bool_)) 50 x = Tensor(np.ones([3, 3]).astype(np.int8)) 51 y = Tensor(np.zeros([3, 3]).astype(np.int8)) 61 x = Tensor(np.ones([3, 3]).astype(np.uint8)) 62 y = Tensor(np.zeros([3, 3]).astype(np.uint8)) 72 x = Tensor(np.ones([3, 3]).astype(np.int16)) 73 y = Tensor(np.zeros([3, 3]).astype(np.int16)) 83 x = Tensor(np.ones([3, 3]).astype(np.uint16)) [all …]
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/third_party/mindspore/tests/ut/python/nn/gradient/ |
D | test_jvp_pynative.py | 21 from mindspore import Tensor 47 x = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32)) 48 v = Tensor(np.array([[1, 1], [1, 1]]).astype(np.float32)) 54 x = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32)) 55 v = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32)) 61 x = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32)) 62 v = Tensor(np.array([[1, 1], [1, 1]]).astype(np.float32)) 68 x = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32)) 69 v = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32)) 75 x = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32)) [all …]
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D | test_jvp_graph.py | 21 from mindspore import Tensor 48 x = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32)) 49 v = Tensor(np.array([[1, 1], [1, 1]]).astype(np.float32)) 55 x = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32)) 56 v = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32)) 62 x = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32)) 63 v = Tensor(np.array([[1, 1], [1, 1]]).astype(np.float32)) 69 x = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32)) 70 v = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32)) 76 x = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32)) [all …]
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/third_party/mindspore/tests/st/auto_monad/ |
D | test_effect_optimizer.py | 18 from mindspore import context, Tensor 45 var = Tensor(np.ones([3, 3, 3]).astype(np.float32)) 46 m = Tensor(np.ones([3, 3, 3]).astype(np.float32)) 47 v = Tensor(np.ones([3, 3, 3]).astype(np.float32)) 50 beta1_power = Tensor(0.9, mstype.float32) 51 beta2_power = Tensor(0.999, mstype.float32) 52 lr = Tensor(0.001, mstype.float32) 53 beta1 = Tensor(0.9, mstype.float32) 54 beta2 = Tensor(0.999, mstype.float32) 55 epsilon = Tensor(1e-8, mstype.float32) [all …]
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/third_party/mindspore/mindspore/lite/src/ |
D | lite_mindrt.h | 44 class LiteOpActor : public OpActor<lite::Tensor> { 46 …explicit LiteOpActor(kernel::LiteKernel *kernel) : OpActor<lite::Tensor>(kernel->name()), kernel_(… in LiteOpActor() 62 …void RunOpData(OpData<lite::Tensor> *input_data, OpContext<lite::Tensor> *context = nullptr) overr… 85 void SetOutputData(OpContext<Tensor> *context); 86 void AsyncOutput(OpContext<Tensor> *context); 94 std::vector<OpDataPtr<Tensor>> outputs_data_{}; 95 std::vector<Tensor *> inputs_data_{}; 96 …std::unordered_map<Tensor *, Tensor *> isolate_input_map_{}; /* <calculate-tensor, src-input-tens… 99 void ReplaceNodeInTensor(kernel::LiteKernel *kernel, Tensor *old_tensor, Tensor *new_tensor); 101 void MoveTensorInputData(Tensor *dst_tensor, Tensor *src_tensor); [all …]
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/third_party/mindspore/tests/st/gradient/ |
D | test_jvp_graph.py | 21 from mindspore import Tensor 51 x = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32)) 52 v = Tensor(np.array([[1, 1], [1, 1]]).astype(np.float32)) 54 expect_primal = Tensor(np.array([[1, 8], [27, 64]]).astype(np.float32)) 55 expect_grad = Tensor(np.array([[3, 12], [27, 48]]).astype(np.float32)) 65 x = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32)) 66 v = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32)) 68 expect_primal = Tensor(np.array([[1, 8], [27, 64]]).astype(np.float32)) 69 expect_grad = Tensor(np.array([[3, 24], [81, 192]]).astype(np.float32)) 79 x = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32)) [all …]
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