.. _op_ai_onnx_Tan: Tan === - **Domain**: ``ai.onnx`` - **Since version**: 22 Computes the Tan value of the input tensor element-wise. **Inputs** - **input** (*T*): Input tensor **Outputs** - **output** (*T*): The tangent of the input tensor computed element-wise **Type Constraints** - **T**: Constrain input and output types to float tensors. Allowed types: tensor(bfloat16), tensor(double), tensor(float), tensor(float16). Examples -------- **test_cc_tan** .. code-block:: text Node: Tan(x) -> (y) .. code-block:: text Inputs: x: shape=(2, 3), dtype=float32 [[-1. , -0.5 , 0. ], [ 0.25, 0.5 , 1. ]] Outputs: y: shape=(2, 3), dtype=float32 [[-1.5574077 , -0.5463025 , 0. ], [ 0.25534192, 0.5463025 , 1.5574077 ]] **test_tan** .. code-block:: text Node: Tan(x) -> (y) .. code-block:: text Inputs: x: shape=(3, 4, 5), dtype=float32 [[[ 1.4243481 , -0.61890423, -0.5907667 , 1.4329695 , 0.5837956 ], [-1.3854368 , 1.2791865 , 0.32735094, 0.6038593 , 0.24222691], [-0.89236253, -1.1303798 , -0.09180629, -0.12591071, -1.2615176 ], [-0.55638343, -0.747256 , -0.59118223, -0.9279915 , -0.73401135]], [[ 1.1054384 , -0.69560546, -2.1534553 , 0.11396561, -0.8268097 ], [ 1.2137318 , -0.22223468, 0.32949635, -0.21049212, 1.3518724 ], [ 0.01262847, 0.6841954 , -1.2623075 , 0.20052178, -1.1255072 ], [-0.6395738 , 1.5355366 , -1.1466801 , -0.42676184, -0.74427605]], [[-1.5989435 , 2.3646672 , -1.0641551 , 0.90345967, -0.24993172], [-1.784248 , -0.47239977, 0.09873669, -0.36464727, 0.6651279 ], [-1.01641 , -0.39525023, 0.45574856, -0.3439513 , -0.5487247 ], [ 0.06280329, -0.14411083, -1.1603392 , 0.49200374, -0.16951095]]] Outputs: y: shape=(3, 4, 5), dtype=float32 [[[ 6.77946663e+00, -7.12256074e-01, -6.70666695e-01, 7.20947838e+00, 6.60606861e-01], [-5.33299160e+00, 3.33148074e+00, 3.39567691e-01, 6.89817429e-01, 2.47078270e-01], [-1.24058056e+00, -2.12183809e+00, -9.20650885e-02, -1.26580343e-01, -3.12957358e+00], [-6.21922791e-01, -9.26484048e-01, -6.71269238e-01, -1.33526921e+00, -9.02167559e-01]], [[ 1.99147725e+00, -8.34803820e-01, 1.51750743e+00, 1.14461586e-01, -1.08645260e+00], [ 2.68056846e+00, -2.25967020e-01, 3.41962218e-01, -2.13656977e-01, 4.49458885e+00], [ 1.26291458e-02, 8.15623939e-01, -3.13812089e+00, 2.03253314e-01, -2.09530258e+00], [-7.43881583e-01, 2.83492527e+01, -2.21474743e+00, -4.54707563e-01, -9.20961440e-01]], [[ 3.55181999e+01, -9.83196616e-01, -1.80194044e+00, 1.26915109e+00, -2.55269200e-01], [ 4.61353350e+00, -5.10988593e-01, 9.90588069e-02, -3.81717891e-01, 7.84354389e-01], [-1.61510015e+00, -4.17205602e-01, 4.90164816e-01, -3.58188868e-01, -6.11351907e-01], [ 6.28859922e-02, -1.45116821e-01, -2.29792738e+00, 5.35964727e-01, -1.71153396e-01]]] **test_tan_example** .. code-block:: text Node: Tan(x) -> (y) .. code-block:: text Inputs: x: shape=(3,), dtype=float32 [-1., 0., 1.] Outputs: y: shape=(3,), dtype=float32 [-1.5574077, 0. , 1.5574077] Differences with previous version (7) ------------------------------------- **SchemaDiff**: ``Tan`` (domain ``'ai.onnx'``) * old version: 7 * new version: 22 * breaking: no **Type constraints:** * changed 'T': added types: ['tensor(bfloat16)'] Version History --------------- - :doc:`Version 7 `