.. _op_ai_onnx_Erf: Erf === - **Domain**: ``ai.onnx`` - **Since version**: 13 Computes the Erf value of the input tensor element-wise. **Inputs** - **input** (*T*): Input tensor **Outputs** - **output** (*T*): The error function of the input tensor computed element-wise. It has the same shape and type of the input. **Type Constraints** - **T**: Constrain input and output types to float tensors. Allowed types: tensor(bfloat16), tensor(double), tensor(float), tensor(float16). Examples -------- **test_cc_erf** .. code-block:: text Node: Erf(x) -> (y) .. code-block:: text Inputs: x: shape=(2, 3), dtype=float32 [[-2. , -1. , 0. ], [ 0.5, 1. , 2. ]] Outputs: y: shape=(2, 3), dtype=float32 [[-0.9953223, -0.8427008, 0. ], [ 0.5204999, 0.8427008, 0.9953223]] **test_cc_erf_bfloat16** .. code-block:: text Node: Erf(x) -> (y) .. code-block:: text Inputs: x: shape=(2, 3), dtype=bfloat16 [[-2, -1, 0], [0.5, 1, 2]] Outputs: y: shape=(2, 3), dtype=bfloat16 [[-0.996094, -0.84375, 0], [0.519531, 0.84375, 0.996094]] **test_cc_erf_float16** .. code-block:: text Node: Erf(x) -> (y) .. code-block:: text Inputs: x: shape=(2, 3), dtype=float16 [[-2. , -1. , 0. ], [ 0.5, 1. , 2. ]] Outputs: y: shape=(2, 3), dtype=float16 [[-0.995 , -0.843 , 0. ], [ 0.5205, 0.843 , 0.995 ]] **test_erf** .. code-block:: text Node: Erf(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 [[[ 0.95602536, -0.6185691 , -0.59654707, 0.957289 , 0.5909756 ], [-0.94992274, 0.92955565, 0.3565956 , 0.6068873 , 0.26807094], [-0.793048 , -0.89009017, -0.103302 , -0.14132778, -0.9255853 ], [-0.5686274 , -0.7093878 , -0.5968777 , -0.81060743, -0.7007527 ]], [[ 0.88202405, -0.674754 , -0.9976767 , 0.12804183, -0.75771135], [ 0.91392505, -0.24669716, 0.3587689 , -0.23405321, 0.9441028 ], [ 0.01424895, 0.666755 , -0.92576665, 0.22326821, -0.88854957], [-0.63426644, 0.9701124 , -0.8951218 , -0.4538454 , -0.70745975]], [[-0.9762561 , 0.99917465, -0.8676612 , 0.7986395 , -0.276254 ], [-0.98837435, -0.49591374, 0.11105143, -0.39392844, 0.653107 ], [-0.84940153, -0.4238166 , 0.48076546, -0.373331 , -0.56225926], [ 0.07077286, -0.16149293, -0.89919585, 0.5134449 , -0.1894563 ]]] **test_erf_example** .. code-block:: text Node: Erf(x) -> (y) .. code-block:: text Inputs: x: shape=(3,), dtype=float32 [-1., 0., 1.] Outputs: y: shape=(3,), dtype=float32 [-0.8427008, 0. , 0.8427008] Differences with previous version (9) ------------------------------------- **SchemaDiff**: ``Erf`` (domain ``'ai.onnx'``) * old version: 9 * new version: 13 * breaking: **yes** **Breaking reasons:** * type constraint 'T' (changed): added types: ['tensor(bfloat16)']; removed types: ['tensor(int16)', 'tensor(int32)', 'tensor(int64)', 'tensor(int8)', 'tensor(uint16)', 'tensor(uint32)', 'tensor(uint64)', 'tensor(uint8)'] **Type constraints:** * [BREAKING] changed 'T': added types: ['tensor(bfloat16)']; removed types: ['tensor(int16)', 'tensor(int32)', 'tensor(int64)', 'tensor(int8)', 'tensor(uint16)', 'tensor(uint32)', 'tensor(uint64)', 'tensor(uint8)'] Version History --------------- - :doc:`Version 9 `