:nosearch: .. _op_ai_onnx_Resize-13: Resize - version 13 =================== This page documents version **13** of operator **Resize**. See :doc:`Resize` for the latest version (since version 19). - **Domain**: ``ai.onnx`` - **Since version**: 13 Resize the input tensor. In general, it calculates every value in the output tensor as a weighted average of neighborhood (a.k.a. sampling locations) in the input tensor. Each dimension value of the output tensor is: .. code-block:: text output_dimension = floor(input_dimension * (roi_end - roi_start) * scale) if input \"sizes\" is not specified. **Inputs** - **X** (*T1*): N-D tensor - **roi** (*T2*): 1-D tensor given as [start1, ..., startN, end1, ..., endN], where N is the rank of X. The RoIs' coordinates are normalized in the coordinate system of the input image. It only takes effect when coordinate_transformation_mode is "tf_crop_and_resize" - **scales** (*tensor(float)*): The scale array along each dimension. It takes value greater than 0. If it's less than 1, it's sampling down, otherwise, it's upsampling. The number of elements of 'scales' should be the same as the rank of input 'X'. One of 'scales' and 'sizes' MUST be specified and it is an error if both are specified. If 'sizes' is needed, the user can use an empty string as the name of 'scales' in this operator's input list. - **sizes** (*tensor(int64)*): The size of the output tensor. The number of elements of 'sizes' should be the same as the rank of input 'X'. Only one of 'scales' and 'sizes' can be specified. **Outputs** - **Y** (*T1*): N-D tensor after resizing **Type Constraints** - **T1**: Constrain input 'X' and output 'Y' to all tensor types. Allowed types: tensor(bfloat16), tensor(bool), tensor(complex128), tensor(complex64), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8). - **T2**: Constrain roi type to float or double. Allowed types: tensor(double), tensor(float), tensor(float16). Examples -------- **test_cc_resize_upsample_scales_nearest_1d** .. code-block:: text Node: Resize(X, "", scales) -> (Y) Attributes: mode = "nearest" coordinate_transformation_mode = "asymmetric" .. code-block:: text Inputs: X: shape=(3,), dtype=float32 [10., 20., 30.] scales: shape=(1,), dtype=float32 [2.] Outputs: Y: shape=(6,), dtype=float32 [10., 10., 20., 20., 30., 30.] **test_cc_resize_upsample_scales_nearest_asymmetric** .. code-block:: text Node: Resize(X, "", scales) -> (Y) Attributes: mode = "nearest" coordinate_transformation_mode = "asymmetric" .. code-block:: text Inputs: X: shape=(1, 1, 2, 2), dtype=float32 [[[[1., 2.], [3., 4.]]]] scales: shape=(4,), dtype=float32 [1., 1., 2., 3.] Outputs: Y: shape=(1, 1, 4, 6), dtype=float32 [[[[1., 1., 2., 2., 2., 2.], [1., 1., 2., 2., 2., 2.], [3., 3., 4., 4., 4., 4.], [3., 3., 4., 4., 4., 4.]]]] **test_cc_resize_upsample_sizes_nearest_asymmetric** .. code-block:: text Node: Resize(X, "", "", sizes) -> (Y) Attributes: mode = "nearest" coordinate_transformation_mode = "asymmetric" .. code-block:: text Inputs: X: shape=(1, 1, 2, 2), dtype=float32 [[[[1., 2.], [3., 4.]]]] sizes: shape=(4,), dtype=int64 [1, 1, 4, 6] Outputs: Y: shape=(1, 1, 4, 6), dtype=float32 [[[[1., 1., 2., 2., 2., 2.], [1., 1., 2., 2., 2., 2.], [3., 3., 4., 4., 4., 4.], [3., 3., 4., 4., 4., 4.]]]] **test_cc_shape_inference_resize_tile** .. code-block:: text Node: Resize(X, "", scales) -> (resized_out) Attributes: mode = "nearest" coordinate_transformation_mode = "asymmetric" .. code-block:: text Inputs: X: shape=(10, 6), dtype=float32 [[ 1., 2., 3., 4., 5., 6.], [ 7., 8., 9., 10., 11., 12.], [13., 14., 15., 16., 17., 18.], [19., 20., 21., 22., 23., 24.], [25., 26., 27., 28., 29., 30.], [31., 32., 33., 34., 35., 36.], [37., 38., 39., 40., 41., 42.], [43., 44., 45., 46., 47., 48.], [49., 50., 51., 52., 53., 54.], [55., 56., 57., 58., 59., 60.]] Outputs: resized_out: shape=(10, 6), dtype=float32 [[ 1., 3., 5., 1., 3., 5.], [13., 15., 17., 13., 15., 17.], [25., 27., 29., 25., 27., 29.], [37., 39., 41., 37., 39., 41.], [49., 51., 53., 49., 51., 53.], [ 1., 3., 5., 1., 3., 5.], [13., 15., 17., 13., 15., 17.], [25., 27., 29., 25., 27., 29.], [37., 39., 41., 37., 39., 41.], [49., 51., 53., 49., 51., 53.]] **test_resize_downsample_scales_nearest** .. code-block:: text Node: Resize(X, "", scales) -> (Y) Attributes: mode = "nearest" .. code-block:: text Inputs: X: shape=(1, 1, 2, 4), dtype=float32 [[[[1., 2., 3., 4.], [5., 6., 7., 8.]]]] scales: shape=(4,), dtype=float32 [1. , 1. , 0.6, 0.6] Outputs: Y: shape=(1, 1, 1, 2), dtype=float32 [[[[1., 3.]]]] **test_resize_downsample_sizes_nearest** .. code-block:: text Node: Resize(X, "", "", sizes) -> (Y) Attributes: mode = "nearest" .. code-block:: text Inputs: X: shape=(1, 1, 2, 4), dtype=float32 [[[[1., 2., 3., 4.], [5., 6., 7., 8.]]]] sizes: shape=(4,), dtype=int64 [1, 1, 1, 3] Outputs: Y: shape=(1, 1, 1, 3), dtype=float32 [[[[1., 2., 4.]]]] **test_resize_upsample_scales_nearest** .. code-block:: text Node: Resize(X, "", scales) -> (Y) Attributes: mode = "nearest" .. code-block:: text Inputs: X: shape=(1, 1, 2, 2), dtype=float32 [[[[1., 2.], [3., 4.]]]] scales: shape=(4,), dtype=float32 [1., 1., 2., 3.] Outputs: Y: shape=(1, 1, 4, 6), dtype=float32 [[[[1., 1., 1., 2., 2., 2.], [1., 1., 1., 2., 2., 2.], [3., 3., 3., 4., 4., 4.], [3., 3., 3., 4., 4., 4.]]]] **test_resize_upsample_sizes_nearest** .. code-block:: text Node: Resize(X, "", "", sizes) -> (Y) Attributes: mode = "nearest" .. code-block:: text Inputs: X: shape=(1, 1, 2, 2), dtype=float32 [[[[1., 2.], [3., 4.]]]] sizes: shape=(4,), dtype=int64 [1, 1, 7, 8] Outputs: Y: shape=(1, 1, 7, 8), dtype=float32 [[[[1., 1., 1., 1., 2., 2., 2., 2.], [1., 1., 1., 1., 2., 2., 2., 2.], [1., 1., 1., 1., 2., 2., 2., 2.], [1., 1., 1., 1., 2., 2., 2., 2.], [3., 3., 3., 3., 4., 4., 4., 4.], [3., 3., 3., 3., 4., 4., 4., 4.], [3., 3., 3., 3., 4., 4., 4., 4.]]]] **test_resize_upsample_sizes_nearest_ceil_half_pixel** .. code-block:: text Node: Resize(X, "", "", sizes) -> (Y) Attributes: mode = "nearest" coordinate_transformation_mode = "half_pixel" nearest_mode = "ceil" .. code-block:: text Inputs: X: shape=(1, 1, 4, 4), dtype=float32 [[[[ 1., 2., 3., 4.], [ 5., 6., 7., 8.], [ 9., 10., 11., 12.], [13., 14., 15., 16.]]]] sizes: shape=(4,), dtype=int64 [1, 1, 8, 8] Outputs: Y: shape=(1, 1, 8, 8), dtype=float32 [[[[ 1., 2., 2., 3., 3., 4., 4., 4.], [ 5., 6., 6., 7., 7., 8., 8., 8.], [ 5., 6., 6., 7., 7., 8., 8., 8.], [ 9., 10., 10., 11., 11., 12., 12., 12.], [ 9., 10., 10., 11., 11., 12., 12., 12.], [13., 14., 14., 15., 15., 16., 16., 16.], [13., 14., 14., 15., 15., 16., 16., 16.], [13., 14., 14., 15., 15., 16., 16., 16.]]]] **test_resize_upsample_sizes_nearest_floor_align_corners** .. code-block:: text Node: Resize(X, "", "", sizes) -> (Y) Attributes: mode = "nearest" coordinate_transformation_mode = "align_corners" nearest_mode = "floor" .. code-block:: text Inputs: X: shape=(1, 1, 4, 4), dtype=float32 [[[[ 1., 2., 3., 4.], [ 5., 6., 7., 8.], [ 9., 10., 11., 12.], [13., 14., 15., 16.]]]] sizes: shape=(4,), dtype=int64 [1, 1, 8, 8] Outputs: Y: shape=(1, 1, 8, 8), dtype=float32 [[[[ 1., 1., 1., 2., 2., 3., 3., 4.], [ 1., 1., 1., 2., 2., 3., 3., 4.], [ 1., 1., 1., 2., 2., 3., 3., 4.], [ 5., 5., 5., 6., 6., 7., 7., 8.], [ 5., 5., 5., 6., 6., 7., 7., 8.], [ 9., 9., 9., 10., 10., 11., 11., 12.], [ 9., 9., 9., 10., 10., 11., 11., 12.], [13., 13., 13., 14., 14., 15., 15., 16.]]]] **test_resize_upsample_sizes_nearest_round_prefer_ceil_asymmetric** .. code-block:: text Node: Resize(X, "", "", sizes) -> (Y) Attributes: mode = "nearest" coordinate_transformation_mode = "asymmetric" nearest_mode = "round_prefer_ceil" .. code-block:: text Inputs: X: shape=(1, 1, 4, 4), dtype=float32 [[[[ 1., 2., 3., 4.], [ 5., 6., 7., 8.], [ 9., 10., 11., 12.], [13., 14., 15., 16.]]]] sizes: shape=(4,), dtype=int64 [1, 1, 8, 8] Outputs: Y: shape=(1, 1, 8, 8), dtype=float32 [[[[ 1., 2., 2., 3., 3., 4., 4., 4.], [ 5., 6., 6., 7., 7., 8., 8., 8.], [ 5., 6., 6., 7., 7., 8., 8., 8.], [ 9., 10., 10., 11., 11., 12., 12., 12.], [ 9., 10., 10., 11., 11., 12., 12., 12.], [13., 14., 14., 15., 15., 16., 16., 16.], [13., 14., 14., 15., 15., 16., 16., 16.], [13., 14., 14., 15., 15., 16., 16., 16.]]]] Differences with previous version (11) -------------------------------------- **SchemaDiff**: ``Resize`` (domain ``'ai.onnx'``) * old version: 11 * new version: 13 * breaking: **yes** **Breaking reasons:** * attribute 'mode' (removed): type=STRING; required=False * attribute 'cubic_coeff_a' (removed): type=FLOAT; required=False * attribute 'exclude_outside' (removed): type=INT; required=False * attribute 'coordinate_transformation_mode' (removed): type=STRING; required=False * attribute 'nearest_mode' (removed): type=STRING; required=False * attribute 'extrapolation_value' (removed): type=FLOAT; required=False **Attributes:** * [BREAKING] removed 'mode': type=STRING; required=False * [BREAKING] removed 'cubic_coeff_a': type=FLOAT; required=False * [BREAKING] removed 'exclude_outside': type=INT; required=False * [BREAKING] removed 'coordinate_transformation_mode': type=STRING; required=False * [BREAKING] removed 'nearest_mode': type=STRING; required=False * [BREAKING] removed 'extrapolation_value': type=FLOAT; required=False **Type constraints:** * changed 'T1': added types: ['tensor(bfloat16)']