19949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfanmodel = Model() 29949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfani1 = Input("input", "TENSOR_FLOAT32", "{1, 2, 2, 8}") 39949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfanblock = Int32Scalar("block_size", 2) 49949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfanoutput = Output("output", "TENSOR_FLOAT32", "{1, 4, 4, 2}") 59949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan 69949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfanmodel = model.Operation("DEPTH_TO_SPACE", i1, block).To(output) 79949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan 89949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan# Example 1. Input in operand 0, 99949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan 109949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfaninput0 = {i1: # input 0 119949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan [10, 20, 11, 21, 14, 24, 15, 25, 129949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan 12, 22, 13, 23, 16, 26, 17, 27, 139949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan 18, 28, 19, 29, 112, 212, 113, 213, 149949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan 110, 210, 111, 211, 114, 214, 115, 215]} 159949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan 169949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfanoutput0 = {output: # output 0 179949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan [10, 20, 11, 21, 12, 22, 13, 23, 189949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan 14, 24, 15, 25, 16, 26, 17, 27, 199949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan 18, 28, 19, 29, 110, 210, 111, 211, 209949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan 112, 212, 113, 213, 114, 214, 115, 215]} 219949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfan# Instantiate an example 229949232ba3d5b1d95f5b3d9ea310b88b81ee1a45gfanExample((input0, output0)) 23