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