Created
May 25, 2019 14:56
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DeepLearning#3
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| def argument_input_interface( | |
| n_conv, | |
| kernel_conv, | |
| stride_conv, | |
| kernel_pool, | |
| stride_pool, | |
| n_layers, | |
| dim1=(6, 32), | |
| dim2=(120, 40) | |
| ): | |
| _dim1 = np.linspace(dim1[0], dim1[1], int(n_conv)).astype(int) | |
| _dim2 = np.linspace(dim2[0], dim2[1], int(n_conv)).astype(int) | |
| _kernel_conv = [int(kernel_conv)] * int(n_conv) | |
| _stride_conv = [int(stride_conv)] * int(n_conv) | |
| _kernel_pool = [int(kernel_pool)] * int(n_conv) | |
| _stride_pool = [int(stride_pool)] * int(n_conv) | |
| return int(n_conv), list(_dim1), _kernel_conv, _stride_conv, _kernel_pool, _stride_pool, int(n_layers), list(_dim2) | |
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