()
| 29 | |
| 30 | |
| 31 | def memory_benchmark(): |
| 32 | print( |
| 33 | "======================= ====================== ====================== ====================" |
| 34 | ) |
| 35 | print( |
| 36 | "Sparse (megabytes used) Dense (megabytes used) Ratio (Sparse/Dense) % % of non zero values" |
| 37 | ) |
| 38 | print( |
| 39 | "======================= ====================== ====================== ====================" |
| 40 | ) |
| 41 | percent_of_true_values = 0.005 |
| 42 | while percent_of_true_values < 0.1: |
| 43 | result = {} |
| 44 | for sparse in [True, False]: |
| 45 | result[sparse] = create_spikes_tensor(percent_of_true_values, sparse) |
| 46 | percent = round((result[True] / result[False]) * 100) |
| 47 | |
| 48 | row = [ |
| 49 | str(result[True]).ljust(23), |
| 50 | str(result[False]).ljust(22), |
| 51 | str(percent).ljust(22), |
| 52 | str(round(percent_of_true_values * 100, 1)).ljust(20), |
| 53 | ] |
| 54 | print(" ".join(row)) |
| 55 | percent_of_true_values += 0.005 |
| 56 | |
| 57 | print( |
| 58 | "======================= ====================== ====================== ====================" |
| 59 | ) |
| 60 | |
| 61 | |
| 62 | def run(sparse): |
no test coverage detected