checkpoints/shallow999_reproduceMaxim001_simplenet_2b4b8b/statistics_hardware_checkpoint

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   epoch
   extras
   state_dict
   arch
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arch: ai85nascifarnet
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extras: {'best epoch': 123456789, 'best_top1': 53.65999937057495, 'clipping_method': 'MAX_BIT_SHIFT', 'current_top1': 53.65999937057495}
-------------------------------------
state_dict:
   conv1
     output_shift:         [-0.]
     adjust_output_shift:  [0.]
     quantize_activation:  [1.]
     shift_quantile:       [0.985]
     weight bits:          [8.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 16 , [16]
        # of unique elements:       16
        min, max, mean: -1407.0 ,  1368.0 ,  81.0
     weight
        total # of elements, shape: 432 , [16, 3, 3, 3]
        # of unique elements:       99
        min, max, mean: -77.0 ,  81.0 ,  -0.011574074
   conv2
     output_shift:         [-1.]
     adjust_output_shift:  [0.]
     quantize_activation:  [1.]
     shift_quantile:       [0.985]
     weight bits:          [4.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 20 , [20]
        # of unique elements:       20
        min, max, mean: -577.0 ,  551.0 ,  124.1
     weight
        total # of elements, shape: 2880 , [20, 16, 3, 3]
        # of unique elements:       16
        min, max, mean: -8.0 ,  7.0 ,  -0.090625
   conv3
     output_shift:         [-1.]
     adjust_output_shift:  [0.]
     quantize_activation:  [1.]
     shift_quantile:       [0.985]
     weight bits:          [2.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 20 , [20]
        # of unique elements:       19
        min, max, mean: -51.0 ,  206.0 ,  93.85
     weight
        total # of elements, shape: 3600 , [20, 20, 3, 3]
        # of unique elements:       4
        min, max, mean: -2.0 ,  1.0 ,  -0.045
   conv4
     output_shift:         [-1.]
     adjust_output_shift:  [0.]
     quantize_activation:  [1.]
     shift_quantile:       [0.985]
     weight bits:          [2.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 20 , [20]
        # of unique elements:       19
        min, max, mean: -72.0 ,  232.0 ,  48.45
     weight
        total # of elements, shape: 3600 , [20, 20, 3, 3]
        # of unique elements:       4
        min, max, mean: -2.0 ,  1.0 ,  -0.031666666
   conv5
     output_shift:         [-2.]
     adjust_output_shift:  [0.]
     quantize_activation:  [1.]
     shift_quantile:       [0.985]
     weight bits:          [2.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 20 , [20]
        # of unique elements:       15
        min, max, mean: -256.0 ,  255.0 ,  -5.3
     weight
        total # of elements, shape: 3600 , [20, 20, 3, 3]
        # of unique elements:       4
        min, max, mean: -2.0 ,  1.0 ,  0.0055555557
   conv6
     output_shift:         [-2.]
     adjust_output_shift:  [0.]
     quantize_activation:  [1.]
     shift_quantile:       [0.985]
     weight bits:          [2.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 20 , [20]
        # of unique elements:       17
        min, max, mean: -256.0 ,  255.0 ,  81.6
     weight
        total # of elements, shape: 3600 , [20, 20, 3, 3]
        # of unique elements:       4
        min, max, mean: -2.0 ,  1.0 ,  -0.03277778
   conv7
     output_shift:         [-2.]
     adjust_output_shift:  [0.]
     quantize_activation:  [1.]
     shift_quantile:       [0.985]
     weight bits:          [2.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 44 , [44]
        # of unique elements:       37
        min, max, mean: -220.0 ,  255.0 ,  93.27273
     weight
        total # of elements, shape: 7920 , [44, 20, 3, 3]
        # of unique elements:       4
        min, max, mean: -2.0 ,  1.0 ,  -0.06792929
   conv8
     output_shift:         [-3.]
     adjust_output_shift:  [0.]
     quantize_activation:  [1.]
     shift_quantile:       [0.985]
     weight bits:          [2.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 48 , [48]
        # of unique elements:       17
        min, max, mean: -256.0 ,  255.0 ,  88.291664
     weight
        total # of elements, shape: 19008 , [48, 44, 3, 3]
        # of unique elements:       4
        min, max, mean: -2.0 ,  1.0 ,  -0.021569865
   conv9
     output_shift:         [-2.]
     adjust_output_shift:  [0.]
     quantize_activation:  [1.]
     shift_quantile:       [0.985]
     weight bits:          [2.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 48 , [48]
        # of unique elements:       30
        min, max, mean: -256.0 ,  255.0 ,  102.729164
     weight
        total # of elements, shape: 20736 , [48, 48, 3, 3]
        # of unique elements:       4
        min, max, mean: -2.0 ,  1.0 ,  -0.02425733
   conv10
     output_shift:         [-3.]
     adjust_output_shift:  [0.]
     quantize_activation:  [1.]
     shift_quantile:       [0.985]
     weight bits:          [2.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 96 , [96]
        # of unique elements:       26
        min, max, mean: -256.0 ,  255.0 ,  -125.552086
     weight
        total # of elements, shape: 41472 , [96, 48, 3, 3]
        # of unique elements:       4
        min, max, mean: -2.0 ,  1.0 ,  0.030864198
   conv11
     output_shift:         [-1.]
     adjust_output_shift:  [0.]
     quantize_activation:  [1.]
     shift_quantile:       [0.985]
     weight bits:          [4.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 512 , [512]
        # of unique elements:       432
        min, max, mean: -1024.0 ,  1023.0 ,  161.24219

[WARNING]: # of unique elements in bias tensor is more than that allowed by bias_bits.
           This might be OK, since Maxim deployment repository right shifts these.

     weight
        total # of elements, shape: 49152 , [512, 96, 1, 1]
        # of unique elements:       16
        min, max, mean: -8.0 ,  7.0 ,  -0.040649414
   conv12
     output_shift:         [-2.]
     adjust_output_shift:  [0.]
     quantize_activation:  [1.]
     shift_quantile:       [0.985]
     weight bits:          [4.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 128 , [128]
        # of unique elements:       99
        min, max, mean: -1024.0 ,  1023.0 ,  235.99219
     weight
        total # of elements, shape: 65536 , [128, 512, 1, 1]
        # of unique elements:       16
        min, max, mean: -8.0 ,  7.0 ,  -0.012710571
   conv13
     output_shift:         [-2.]
     adjust_output_shift:  [0.]
     quantize_activation:  [1.]
     shift_quantile:       [0.985]
     weight bits:          [4.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 128 , [128]
        # of unique elements:       113
        min, max, mean: -1024.0 ,  1023.0 ,  212.21094
     weight
        total # of elements, shape: 147456 , [128, 128, 3, 3]
        # of unique elements:       16
        min, max, mean: -8.0 ,  7.0 ,  0.0015123156
   conv14
     output_shift:         [2.]
     adjust_output_shift:  [0.]
     quantize_activation:  [1.]
     shift_quantile:       [0.985]
     weight bits:          [4.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 100 , [100]
        # of unique elements:       78
        min, max, mean: -152.0 ,  129.0 ,  -2.28
     weight
        total # of elements, shape: 12800 , [100, 128, 1, 1]
        # of unique elements:       16
        min, max, mean: -8.0 ,  7.0 ,  -1.1907812