Top:
   epoch
   extras
   state_dict
   arch
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arch: ai85nascifarnet
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extras: {'best epoch': 123456789, 'best_top1': 57.9800009727478, 'clipping_method': 'MAX_BIT_SHIFT', 'current_top1': 57.9800009727478}
-------------------------------------
state_dict:
   conv1_1
     output_shift:         [-1.]
     adjust_output_shift:  [0.]
     quantize_activation:  [1.]
     shift_quantile:       [0.985]
     weight bits:          [8.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 64 , [64]
        # of unique elements:       64
        min, max, mean: -3211.0 ,  2946.0 ,  290.875
     weight
        total # of elements, shape: 1728 , [64, 3, 3, 3]
        # of unique elements:       224
        min, max, mean: -128.0 ,  127.0 ,  -0.2181713
   conv1_2
     output_shift:         [-1.]
     adjust_output_shift:  [0.]
     quantize_activation:  [1.]
     shift_quantile:       [0.985]
     weight bits:          [8.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 32 , [32]
        # of unique elements:       32
        min, max, mean: -10399.0 ,  7336.0 ,  3322.6562
     weight
        total # of elements, shape: 2048 , [32, 64, 1, 1]
        # of unique elements:       198
        min, max, mean: -128.0 ,  104.0 ,  -4.753418
   conv1_3
     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: 64 , [64]
        # of unique elements:       56
        min, max, mean: -119.0 ,  255.0 ,  42.28125
     weight
        total # of elements, shape: 18432 , [64, 32, 3, 3]
        # of unique elements:       4
        min, max, mean: -2.0 ,  1.0 ,  -0.025716146
   conv2_1
     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: 32 , [32]
        # of unique elements:       16
        min, max, mean: -256.0 ,  255.0 ,  71.90625
     weight
        total # of elements, shape: 18432 , [32, 64, 3, 3]
        # of unique elements:       4
        min, max, mean: -2.0 ,  1.0 ,  -0.011230469
   conv2_2
     output_shift:         [-0.]
     adjust_output_shift:  [0.]
     quantize_activation:  [1.]
     shift_quantile:       [0.985]
     weight bits:          [2.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 64 , [64]
        # of unique elements:       50
        min, max, mean: -135.0 ,  145.0 ,  13.59375
     weight
        total # of elements, shape: 2048 , [64, 32, 1, 1]
        # of unique elements:       4
        min, max, mean: -2.0 ,  1.0 ,  -0.047851562
   conv3_1
     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: 128 , [128]
        # of unique elements:       47
        min, max, mean: -256.0 ,  255.0 ,  76.47656
     weight
        total # of elements, shape: 73728 , [128, 64, 3, 3]
        # of unique elements:       4
        min, max, mean: -2.0 ,  1.0 ,  -0.0105523
   conv3_2
     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: 128 , [128]
        # of unique elements:       99
        min, max, mean: -193.0 ,  255.0 ,  78.0
     weight
        total # of elements, shape: 16384 , [128, 128, 1, 1]
        # of unique elements:       4
        min, max, mean: -2.0 ,  1.0 ,  -0.064453125
   conv4_1
     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: 64 , [64]
        # of unique elements:       22
        min, max, mean: -256.0 ,  255.0 ,  -76.265625
     weight
        total # of elements, shape: 73728 , [64, 128, 3, 3]
        # of unique elements:       4
        min, max, mean: -2.0 ,  1.0 ,  0.004977756
   conv4_2
     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: 128 , [128]
        # of unique elements:       107
        min, max, mean: -256.0 ,  255.0 ,  58.773438
     weight
        total # of elements, shape: 73728 , [128, 64, 3, 3]
        # of unique elements:       4
        min, max, mean: -2.0 ,  1.0 ,  -0.008056641
   conv5_1
     output_shift:         [-1.]
     adjust_output_shift:  [0.]
     quantize_activation:  [1.]
     shift_quantile:       [0.985]
     weight bits:          [8.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 128 , [128]
        # of unique elements:       123
        min, max, mean: -12583.0 ,  16383.0 ,  3161.289
     weight
        total # of elements, shape: 16384 , [128, 128, 1, 1]
        # of unique elements:       215
        min, max, mean: -119.0 ,  127.0 ,  -0.15649414
   fc
     output_shift:         [1.]
     adjust_output_shift:  [0.]
     quantize_activation:  [1.]
     shift_quantile:       [0.985]
     weight bits:          [8.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 100 , [100]
        # of unique elements:       99
        min, max, mean: -1628.0 ,  1485.0 ,  -32.65
     weight
        total # of elements, shape: 51200 , [100, 512]
        # of unique elements:       211
        min, max, mean: -128.0 ,  89.0 ,  -10.200137