Top:
   epoch
   extras
   state_dict
   arch
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arch: ai85nascifarnet
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extras: None
-------------------------------------
state_dict:
   conv1_1
     output_shift:         [-0.]
     adjust_output_shift:  [0.]
     quantize_activation:  [1.]
     shift_quantile:       [1.]
     weight bits:          [8.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 64 , [64]
        # of unique elements:       27
        min, max, mean: -8704.0 ,  1408.0 ,  -868.0
     weight
        total # of elements, shape: 1728 , [64, 3, 3, 3]
        # of unique elements:       122
        min, max, mean: -73.0 ,  118.0 ,  -0.17418982
   conv1_2
     output_shift:         [-1.]
     adjust_output_shift:  [0.]
     quantize_activation:  [1.]
     shift_quantile:       [1.]
     weight bits:          [2.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 32 , [32]
        # of unique elements:       26
        min, max, mean: -128.0 ,  68.0 ,  14.0625
     weight
        total # of elements, shape: 2048 , [32, 64, 1, 1]
        # of unique elements:       2
        min, max, mean: -1.0 ,  1.0 ,  -0.15136719
   conv1_3
     output_shift:         [-2.]
     adjust_output_shift:  [0.]
     quantize_activation:  [1.]
     shift_quantile:       [1.]
     weight bits:          [2.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 64 , [64]
        # of unique elements:       40
        min, max, mean: -120.0 ,  98.0 ,  -2.21875
     weight
        total # of elements, shape: 18432 , [64, 32, 3, 3]
        # of unique elements:       2
        min, max, mean: -1.0 ,  1.0 ,  -0.11306424
   conv2_1
     output_shift:         [-3.]
     adjust_output_shift:  [0.]
     quantize_activation:  [1.]
     shift_quantile:       [1.]
     weight bits:          [2.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 32 , [32]
        # of unique elements:       20
        min, max, mean: -128.0 ,  126.0 ,  29.0625
     weight
        total # of elements, shape: 18432 , [32, 64, 3, 3]
        # of unique elements:       2
        min, max, mean: -1.0 ,  1.0 ,  -0.035047743
   conv2_2
     output_shift:         [0.]
     adjust_output_shift:  [0.]
     quantize_activation:  [1.]
     shift_quantile:       [1.]
     weight bits:          [2.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 64 , [64]
        # of unique elements:       47
        min, max, mean: -96.0 ,  126.0 ,  29.3125
     weight
        total # of elements, shape: 2048 , [64, 32, 1, 1]
        # of unique elements:       2
        min, max, mean: -1.0 ,  1.0 ,  -0.2421875
   conv3_1
     output_shift:         [-4.]
     adjust_output_shift:  [0.]
     quantize_activation:  [1.]
     shift_quantile:       [1.]
     weight bits:          [2.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 128 , [128]
        # of unique elements:       55
        min, max, mean: -128.0 ,  126.0 ,  35.21875
     weight
        total # of elements, shape: 73728 , [128, 64, 3, 3]
        # of unique elements:       2
        min, max, mean: -1.0 ,  1.0 ,  -0.026529947
   conv3_2
     output_shift:         [-2.]
     adjust_output_shift:  [0.]
     quantize_activation:  [1.]
     shift_quantile:       [1.]
     weight bits:          [2.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 128 , [128]
        # of unique elements:       77
        min, max, mean: -128.0 ,  126.0 ,  20.734375
     weight
        total # of elements, shape: 16384 , [128, 128, 1, 1]
        # of unique elements:       2
        min, max, mean: -1.0 ,  1.0 ,  -0.09436035
   conv4_1
     output_shift:         [-4.]
     adjust_output_shift:  [0.]
     quantize_activation:  [1.]
     shift_quantile:       [1.]
     weight bits:          [2.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 64 , [64]
        # of unique elements:       35
        min, max, mean: -128.0 ,  126.0 ,  -5.09375
     weight
        total # of elements, shape: 73728 , [64, 128, 3, 3]
        # of unique elements:       2
        min, max, mean: -1.0 ,  1.0 ,  0.0046115452
   conv4_2
     output_shift:         [-3.]
     adjust_output_shift:  [0.]
     quantize_activation:  [1.]
     shift_quantile:       [1.]
     weight bits:          [2.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 128 , [128]
        # of unique elements:       73
        min, max, mean: -128.0 ,  126.0 ,  -19.015625
     weight
        total # of elements, shape: 73728 , [128, 64, 3, 3]
        # of unique elements:       2
        min, max, mean: -1.0 ,  1.0 ,  -0.03000217
   conv5_1
     output_shift:         [-2.]
     adjust_output_shift:  [0.]
     quantize_activation:  [1.]
     shift_quantile:       [1.]
     weight bits:          [2.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 128 , [128]
        # of unique elements:       75
        min, max, mean: -128.0 ,  126.0 ,  34.890625
     weight
        total # of elements, shape: 16384 , [128, 128, 1, 1]
        # of unique elements:       2
        min, max, mean: -1.0 ,  1.0 ,  -0.035888672
   fc
     output_shift:         [3.]
     adjust_output_shift:  [0.]
     quantize_activation:  [1.]
     shift_quantile:       [1.]
     weight bits:          [8.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 100 , [100]
        # of unique elements:       26
        min, max, mean: -1920.0 ,  1664.0 ,  -57.6
     weight
        total # of elements, shape: 51200 , [100, 512]
        # of unique elements:       130
        min, max, mean: -93.0 ,  73.0 ,  -4.9889455