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pytorch-image-models/timm/models/_pruned/efficientnet_b1_pruned.txt

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conv_stem.weight:[32, 3, 3, 3]***bn1.weight:[32]***bn1.bias:[32]***bn1.running_mean:[32]***bn1.running_var:[32]***bn1.num_batches_tracked:[]***blocks.0.0.conv_dw.weight:[32, 1, 3, 3]***blocks.0.0.bn1.weight:[32]***blocks.0.0.bn1.bias:[32]***blocks.0.0.bn1.running_mean:[32]***blocks.0.0.bn1.running_var:[32]***blocks.0.0.bn1.num_batches_tracked:[]***blocks.0.0.se.conv_reduce.weight:[8, 32, 1, 1]***blocks.0.0.se.conv_reduce.bias:[8]***blocks.0.0.se.conv_expand.weight:[32, 8, 1, 1]***blocks.0.0.se.conv_expand.bias:[32]***blocks.0.0.conv_pw.weight:[16, 32, 1, 1]***blocks.0.0.bn2.weight:[16]***blocks.0.0.bn2.bias:[16]***blocks.0.0.bn2.running_mean:[16]***blocks.0.0.bn2.running_var:[16]***blocks.0.0.bn2.num_batches_tracked:[]***blocks.0.1.conv_dw.weight:[16, 1, 3, 3]***blocks.0.1.bn1.weight:[16]***blocks.0.1.bn1.bias:[16]***blocks.0.1.bn1.running_mean:[16]***blocks.0.1.bn1.running_var:[16]***blocks.0.1.bn1.num_batches_tracked:[]***blocks.0.1.se.conv_reduce.weight:[4, 16, 1, 1]***blocks.0.1.se.conv_reduce.bias:[4]***blocks.0.1.se.conv_expand.weight:[16, 4, 1, 1]***blocks.0.1.se.conv_expand.bias:[16]***blocks.0.1.conv_pw.weight:[16, 16, 1, 1]***blocks.0.1.bn2.weight:[16]***blocks.0.1.bn2.bias:[16]***blocks.0.1.bn2.running_mean:[16]***blocks.0.1.bn2.running_var:[16]***blocks.0.1.bn2.num_batches_tracked:[]***blocks.1.0.conv_pw.weight:[48, 16, 1, 1]***blocks.1.0.bn1.weight:[48]***blocks.1.0.bn1.bias:[48]***blocks.1.0.bn1.running_mean:[48]***blocks.1.0.bn1.running_var:[48]***blocks.1.0.bn1.num_batches_tracked:[]***blocks.1.0.conv_dw.weight:[48, 1, 3, 3]***blocks.1.0.bn2.weight:[48]***blocks.1.0.bn2.bias:[48]***blocks.1.0.bn2.running_mean:[48]***blocks.1.0.bn2.running_var:[48]***blocks.1.0.bn2.num_batches_tracked:[]***blocks.1.0.se.conv_reduce.weight:[4, 48, 1, 1]***blocks.1.0.se.conv_reduce.bias:[4]***blocks.1.0.se.conv_expand.weight:[48, 4, 1, 1]***blocks.1.0.se.conv_expand.bias:[48]***blocks.1.0.conv_pwl.weight:[12, 48, 1, 1]***blocks.1.0.bn3.weight:[12]***blocks.1.0.bn3.bias:[12]***blocks.1.0.bn3.running_mean:[12]***blocks.1.0.bn3.running_var:[12]***blocks.1.0.bn3.num_batches_tracked:[]***blocks.1.1.conv_pw.weight:[62, 12, 1, 1]***blocks.1.1.bn1.weight:[62]***blocks.1.1.bn1.bias:[62]***blocks.1.1.bn1.running_mean:[62]***blocks.1.1.bn1.running_var:[62]***blocks.1.1.bn1.num_batches_tracked:[]***blocks.1.1.conv_dw.weight:[62, 1, 3, 3]***blocks.1.1.bn2.weight:[62]***blocks.1.1.bn2.bias:[62]***blocks.1.1.bn2.running_mean:[62]***blocks.1.1.bn2.running_var:[62]***blocks.1.1.bn2.num_batches_tracked:[]***blocks.1.1.se.conv_reduce.weight:[6, 62, 1, 1]***blocks.1.1.se.conv_reduce.bias:[6]***blocks.1.1.se.conv_expand.weight:[62, 6, 1, 1]***blocks.1.1.se.conv_expand.bias:[62]***blocks.1.1.conv_pwl.weight:[12, 62, 1, 1]***blocks.1.1.bn3.weight:[12]***blocks.1.1.bn3.bias:[12]***blocks.1.1.bn3.running_mean:[12]***blocks.1.1.bn3.running_var:[12]***blocks.1.1.bn3.num_batches_tracked:[]***blocks.1.2.conv_pw.weight:[48, 12, 1, 1]***blocks.1.2.bn1.weight:[48]***blocks.1.2.bn1.bias:[48]***blocks.1.2.bn1.running_mean:[48]***blocks.1.2.bn1.running_var:[48]***blocks.1.2.bn1.num_batches_tracked:[]***blocks.1.2.conv_dw.weight:[48, 1, 3, 3]***blocks.1.2.bn2.weight:[48]***blocks.1.2.bn2.bias:[48]***blocks.1.2.bn2.running_mean:[48]***blocks.1.2.bn2.running_var:[48]***blocks.1.2.bn2.num_batches_tracked:[]***blocks.1.2.se.conv_reduce.weight:[6, 48, 1, 1]***blocks.1.2.se.conv_reduce.bias:[6]***blocks.1.2.se.conv_expand.weight:[48, 6, 1, 1]***blocks.1.2.se.conv_expand.bias:[48]***blocks.1.2.conv_pwl.weight:[12, 48, 1, 1]***blocks.1.2.bn3.weight:[12]***blocks.1.2.bn3.bias:[12]***blocks.1.2.bn3.running_mean:[12]***blocks.1.2.bn3.running_var:[12]***blocks.1.2.bn3.num_batches_tracked:[]***blocks.2.0.conv_pw.weight:[70, 12, 1, 1]***blocks.2.0.bn1.weight:[70]***blocks.2.0.bn1.bias:[70]***blocks.2.0.bn1.running_mean:[70]***blocks.2.0.bn1.running_var:[70]***blocks.2.0.bn1.num_batches_tracked:[]***blocks.2.0.conv_dw.weight:[70, 1, 5, 5]***blocks.2.0.bn2.weight:[70]***blocks.2.0.bn2.bias:[70]***blocks.2.0.bn2.running_mean:[70]***blocks.2.0.bn2.running_var:[70]***blocks.2.0