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id: 144
unit: def get_weight()
file: models/modules.py
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id: 145
unit: def __init__()
file: models/networks/channel_selection.py
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id: 146
unit: def __init__()
file: models/networks/model_profiling.py
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id: 147
unit: def forward()
file: models/quantize_affine.py
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id: 148
unit: def get_quantization_params()
file: models/quantize_affine.py
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id: 149
unit: def is_active()
file: models/quantize_affine.py
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id: 150
unit: def update_bn_stats()
file: models/quantized_modules.py
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size: 4 LOC
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id: 151
unit: def freeze_bn_stats()
file: models/quantized_modules.py
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id: 152
unit: def __init__()
file: models/sparse_modules.py
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id: 153
unit: def _check_type()
file: models/special_tensors.py
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size: 4 LOC
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id: 154
unit: def tag_with_metadata()
file: models/special_tensors.py
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size: 4 LOC
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number of parameters: 2

id: 155
unit: def save()
file: model_logging.py
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size: 3 LOC
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id: 156
unit: def __init__()
file: models/modules.py
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id: 157
unit: def initialize()
file: models/modules.py
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id: 158
unit: def get_weight()
file: models/modules.py
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id: 159
unit: def forward()
file: models/modules.py
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id: 160
unit: def get_weight()
file: models/modules.py
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id: 161
unit: def __enter__()
file: models/networks/model_profiling.py
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size: 3 LOC
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id: 162
unit: def get_quantized_representation()
file: models/quantize_affine.py
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size: 3 LOC
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id: 163
unit: def quantize_affine_function_continuous()
file: models/quantize_affine.py
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size: 3 LOC
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id: 164
unit: def quantize_affine_given_quant_params()
file: models/quantize_affine.py
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size: 3 LOC
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id: 165
unit: def dequantize()
file: models/quantize_affine.py
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size: 3 LOC
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id: 166
unit: def update_num_bits()
file: models/quantized_modules.py
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size: 3 LOC
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number of parameters: 2

id: 167
unit: def forward()
file: models/quantized_modules.py
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id: 168
unit: def __init__()
file: models/quantized_modules.py
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id: 169
unit: def initialize()
file: models/quantized_modules.py
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id: 170
unit: def get_weight()
file: models/quantized_modules.py
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id: 171
unit: def forward()
file: models/sparse_modules.py
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size: 3 LOC
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id: 172
unit: def __init__()
file: models/sparse_modules.py
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id: 173
unit: def initialize()
file: models/sparse_modules.py
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id: 174
unit: def get_weight()
file: models/sparse_modules.py
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size: 3 LOC
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number of parameters: 1

id: 175
unit: def assign_learning_rate()
file: schedulers.py
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size: 3 LOC
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number of parameters: 2

id: 176
unit: def unregister_bn_tracking_hooks()
file: utils.py
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size: 3 LOC
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number of parameters: 1

id: 177
unit: def us_logging()
file: model_logging.py
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size: 2 LOC
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number of parameters: 2

id: 178
unit: def batchnorm()
file: models/builder.py
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size: 2 LOC
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number of parameters: 2

id: 179
unit: def StandardIN()
file: models/modules.py
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size: 2 LOC
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id: 180
unit: def get_weight()
file: models/modules.py
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size: 2 LOC
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id: 181
unit: def get_weight()
file: models/modules.py
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size: 2 LOC
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number of parameters: 1

id: 182
unit: def get_num_parameters()
file: models/modules.py
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size: 2 LOC
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number of parameters: 1

id: 183
unit: def __repr__()
file: models/networks/channel_selection.py
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size: 2 LOC
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number of parameters: 1

id: 184
unit: def model_profiling()
file: models/networks/model_profiling.py
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size: 2 LOC
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id: 185
unit: def make_layers()
file: models/networks/vgg.py
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size: 2 LOC
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id: 186
unit: def vgg11()
file: models/networks/vgg.py
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size: 2 LOC
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number of parameters: 1

id: 187
unit: def vgg13()
file: models/networks/vgg.py
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size: 2 LOC
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number of parameters: 1

id: 188
unit: def vgg16()
file: models/networks/vgg.py
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size: 2 LOC
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id: 189
unit: def vgg19()
file: models/networks/vgg.py
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size: 2 LOC
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number of parameters: 1

id: 190
unit: def backward()
file: models/quantize_affine.py
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size: 2 LOC
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number of parameters: 2

id: 191
unit: def get_qmin_qmax()
file: models/quantize_affine.py
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size: 2 LOC
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number of parameters: 1

id: 192
unit: def quantize()
file: models/quantize_affine.py
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size: 2 LOC
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number of parameters: 0

id: 193
unit: def update_num_bits()
file: models/quantize_affine.py
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size: 2 LOC
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number of parameters: 2

id: 194
unit: def get_weight()
file: models/quantized_modules.py
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id: 195
unit: def __init__()
file: models/quantized_modules.py
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id: 196
unit: def forward()
file: models/quantized_modules.py
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id: 197
unit: def reset_running_stats()
file: models/quantized_modules.py
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id: 198
unit: def reset_parameters()
file: models/quantized_modules.py
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id: 199
unit: def start_counter()
file: models/quantized_modules.py
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number of parameters: 1

id: 200
unit: def stop_counter()
file: models/quantized_modules.py
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number of parameters: 1

id: 201
unit: def is_active()
file: models/quantized_modules.py
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size: 2 LOC
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number of parameters: 1

id: 202
unit: def extra_repr()
file: models/quantized_modules.py
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size: 2 LOC
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number of parameters: 1

id: 203
unit: def apply_sparsity()
file: models/sparse_modules.py
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size: 2 LOC
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number of parameters: 2

id: 204
unit: def cuda()
file: models/special_tensors.py
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size: 2 LOC
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id: 205
unit: def _warmup_lr()
file: schedulers.py
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size: 2 LOC
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number of parameters: 3

id: 206
unit: def quantized_module_updates()
file: train_curve.py
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size: 2 LOC
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number of parameters: 0

id: 207
unit: def train()
file: train_curve.py
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size: 2 LOC
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id: 208
unit: def us_update()
file: train_indep.py
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size: 2 LOC
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number of parameters: 2

id: 209
unit: def train()
file: train_indep.py
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size: 2 LOC
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id: 210
unit: def apply_sparsity()
file: utils.py
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number of parameters: 0