commit file to HF hub
Browse files- config.json +28 -0
- lpot_config.yml +1441 -0
- pytorch_model.bin +3 -0
- quantization.yml +14 -0
- special_tokens_map.json +1 -0
- tokenizer_config.json +1 -0
- training_args.bin +3 -0
- vocab.txt +0 -0
config.json
ADDED
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{
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"_name_or_path": "textattack/bert-base-uncased-SST-2",
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"architectures": [
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"BertForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"classifier_dropout": null,
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"finetuning_task": "sst2",
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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "bert",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 0,
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"position_embedding_type": "absolute",
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"problem_type": "single_label_classification",
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"torch_dtype": "float32",
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"transformers_version": "4.10.2",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 30522
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}
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lpot_config.yml
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|
| 1 |
+
advance: null
|
| 2 |
+
approach: post_training_static_quant
|
| 3 |
+
calib_iteration: 7
|
| 4 |
+
framework: pytorch
|
| 5 |
+
op:
|
| 6 |
+
? !!python/tuple
|
| 7 |
+
- quant
|
| 8 |
+
- QuantStub
|
| 9 |
+
: activation:
|
| 10 |
+
dtype: uint8
|
| 11 |
+
scheme: asym
|
| 12 |
+
granularity: per_tensor
|
| 13 |
+
algorithm: minmax
|
| 14 |
+
? !!python/tuple
|
| 15 |
+
- bert.encoder.layer.0.attention.self.quant
|
| 16 |
+
- QuantStub
|
| 17 |
+
: activation:
|
| 18 |
+
dtype: uint8
|
| 19 |
+
scheme: asym
|
| 20 |
+
granularity: per_tensor
|
| 21 |
+
algorithm: minmax
|
| 22 |
+
? !!python/tuple
|
| 23 |
+
- bert.encoder.layer.0.attention.self.query
|
| 24 |
+
- Linear
|
| 25 |
+
: weight:
|
| 26 |
+
dtype: int8
|
| 27 |
+
scheme: sym
|
| 28 |
+
granularity: per_channel
|
| 29 |
+
algorithm: minmax
|
| 30 |
+
bit: 7.0
|
| 31 |
+
activation:
|
| 32 |
+
dtype: uint8
|
| 33 |
+
scheme: sym
|
| 34 |
+
granularity: per_tensor
|
| 35 |
+
algorithm: kl
|
| 36 |
+
? !!python/tuple
|
| 37 |
+
- bert.encoder.layer.0.attention.self.key
|
| 38 |
+
- Linear
|
| 39 |
+
: weight:
|
| 40 |
+
dtype: int8
|
| 41 |
+
scheme: sym
|
| 42 |
+
granularity: per_channel
|
| 43 |
+
algorithm: minmax
|
| 44 |
+
bit: 7.0
|
| 45 |
+
activation:
|
| 46 |
+
dtype: uint8
|
| 47 |
+
scheme: sym
|
| 48 |
+
granularity: per_tensor
|
| 49 |
+
algorithm: kl
|
| 50 |
+
? !!python/tuple
|
| 51 |
+
- bert.encoder.layer.0.attention.self.value
|
| 52 |
+
- Linear
|
| 53 |
+
: weight:
|
| 54 |
+
dtype: int8
|
| 55 |
+
scheme: sym
|
| 56 |
+
granularity: per_channel
|
| 57 |
+
algorithm: minmax
|
| 58 |
+
bit: 7.0
|
| 59 |
+
activation:
|
| 60 |
+
dtype: uint8
|
| 61 |
+
scheme: sym
|
| 62 |
+
granularity: per_tensor
|
| 63 |
+
algorithm: kl
|
| 64 |
+
? !!python/tuple
|
| 65 |
+
- bert.encoder.layer.0.attention.output.quant
|
| 66 |
+
- QuantStub
|
| 67 |
+
: activation:
|
| 68 |
+
dtype: uint8
|
| 69 |
+
scheme: asym
|
| 70 |
+
granularity: per_tensor
|
| 71 |
+
algorithm: minmax
|
| 72 |
+
? !!python/tuple
|
| 73 |
+
- bert.encoder.layer.0.attention.output.dense
|
| 74 |
+
- Linear
|
| 75 |
+
: weight:
|
| 76 |
+
dtype: int8
|
| 77 |
+
scheme: sym
|
| 78 |
+
granularity: per_channel
|
| 79 |
+
algorithm: minmax
|
| 80 |
+
bit: 7.0
|
| 81 |
+
activation:
|
| 82 |
+
dtype: uint8
|
| 83 |
+
scheme: sym
|
| 84 |
+
granularity: per_tensor
|
| 85 |
+
algorithm: kl
|
| 86 |
+
? !!python/tuple
|
| 87 |
+
- bert.encoder.layer.0.intermediate.quant
|
| 88 |
+
- QuantStub
|
| 89 |
+
: activation:
|
| 90 |
+
dtype: uint8
|
| 91 |
+
scheme: asym
|
| 92 |
+
granularity: per_tensor
|
| 93 |
+
algorithm: minmax
|
| 94 |
+
? !!python/tuple
|
| 95 |
+
- bert.encoder.layer.0.intermediate.dense
|
| 96 |
+
- Linear
|
| 97 |
+
: weight:
|
| 98 |
+
dtype: int8
|
| 99 |
+
scheme: sym
|
| 100 |
+
granularity: per_channel
|
| 101 |
+
algorithm: minmax
|
| 102 |
+
bit: 7.0
|
| 103 |
+
activation:
|
| 104 |
+
dtype: uint8
|
| 105 |
+
scheme: sym
|
| 106 |
+
granularity: per_tensor
|
| 107 |
+
algorithm: kl
|
| 108 |
+
? !!python/tuple
|
| 109 |
+
- bert.encoder.layer.0.output.quant
|
| 110 |
+
- QuantStub
|
| 111 |
+
: activation:
|
| 112 |
+
dtype: uint8
|
| 113 |
+
scheme: asym
|
| 114 |
+
granularity: per_tensor
|
| 115 |
+
algorithm: minmax
|
| 116 |
+
? !!python/tuple
|
| 117 |
+
- bert.encoder.layer.0.output.dense
|
| 118 |
+
- Linear
|
| 119 |
+
: weight:
|
| 120 |
+
dtype: int8
|
| 121 |
+
scheme: sym
|
| 122 |
+
granularity: per_channel
|
| 123 |
+
algorithm: minmax
|
| 124 |
+
bit: 7.0
|
| 125 |
+
activation:
|
| 126 |
+
dtype: uint8
|
| 127 |
+
scheme: sym
|
| 128 |
+
granularity: per_tensor
|
| 129 |
+
algorithm: kl
|
| 130 |
+
? !!python/tuple
|
| 131 |
+
- bert.encoder.layer.1.attention.self.quant
|
| 132 |
+
- QuantStub
|
| 133 |
+
: activation:
|
| 134 |
+
dtype: uint8
|
| 135 |
+
scheme: asym
|
| 136 |
+
granularity: per_tensor
|
| 137 |
+
algorithm: minmax
|
| 138 |
+
? !!python/tuple
|
| 139 |
+
- bert.encoder.layer.1.attention.self.query
|
| 140 |
+
- Linear
|
| 141 |
+
: weight:
|
| 142 |
+
dtype: int8
|
| 143 |
+
scheme: sym
|
| 144 |
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granularity: per_channel
|
| 145 |
+
algorithm: minmax
|
| 146 |
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bit: 7.0
|
| 147 |
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activation:
|
| 148 |
+
dtype: uint8
|
| 149 |
+
scheme: sym
|
| 150 |
+
granularity: per_tensor
|
| 151 |
+
algorithm: kl
|
| 152 |
+
? !!python/tuple
|
| 153 |
+
- bert.encoder.layer.1.attention.self.key
|
| 154 |
+
- Linear
|
| 155 |
+
: weight:
|
| 156 |
+
dtype: int8
|
| 157 |
+
scheme: sym
|
| 158 |
+
granularity: per_channel
|
| 159 |
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algorithm: minmax
|
| 160 |
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bit: 7.0
|
| 161 |
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activation:
|
| 162 |
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dtype: uint8
|
| 163 |
+
scheme: sym
|
| 164 |
+
granularity: per_tensor
|
| 165 |
+
algorithm: kl
|
| 166 |
+
? !!python/tuple
|
| 167 |
+
- bert.encoder.layer.1.attention.self.value
|
| 168 |
+
- Linear
|
| 169 |
+
: weight:
|
| 170 |
+
dtype: int8
|
| 171 |
+
scheme: sym
|
| 172 |
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granularity: per_channel
|
| 173 |
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algorithm: minmax
|
| 174 |
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bit: 7.0
|
| 175 |
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activation:
|
| 176 |
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dtype: uint8
|
| 177 |
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scheme: sym
|
| 178 |
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granularity: per_tensor
|
| 179 |
+
algorithm: kl
|
| 180 |
+
? !!python/tuple
|
| 181 |
+
- bert.encoder.layer.1.attention.output.quant
|
| 182 |
+
- QuantStub
|
| 183 |
+
: activation:
|
| 184 |
+
dtype: uint8
|
| 185 |
+
scheme: asym
|
| 186 |
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granularity: per_tensor
|
| 187 |
+
algorithm: minmax
|
| 188 |
+
? !!python/tuple
|
| 189 |
+
- bert.encoder.layer.1.attention.output.dense
|
| 190 |
+
- Linear
|
| 191 |
+
: weight:
|
| 192 |
+
dtype: int8
|
| 193 |
+
scheme: sym
|
| 194 |
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granularity: per_channel
|
| 195 |
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algorithm: minmax
|
| 196 |
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bit: 7.0
|
| 197 |
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activation:
|
| 198 |
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dtype: uint8
|
| 199 |
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scheme: sym
|
| 200 |
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granularity: per_tensor
|
| 201 |
+
algorithm: kl
|
| 202 |
+
? !!python/tuple
|
| 203 |
+
- bert.encoder.layer.1.intermediate.quant
|
| 204 |
+
- QuantStub
|
| 205 |
+
: activation:
|
| 206 |
+
dtype: uint8
|
| 207 |
+
scheme: asym
|
| 208 |
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granularity: per_tensor
|
| 209 |
+
algorithm: minmax
|
| 210 |
+
? !!python/tuple
|
| 211 |
+
- bert.encoder.layer.1.intermediate.dense
|
| 212 |
+
- Linear
|
| 213 |
+
: weight:
|
| 214 |
+
dtype: int8
|
| 215 |
+
scheme: sym
|
| 216 |
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granularity: per_channel
|
| 217 |
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algorithm: minmax
|
| 218 |
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bit: 7.0
|
| 219 |
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activation:
|
| 220 |
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dtype: uint8
|
| 221 |
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scheme: sym
|
| 222 |
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granularity: per_tensor
|
| 223 |
+
algorithm: kl
|
| 224 |
+
? !!python/tuple
|
| 225 |
+
- bert.encoder.layer.1.output.quant
|
| 226 |
+
- QuantStub
|
| 227 |
+
: activation:
|
| 228 |
+
dtype: uint8
|
| 229 |
+
scheme: asym
|
| 230 |
+
granularity: per_tensor
|
| 231 |
+
algorithm: minmax
|
| 232 |
+
? !!python/tuple
|
| 233 |
+
- bert.encoder.layer.1.output.dense
|
| 234 |
+
- Linear
|
| 235 |
+
: weight:
|
| 236 |
+
dtype: int8
|
| 237 |
+
scheme: sym
|
| 238 |
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granularity: per_channel
|
| 239 |
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algorithm: minmax
|
| 240 |
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bit: 7.0
|
| 241 |
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activation:
|
| 242 |
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dtype: uint8
|
| 243 |
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scheme: sym
|
| 244 |
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granularity: per_tensor
|
| 245 |
+
algorithm: kl
|
| 246 |
+
? !!python/tuple
|
| 247 |
+
- bert.encoder.layer.2.attention.self.quant
|
| 248 |
+
- QuantStub
|
| 249 |
+
: activation:
|
| 250 |
+
dtype: uint8
|
| 251 |
+
scheme: asym
|
| 252 |
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granularity: per_tensor
|
| 253 |
+
algorithm: minmax
|
| 254 |
+
? !!python/tuple
|
| 255 |
+
- bert.encoder.layer.2.attention.self.query
|
| 256 |
+
- Linear
|
| 257 |
+
: weight:
|
| 258 |
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dtype: int8
|
| 259 |
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scheme: sym
|
| 260 |
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granularity: per_channel
|
| 261 |
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algorithm: minmax
|
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bit: 7.0
|
| 263 |
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activation:
|
| 264 |
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dtype: uint8
|
| 265 |
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scheme: sym
|
| 266 |
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granularity: per_tensor
|
| 267 |
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algorithm: kl
|
| 268 |
+
? !!python/tuple
|
| 269 |
+
- bert.encoder.layer.2.attention.self.key
|
| 270 |
+
- Linear
|
| 271 |
+
: weight:
|
| 272 |
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dtype: int8
|
| 273 |
+
scheme: sym
|
| 274 |
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granularity: per_channel
|
| 275 |
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algorithm: minmax
|
| 276 |
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bit: 7.0
|
| 277 |
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activation:
|
| 278 |
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dtype: uint8
|
| 279 |
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scheme: sym
|
| 280 |
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granularity: per_tensor
|
| 281 |
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algorithm: kl
|
| 282 |
+
? !!python/tuple
|
| 283 |
+
- bert.encoder.layer.2.attention.self.value
|
| 284 |
+
- Linear
|
| 285 |
+
: weight:
|
| 286 |
+
dtype: int8
|
| 287 |
+
scheme: sym
|
| 288 |
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granularity: per_channel
|
| 289 |
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algorithm: minmax
|
| 290 |
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bit: 7.0
|
| 291 |
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activation:
|
| 292 |
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dtype: uint8
|
| 293 |
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scheme: sym
|
| 294 |
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granularity: per_tensor
|
| 295 |
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algorithm: kl
|
| 296 |
+
? !!python/tuple
|
| 297 |
+
- bert.encoder.layer.2.attention.output.quant
|
| 298 |
+
- QuantStub
|
| 299 |
+
: activation:
|
| 300 |
+
dtype: uint8
|
| 301 |
+
scheme: asym
|
| 302 |
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granularity: per_tensor
|
| 303 |
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algorithm: minmax
|
| 304 |
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? !!python/tuple
|
| 305 |
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- bert.encoder.layer.2.attention.output.dense
|
| 306 |
+
- Linear
|
| 307 |
+
: weight:
|
| 308 |
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dtype: int8
|
| 309 |
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scheme: sym
|
| 310 |
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granularity: per_channel
|
| 311 |
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algorithm: minmax
|
| 312 |
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bit: 7.0
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activation:
|
| 314 |
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dtype: uint8
|
| 315 |
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scheme: sym
|
| 316 |
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granularity: per_tensor
|
| 317 |
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algorithm: kl
|
| 318 |
+
? !!python/tuple
|
| 319 |
+
- bert.encoder.layer.2.intermediate.quant
|
| 320 |
+
- QuantStub
|
| 321 |
+
: activation:
|
| 322 |
+
dtype: uint8
|
| 323 |
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scheme: asym
|
| 324 |
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granularity: per_tensor
|
| 325 |
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algorithm: minmax
|
| 326 |
+
? !!python/tuple
|
| 327 |
+
- bert.encoder.layer.2.intermediate.dense
|
| 328 |
+
- Linear
|
| 329 |
+
: weight:
|
| 330 |
+
dtype: int8
|
| 331 |
+
scheme: sym
|
| 332 |
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granularity: per_channel
|
| 333 |
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algorithm: minmax
|
| 334 |
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bit: 7.0
|
| 335 |
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activation:
|
| 336 |
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dtype: uint8
|
| 337 |
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scheme: sym
|
| 338 |
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granularity: per_tensor
|
| 339 |
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algorithm: kl
|
| 340 |
+
? !!python/tuple
|
| 341 |
+
- bert.encoder.layer.2.output.quant
|
| 342 |
+
- QuantStub
|
| 343 |
+
: activation:
|
| 344 |
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dtype: uint8
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| 345 |
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scheme: asym
|
| 346 |
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granularity: per_tensor
|
| 347 |
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algorithm: minmax
|
| 348 |
+
? !!python/tuple
|
| 349 |
+
- bert.encoder.layer.2.output.dense
|
| 350 |
+
- Linear
|
| 351 |
+
: weight:
|
| 352 |
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dtype: int8
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scheme: sym
|
| 354 |
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granularity: per_channel
|
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algorithm: minmax
|
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bit: 7.0
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activation:
|
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dtype: uint8
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scheme: sym
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| 360 |
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granularity: per_tensor
|
| 361 |
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algorithm: kl
|
| 362 |
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? !!python/tuple
|
| 363 |
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- bert.encoder.layer.3.attention.self.quant
|
| 364 |
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- QuantStub
|
| 365 |
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: activation:
|
| 366 |
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dtype: uint8
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| 367 |
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scheme: asym
|
| 368 |
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granularity: per_tensor
|
| 369 |
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algorithm: minmax
|
| 370 |
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? !!python/tuple
|
| 371 |
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- bert.encoder.layer.3.attention.self.query
|
| 372 |
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- Linear
|
| 373 |
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: weight:
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dtype: int8
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granularity: per_channel
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algorithm: minmax
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bit: 7.0
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activation:
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dtype: uint8
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scheme: sym
|
| 382 |
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granularity: per_tensor
|
| 383 |
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algorithm: kl
|
| 384 |
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? !!python/tuple
|
| 385 |
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- bert.encoder.layer.3.attention.self.key
|
| 386 |
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- Linear
|
| 387 |
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: weight:
|
| 388 |
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dtype: int8
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scheme: sym
|
| 390 |
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granularity: per_channel
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algorithm: minmax
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bit: 7.0
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activation:
|
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dtype: uint8
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scheme: sym
|
| 396 |
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granularity: per_tensor
|
| 397 |
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algorithm: kl
|
| 398 |
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? !!python/tuple
|
| 399 |
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- bert.encoder.layer.3.attention.self.value
|
| 400 |
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- Linear
|
| 401 |
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: weight:
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dtype: int8
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scheme: sym
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granularity: per_channel
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algorithm: minmax
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bit: 7.0
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activation:
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dtype: uint8
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granularity: per_tensor
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algorithm: kl
|
| 412 |
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? !!python/tuple
|
| 413 |
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- bert.encoder.layer.3.attention.output.quant
|
| 414 |
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- QuantStub
|
| 415 |
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: activation:
|
| 416 |
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dtype: uint8
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scheme: asym
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| 418 |
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granularity: per_tensor
|
| 419 |
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algorithm: minmax
|
| 420 |
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? !!python/tuple
|
| 421 |
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|
| 422 |
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- Linear
|
| 423 |
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: weight:
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dtype: int8
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granularity: per_channel
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activation:
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dtype: uint8
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| 432 |
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granularity: per_tensor
|
| 433 |
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algorithm: kl
|
| 434 |
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? !!python/tuple
|
| 435 |
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- bert.encoder.layer.3.intermediate.quant
|
| 436 |
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- QuantStub
|
| 437 |
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: activation:
|
| 438 |
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dtype: uint8
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| 439 |
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scheme: asym
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| 440 |
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granularity: per_tensor
|
| 441 |
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algorithm: minmax
|
| 442 |
+
? !!python/tuple
|
| 443 |
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- bert.encoder.layer.3.intermediate.dense
|
| 444 |
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- Linear
|
| 445 |
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: weight:
|
| 446 |
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dtype: int8
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scheme: sym
|
| 448 |
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granularity: per_channel
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bit: 7.0
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activation:
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dtype: uint8
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scheme: sym
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granularity: per_tensor
|
| 455 |
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algorithm: kl
|
| 456 |
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? !!python/tuple
|
| 457 |
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- bert.encoder.layer.3.output.quant
|
| 458 |
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- QuantStub
|
| 459 |
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: activation:
|
| 460 |
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dtype: uint8
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| 462 |
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granularity: per_tensor
|
| 463 |
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algorithm: minmax
|
| 464 |
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? !!python/tuple
|
| 465 |
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- bert.encoder.layer.3.output.dense
|
| 466 |
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- Linear
|
| 467 |
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: weight:
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| 468 |
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dtype: int8
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granularity: per_channel
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bit: 7.0
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dtype: uint8
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granularity: per_tensor
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| 477 |
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algorithm: kl
|
| 478 |
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? !!python/tuple
|
| 479 |
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- bert.encoder.layer.4.attention.self.quant
|
| 480 |
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- QuantStub
|
| 481 |
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: activation:
|
| 482 |
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dtype: uint8
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| 483 |
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| 484 |
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granularity: per_tensor
|
| 485 |
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algorithm: minmax
|
| 486 |
+
? !!python/tuple
|
| 487 |
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- bert.encoder.layer.4.attention.self.query
|
| 488 |
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- Linear
|
| 489 |
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: weight:
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dtype: int8
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granularity: per_channel
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dtype: uint8
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granularity: per_tensor
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| 499 |
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algorithm: kl
|
| 500 |
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? !!python/tuple
|
| 501 |
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|
| 502 |
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- Linear
|
| 503 |
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: weight:
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dtype: int8
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granularity: per_tensor
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algorithm: kl
|
| 514 |
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? !!python/tuple
|
| 515 |
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- bert.encoder.layer.4.attention.self.value
|
| 516 |
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- Linear
|
| 517 |
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: weight:
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dtype: int8
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granularity: per_channel
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dtype: uint8
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granularity: per_tensor
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algorithm: kl
|
| 528 |
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? !!python/tuple
|
| 529 |
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| 530 |
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- QuantStub
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| 531 |
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: activation:
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granularity: per_tensor
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algorithm: minmax
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| 536 |
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? !!python/tuple
|
| 537 |
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|
| 538 |
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- Linear
|
| 539 |
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: weight:
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dtype: int8
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dtype: uint8
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granularity: per_tensor
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algorithm: kl
|
| 550 |
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? !!python/tuple
|
| 551 |
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| 552 |
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- QuantStub
|
| 553 |
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: activation:
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dtype: uint8
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granularity: per_tensor
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algorithm: minmax
|
| 558 |
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? !!python/tuple
|
| 559 |
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| 560 |
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- Linear
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| 561 |
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: weight:
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dtype: int8
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dtype: uint8
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granularity: per_tensor
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| 571 |
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algorithm: kl
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| 572 |
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? !!python/tuple
|
| 573 |
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| 574 |
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| 575 |
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: activation:
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dtype: uint8
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| 578 |
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granularity: per_tensor
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| 579 |
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algorithm: minmax
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| 580 |
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? !!python/tuple
|
| 581 |
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- bert.encoder.layer.4.output.dense
|
| 582 |
+
- Linear
|
| 583 |
+
: weight:
|
| 584 |
+
dtype: int8
|
| 585 |
+
scheme: sym
|
| 586 |
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granularity: per_channel
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| 587 |
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algorithm: minmax
|
| 588 |
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bit: 7.0
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activation:
|
| 590 |
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dtype: uint8
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scheme: sym
|
| 592 |
+
granularity: per_tensor
|
| 593 |
+
algorithm: kl
|
| 594 |
+
? !!python/tuple
|
| 595 |
+
- bert.encoder.layer.5.attention.self.quant
|
| 596 |
+
- QuantStub
|
| 597 |
+
: activation:
|
| 598 |
+
dtype: uint8
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| 599 |
+
scheme: asym
|
| 600 |
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granularity: per_tensor
|
| 601 |
+
algorithm: minmax
|
| 602 |
+
? !!python/tuple
|
| 603 |
+
- bert.encoder.layer.5.attention.self.query
|
| 604 |
+
- Linear
|
| 605 |
+
: weight:
|
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+
dtype: int8
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+
scheme: sym
|
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granularity: per_channel
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bit: 7.0
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activation:
|
| 612 |
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dtype: uint8
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scheme: sym
|
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granularity: per_tensor
|
| 615 |
+
algorithm: kl
|
| 616 |
+
? !!python/tuple
|
| 617 |
+
- bert.encoder.layer.5.attention.self.key
|
| 618 |
+
- Linear
|
| 619 |
+
: weight:
|
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dtype: int8
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scheme: sym
|
| 622 |
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granularity: per_channel
|
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algorithm: minmax
|
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bit: 7.0
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activation:
|
| 626 |
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dtype: uint8
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scheme: sym
|
| 628 |
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granularity: per_tensor
|
| 629 |
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algorithm: kl
|
| 630 |
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? !!python/tuple
|
| 631 |
+
- bert.encoder.layer.5.attention.self.value
|
| 632 |
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- Linear
|
| 633 |
+
: weight:
|
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dtype: int8
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granularity: per_channel
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algorithm: minmax
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bit: 7.0
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activation:
|
| 640 |
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dtype: uint8
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scheme: sym
|
| 642 |
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granularity: per_tensor
|
| 643 |
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algorithm: kl
|
| 644 |
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? !!python/tuple
|
| 645 |
+
- bert.encoder.layer.5.attention.output.quant
|
| 646 |
+
- QuantStub
|
| 647 |
+
: activation:
|
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dtype: uint8
|
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scheme: asym
|
| 650 |
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granularity: per_tensor
|
| 651 |
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algorithm: minmax
|
| 652 |
+
? !!python/tuple
|
| 653 |
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- bert.encoder.layer.5.attention.output.dense
|
| 654 |
+
- Linear
|
| 655 |
+
: weight:
|
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dtype: int8
|
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scheme: sym
|
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granularity: per_channel
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algorithm: minmax
|
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bit: 7.0
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activation:
|
| 662 |
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dtype: uint8
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scheme: sym
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granularity: per_tensor
|
| 665 |
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algorithm: kl
|
| 666 |
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? !!python/tuple
|
| 667 |
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- bert.encoder.layer.5.intermediate.quant
|
| 668 |
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- QuantStub
|
| 669 |
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: activation:
|
| 670 |
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dtype: uint8
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scheme: asym
|
| 672 |
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granularity: per_tensor
|
| 673 |
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algorithm: minmax
|
| 674 |
+
? !!python/tuple
|
| 675 |
+
- bert.encoder.layer.5.intermediate.dense
|
| 676 |
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- Linear
|
| 677 |
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: weight:
|
| 678 |
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dtype: int8
|
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scheme: sym
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| 680 |
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granularity: per_channel
|
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algorithm: minmax
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bit: 7.0
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activation:
|
| 684 |
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dtype: uint8
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scheme: sym
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granularity: per_tensor
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algorithm: kl
|
| 688 |
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? !!python/tuple
|
| 689 |
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- bert.encoder.layer.5.output.quant
|
| 690 |
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- QuantStub
|
| 691 |
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: activation:
|
| 692 |
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dtype: uint8
|
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scheme: asym
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| 694 |
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granularity: per_tensor
|
| 695 |
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algorithm: minmax
|
| 696 |
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? !!python/tuple
|
| 697 |
+
- bert.encoder.layer.5.output.dense
|
| 698 |
+
- Linear
|
| 699 |
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: weight:
|
| 700 |
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dtype: int8
|
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scheme: sym
|
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granularity: per_channel
|
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algorithm: minmax
|
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bit: 7.0
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activation:
|
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dtype: uint8
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scheme: sym
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| 708 |
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granularity: per_tensor
|
| 709 |
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algorithm: kl
|
| 710 |
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? !!python/tuple
|
| 711 |
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- bert.encoder.layer.6.attention.self.quant
|
| 712 |
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- QuantStub
|
| 713 |
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: activation:
|
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dtype: uint8
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scheme: asym
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granularity: per_tensor
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algorithm: minmax
|
| 718 |
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? !!python/tuple
|
| 719 |
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|
| 720 |
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- Linear
|
| 721 |
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: weight:
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dtype: int8
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scheme: sym
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| 724 |
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granularity: per_channel
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algorithm: minmax
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bit: 7.0
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activation:
|
| 728 |
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dtype: uint8
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scheme: sym
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| 730 |
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granularity: per_tensor
|
| 731 |
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algorithm: kl
|
| 732 |
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? !!python/tuple
|
| 733 |
+
- bert.encoder.layer.6.attention.self.key
|
| 734 |
+
- Linear
|
| 735 |
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: weight:
|
| 736 |
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dtype: int8
|
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scheme: sym
|
| 738 |
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granularity: per_channel
|
| 739 |
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algorithm: minmax
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| 740 |
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bit: 7.0
|
| 741 |
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activation:
|
| 742 |
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dtype: uint8
|
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scheme: sym
|
| 744 |
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granularity: per_tensor
|
| 745 |
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algorithm: kl
|
| 746 |
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? !!python/tuple
|
| 747 |
+
- bert.encoder.layer.6.attention.self.value
|
| 748 |
+
- Linear
|
| 749 |
+
: weight:
|
| 750 |
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dtype: int8
|
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scheme: sym
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| 752 |
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granularity: per_channel
|
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algorithm: minmax
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bit: 7.0
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| 755 |
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activation:
|
| 756 |
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dtype: uint8
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scheme: sym
|
| 758 |
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granularity: per_tensor
|
| 759 |
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algorithm: kl
|
| 760 |
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? !!python/tuple
|
| 761 |
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- bert.encoder.layer.6.attention.output.quant
|
| 762 |
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- QuantStub
|
| 763 |
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: activation:
|
| 764 |
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dtype: uint8
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scheme: asym
|
| 766 |
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granularity: per_tensor
|
| 767 |
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algorithm: minmax
|
| 768 |
+
? !!python/tuple
|
| 769 |
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- bert.encoder.layer.6.attention.output.dense
|
| 770 |
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- Linear
|
| 771 |
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: weight:
|
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dtype: int8
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granularity: per_channel
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bit: 7.0
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activation:
|
| 778 |
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dtype: uint8
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| 780 |
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granularity: per_tensor
|
| 781 |
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algorithm: kl
|
| 782 |
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? !!python/tuple
|
| 783 |
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- bert.encoder.layer.6.intermediate.quant
|
| 784 |
+
- QuantStub
|
| 785 |
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: activation:
|
| 786 |
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dtype: uint8
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scheme: asym
|
| 788 |
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granularity: per_tensor
|
| 789 |
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algorithm: minmax
|
| 790 |
+
? !!python/tuple
|
| 791 |
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- bert.encoder.layer.6.intermediate.dense
|
| 792 |
+
- Linear
|
| 793 |
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: weight:
|
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dtype: int8
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scheme: sym
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granularity: per_channel
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algorithm: minmax
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| 798 |
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bit: 7.0
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| 799 |
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activation:
|
| 800 |
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dtype: uint8
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scheme: sym
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granularity: per_tensor
|
| 803 |
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algorithm: kl
|
| 804 |
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? !!python/tuple
|
| 805 |
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- bert.encoder.layer.6.output.quant
|
| 806 |
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- QuantStub
|
| 807 |
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: activation:
|
| 808 |
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dtype: uint8
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scheme: asym
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| 810 |
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granularity: per_tensor
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algorithm: minmax
|
| 812 |
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? !!python/tuple
|
| 813 |
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|
| 814 |
+
- Linear
|
| 815 |
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: weight:
|
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dtype: int8
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scheme: sym
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| 818 |
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granularity: per_channel
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bit: 7.0
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activation:
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dtype: uint8
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| 824 |
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granularity: per_tensor
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| 825 |
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algorithm: kl
|
| 826 |
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? !!python/tuple
|
| 827 |
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- bert.encoder.layer.7.attention.self.quant
|
| 828 |
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- QuantStub
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| 829 |
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: activation:
|
| 830 |
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dtype: uint8
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scheme: asym
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| 832 |
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granularity: per_tensor
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| 833 |
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algorithm: minmax
|
| 834 |
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? !!python/tuple
|
| 835 |
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- bert.encoder.layer.7.attention.self.query
|
| 836 |
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- Linear
|
| 837 |
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: weight:
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dtype: int8
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activation:
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granularity: per_tensor
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algorithm: kl
|
| 848 |
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? !!python/tuple
|
| 849 |
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|
| 850 |
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- Linear
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: weight:
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dtype: int8
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activation:
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dtype: uint8
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granularity: per_tensor
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algorithm: kl
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| 862 |
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? !!python/tuple
|
| 863 |
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|
| 864 |
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- Linear
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| 865 |
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: weight:
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dtype: int8
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activation:
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dtype: uint8
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granularity: per_tensor
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algorithm: kl
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| 876 |
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? !!python/tuple
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| 877 |
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- bert.encoder.layer.7.attention.output.quant
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| 878 |
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- QuantStub
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| 879 |
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: activation:
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| 880 |
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dtype: uint8
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granularity: per_tensor
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algorithm: minmax
|
| 884 |
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? !!python/tuple
|
| 885 |
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- bert.encoder.layer.7.attention.output.dense
|
| 886 |
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- Linear
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| 887 |
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: weight:
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| 890 |
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activation:
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dtype: uint8
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granularity: per_tensor
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algorithm: kl
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| 898 |
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? !!python/tuple
|
| 899 |
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| 900 |
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- QuantStub
|
| 901 |
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: activation:
|
| 902 |
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dtype: uint8
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granularity: per_tensor
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algorithm: minmax
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| 906 |
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? !!python/tuple
|
| 907 |
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- bert.encoder.layer.7.intermediate.dense
|
| 908 |
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- Linear
|
| 909 |
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: weight:
|
| 910 |
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dtype: int8
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| 912 |
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activation:
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granularity: per_tensor
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| 920 |
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? !!python/tuple
|
| 921 |
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| 922 |
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- QuantStub
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| 923 |
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: activation:
|
| 924 |
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dtype: uint8
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granularity: per_tensor
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algorithm: minmax
|
| 928 |
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? !!python/tuple
|
| 929 |
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|
| 930 |
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- Linear
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| 931 |
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: weight:
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activation:
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granularity: per_tensor
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algorithm: kl
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| 942 |
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? !!python/tuple
|
| 943 |
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- bert.encoder.layer.8.attention.self.quant
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| 944 |
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- QuantStub
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| 945 |
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: activation:
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dtype: uint8
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granularity: per_tensor
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|
| 950 |
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? !!python/tuple
|
| 951 |
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| 952 |
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- Linear
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| 953 |
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: weight:
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granularity: per_tensor
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| 964 |
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? !!python/tuple
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| 965 |
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| 966 |
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- Linear
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| 967 |
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: weight:
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dtype: int8
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|
| 978 |
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? !!python/tuple
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| 979 |
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| 980 |
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- Linear
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| 981 |
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: weight:
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activation:
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dtype: uint8
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granularity: per_tensor
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| 992 |
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? !!python/tuple
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| 993 |
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dtype: uint8
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granularity: per_tensor
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| 999 |
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| 1000 |
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? !!python/tuple
|
| 1001 |
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| 1002 |
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- Linear
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| 1003 |
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: weight:
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dtype: int8
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algorithm: kl
|
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? !!python/tuple
|
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? !!python/tuple
|
| 1023 |
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? !!python/tuple
|
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? !!python/tuple
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| 1045 |
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? !!python/tuple
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? !!python/tuple
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? !!python/tuple
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? !!python/tuple
|
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? !!python/tuple
|
| 1131 |
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? !!python/tuple
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| 1140 |
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? !!python/tuple
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|
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? !!python/tuple
|
| 1161 |
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|
| 1162 |
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? !!python/tuple
|
| 1175 |
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|
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? !!python/tuple
|
| 1183 |
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? !!python/tuple
|
| 1197 |
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|
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? !!python/tuple
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|
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| 1224 |
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? !!python/tuple
|
| 1225 |
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|
| 1226 |
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| 1227 |
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| 1228 |
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? !!python/tuple
|
| 1233 |
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|
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? !!python/tuple
|
| 1247 |
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| 1248 |
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| 1250 |
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? !!python/tuple
|
| 1255 |
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|
| 1256 |
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| 1257 |
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|
| 1278 |
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| 1299 |
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|
| 1300 |
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| 1313 |
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|
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| 1340 |
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? !!python/tuple
|
| 1341 |
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|
| 1342 |
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|
| 1343 |
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|
| 1344 |
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? !!python/tuple
|
| 1349 |
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|
| 1350 |
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|
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? !!python/tuple
|
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|
| 1364 |
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| 1366 |
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|
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? !!python/tuple
|
| 1371 |
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|
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| 1373 |
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| 1374 |
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|
| 1380 |
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|
| 1381 |
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|
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|
| 1384 |
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? !!python/tuple
|
| 1385 |
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|
| 1386 |
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|
| 1387 |
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|
| 1388 |
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dtype: uint8
|
| 1389 |
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|
| 1390 |
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|
| 1391 |
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|
| 1392 |
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? !!python/tuple
|
| 1393 |
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|
| 1394 |
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|
| 1395 |
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: weight:
|
| 1396 |
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| 1397 |
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|
| 1398 |
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granularity: per_channel
|
| 1399 |
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|
| 1400 |
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|
| 1401 |
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|
| 1402 |
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|
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|
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|
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|
| 1406 |
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? !!python/tuple
|
| 1407 |
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|
| 1408 |
+
- QuantStub
|
| 1409 |
+
: activation:
|
| 1410 |
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dtype: uint8
|
| 1411 |
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scheme: asym
|
| 1412 |
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granularity: per_tensor
|
| 1413 |
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|
| 1414 |
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? !!python/tuple
|
| 1415 |
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|
| 1416 |
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- Linear
|
| 1417 |
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: weight:
|
| 1418 |
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dtype: int8
|
| 1419 |
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|
| 1420 |
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granularity: per_channel
|
| 1421 |
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|
| 1422 |
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|
| 1423 |
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|
| 1424 |
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dtype: uint8
|
| 1425 |
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|
| 1426 |
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granularity: per_tensor
|
| 1427 |
+
algorithm: kl
|
| 1428 |
+
? !!python/tuple
|
| 1429 |
+
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|
| 1430 |
+
- Linear
|
| 1431 |
+
: weight:
|
| 1432 |
+
dtype: int8
|
| 1433 |
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scheme: sym
|
| 1434 |
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granularity: per_channel
|
| 1435 |
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algorithm: minmax
|
| 1436 |
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bit: 7.0
|
| 1437 |
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|
| 1438 |
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dtype: uint8
|
| 1439 |
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|
| 1440 |
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granularity: per_tensor
|
| 1441 |
+
algorithm: kl
|
pytorch_model.bin
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:179044d0850f8afbccb6984920932163008d58888bad9c938d7d26ea548f936b
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size 182910677
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quantization.yml
ADDED
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device: cpu
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model:
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framework: pytorch
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name: bert
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quantization:
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approach: post_training_static_quant
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tuning:
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accuracy_criterion:
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relative: 0.01
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exit_policy:
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max_trials: 1200
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timeout: 0
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random_seed: 9527
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version: 1.0
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special_tokens_map.json
ADDED
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{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}
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tokenizer_config.json
ADDED
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{"do_lower_case": true, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "model_max_length": 512, "special_tokens_map_file": "/home/ella/.cache/huggingface/transformers/c7c9b9c5d8bab3ba2ddaa08b138aa385f9790f30e8dce3bfe47e3f10bd97f4ad.dd8bd9bfd3664b530ea4e645105f557769387b3da9f79bdb55ed556bdd80611d", "name_or_path": "textattack/bert-base-uncased-SST-2", "do_basic_tokenize": true, "never_split": null, "tokenizer_class": "BertTokenizer"}
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training_args.bin
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:c152f8d6703bcfb25907ed7f88687985141b19e631a632e3a8923f6e07defe49
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| 3 |
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size 2671
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vocab.txt
ADDED
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