|
19 | 19 | "name": "config_file",
|
20 | 20 | "type": str,
|
21 | 21 | "default": argparse.SUPPRESS,
|
22 |
| - "help": "specify model configuration file", |
| 22 | + "help": "Specify alternate model configuration file", |
23 | 23 | },
|
24 | 24 | {
|
25 | 25 | "name": "data_type",
|
26 | 26 | "abv": "d",
|
27 | 27 | "type": str,
|
28 | 28 | "default": argparse.SUPPRESS,
|
29 | 29 | "choices": ["f16", "f32", "f64"],
|
30 |
| - "help": "default floating point.", |
| 30 | + "help": "Specify default floating points precision", |
31 | 31 | },
|
32 | 32 | {
|
33 | 33 | "name": "rng_seed",
|
34 | 34 | "abv": "r",
|
35 | 35 | "type": int,
|
36 | 36 | "default": argparse.SUPPRESS,
|
37 |
| - "help": "random number generator seed.", |
| 37 | + "help": "Random number generator seed", |
38 | 38 | },
|
39 | 39 | {
|
40 | 40 | "name": "train_bool",
|
41 | 41 | "type": hutils.str2bool,
|
42 | 42 | "default": True,
|
43 |
| - "help": "train model.", |
| 43 | + "help": "Flag to toggle model training", |
44 | 44 | },
|
45 | 45 | {
|
46 | 46 | "name": "eval_bool",
|
47 | 47 | "type": hutils.str2bool,
|
48 | 48 | "default": argparse.SUPPRESS,
|
49 |
| - "help": "evaluate model (use it for inference).", |
| 49 | + "help": "Flag to evaluate model (use it for inference).", |
50 | 50 | },
|
51 | 51 | {
|
52 | 52 | "name": "timeout",
|
53 | 53 | "action": "store",
|
54 | 54 | "type": int,
|
55 | 55 | "default": argparse.SUPPRESS,
|
56 |
| - "help": "seconds allowed to train model (default: no timeout).", |
| 56 | + "help": "Maximum time in seconds allowed to train model (default: no timeout).", |
57 | 57 | },
|
58 | 58 | {
|
59 | 59 | "name": "gpus",
|
60 | 60 | "nargs": "+",
|
61 | 61 | "type": int,
|
62 | 62 | "default": argparse.SUPPRESS,
|
63 |
| - "help": "set IDs of GPUs to use.", |
| 63 | + "help": "Set IDs of GPUs to use.", |
64 | 64 | },
|
65 | 65 | {
|
66 | 66 | "name": "profiling",
|
|
77 | 77 | "abv": "s",
|
78 | 78 | "type": str,
|
79 | 79 | "default": argparse.SUPPRESS,
|
80 |
| - "help": "file path to save model snapshots.", |
| 80 | + "help": "File path to save model snapshots.", |
81 | 81 | },
|
82 | 82 | {
|
83 | 83 | "name": "model_name",
|
84 | 84 | "type": str,
|
85 | 85 | "default": argparse.SUPPRESS,
|
86 |
| - "help": "specify model name to use when building filenames for saving.", |
| 86 | + "help": "Specify model name to use when building filenames for saving.", |
87 | 87 | },
|
88 | 88 | {
|
89 | 89 | "name": "home_dir",
|
90 | 90 | "type": str,
|
91 | 91 | "default": argparse.SUPPRESS,
|
92 |
| - "help": "set home directory.", |
| 92 | + "help": "Set home directory.", |
93 | 93 | },
|
94 | 94 | {
|
95 | 95 | "name": "train_data",
|
96 | 96 | "action": "store",
|
97 | 97 | "type": str,
|
98 | 98 | "default": argparse.SUPPRESS,
|
99 |
| - "help": "training data filename.", |
| 99 | + "help": "Training data filename.", |
100 | 100 | },
|
101 | 101 | {
|
102 | 102 | "name": "val_data",
|
103 | 103 | "action": "store",
|
104 | 104 | "type": str,
|
105 | 105 | "default": argparse.SUPPRESS,
|
106 |
| - "help": "validation data filename.", |
| 106 | + "help": "Validation data filename.", |
107 | 107 | },
|
108 | 108 | {
|
109 | 109 | "name": "test_data",
|
110 | 110 | "type": str,
|
111 | 111 | "action": "store",
|
112 | 112 | "default": argparse.SUPPRESS,
|
113 |
| - "help": "testing data filename.", |
| 113 | + "help": "Testing data filename.", |
114 | 114 | },
|
115 | 115 | {
|
116 | 116 | "name": "output_dir",
|
117 | 117 | "type": str,
|
118 | 118 | "default": argparse.SUPPRESS,
|
119 |
| - "help": "output directory.", |
| 119 | + "help": "Set output directory.", |
120 | 120 | },
|
121 | 121 | {
|
122 | 122 | "name": "data_url",
|
123 | 123 | "type": str,
|
124 | 124 | "default": argparse.SUPPRESS,
|
125 |
| - "help": "set data source url.", |
| 125 | + "help": "Set data source url.", |
126 | 126 | },
|
127 | 127 | {
|
128 | 128 | "name": "experiment_id",
|
129 | 129 | "type": str,
|
130 | 130 | "default": "EXP000",
|
131 |
| - "help": "set the experiment unique identifier.", |
| 131 | + "help": "Set the experiment unique identifier.", |
132 | 132 | },
|
133 | 133 | {
|
134 | 134 | "name": "run_id",
|
135 | 135 | "type": str,
|
136 | 136 | "default": "RUN000",
|
137 |
| - "help": "set the run unique identifier.", |
| 137 | + "help": "Set the run unique identifier.", |
138 | 138 | },
|
139 | 139 | ]
|
140 | 140 |
|
|
144 | 144 | "abv": "v",
|
145 | 145 | "type": hutils.str2bool,
|
146 | 146 | "default": False,
|
147 |
| - "help": "increase output verbosity.", |
| 147 | + "help": "Increase output verbosity.", |
148 | 148 | },
|
149 | 149 | {"name": "logfile", "abv": "l", "type": str, "default": None, "help": "log file"},
|
150 | 150 | ]
|
|
155 | 155 | "type": str,
|
156 | 156 | "default": argparse.SUPPRESS,
|
157 | 157 | "choices": ["minabs", "minmax", "std", "none"],
|
158 |
| - "help": "type of feature scaling; 'minabs': to [-1,1]; 'minmax': to [0,1], 'std': standard unit normalization; 'none': no normalization.", |
| 158 | + "help": "Type of feature scaling; 'minabs': to [-1,1]; 'minmax': to [0,1], 'std': standard unit normalization; 'none': no normalization.", |
159 | 159 | },
|
160 | 160 | {
|
161 | 161 | "name": "shuffle",
|
162 | 162 | "type": hutils.str2bool,
|
163 | 163 | "default": False,
|
164 |
| - "help": "randomly shuffle data set (produces different training and testing partitions each run depending on the seed)", |
| 164 | + "help": "Randomly shuffle data set (produces different training and testing partitions each run depending on the seed)", |
165 | 165 | },
|
166 | 166 | {
|
167 | 167 | "name": "feature_subsample",
|
168 | 168 | "type": int,
|
169 | 169 | "default": argparse.SUPPRESS,
|
170 |
| - "help": "number of features to randomly sample from each category (cellline expression, drug descriptors, etc), 0 means using all features", |
| 170 | + "help": "Number of features to randomly sample from each category (cellline expression, drug descriptors, etc), 0 means using all features", |
171 | 171 | },
|
172 | 172 | ]
|
173 | 173 |
|
|
176 | 176 | "name": "dense",
|
177 | 177 | "nargs": "+",
|
178 | 178 | "type": int,
|
179 |
| - "help": "number of units in fully connected layers in an integer array.", |
| 179 | + "help": "Number of units in fully connected layers in an integer array.", |
180 | 180 | },
|
181 | 181 | {
|
182 | 182 | "name": "conv",
|
183 | 183 | "nargs": "+",
|
184 | 184 | "type": int,
|
185 | 185 | "default": argparse.SUPPRESS,
|
186 |
| - "help": "integer array describing convolution layers: conv1_filters, conv1_filter_len, conv1_stride, conv2_filters, conv2_filter_len, conv2_stride ....", |
| 186 | + "help": "Integer array describing convolution layers: conv1_filters, conv1_filter_len, conv1_stride, conv2_filters, conv2_filter_len, conv2_stride ....", |
187 | 187 | },
|
188 | 188 | {
|
189 | 189 | "name": "locally_connected",
|
190 | 190 | "type": hutils.str2bool,
|
191 | 191 | "default": argparse.SUPPRESS,
|
192 |
| - "help": "use locally connected layers instead of convolution layers.", |
| 192 | + "help": "Use locally connected layers instead of convolution layers.", |
193 | 193 | },
|
194 | 194 | {
|
195 | 195 | "name": "activation",
|
196 | 196 | "abv": "a",
|
197 | 197 | "type": str,
|
198 | 198 | "default": argparse.SUPPRESS,
|
199 |
| - "help": "keras activation function to use in inner layers: relu, tanh, sigmoid...", |
| 199 | + "help": "Activation function to use in inner layers: relu, tanh, sigmoid...", |
200 | 200 | },
|
201 | 201 | {
|
202 | 202 | "name": "out_activation",
|
203 | 203 | "type": str,
|
204 | 204 | "default": argparse.SUPPRESS,
|
205 |
| - "help": "keras activation function to use in out layer: softmax, linear, ...", |
| 205 | + "help": "Activation function to use in out layer: softmax, linear, ...", |
206 | 206 | },
|
207 | 207 | {
|
208 | 208 | "name": "lstm_size",
|
209 | 209 | "nargs": "+",
|
210 | 210 | "type": int,
|
211 | 211 | "default": argparse.SUPPRESS,
|
212 |
| - "help": "integer array describing size of LSTM internal state per layer.", |
| 212 | + "help": "Integer array describing size of LSTM internal state per layer.", |
213 | 213 | },
|
214 | 214 | {
|
215 | 215 | "name": "recurrent_dropout",
|
216 | 216 | "action": "store",
|
217 | 217 | "type": float,
|
218 | 218 | "default": argparse.SUPPRESS,
|
219 |
| - "help": "ratio of recurrent dropout.", |
| 219 | + "help": "Ratio of recurrent dropout.", |
220 | 220 | },
|
221 | 221 | {
|
222 | 222 | "name": "dropout",
|
223 | 223 | "type": float,
|
224 | 224 | "default": argparse.SUPPRESS,
|
225 |
| - "help": "ratio of dropout used in fully connected layers.", |
| 225 | + "help": "Ratio of dropout used in fully connected layers.", |
226 | 226 | },
|
227 | 227 | {
|
228 | 228 | "name": "pool",
|
229 | 229 | "type": int,
|
230 | 230 | "default": argparse.SUPPRESS,
|
231 |
| - "help": "pooling layer length.", |
| 231 | + "help": "Pooling layer length.", |
232 | 232 | },
|
233 | 233 | {
|
234 | 234 | "name": "batch_normalization",
|
235 | 235 | "type": hutils.str2bool,
|
236 | 236 | "default": argparse.SUPPRESS,
|
237 |
| - "help": "use batch normalization.", |
| 237 | + "help": "Use batch normalization.", |
238 | 238 | },
|
239 | 239 | {
|
240 | 240 | "name": "loss",
|
241 | 241 | "type": str,
|
242 | 242 | "default": argparse.SUPPRESS,
|
243 |
| - "help": "keras loss function to use: mse, ...", |
| 243 | + "help": "Loss function to use: mse, ...", |
244 | 244 | },
|
245 | 245 | {
|
246 | 246 | "name": "optimizer",
|
247 | 247 | "type": str,
|
248 | 248 | "default": argparse.SUPPRESS,
|
249 |
| - "help": "keras optimizer to use: sgd, rmsprop, ...", |
| 249 | + "help": "Optimizer to use: sgd, rmsprop, ...", |
250 | 250 | },
|
251 | 251 | {
|
252 | 252 | "name": "metrics",
|
253 | 253 | "type": str,
|
254 | 254 | "default": argparse.SUPPRESS,
|
255 |
| - "help": "metrics to evaluate performance: accuracy, ...", |
| 255 | + "help": "Metrics to evaluate performance: accuracy, ...", |
256 | 256 | },
|
257 | 257 | ]
|
258 | 258 |
|
|
262 | 262 | "type": int,
|
263 | 263 | "abv": "e",
|
264 | 264 | "default": argparse.SUPPRESS,
|
265 |
| - "help": "number of training epochs.", |
| 265 | + "help": "Number of training epochs.", |
266 | 266 | },
|
267 | 267 | {
|
268 | 268 | "name": "batch_size",
|
269 | 269 | "type": int,
|
270 | 270 | "abv": "z",
|
271 | 271 | "default": argparse.SUPPRESS,
|
272 |
| - "help": "batch size.", |
| 272 | + "help": "Batch size.", |
273 | 273 | },
|
274 | 274 | {
|
275 | 275 | "name": "learning_rate",
|
276 | 276 | "abv": "lr",
|
277 | 277 | "type": float,
|
278 | 278 | "default": argparse.SUPPRESS,
|
279 |
| - "help": "overrides the learning rate for training.", |
| 279 | + "help": "Overrides the default learning rate for training.", |
280 | 280 | },
|
281 | 281 | {
|
282 | 282 | "name": "early_stop",
|
283 | 283 | "type": hutils.str2bool,
|
284 | 284 | "default": argparse.SUPPRESS,
|
285 |
| - "help": "activates keras callback for early stopping of training in function of the monitored variable specified.", |
| 285 | + "help": "Activates keras callback for early stopping of training in function of the monitored variable specified.", |
286 | 286 | },
|
287 | 287 | {
|
288 | 288 | "name": "momentum",
|
289 | 289 | "type": float,
|
290 | 290 | "default": argparse.SUPPRESS,
|
291 |
| - "help": "overrides the momentum to use in the SGD optimizer when training.", |
| 291 | + "help": "Overrides the default momentum to use in the SGD optimizer when training.", |
292 | 292 | },
|
293 | 293 | {
|
294 | 294 | "name": "initialization",
|
|
303 | 303 | "lecun_uniform",
|
304 | 304 | "he_normal",
|
305 | 305 | ],
|
306 |
| - "help": "type of weight initialization; 'constant': to 0; 'uniform': to [-0.05,0.05], 'normal': mean 0, stddev 0.05; 'glorot_uniform': [-lim,lim] with lim = sqrt(6/(fan_in+fan_out)); 'lecun_uniform' : [-lim,lim] with lim = sqrt(3/fan_in); 'he_normal' : mean 0, stddev sqrt(2/fan_in).", |
| 306 | + "help": "Type of weight initialization; 'constant': to 0; 'uniform': to [-0.05,0.05], 'normal': mean 0, stddev 0.05; 'glorot_uniform': [-lim,lim] with lim = sqrt(6/(fan_in+fan_out)); 'lecun_uniform' : [-lim,lim] with lim = sqrt(3/fan_in); 'he_normal' : mean 0, stddev sqrt(2/fan_in).", |
307 | 307 | },
|
308 | 308 | {
|
309 | 309 | "name": "val_split",
|
310 | 310 | "type": float,
|
311 | 311 | "default": argparse.SUPPRESS,
|
312 |
| - "help": "fraction of data to use in validation.", |
| 312 | + "help": "Fraction of data to use in validation.", |
313 | 313 | },
|
314 | 314 | {
|
315 | 315 | "name": "train_steps",
|
316 | 316 | "type": int,
|
317 | 317 | "default": argparse.SUPPRESS,
|
318 |
| - "help": "overrides the number of training batches per epoch if set to nonzero.", |
| 318 | + "help": "Overrides the number of training batches per epoch if set to nonzero.", |
319 | 319 | },
|
320 | 320 | {
|
321 | 321 | "name": "val_steps",
|
322 | 322 | "type": int,
|
323 | 323 | "default": argparse.SUPPRESS,
|
324 |
| - "help": "overrides the number of validation batches per epoch if set to nonzero.", |
| 324 | + "help": "Overrides the number of validation batches per epoch if set to nonzero.", |
325 | 325 | },
|
326 | 326 | {
|
327 | 327 | "name": "test_steps",
|
328 | 328 | "type": int,
|
329 | 329 | "default": argparse.SUPPRESS,
|
330 |
| - "help": "overrides the number of test batches per epoch if set to nonzero.", |
| 330 | + "help": "Overrides the number of test batches per epoch if set to nonzero.", |
331 | 331 | },
|
332 | 332 | {
|
333 | 333 | "name": "train_samples",
|
334 | 334 | "type": int,
|
335 | 335 | "default": argparse.SUPPRESS,
|
336 |
| - "help": "overrides the number of training samples if set to nonzero.", |
| 336 | + "help": "Overrides the number of training samples if set to nonzero.", |
337 | 337 | },
|
338 | 338 | {
|
339 | 339 | "name": "val_samples",
|
340 | 340 | "type": int,
|
341 | 341 | "default": argparse.SUPPRESS,
|
342 |
| - "help": "overrides the number of validation samples if set to nonzero.", |
| 342 | + "help": "Overrides the number of validation samples if set to nonzero.", |
343 | 343 | },
|
344 | 344 | ]
|
345 | 345 |
|
|
362 | 362 | "name": "clr_base_lr",
|
363 | 363 | "type": float,
|
364 | 364 | "default": argparse.SUPPRESS,
|
365 |
| - "help": "Base lr for cycle lr.", |
| 365 | + "help": "Base lr for cyclic lr.", |
366 | 366 | },
|
367 | 367 | {
|
368 | 368 | "name": "clr_max_lr",
|
369 | 369 | "type": float,
|
370 | 370 | "default": argparse.SUPPRESS,
|
371 |
| - "help": "Max lr for cycle lr.", |
| 371 | + "help": "Max lr for cyclic lr.", |
372 | 372 | },
|
373 | 373 | {
|
374 | 374 | "name": "clr_gamma",
|
375 | 375 | "type": float,
|
376 | 376 | "default": argparse.SUPPRESS,
|
377 |
| - "help": "Gamma parameter for learning cycle LR.", |
| 377 | + "help": "Gamma parameter for cyclic LR.", |
378 | 378 | },
|
379 | 379 | ]
|
380 | 380 |
|
|
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