Remove solr_root from README files

Author: jmohdyusof

Pilot1/Attn/README.md

@@ -9,7 +9,7 @@ Any file of the form top*21_1fold*"ijk".h5 can be used as input
 
 ```
 python attn_baseline_keras2.py
-Params: {'model_name': 'attn', 'dense': [2000, 600], 'batch_size': 32, 'epochs': 1, 'activation': 'relu', 'loss': 'categorical_crossentropy', 'optimizer': 'sgd', 'drop': 0.2, 'learning_rate': 1e-05, 'momentum': 0.7, 'scaling': 'minmax', 'validation_split': 0.1, 'epsilon_std': 1.0, 'rng_seed': 2017, 'initialization': 'glorot_uniform', 'latent_dim': 2, 'batch_normalization': False, 'in': 'top_21_1fold_001.h5', 'save_path': 'candle_save', 'save_dir': './save/001/', 'use_cp': False, 'early_stop': True, 'reduce_lr': True, 'feature_subsample': 0, 'nb_classes': 2, 'solr_root': '', 'timeout': 3600, 'verbose': None, 'logfile': None, 'train_bool': True, 'experiment_id': 'EXP000', 'run_id': 'RUN000', 'shuffle': False, 'gpus': [], 'profiling': False, 'residual': False, 'warmup_lr': False, 'use_tb': False, 'tsne': False, 'datatype': <class 'numpy.float32'>, 'output_dir': '/nfs2/jain/Benchmarks/Pilot1/Attn/Output/EXP000/RUN000'}
+Params: {'model_name': 'attn', 'dense': [2000, 600], 'batch_size': 32, 'epochs': 1, 'activation': 'relu', 'loss': 'categorical_crossentropy', 'optimizer': 'sgd', 'drop': 0.2, 'learning_rate': 1e-05, 'momentum': 0.7, 'scaling': 'minmax', 'validation_split': 0.1, 'epsilon_std': 1.0, 'rng_seed': 2017, 'initialization': 'glorot_uniform', 'latent_dim': 2, 'batch_normalization': False, 'in': 'top_21_1fold_001.h5', 'save_path': 'candle_save', 'save_dir': './save/001/', 'use_cp': False, 'early_stop': True, 'reduce_lr': True, 'feature_subsample': 0, 'nb_classes': 2, 'timeout': 3600, 'verbose': None, 'logfile': None, 'train_bool': True, 'experiment_id': 'EXP000', 'run_id': 'RUN000', 'shuffle': False, 'gpus': [], 'profiling': False, 'residual': False, 'warmup_lr': False, 'use_tb': False, 'tsne': False, 'datatype': <class 'numpy.float32'>, 'output_dir': '/nfs2/jain/Benchmarks/Pilot1/Attn/Output/EXP000/RUN000'}
 ...
 ...
 processing h5 in file top_21_1fold_001.h5

Pilot1/Combo/README.md

@@ -39,7 +39,7 @@ $ python combo_baseline_keras2.py
 python combo_baseline_keras2.py --use_landmark_genes --warmup_lr --reduce_lr -z 256
 
 Using TensorFlow backend.
-Params: {'activation': 'relu', 'batch_size': 256, 'dense': [1000, 1000, 1000], 'dense_feature_layers': [1000, 1000, 1000], 'drop': 0, 'epochs': 10, 'learning_rate': None, 'loss': 'mse', 'optimizer': 'adam', 'residual': False, 'rng_seed': 2017, 'save': 'save/combo', 'scaling': 'std', 'feature_subsample': 0, 'validation_split': 0.2, 'solr_root': '', 'timeout': -1, 'cell_features': ['expression'], 'drug_features': ['descriptors'], 'cv': 1, 'max_val_loss': 1.0, 'base_lr': None, 'reduce_lr': True, 'warmup_lr': True, 'batch_normalization': False, 'gen': False, 'use_combo_score': False, 'config_file': '/home/fangfang/work/Benchmarks.combo/Pilot1/Combo/combo_default_model.txt', 'verbose': False, 'logfile': None, 'train_bool': True, 'shuffle': True, 'alpha_dropout': False, 'gpus': [], 'experiment_id': 'EXP.000', 'run_id': 'RUN.000', 'use_landmark_genes': True, 'cp': False, 'tb': False, 'datatype': <class 'numpy.float32'>}
+Params: {'activation': 'relu', 'batch_size': 256, 'dense': [1000, 1000, 1000], 'dense_feature_layers': [1000, 1000, 1000], 'drop': 0, 'epochs': 10, 'learning_rate': None, 'loss': 'mse', 'optimizer': 'adam', 'residual': False, 'rng_seed': 2017, 'save': 'save/combo', 'scaling': 'std', 'feature_subsample': 0, 'validation_split': 0.2, 'timeout': -1, 'cell_features': ['expression'], 'drug_features': ['descriptors'], 'cv': 1, 'max_val_loss': 1.0, 'base_lr': None, 'reduce_lr': True, 'warmup_lr': True, 'batch_normalization': False, 'gen': False, 'use_combo_score': False, 'config_file': '/home/fangfang/work/Benchmarks.combo/Pilot1/Combo/combo_default_model.txt', 'verbose': False, 'logfile': None, 'train_bool': True, 'shuffle': True, 'alpha_dropout': False, 'gpus': [], 'experiment_id': 'EXP.000', 'run_id': 'RUN.000', 'use_landmark_genes': True, 'cp': False, 'tb': False, 'datatype': <class 'numpy.float32'>}
 Loaded 311737 unique (CL, D1, D2) response sets.
 Filtered down to 85303 rows with matching information.
 Unique cell lines: 59
@@ -196,4 +196,4 @@ python uno_baseline_keras2.py --conf combo_perf_benchmark.txt
 | Nucleus | 0:14:13 | 72 | 3.47 | 3.8 | 9.3 | 21.9 | 63.4 | 91.9 |
 | Tesla (K20) | 0:44:17 | 250 | 1.00 | 3.9 | 42.3 | 12.9 | 73.8 | 53.3 |
 | Titan | | | | | | | | | keras version 2.0.3 does not supprot model.clone_model() which is introduced in 2.0.7 |
-* Time per epoch on the machine divided by time per epoch of Titan (or Tesla)
+* Time per epoch on the machine divided by time per epoch of Titan (or Tesla)

Pilot1/Uno_UQ/README.md

@@ -101,7 +101,6 @@ Params:
  'scaling': 'std',
  'shuffle': False,
  'single': True,
- 'solr_root': '',
  'tb': False,
  'tb_prefix': 'tb',
  'test_sources': ['train'],
@@ -203,7 +202,6 @@ Params:
  'scaling': 'std',
  'shuffle': False,
  'single': True,
- 'solr_root': '',
  'tb': False,
  'tb_prefix': 'tb',
  'test_sources': ['train'],
@@ -413,7 +411,6 @@ Params:
  'scaling': 'std',
  'shuffle': False,
  'single': True,
- 'solr_root': '',
  'tb': False,
  'tb_prefix': 'tb',
  'test_sources': ['train'],