cpu thread flag

README.md

@@ -55,7 +55,6 @@ The r2 on the Lipophilicity dataset should be arround 0.731 +/- 0.029.
 ## Getting Started
 ### Extracting Molecular Descripotrs
 Run the script run_cddd.py to extract molecular descripotrs of your provided SMILES:
-<<<<<<< HEAD
 ```bash
 cddd --input smiles.smi --output descriptors.csv --smiles_header smiles
 ```

cddd/inference.py

@@ -77,7 +77,8 @@ def embedding2sequence(model, hparams, embedding, num_top=1, maximum_iterations=
 class InferenceModel(object):
  """Class that handles the inference of a trained model."""
  def __init__(self, model_dir=_default_model_dir, use_gpu=True, batch_size=256,
- gpu_mem_frac=0.1, beam_width=10, num_top=1, maximum_iterations=1000, emb_activation=None):
+ gpu_mem_frac=0.1, beam_width=10, num_top=1, maximum_iterations=1000,
+ cpu_threads=5, emb_activation=None):
  """Constructor for the inference model.
 
  Args:
@@ -103,6 +104,7 @@ def __init__(self, model_dir=_default_model_dir, use_gpu=True, batch_size=256,
  self.hparams.set_hparam("batch_size", batch_size)
  self.hparams.set_hparam("gpu_mem_frac", gpu_mem_frac)
  self.hparams.add_hparam("beam_width", beam_width)
+ self.hparams.set_hparam("cpu_threads", cpu_threads)
  self.encode_model, self.decode_model = build_models(self.hparams,
  modes=["ENCODE", "DECODE"])
  self.maximum_iterations = maximum_iterations

cddd/model_helper.py

@@ -31,7 +31,7 @@ def build_models(hparams, modes=["TRAIN", "EVAL", "ENCODE"]):
 def create_model(mode, model_creator, input_pipeline_creator, hparams):
  """Helper function to build a translation model for a certain mode.
 
- Args:
+ Args:cpu_threads
  mode: The mode the model is supposed to run(e.g. Train, EVAL, ENCODE, DECODE).
  model_creator: Type of model class (e.g. NoisyGRUSeq2SeqWithFeatures).
  input_pipeline_creator: Type of input pipeline class (e.g. InputPipelineWithFeatures).

example/run_qsar_test.py

@@ -33,6 +33,7 @@ def add_arguments(parser):
  parser.add_argument('--use_gpu', dest='gpu', action='store_true')
  parser.set_defaults(gpu=False)
  parser.add_argument('--device', default="0", type=str)
+ parser.add_argument('--cpu_threads', default=5, type=int)
 
 def main(unused_argv):
  """Main function to test the performance of the translation model to extract
@@ -44,7 +45,7 @@ def main(unused_argv):
  os.environ['CUDA_VISIBLE_DEVICES'] = '-1'
  model_dir = FLAGS.model_dir
 
- infer_model = InferenceModel(model_dir, use_gpu=FLAGS.gpu)
+ infer_model = InferenceModel(model_dir, use_gpu=FLAGS.gpu, cpu_threads=FLAGS.cpu_threads)
  ames_df = pd.read_csv("ames.csv")
  ames_smls = ames_df.smiles.tolist()
  ames_labels = ames_df.label.values