def inference(self,
data_reader,
inference_batch_size=64,
output_path=None,
category_name=None):
pad_id = 0
eval_batches = data_reader.gen_mini_batches('test',
inference_batch_size,
pad_id,
shuffle=False)
Trainer._test_sess(self, eval_batches)
def train_and_evaluate(self,
data_reader,
evaluator,
epochs=1,
eposides=1,
save_dir=None,
summary_dir=None,
save_summary_steps=10,
batch_size=32):
if not self.initialized:
self.session.run(tf.global_variables_initializer())
Trainer._train_and_evaluate(self,
data_reader,
evaluator,
epochs=epochs,
eposides=eposides,
save_dir=save_dir,
summary_dir=summary_dir,
save_summary_steps=save_summary_steps,
batch_size=batch_size)
def evaluate(self, batch_generator, evaluator):
Trainer._evaluate(self, batch_generator, evaluator)