Removing some unuseful logs that might hinder clearer visualization.

gugarosa · Apr 20, 2021 · 3d2e401 · 3d2e401
1 parent 0ef1369
commit 3d2e401
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Showing 6 changed files with 0 additions and 26 deletions.
diff --git a/nalp/core/model.py b/nalp/core/model.py
@@ -97,8 +97,6 @@ def generate_greedy_search(self, start, max_length=100):
 
         """
 
-        logger.debug('Greedy search generation with maximum length: %d', max_length)
-
         # Encoding the start string into tokens, while expanding its first dimension
         start_tokens = self.encoder.encode(start)
         start_tokens = tf.expand_dims(start_tokens, 0)
@@ -145,8 +143,6 @@ def generate_temperature_sampling(self, start, max_length=100, temperature=1.0):
 
         """
 
-        logger.debug('Temperature sampling generation with maximum length: %d', max_length)
-
         # Encoding the start string into tokens, while expanding its first dimension
         start_tokens = self.encoder.encode(start)
         start_tokens = tf.expand_dims(start_tokens, 0)
@@ -198,8 +194,6 @@ def generate_top_sampling(self, start, max_length=100, k=0, p=0.0):
 
         """
 
-        logger.debug('Top-based sampling generation with maximum length: %d', max_length)
-
         # Encoding the start string into tokens, while expanding its first dimension
         start_tokens = self.encoder.encode(start)
         start_tokens = tf.expand_dims(start_tokens, 0)

diff --git a/nalp/datasets/language_modeling.py b/nalp/datasets/language_modeling.py
@@ -55,8 +55,6 @@ def _create_sequences(self, encoded_tokens, rank, max_contiguous_pad_length):
 
         """
 
-        logger.debug('Creating sequences ...')
-
         # Slices the tensors into sequences
         sequences = data.Dataset.from_tensor_slices(encoded_tokens)
 
@@ -66,8 +64,6 @@ def _create_sequences(self, encoded_tokens, rank, max_contiguous_pad_length):
             # Creates the sequences
             sequences = sequences.batch(max_contiguous_pad_length + 1, drop_remainder=True)
 
-            logger.debug('Maximum contiguous pad length: %d.', max_contiguous_pad_length)
-
         return sequences
 
     def _create_input_target(self, sequence):

diff --git a/nalp/encoders/integer.py b/nalp/encoders/integer.py
@@ -51,8 +51,6 @@ def learn(self, dictionary, reverse_dictionary):
 
         """
 
-        logger.debug('Learning how to encode ...')
-
         # Creates the encoder property
         self.encoder = dictionary
 

diff --git a/nalp/encoders/word2vec.py b/nalp/encoders/word2vec.py
@@ -47,8 +47,6 @@ def learn(self, tokens, max_features=128, window_size=5, min_count=1,
 
         """
 
-        logger.debug('Learning how to encode ...')
-
         # Creates a Word2Vec model
         self.encoder = W2V(sentences=[tokens], size=max_features, window=window_size, min_count=min_count,
                            sg=algorithm, alpha=learning_rate, iter=iterations,

diff --git a/nalp/models/generators/gumbel_lstm.py b/nalp/models/generators/gumbel_lstm.py
@@ -93,8 +93,6 @@ def generate_greedy_search(self, start, max_length=100):
 
         """
 
-        logger.debug('Greedy search generation with maximum length: %d', max_length)
-
         # Encoding the start string into tokens and expanding its first dimension
         start_tokens = self.encoder.encode(start)
         start_tokens = tf.expand_dims(start_tokens, 0)
@@ -141,8 +139,6 @@ def generate_temperature_sampling(self, start, max_length=100, temperature=1.0):
 
         """
 
-        logger.debug('Temperature sampling generation with maximum length: %d', max_length)
-
         # Applying Gumbel-Softmax temperature as argument
         self.tau = temperature
 
@@ -197,8 +193,6 @@ def generate_top_sampling(self, start, max_length=100, k=0, p=0.0):
 
         """
 
-        logger.debug('Top-based sampling generation with maximum length: %d', max_length)
-
         # Encoding the start string into tokens and expanding its first dimension
         start_tokens = self.encoder.encode(start)
         start_tokens = tf.expand_dims(start_tokens, 0)

diff --git a/nalp/models/generators/gumbel_rmc.py b/nalp/models/generators/gumbel_rmc.py
@@ -99,8 +99,6 @@ def generate_greedy_search(self, start, max_length=100):
 
         """
 
-        logger.debug('Greedy search generation with maximum length: %d', max_length)
-
         # Encoding the start string into tokens and expanding its first dimension
         start_tokens = self.encoder.encode(start)
         start_tokens = tf.expand_dims(start_tokens, 0)
@@ -147,8 +145,6 @@ def generate_temperature_sampling(self, start, max_length=100, temperature=1.0):
 
         """
 
-        logger.debug('Temperature sampling generation with maximum length: %d', max_length)
-
         # Applying Gumbel-Softmax temperature as argument
         self.tau = temperature
 
@@ -203,8 +199,6 @@ def generate_top_sampling(self, start, max_length=100, k=0, p=0.0):
 
         """
 
-        logger.debug('Top-based sampling generation with maximum length: %d', max_length)
-
         # Encoding the start string into tokens and expanding its first dimension
         start_tokens = self.encoder.encode(start)
         start_tokens = tf.expand_dims(start_tokens, 0)