@@ -78,9 +78,9 @@ def get_imdb_data(vocabulary_size, max_len):
7878 max_len: Cut text after this number of words.
7979
8080 Returns:
81- x_train: An int array of shape `(num_exapmles , max_len)`: index-encoded
81+ x_train: An int array of shape `(num_examples , max_len)`: index-encoded
8282 sentences.
83- y_train: An int array of shape `(num_exapmles ,)`: labels for the sentences.
83+ y_train: An int array of shape `(num_examples ,)`: labels for the sentences.
8484 x_test: Same as `x_train`, but for test.
8585 y_test: Same as `y_train`, but for test.
8686 """
@@ -107,9 +107,9 @@ def train_model(model_type,
107107 model_type: Type of the model to train, as a `str`.
108108 vocabulary_size: Vocabulary size.
109109 embedding_size: Embedding dimensions.
110- x_train: An int array of shape `(num_exapmles , max_len)`: index-encoded
110+ x_train: An int array of shape `(num_examples , max_len)`: index-encoded
111111 sentences.
112- y_train: An int array of shape `(num_exapmles ,)`: labels for the sentences.
112+ y_train: An int array of shape `(num_examples ,)`: labels for the sentences.
113113 x_test: Same as `x_train`, but for test.
114114 y_test: Same as `y_train`, but for test.
115115 epochs: Number of epochs to train the model for.
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