Pads sequences to the same length.
Compat aliases for migration
See Migration guide for more details.
tf.keras.preprocessing.sequence.pad_sequences( sequences, maxlen=None, dtype='int32', padding='pre', truncating='pre', value=0.0 )
This function transforms a list of
num_samples sequences (lists of integers) into a 2D Numpy array of shape
num_timesteps is either the
maxlen argument if provided, or the length of the longest sequence otherwise.
Sequences that are shorter than
num_timesteps are padded with
value at the beginning or the end if padding='post.
Sequences longer than
num_timesteps are truncated so that they fit the desired length. The position where padding or truncation happens is determined by the arguments
Pre-padding is the default.
sequences: List of lists, where each element is a sequence. maxlen: Int, maximum length of all sequences. dtype: Type of the output sequences. To pad sequences with variable length strings, you can use `object`. padding: String, 'pre' or 'post': pad either before or after each sequence. truncating: String, 'pre' or 'post': remove values from sequences larger than `maxlen`, either at the beginning or at the end of the sequences. value: Float or String, padding value.
x: Numpy array with shape `(len(sequences), maxlen)`
ValueError: In case of invalid values for `truncating` or `padding`, or in case of invalid shape for a `sequences` entry.
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Code samples licensed under the Apache 2.0 License.