Created
February 7, 2019 22:17
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# Defining method to make mini-batches for training | |
def get_batches(arr, batch_size, seq_length): | |
'''Create a generator that returns batches of size | |
batch_size x seq_length from arr. | |
Arguments | |
--------- | |
arr: Array you want to make batches from | |
batch_size: Batch size, the number of sequences per batch | |
seq_length: Number of encoded chars in a sequence | |
''' | |
batch_size_total = batch_size * seq_length | |
# total number of batches we can make | |
n_batches = len(arr)//batch_size_total | |
# Keep only enough characters to make full batches | |
arr = arr[:n_batches * batch_size_total] | |
# Reshape into batch_size rows | |
arr = arr.reshape((batch_size, -1)) | |
# iterate through the array, one sequence at a time | |
for n in range(0, arr.shape[1], seq_length): | |
# The features | |
x = arr[:, n:n+seq_length] | |
# The targets, shifted by one | |
y = np.zeros_like(x) | |
try: | |
y[:, :-1], y[:, -1] = x[:, 1:], arr[:, n+seq_length] | |
except IndexError: | |
y[:, :-1], y[:, -1] = x[:, 1:], arr[:, 0] | |
yield x, y |
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