330626a775087bfda043dceb98522aedb447c703,seq2seq/python/pytorch/train.py,,show_examples,#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#,101

Before Change

// Mashed together from code using numpy only, hacked for th Tensors
def show_examples(use_gpu, model, es, rlut1, rlut2, embed2, mxlen, sample, prob_clip, max_examples):

    batch = data.batch(es, 0, max_examples, long_tensor_alloc, tensor_shape, tensor_max)
    GO = embed2.vocab["<GO>"]
    EOS = embed2.vocab["<EOS>"]

    src_array = batch["src"]
    tgt_array = batch["tgt"]
    if use_gpu:
        src_array = src_array.cuda()
    

After Change

def show_examples(use_gpu, model, es, rlut1, rlut2, embed2, mxlen, sample, prob_clip, max_examples):
    si = np.random.randint(0, len(es))

    src_array, tgt_array, src_len, _ = es[si]

    if max_examples > 0:
        max_examples = min(max_examples, src_array.size(0))

Instances