Pibborn

import torch.nn as nn
import torch.nn.functional as F
import math

batch_size = 8

## data loading
from torchvision import datasets, transforms
train_loader = torch.utils.data.DataLoader(
        datasets.MNIST('../data', train=True, download=True,

Pibborn

from DeepSpeech import BiRNN, create_inference_graph, export, initialize_globals
import tensorflow as tf

if __name__ == '__main__':
    batch_size = 8
    input_tensor = tf.placeholder(tf.float32, [batch_size, None, 494])
    seq_length = tf.placeholder(tf.int32, [batch_size])
    dropout = [0.] * 6
    initialize_globals()
    logits = BiRNN(input_tensor, tf.to_int64(seq_length), dropout)