420747a2f5f6f23b84f62f9a00481ef53a4a4623,train.py,,sample_from_model,#,82

Before Change

    for yi in range(obs_shape[0]):
        for xi in range(obs_shape[1]):
            new_x_gen_np = sess.run(new_x_gen, {x_sample: x_gen})
            x_gen[:,yi,xi,:] = new_x_gen_np[:,yi,xi,:].copy()
    return x_gen

// get loss gradients over multiple GPUs
xs = []

After Change

    x_gen = [np.zeros((args.batch_size,) + obs_shape, dtype=np.float32) for i in range(args.nr_gpu)]
    for yi in range(obs_shape[0]):
        for xi in range(obs_shape[1]):
            new_x_gen_np = sess.run(new_x_gen, {xs[i]: x_gen[i] for i in range(args.nr_gpu)})
            for i in range(args.nr_gpu):
                x_gen[i][:,yi,xi,:] = new_x_gen_np[i][:,yi,xi,:]
    return np.concat(x_gen, axis=0)

Instances