在培训期间，我收到以下错误。 “ ValueError：没有为任何变量提供梯度”

Question

我计算了梯度，但我仍然没有得到梯度错误。即使在查看了类似类型错误的答案后，我也无法弄清楚我错过了哪里。 我正在使用 tensorflow 2。我的代码的链接是https://github.com/Gadamsetty/ML_practise/blob/master/translatron_test.py

错误如下

ValueError: in converted code:

    <ipython-input-15-031ef53603dd>:92 train_step  *
        optimizer.apply_gradients(zip(gradients,variables))
    /tensorflow-2.0.0/python3.6/tensorflow_core/python/keras/optimizer_v2/optimizer_v2.py:427 apply_gradients
        grads_and_vars = _filter_grads(grads_and_vars)
    /tensorflow-2.0.0/python3.6/tensorflow_core/python/keras/optimizer_v2/optimizer_v2.py:1025 _filter_grads
        ([v.name for _, v in grads_and_vars],))

    ValueError: No gradients provided for any variable: ['encoder_rnn_3/layer0/forward_gru_12/kernel:0', 'encoder_rnn_3/layer0/forward_gru_12/recurrent_kernel:0', 'encoder_rnn_3/layer0/forward_gru_12/bias:0', 'encoder_rnn_3/layer0/backward_gru_12/kernel:0', 'encoder_rnn_3/layer0/backward_gru_12/recurrent_kernel:0', 'encoder_rnn_3/layer0/backward_gru_12/bias:0', 'encoder_rnn_3/layer1/forward_gru_13/kernel:0', 'encoder_rnn_3/layer1/forward_gru_13/recurrent_kernel:0', 'encoder_rnn_3/layer1/forward_gru_13/bias:0', 'encoder_rnn_3/layer1/backward_gru_13/kernel:0', 'encoder_rnn_3/layer1/backward_gru_13/recurrent_kernel:0', 'encoder_rnn_3/layer1/backward_gru_13/bias:0', 'encoder_rnn_3/layer2/forward_gru_14/kernel:0', 'encoder_rnn_3/layer2/forward_gru_14/recurrent_kernel:0', 'encoder_rnn_3/layer2/forward_gru_14/bias:0', 'encoder_rnn_3/layer2/backward_gru_14/kernel:0', 'encoder_rnn_3/layer2/backward_gru_14/recurrent_kernel:0', 'encoder_rnn_3/layer2/backward_gru_14/bias:0', 'encoder_rnn_3/layer3/forward_gru_15/kernel:0', 'encoder_rnn_3/layer3/forward_gru_15/recurrent_kernel:0', 'encoder_rnn_3/layer3/forward_gru_15/bias:0', 'encoder_rnn_3/layer3/backward_gru_15/kernel:0', 'encoder_rnn_3/layer3/backward_gru_15/recurrent_kernel:0', 'encoder_rnn_3/layer3/backward_gru_15/bias:0', 'decoder_rnn_3/bidirectional_6/forward_decoder_layer1/kernel:0', 'decoder_rnn_3/bidirectional_6/forward_decoder_layer1/recurrent_kernel:0', 'decoder_rnn_3/bidirectional_6/forward_decoder_layer1/bias:0', 'decoder_...

Answer 1

由于您没有对梯度进行任何操作，因此您可以尝试直接使用optimizer.minimize(loss)而不是先计算梯度然后单独应用它们。 （第 159-161 行）