[英]Tensorflow: No gradients provided for any variable
我是tensorflow
,我正在建立一個網絡,但沒有為它計算/應用漸變。 我收到錯誤:
ValueError: No gradients provided for any variable: ((None, tensorflow.python.ops.variables.Variable object at 0x1025436d0), ... (None, tensorflow.python.ops.variables.Variable object at 0x10800b590))
我嘗試使用張量板圖來查看是否有某些東西使得無法跟蹤圖形並獲得漸變但我看不到任何東西。
這是代碼的一部分:
sess = tf.Session()
X = tf.placeholder(type, [batch_size,feature_size])
W = tf.Variable(tf.random_normal([feature_size, elements_size * dictionary_size]), name="W")
target_probabilties = tf.placeholder(type, [batch_size * elements_size, dictionary_size])
lstm = tf.nn.rnn_cell.BasicLSTMCell(lstm_hidden_size)
stacked_lstm = tf.nn.rnn_cell.MultiRNNCell([lstm] * number_of_layers)
initial_state = state = stacked_lstm.zero_state(batch_size, type)
output, state = stacked_lstm(X, state)
pred = tf.matmul(output,W)
pred = tf.reshape(pred, (batch_size * elements_size, dictionary_size))
# instead of calculating this, I will calculate the difference between the target_W and the current W
cross_entropy = tf.nn.softmax_cross_entropy_with_logits(target_probabilties, pred)
cost = tf.reduce_mean(cross_entropy)
optimizer = tf.train.GradientDescentOptimizer(learning_rate).minimize(cost)
sess.run(optimizer, feed_dict={X:my_input, target_probabilties:target_prob})
我會很感激任何有關解決這個問題的幫助。
我總是使用tf.nn.softmax_cross_entropy_with_logits(),這樣我就可以將logits作為第一個參數,將標簽作為第二個參數。 你能試試嗎?
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