Я новичок в tenorflow.Я хочу передать обучающие данные (Xs и Ys - это 3d ndarrays [85,31951,9] и [85,31951,1]) для входных данных и целей заполнителей внутри блока tf.session.
85 сэмплов, 31951 отметок времени и 9 функций в X.
Я попытался передать np.random.random((85, 31951, 9)) в feed dict, просто чтобы увидеть, есть ли какие-либо проблемыс моими размерами входных данных.Тем не менее ошибка сохраняется.
"Вы должны передать значение для тензора-заполнителя 'Placeholder' с плавающей точкой dtype и формы [85,31951,9]".
Если я поверну первое измерение (примеры) от 85 до None, код выполняется, но я сталкиваюсь с Unknown shape ошибкой в tf.gather.Я могу опубликовать больше кода, если это необходимо.Любая помощь приветствуется.
with tf.Session(graph=lstm_graph) as sess:
tf.global_variables_initializer().run()
x_train_IV_nd, x_train_DV_nd = prep_data()
print(np.shape(x_train_IV_nd))
print(type(x_train_IV_nd))
# print(x_train_IV_nd.dtype)
learning_rates_to_use = [
config.init_learning_rate * (
config.learning_rate_decay ** max(float(i + 1 - config.init_epoch), 0.0)
) for i in range(config.max_epoch)]
for epoch_step in range(config.max_epoch):
current_lr = learning_rates_to_use[epoch_step]
train_loss, _ = sess.run([loss, minimize], feed_dict={inputs: np.random.random((85, 31951, 9)), targets: np.random.random((85, 31951, 1))})
И мои заполнители для ввода входных данных и целей:
inputs = tf.placeholder(tf.float32, shape = (85,31951,9))
targets = tf.placeholder(tf.float32, shape = (85,31951,1))
Сетевые настройки:
class RNNConfig():
input_size=9
num_steps=31951
num_units = 128
lstm_size=9
num_layers=9
keep_prob=0.8
batch_size = 85
init_learning_rate = 0.001
learning_rate_decay = 0.99
init_epoch = 5
max_epoch = 50
Ошибка:
#[[Node: Placeholder = Placeholder[dtype=DT_FLOAT, shape=[85,31951,9], _device="/job:localhost/replica:0/task:0/device:GPU:0"]()]]
[[Node: rnn/transpose_1/_17 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_170_rnn/transpose_1", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/antpc/Documents/Python/testpycharm/my_csv.py", line 198, in <module>
tf.global_variables_initializer().run()
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py", line 2377, in run
_run_using_default_session(self, feed_dict, self.graph, session)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py", line 5215, in _run_using_default_session
session.run(operation, feed_dict)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 900, in run
run_metadata_ptr)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1135, in _run
feed_dict_tensor, options, run_metadata)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1316, in _do_run
run_metadata)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1335, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.InvalidArgumentError: You must feed a value for placeholder tensor 'Placeholder' with dtype float and shape [85,31951,9]
[[Node: Placeholder = Placeholder[dtype=DT_FLOAT, shape=[85,31951,9], _device="/job:localhost/replica:0/task:0/device:GPU:0"]()]]
[[Node: rnn/transpose_1/_17 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_170_rnn/transpose_1", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]
Caused by op 'Placeholder', defined at:
File "/home/antpc/Documents/Python/testpycharm/my_csv.py", line 145, in <module>
##inputs = tf.placeholder(tf.float32, shape = (85,31951,9)) (85,31951,9)##
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/array_ops.py", line 1808, in placeholder
return gen_array_ops.placeholder(dtype=dtype, shape=shape, name=name)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/gen_array_ops.py", line 4848, in placeholder
"Placeholder", dtype=dtype, shape=shape, name=name)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py", line 3392, in create_op
op_def=op_def)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py", line 1718, in __init__
self._traceback = self._graph._extract_stack() # pylint: disable=protected-access
###InvalidArgumentError (see above for traceback): You must feed a value for placeholder tensor 'Placeholder' with dtype float and shape [85,31951,9] ####
[[Node: Placeholder = Placeholder[dtype=DT_FLOAT, shape=[85,31951,9], _device="/job:localhost/replica:0/task:0/device:GPU:0"]()]]
[[Node: rnn/transpose_1/_17 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_170_rnn/transpose_1", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]