Tensorflow: строка с плавающей точкой не поддерживается при использовании tflearn, несмотря на отсутствие строк в данных

Question

Я не могу найти свою ошибку в своем коде, где есть какая-либо строка, которая неправильно преобразуется в float. Но все же это дает мне эту ошибку:

W tensorflow/core/framework/op_kernel.cc:958] Unimplemented: Cast string to float is not supported 
E tensorflow/core/common_runtime/executor.cc:334] Executor failed to create kernel. Unimplemented: Cast string to float is not supported 
    [[Node: Adam/apply_grad_op_0/update_FullyConnected_1/b/Cast_2 = Cast[DstT=DT_FLOAT, SrcT=DT_STRING, _class=["loc:@FullyConnected_1/b"], _device="/job:localhost/replica:0/task:0/cpu:0"](Adam/apply_grad_op_0/learning_rate)]] 
W tensorflow/core/framework/op_kernel.cc:958] Unimplemented: Cast string to float is not supported 
E tensorflow/core/common_runtime/executor.cc:334] Executor failed to create kernel. Unimplemented: Cast string to float is not supported 
    [[Node: Adam/apply_grad_op_0/update_Conv2D/W/Cast_2 = Cast[DstT=DT_FLOAT, SrcT=DT_STRING, _class=["loc:@Conv2D/W"], _device="/job:localhost/replica:0/task:0/cpu:0"](Adam/apply_grad_op_0/learning_rate)]] 
-- 
Traceback (most recent call last): 
    File "code.py", line 63, in <module> 
    snapshot_step = 100, show_metric = True, run_id = 'convnet_images') 
    File "/usr/local/lib/python2.7/dist-packages/tflearn/models/dnn.py", line 214, in fit 
    callbacks=callbacks) 
    File "/usr/local/lib/python2.7/dist-packages/tflearn/helpers/trainer.py", line 304, in fit 
    show_metric) 
    File "/usr/local/lib/python2.7/dist-packages/tflearn/helpers/trainer.py", line 759, in _train 
    feed_batch) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 717, in run 
    run_metadata_ptr) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 915, in _run 
    feed_dict_string, options, run_metadata) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 965, in _do_run 
    target_list, options, run_metadata) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 985, in _do_call 
    raise type(e)(node_def, op, message) 
tensorflow.python.framework.errors.UnimplementedError: Cast string to float is not supported 
    [[Node: Adam/apply_grad_op_0/update_Conv2D/W/Cast_2 = Cast[DstT=DT_FLOAT, SrcT=DT_STRING, _class=["loc:@Conv2D/W"], _device="/job:localhost/replica:0/task:0/cpu:0"](Adam/apply_grad_op_0/learning_rate)]] 

Caused by op u'Adam/apply_grad_op_0/update_Conv2D/W/Cast_2', defined at: 
    File "code.py", line 59, in <module> 
    model = tflearn.DNN(network, tensorboard_verbose = 3) 
    File "/usr/local/lib/python2.7/dist-packages/tflearn/models/dnn.py", line 63, in __init__ 
    best_val_accuracy=best_val_accuracy) 
    File "/usr/local/lib/python2.7/dist-packages/tflearn/helpers/trainer.py", line 119, in __init__ 
    clip_gradients) 
    File "/usr/local/lib/python2.7/dist-packages/tflearn/helpers/trainer.py", line 649, in initialize_training_ops 
    name="apply_grad_op_" + str(i)) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/optimizer.py", line 322, in apply_gradients 
    update_ops.append(self._apply_dense(grad, var)) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/adam.py", line 135, in _apply_dense 
    math_ops.cast(self._lr_t, var.dtype.base_dtype), 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/math_ops.py", line 616, in cast 
    return gen_math_ops.cast(x, base_type, name=name) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/gen_math_ops.py", line 419, in cast 
    result = _op_def_lib.apply_op("Cast", x=x, DstT=DstT, name=name) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/op_def_library.py", line 749, in apply_op 
    op_def=op_def) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 2380, in create_op 
    original_op=self._default_original_op, op_def=op_def) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 1298, in __init__ 
    self._traceback = _extract_stack() 

UnimplementedError (see above for traceback): Cast string to float is not supported 
    [[Node: Adam/apply_grad_op_0/update_Conv2D/W/Cast_2 = Cast[DstT=DT_FLOAT, SrcT=DT_STRING, _class=["loc:@Conv2D/W"], _device="/job:localhost/replica:0/task:0/cpu:0"](Adam/apply_grad_op_0/learning_rate)]] 

Я проверил до числовых значений пикселей моих изображений и обеспечил они не являются строками. Где строка неверно преобразована в код?

Мой код заключается в следующем:

import tensorflow as tf 
import tflearn 
from scipy.misc import imread, imresize 
import numpy as np 
np.set_printoptions(threshold=np.nan) 

image = imread('image.jpg') 
image2 = imread('image2.jpg') 

image3 = imread('image3.jpg') 
image4 = imread('image4.jpg') 

image = np.resize(image, (256, 256, 1)) 
image2 = np.resize(image2, (256, 256, 1)) 
image3 = np.resize(image3, (256, 256, 1)) 
image4 = np.resize(image4, (256, 256, 1)) 

image_train = np.stack((image, image2), axis = 0)/255.0 
image_test = np.stack((image3, image4), axis = 0)/255.0 

Y = np.zeros((2,1), dtype = np.float64) 

# build the neural net 
from tflearn.layers.core import input_data, dropout, fully_connected 
from tflearn.layers.conv import conv_2d, max_pool_2d 
from tflearn.layers.normalization import local_response_normalization 
from tflearn.layers.estimator import regression 

network = input_data(shape = [None, 256, 256, 1], name = 'input') 
network = conv_2d(network, 32, 3, activation = 'relu', regularizer = 'L2') 
network = max_pool_2d(network, 2) 
network = local_response_normalization(network) 
network = conv_2d(network, 64, 3, activation = 'relu', regularizer = 'L2') 
network = max_pool_2d(network, 2) 
network = local_response_normalization(network) 
network = fully_connected(network, 128, activation = 'tanh') 
network = dropout(network, 0.8) 
network = fully_connected(network, 1, activation = 'softmax') 
network = regression(network, optimizer = 'adam', learning_rate = '0.001', name = 'target') 

#Training 
model = tflearn.DNN(network, tensorboard_verbose = 3) 
print type(model) 
model.fit({'input': image_train}, {'target': Y}, n_epoch = 20, batch_size = 1, 
      validation_set = ({'input': image_test}, {'target': Y}), 
      snapshot_step = 100, show_metric = True, run_id = 'convnet_images') 

Answer 1

У меня была такая же проблема, вы пишете:

learning_rate = '0.001' 

Но learning_rate является float не string так просто написать:

learning_rate = 0.001