Tensorflow：尽管数据中没有字符串，但使用 tflearn 时不支持将字符串转换为浮点数错误
Tensorflow: Cast string to float is not supported error when using tflearn despite having no strings in data
我似乎无法在我的代码中找到我的错误，其中有任何字符串被错误地转换为浮点数。但它给了我这个错误：
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)]]
我检查了图像像素的数值并确保它们不是字符串。代码中哪里转换错了字符串？
我的代码是这样的：
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')
我遇到了同样的问题，你写：
learning_rate = '0.001'
但是 learning_rate 是 float 而不是 string 所以只写：
learning_rate = 0.001
我似乎无法在我的代码中找到我的错误，其中有任何字符串被错误地转换为浮点数。但它给了我这个错误：
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)]]
我检查了图像像素的数值并确保它们不是字符串。代码中哪里转换错了字符串？
我的代码是这样的：
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')
我遇到了同样的问题，你写：
learning_rate = '0.001'
但是 learning_rate 是 float 而不是 string 所以只写：
learning_rate = 0.001