tflearn

问题 I keep getting a typeError when I try to use to_categorical from tflearn . The output error is:` trainY = to_categorical(y = trainY, nb_classes=2) File "C:\Users\saleh\Anaconda3\lib\site-packages\tflearn\data_utils.py", line 46, in to_categorical return (y[:, None] == np.unique(y)).astype(np.float32) TypeError: list indices must be integers or slices, not tuple This is the reproducible code that I am trying to run: import tflearn from tflearn.data_utils import to_categorical from tflearn

问题 I am trying to run example from https://github.com/tflearn/tflearn/blob/master/examples/nlp/bidirectional_lstm.py on jupyter notebook. Since I am new on Tflearn, Jupyter and DNN I could not debug what is the error and how to resolve it. The error look like: `TypeError Traceback (most recent call last) <ipython-input-1-fa67bb48a391> in <module>() 38 testX = pad_sequences(testX, maxlen=100, value=0.) 39 # Converting labels to binary vectors ---> 40 trainY = to_categorical(trainY) 41 testY = to

问题 I would like to ask whether tf.one_hot() function supports SparseTensor as the "indices" parameter. I want to do a multi-label classification (each example has multiple labels) which requires to calculate a cross_entropy loss. I try to directly put the SparseTensor in the "indices" parameter but it raises the following error: TypeError: Failed to convert object of type to Tensor. Contents: SparseTensor(indices=Tensor("read_batch_features/fifo_queue_Dequeue:106", shape=(?, 2), dtype=int64,

问题 I have already install most of the libraries on anaconda. In one of my code is showing that No module named 'tflearn'. I also used the command conda install tflearn. it shows the failed message. PackagesNotFoundError: The following packages are not available from current channels: tflearn Current channels: https://repo.continuum.io/pkgs/main/win-64 https://repo.continuum.io/pkgs/main/noarch https://repo.continuum.io/pkgs/free/win-64 https://repo.continuum.io/pkgs/free/noarch https://repo

问题 I can't seem to find my error in my code where there is any string that is wrongly converted to a float. But yet it gives me this error: 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:

问题 I am using Windows 7 and tflearn (version 0.2.2, tensorflow version 0.12.1, python 3.5)and I have scipy manually installed from http://www.lfd.uci.edu/~gohlke/pythonlibs/ When I am running a tflearn code there is always the error message “scipy not supported”. The code is running fine so far, if I don’t need scipy depending things. When I use tflearn.data_preprocessing.ImageAugementation that needs scipy, it gives me a NameError: name ‘scipy’not defined. I checked the script and it tries to

问题 My question is about preprocessing csv files before inputing them into a neural network. I want to build a deep neural network for the famous iris dataset using tflearn in python 3. Dataset: http://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data I'm using tflearn to load the csv file. However, the classes column of my data set has words such as iris-setosa, iris-versicolor, iris-virginica. Nueral networks work only with numbers. So, I have to find a way to change the classes

问题 Can someone provide examples of full working code for Tensorflow tf.contrib.learn.ExportStrategy The documentation lacks examples. I also could not find any examples on Github or Stackoverflow for this seemingly obscure Tensorflow operation. Documentation: https://www.tensorflow.org/api_docs/python/tf/contrib/learn/ExportStrategy 回答1: Google CloudML has a good working example here: https://github.com/GoogleCloudPlatform/cloudml-samples/tree/master/census/customestimator/trainer You'll need to

问题 This question already has answers here : Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2 (6 answers) Closed last year . I have a python code connected with Tensorflow. It is supposed to return single result set. But i'm getting below mentioned warning along with result. WARNING:tensorflow:From C:\Users\vsureshx079451\AppData\Local\Programs\Python\Python36\lib\site-packages\tflearn\objectives.py:66: calling reduce_sum (from tensorflow.python.ops

问题 I'm using the tflearn wrapper over tensorflow to build a model, and would like to add metadata (labels) to the resultant embedding visualization. Is there a way to link a metadata.tsv file to a saved checkpoint after the fact of running it? I've created a projector_config.pbtxt file in the logdir of the checkpoint summaries, with the metadata.tsv being in the same folder. The config looks like this: embeddings { tensor_name: "Embedding/W" metadata_path: "C:/tmp/tflearn_logs/shallow_lstm/" }