Fix Python – Tensorflow Strides Argument

I am trying to understand the strides argument in tf.nn.avg_pool, tf.nn.max_pool, tf.nn.conv2d.
The documentation repeatedly says

strides: A list of ints that has length >= 4. The stride of the sliding window for each dimension of the input tensor.

My questions are:

What do each of the 4+ integers represent?
Why must they have strides[0] = st….

Fix Python – Tensorflow – ValueError: Failed to convert a NumPy array to a Tensor (Unsupported object type float)

Continuation from previous question: Tensorflow – TypeError: ‘int’ object is not iterable
My training data is a list of lists each comprised of 1000 floats. For example, x_train[0] =
[0.0, 0.0, 0.1, 0.25, 0.5, …]

Here is my model:
model = Sequential()

model.add(LSTM(128, activation=’relu’,
input_shape=(1000, 1), return_sequences….

Fix Python – Difference between Variable and get_variable in TensorFlow

As far as I know, Variable is the default operation for making a variable, and get_variable is mainly used for weight sharing.
On the one hand, there are some people suggesting using get_variable instead of the primitive Variable operation whenever you need a variable. On the other hand, I merely see any use of get_variable in TensorFlow’s officia….

Fix Python – Deep-Learning Nan loss reasons

Perhaps too general a question, but can anyone explain what would cause a Convolutional Neural Network to diverge?
I am using Tensorflow’s iris_training model with some of my own data and keep getting

ERROR:tensorflow:Model diverged with loss = NaN.

Fix Python – Loading a trained Keras model and continue training

I was wondering if it was possible to save a partly trained Keras model and continue the training after loading the model again.
The reason for this is that I will have more training data in the future and I do not want to retrain the whole model again.
The functions which I am using are:
#Partly train model, first_classes….

Fix Python – In Tensorflow, get the names of all the Tensors in a graph

I am creating neural nets with Tensorflow and skflow; for some reason I want to get the values of some inner tensors for a given input, so I am using myClassifier.get_layer_value(input, “tensorName”), myClassifier being a skflow.estimators.TensorFlowEstimator.
However, I find it difficult to find the correct syntax of the tensor name, even knowin….

Fix Python – How are the new tf.contrib.summary summaries in TensorFlow evaluated?

I’m having a bit of trouble understanding the new tf.contrib.summary API. In the old one, it seemed that all one was supposed to do was to run tf.summary.merge_all() and run that as an op.
But now we have things like tf.contrib.summary.record_summaries_every_n_global_steps, which can be used like this:
import tensorflow.contrib.summary as tfsum


Fix Python – Could not load dynamic library ‘cudart64_101.dll’ on tensorflow CPU-only installation

I just installed the latest version of Tensorflow via pip install tensorflow and whenever I run a program, I get the log message:

W tensorflow/stream_executor/platform/default/] Could not load dynamic library ‘cudart64_101.dll’; dlerror: cudart64_101.dll not found

Is this bad? How do I fix the error?

Fix Python – What does tf.nn.embedding_lookup function do?

tf.nn.embedding_lookup(params, ids, partition_strategy=’mod’, name=None)

I cannot understand the duty of this function. Is it like a lookup table? Which means to return the parameters corresponding to each id (in ids)?
For instance, in the skip-gram model if we use tf.nn.embedding_lookup(embeddings, train_inputs), then for each train_input it fin….