changeable loss weights for multiple output · Issue #2595 · keras-team/kerasYou signed in with another tab or window. Reload to refresh your session. You signed out in another tab or window. Reload to refresh your session. You switched accounts on another tab or window. Reload to refresh your session. Dismiss alert
tensorflow/tensorflow
System information Have I written custom code (as opposed to using a stock example script provided in TensorFlow): No OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Linux Ubuntu 14.04 TensorFlow installed from (source or binary): Source TensorFlow version (use command below): Python version: Python3.6 Bazel version (if compiling from source): GCC/Compiler version (if compiling from sourc
tensorflow/tensorflow/contrib/lite at master · tensorflow/tensorflow · GitHub
This change moves //tensorflow/contrib/lite to //tensorflow/lite in preparation for TensorFlow 2.0's deprecation of contrib/. If you refer to TF Lite build targets or headers, you will need to update them manually. If you use TF Lite from the TensorFlow python package, "tf.contrib.lite" now points to "tf.lite". Please update your imports as soon as possible. For more details, see https://groups.go
Mac + Python 3.6.1: Attempting to download mnist data results in CERTIFICATE_VERIFY_FAILED error · Issue #10779 · tensorflow/tensorflow
System information Have I written custom code (as opposed to using a stock example script provided in TensorFlow): No OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Mac OS X 10.12.5 TensorFlow installed from (source or binary): binary TensorFlow version (use command below): v1.2.0-rc2-21-g12f033d 1.2.0 Bazel version (if compiling from source): n/a CUDA/cuDNN version: none GPU model and m
models/detection_model_zoo.md at master · tensorflow/models · GitHub
Tensorflow detection model zoo We provide a collection of detection models pre-trained on the COCO dataset, the Kitti dataset, the Open Images dataset, the AVA v2.1 dataset and the iNaturalist Species Detection Dataset. These models can be useful for out-of-the-box inference if you are interested in categories already in those datasets. They are also useful for initializing your models when traini
Error importing tensorflow on windows 10 ( Tensorflow 0.12.0 RC0, python3.5 ) · Issue #5949 · tensorflow/tensorflow
Was excited to try out 0.12.0 RC0 for windows Followed Tensorflow 0.12.0 RC0 Installation guide for Windows, on Windows 10. Ran into following error. Python 3.5.2 (v3.5.2:4def2a2901a5, Jun 25 2016, 22:18:55) [MSC v.1900 64 bit (AMD64)] on win32 Type "copyright", "credits" or "license()" for more information. import tensorflow Traceback (most recent call last): File "C:\Users\hp\AppData\Local\Progr
Refactor regularizers and add add_weight method. by fchollet · Pull Request #4703 · keras-team/keras
Keras use only single thread · Issue #1245 · keras-team/keras
I have installed keras on a redhat 6 server, it is really a attractive framework cause it is really easy to build a deep neural network. However, I found my keras use only single thread(or single core). I ran examples given in the source code package, such as "mnist_mlp.py", and used "top" command, found the usage of CPU is 100%, never more than CPU, I have 6 cores, each with four threads, no GPU,
Keras 2.0 release notes
The nb_epoch argument has been renamed epochs everywhere. The methods fit_generator, evaluate_generator and predict_generator now work by drawing a number of batches from a generator (number of training steps), rather than a number of samples. samples_per_epoch was changed to steps_per_epoch in fit_generator. It now refers to the number of batches an epoch is considered as done. nb_val_samples was
None is not supported in input_shape [bug] · Issue #5900 · keras-team/keras
>>> model = Sequential() model = Sequential() >>> model.add(Conv2D(32, (3, 3), activation='relu', input_shape=(3, None, None))) ) Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/nfs/isicvlnas01/share/anaconda/lib/python2.7/site-packages/keras/models.py", line 422, in add layer(x) File "/nfs/isicvlnas01/share/anaconda/lib/python2.7/site-packages/keras/engine/topology.p
![None is not supported in input_shape [bug] · Issue #5900 · keras-team/keras](https://cdn-ak-scissors.b.st-hatena.com/image/square/f3b23ea18582763f7fe3950c8b608e59cbecd218/height=288;version=1;width=512/https%3A%2F%2Fopengraph.githubassets.com%2Fbe4c96e0b64dc5304fb220281174e37548224728be1cfc311301231353dcb379%2Fkeras-team%2Fkeras%2Fissues%2F5900)
A concrete example for using data generator for large datasets such as ImageNet · Issue #1627 · keras-team/keras
I am already aware of some discussions on how to use Keras for very large datasets (>1,000,000 images) such as this and this. However, for my scenario, I can't figure out the appropriate way to use the ImageDataGenerator or write my own dataGenerator. Specifically, I have the following four questions: From this link: when we do datagen.fit(X_sample), do we assume that X_sample is a big enough chun
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LSTM Autoencoder · Issue #1401 · keras-team/keras
Does it make sense that the validation loss is lower than training loss? · Issue #472 · keras-team/keras
ecosystem/spark/spark-tensorflow-connector at master · tensorflow/ecosystem
Operations used for inference are dropped by optimize_for_inference · Issue #8242 · tensorflow/tensorflow
models/research/object_detection at master · tensorflow/models
tensorflow/RELEASE.md at master · tensorflow/tensorflow
keras/topology.py at master · keras-team/keras · GitHub
Neural Network Exchange Format (NNEF) · Issue #4815 · tensorflow/tensorflow
Incorporating Word Vectors rather than using an Embedding class · Issue #853 · keras-team/keras
