Alexnet implementation in tensorflow has incomplete architecture where 2 convolution neural layers are missing. This issue is in reference to the python notebook mentioned below.

https://github.com/donnemartin/data-science-ipython-notebooks/blob/master/deep-learning/tensor-flow-examples/notebooks/3_neural_networks/alexnet.ipynb

This has a very good explanation!!

Does any of you donne this without mask, I mean a new branch but with the mask remove just bouding boxes?

Environment:

1. Framework: PyTorch
2. Framework version: 1.3.1
3. Horovod version: 0.19.0
4. MPI version: 4.0.2
5. CUDA version: N/A
6. NCCL version: N/A
7. Python version: 3.7.5
8. OS and version: Mac OS 10.15.2
9. GCC version: 9.2.0

Checklist:

1. Did you search issues to find if somebody asked this question before? Yes
2. If your question is about hang, did you read [this d

Several parts of the op sec like the main op description, attributes, input and output descriptions become part of the binary that consumes ONNX e.g. onnxruntime causing an increase in its size due to strings that take no part in the execution of the model or its verification.

Setting __ONNX_NO_DOC_STRINGS doesn't really help here since (1) it's not used in the SetDoc(string) overload (s

Feature Description

The source file for all the tutorials on the website (autokeras.com) should be a .ipynb file.

Reason

Make it easier for people to try out the tutorials.

Solution

Please help us change any of the .md files in the following director

I couldn't find any usage of img_hr in SRGAN model. Is it unnecessary to add img_hr as input of combined model?

My suggestions for line 95 and line 229 of srgan.py:
line-95: self.combined = Model(img_lr, [validity, fake_features])
line-229: g_loss = self.combined.train_on_batch(imgs_lr, [valid, image_features])

It might be useful to write the ReadME of the repo in English for ease of understanding.
It looks pretty useful.

Sample on front page:

const model = new KerasJS.Model({
  filepaths: {

filepaths in plural.
code for Model:

if (!filepath) {
      throw new Error('[Model] path to protobuf-serialized model definition file is missing.')
    }

Platform (like ubuntu 16.04/win10): Windows 10
Python version: 3.7.4, mmdnn==0.2.5

Running scripts: mmconvert -f caffe -df keras -om test

I know that this command is not supposed to run without passing an input file, but the error message is incorrect and should be improved:

mmconvert: error: argument --srcFramework/-f: invalid choice: 'None' (choose from 'caffe', 'caffe2', 'cn

Priority

Low

Issue Description

In the screenshot below, LAST MODIFIED shows Sat, 26 Oct 1985 08:15:00 GMT,which is incorrect.

Expected Results

LAST MODIFIED shows correct timestamp, so that users know when this file is modified.

Screenshots/Related files

![image](https://user-images.githubusercontent.com/25629006/52917615-75906980-32a2-11e9-8825-10885a5955d2

A good example is here.

Basically, collect something in a FAQ page on Github wiki or in a Markdown directory in the repo itself.

text after a graph

_Alternatively, if context labels are provided with each text document, the model can be trained in a contextual mode, where the model learns the text given the context so the recurrent layers learn the decontextualized language. The text-only path can piggy-back off the decontextualized layers; in all, this results in much faster training and better quantitative and qualitat

Spark 2.3 officially support run on kubernetes. While our guide of "Run on Kubernetes" is still based on a special version of Spark 2.2, which is out of date. We need to:

1. update that document to Spark 2.3
2. release the corresponding docker images.

All tensorflow examples use ancient version of tensorflow. They should be updated to work without deprecation warnings with modern versions (1.14+). It is hard to get into polyaxon when examples are years behind (tf 1.4 was released in 2017) in such fast moving field.