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

Hello All;

Hope your are doing well;

In Mask RCNN I would like change the color of the mask to be White with the Alpha = 1, I change it frome the right place in vizualize.py, but anything change the mask color still red or blue or another color, why the changes on vizualize.py dont have effect ?

Example scripts contains some dependencies not listed for Horovod, and in some cases require datasets without explaining how to obtain them. We should provide a README file along with a set of packages (requirements.txt) for successfully running the examples.

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

Adding types on the public API surface would allow us to do some runtime type checking later on and would allow user's IDE to have more info for static analysis.

The functions/signatures to type are the ones listed here https://github.com/keras-team/autokeras/blob/master/autokeras/__init__.py

For the context, see #856 where I add some type information on a ImageClassifier.

This issue can

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

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

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.')
    }

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

Our default placeholders sometimes cause confusion, like in this thread. Perhaps different placeholders, like "your_email@example.com" and "YourTokenHere" will help with that.

Another thread: https://www.coursera.org/learn/practical-rl/discussions/all/threads/jxK8jdhzQ6iSvI3Yc-Oouw

  File "/root/miniconda3/bin/pipeline", line 11, in <module>
    sys.exit(_main())
  File "/root/miniconda3/lib/python3.7/site-packages/cli_pipeline/cli_pipeline.py", line 5734, in _main
    _fire.Fire()
  File "/root/miniconda3/lib/python3.7/site-packages/fire/core.py", line 127, in Fire
    component_trace = _Fire(component, args, context, name)
  Fil

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.

Feature motivation

Azure storage client is backward incompatible, there's an issue #757 for upgrading the azure connection to the latest client. The new version has an async interface that can be leveraged for the streams module, at least for downloads.

N.B. This is likely a 3~4h work and not a pressing need, so just putting this in the backlog.

Feature implementation

There's a