tf.function makes invalid assumptions about arguments that are Mapping instances. In general, there are no requirements for Mapping instances to have constructors that accept [(key, value)] initializers, as assumed here.

This leads to cryptic exceptions when used with perfectly valid Mapping s

🐛 Bug

To Reproduce

Run following from jupyter lab console

import torch
foo = torch.arange(5)
foo.as_strided((5,), (-1,), storage_offset=4)

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/daniil/.local/lib/python3.6/site-packages/torch/tensor.py", line 159, i

In Transformation Pipeline make class DataFrameSelector for custom transformation and call DataFrameSelector(num_attribs) it show
TypeError: object() takes no parameters
and same with CombinedAttributesAdder
i m using colab

from sklearn.base import BaseEstimator , TransformerMixin
class DataFrameSelector(BaseEstimator,TransformerMixin):
  def _init_(self,attribute_names):
  

What's the ETA for updating the massively outdated documentation?

Please update all documents that are related building CNTK from source with latest CUDA dependencies that are indicated in CNTK.Common.props and CNTK.Cpp.props.
I tried to build from source, but it's a futile effort.

I was going though the existing enhancement issues again and though it'd be nice to collect ideas for spaCy plugins and related projects. There are always people in the community who are looking for new things to build, so here's some inspiration ✨ For existing plugins and projects, check out the spaCy universe.

If you have questions about the projects I suggested,

Reference from TensorFlow: https://www.tensorflow.org/api_docs/cc/class/tensorflow/ops/matrix-band-part

This op is used by the Music Transformer model.

Is there an overview, how the config object for the constructors of the neural network are defined?

This would be interesting:

• Has brain.NeuralNetwork and brain.recurrent.RNN the same config attributes?
• What is the description of the inputSize attribute?

Thank you for the great work with this library, it is realy amazing!

It would be beneficial to write a design document on INT8 DNNL implementation and put it into
FluidDoc next to other Design documents:
https://github.com/PaddlePaddle/FluidDoc/tree/develop/doc/fluid/design/mkldnn

Tutorial: Similarity Queries
https://radimrehurek.com/gensim/auto_examples/core/run_similarity_queries.html#sphx-glr-auto-examples-core-run-similarity-queries-py

Notice the document order in the tutorial:

documents = [
    "Human machine interface for lab abc computer applications",
    "A survey of user opinion of computer system response time",
    "The EPS user interface management

load_csv line can be since there's columns_to_ignore param's supported

data, labels = load_csv('titanic_dataset.csv', target_column=0, columns_to_ignore=[2, 7], categorical_labels=True, n_classes=2)

and we don't need to do that in preprocess()

def preprocess(passengers):
    for i in range(len(passengers)):
        passengers[i][1] = 1. if passengers[i][1] == 'female' else 0.

I cannot effectively use this program because I am missing the instructions because the link to the Install instructions on github produce a 404 error. Could they be added as a .txt file to future versions or at least can you please fix the link?

As we introduce keepdims in reduction op, there exist some cases which are not supported by binaryop. For example: A [7, 7, 1024] B[7, 7, 1] and so on...what do you think about it? @nihui

We can make some discussion here. I'd like to work on it~

Support for storing large tensor values in external files was introduced in #678, but AFAICT is undocumented.

This is a pretty important feature, functionally, but it's also important for end users who may not realise that they need to move around more than just the *.onnx file.

I would suggest it should be documented in IR.md, and perhaps there are other locations from which it could be s

i'm a newbie in programming. I try to use this library. it's very useful for me.
I want to show centroid in K-means clustering. how to show it? thank u so much..

I understand that these two python files show two different methods to construct a model. The original n_epoch is 500 which works perfect for both python files. But if I change n_epoch to 20, only tutorial_mnist_mlp_static.py can achieve a high test accuracy (~0.97). The other file tutorial_mnist_mlp_static_2.py only get 0.47.

The models built from these two files looks the same for me (the s

Hi I would like to propose a better implementation for 'test_indices':

We can remove the unneeded np.array casting:

Cleaner/New:
test_indices = list(set(range(len(texts))) - set(train_indices))

Old:
test_indices = np.array(list(set(range(len(texts))) - set(train_indices)))

The picture of WebUI in PAI doc is out of date.

Short summary about the issue/question:

**Bri

Sphinx (2.2.1 or master) produces the following two kinds of warnings in my environment.

duplicate object description

I think cross refs to such object is ambiguous.

autosummary: stub file not found

There are

• chainer.dataset.Converter base class and
• chainer.dataset.converter decorator.

Therefore the filesystem has to allow to store `chainer.dataset.Conver