### Summary
We have the method `to_list` in keras. Let's use it to make the codebase simpler!
### Related Issues

### PR Overview

- [ ] This PR requires new unit tests [y/n] (make sure tests are included)
- [ ] This PR requires to update the documentation [y/n] (make sure the docs are up-to-date)
- [x] This PR is backwards compatible [y/n]
- [ ] This PR changes the current API [y/n] (all API changes need to be approved by fchollet)

* Fix casting validate generator with stateful metrics.

* Add a stateful metric to Tensboard tests

* Fixing HDF5Matrix `.dtype` and `.shape` output

Adding code to the initialization function of `HDF5Matrix` so that `.dtype` and `.shape` reflect the actual values returned by the normalizer

* Update io_utils_test.py

adding tests for normalizer functions that change dtype and shape

* Update io_utils_test.py

removing unnecessary whitespace to make pep8 happy

* Fix #10737

* Change length to steps

* Make style changes for consistency

### Summary
This PR resolves two issues:
1) The `get_function_signature` in `autogen.py` duplicates module name for non-method functions. For example, it returns `keras.preprocessing.sequence.keras.preprocessing.sequence.pad_sequences` instead of `keras.preprocessing.sequence.pad_sequences`.

2) Method functions and non-method functions should be distinguished from each other. Since, the module name of non-method functions should be included in the signature in the docs (like `keras.preprocessing.sequence.pad_sequences(...)`) whereas for the methods of classes it should not be included (like `compile(...)` for `Sequential` class). Therefore, a new `'methods'` key is introduced to make this distinction.

Note that I temporary resolved the first issue by a merged PR (#10664); however that PR did not address the underlying problem.

### Related Issues
#10658 
#10662 
### PR Overview

- [n] This PR requires new unit tests [y/n] (make sure tests are included)
- [n] This PR requires to update the documentation [y/n] (make sure the docs are up-to-date)
- [y] This PR is backwards compatible [y/n]
- [n] This PR changes the current API [y/n] (all API changes need to be approved by fchollet)

* Numpy ndarray should be serialized as Python list.

* Add test case.

* Fix annotation

* Removed some unused variables.

* Fixed the formatting of an error message.

* Used the function `normalize_data_format` to remove some code. Moved the implementation to keras/backend/common.py.

* Changed all conv_utils.normalize_data_format into K.normalize_data_format

* PEP8 fixed line length examples/

* revert addition_rnn

* Fix PEP8 in babi_memnn

* Refactoring: Simplified some if-else by creating a function similar to `to_list`.

* Changed the name and the description of `first_or_list`.

Batch Normalization should squeeze mean/var/beta/gama tensors when calling tf.nn.fused_batch_norm (#10684)

* Batch Normalization should squeeze mean/var/beta/gama tensors when calling tf.nn.fused_batch_norm

* Only call squeeze if mean / var have more than 1 axes.

* Try testing on Python 3.7

* Try theano

* Update .travis.yml

* Don't pip install tensorflow

* Travis CI: reduce hardcoding of Python 3 versions

Python 2.7 needs __pil__ but _all other_ currently supported versions of Python need __Pillow__ instead.

Removed the exceptions concerning files which were already complient with the 85 chars rule. (#10714)

### Summary

### Related Issues

### PR Overview

- [ ] This PR requires new unit tests [y/n] (make sure tests are included)
- [ ] This PR requires to update the documentation [y/n] (make sure the docs are up-to-date)
- [x] This PR is backwards compatible [y/n]
- [ ] This PR changes the current API [y/n] (all API changes need to be approved by fchollet)

### Summary
Modify `docs/autogen.py` so it complies to PEP8 line length rule (line length = 85).

### Related Issues

### PR Overview

- [ ] This PR requires new unit tests [y/n] (make sure tests are included)
- [ ] This PR requires to update the documentation [y/n] (make sure the docs are up-to-date)
- [X] This PR is backwards compatible [y/n]
- [ ] This PR changes the current API [y/n] (all API changes need to be approved by fchollet)

Update `Conv2D` call to the Keras 2 API

### Summary

I think it was meant to be passed it to the `__init__` of the parent class.

### Related Issues

### PR Overview

- [ ] This PR requires new unit tests [y/n] (make sure tests are included)
- [ ] This PR requires to update the documentation [y/n] (make sure the docs are up-to-date)
- [ ] This PR is backwards compatible [y/n]
- [x] This PR changes the current API [y/n] (all API changes need to be approved by fchollet)

### Summary
This PR fixes the redundant function module names in auto-gen docs. Currently, the module name of functions (those which are not methods of a class) is repeated two times in documentation. [For example](https://keras.io/preprocessing/sequence/#pad_sequences):
> `keras.preprocessing.sequence.keras.preprocessing.sequence.pad_sequences`

which should be: `keras.preprocessing.sequence.pad_sequences`.
Further, this PR also removes from the docs the (wrong) module name of methods of classes like `ImageDataGenerator`. For example, [this is for `apply_transform`](https://keras.io/preprocessing/image/#apply_transform):

> `keras.preprocessing.image.apply_transform` 

which should simply be `apply_transform`, first because it is the method of a class (i.e. `ImageDataGenerator`) and second because the referenced module name is wrong (and this [has caused confusion](https://stackoverflow.com/q/51311062/2099607)).

All of this were caused by the fact that `clean_module_name()` was not called on the `function.__module__` in `render_function` (therefore this mostly affects the docs for `keras.preprocessing` and `keras.applications`). Plus, the way `autogen.py` works, the module name is repeated two times in the signature, but for the non-method functions it should be removed only once (that's why I have added a condition).

### Related Issues
#10658 
#10662 

### PR Overview

- [n] This PR requires new unit tests [y/n] (make sure tests are included)
- [n] This PR requires to update the documentation [y/n] (make sure the docs are up-to-date)
- [y] This PR is backwards compatible [y/n]
- [n] This PR changes the current API [y/n] (all API changes need to be approved by fchollet)

* Fix nested sequential deferred build

* Add test

* Unify style

Enable automatic shape inference when using Lambda layers and CNTK. Also fixed the test_no_grad that was catching ValueErrors that had nothing to do with not having a gradient. (#10647)

### Summary
`normalize_data_format` was being called twice in `_Pooling2D`

### Related Issues

### PR Overview

- [n] This PR requires new unit tests [y/n] (make sure tests are included)
- [n] This PR requires to update the documentation [y/n] (make sure the docs are up-to-date)
- [y] This PR is backwards compatible [y/n]
- [n] This PR changes the current API [y/n] (all API changes need to be approved by fchollet)

### Summary
This PR adds the missing examples to the list of examples in _examples/README.md_.

### PR Overview

- [n] This PR requires new unit tests [y/n] (make sure tests are included)
- [n] This PR requires to update the documentation [y/n] (make sure the docs are up-to-date)
- [y] This PR is backwards compatible [y/n]
- [n] This PR changes the current API [y/n] (all API changes need to be approved by fchollet)

`keras.regularizers.l1_l2()` takes two arguments. The doc was misleading.

In light of SuperConvergence [1], the user might want to increase the learning rate during training so saying 'reducing' is no longer appropriate.
[1]: https://arxiv.org/abs/1708.07120

* Apply mean and stddev to cntk backend's random_normal

* Update backend_test.py

Add test case for non-standard normal distribution parameters

* Make binomial, uniform, and normal random variables vary and add tests

* Fix formatting issues

* Reuse validation enqueuer

* Fix CI

* Indent val_data correctly

* Typo

* Add pr template

* Make uppercase to be consistent

* Change according to review

* Remove unused relu6

* Remove doc for loading relu6

* DOC: Fix IMDB get_word_index documentation

* DOC: Fix reuters get_word_index documentation

* Doc

* Fix indent