message: "All_files" is no longer necessary (ref: cl/190878279)
  `layers` subclassing instructions are out of date.
diff: @@ -47,27 +47,7 @@ licenses(["notice"]) # Apache 2.0
  exports_files(["LICENSE"])
  ```
  -* At the end of every BUILD file, should contain:
  -```
  -filegroup(
  - name = "all_files",
  - srcs = glob(
  - ["**/*"],
  - exclude = [
  - "**/METADATA",
  - "**/OWNERS",
  - ],
  - ),
  - visibility = ["//tensorflow:__subpackages__"],
  -)
  -```
  -
  -* When adding new BUILD file, add this line to `tensorflow/BUILD` file into `all_opensource_files` target.
  -
  -```
  -"//tensorflow/<directory>:all_files",
  -```
  * For all Python BUILD targets (libraries and tests) add next line:
  @@ -80,6 +60,9 @@ srcs_version = "PY2AND3",
  * Operations that deal with batches may assume that the first dimension of a Tensor is the batch dimension.
  +* In most models the *last dimension* is the number of channels.
  +
  +* Dimensions excluding the first and last usually make up the "space" dimensions: Sequence-length or Image-size.
  ## Python operations
  @@ -148,37 +131,6 @@ Usage:
  ## Layers
  -A *Layer* is a Python operation that combines variable creation and/or one or many
  -other graph operations. Follow the same requirements as for regular Python
  -operation.
  -
  -* If a layer creates one or more variables, the layer function
  - should take next arguments also following order:
  - - `initializers`: Optionally allow to specify initializers for the variables.
  - - `regularizers`: Optionally allow to specify regularizers for the variables.
  - - `trainable`: which control if their variables are trainable or not.
  - - `scope`: `VariableScope` object that variable will be put under.
  - - `reuse`: `bool` indicator if the variable should be reused if
  - it's present in the scope.
  -
  -* Layers that behave differently during training should take:
  - - `is_training`: `bool` indicator to conditionally choose different
  - computation paths (e.g. using `tf.cond`) during execution.
  -
  -Example:
  -
  - def conv2d(inputs,
  - num_filters_out,
  - kernel_size,
  - stride=1,
  - padding='SAME',
  - activation_fn=tf.nn.relu,
  - normalization_fn=add_bias,
  - normalization_params=None,
  - initializers=None,
  - regularizers=None,
  - trainable=True,
  - scope=None,
  - reuse=None):
  - ... see implementation at tensorflow/contrib/layers/python/layers/layers.py ...
  +Use `tf.keras.layers`, not `tf.layers`.
  +See `tf.keras.layers` and [the Keras guide](../guide/keras.md#custom_layers) for details on how to sub-class layers.
  