<SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
 Copyright 2020 The TensorFlow Authors.
Step1:  Title
<table class="tfo-notebook-buttons" align="left">
  <td>
    <a target="_blank" href="https
Step2:  Resources
TensorFlow documentation contributor guide
TensorFlow documentation style guide
Google developer documentation style guide
Notebook style
Include the collapsed license at the top (uses the Colab "Form" mode to hide the cells).
Save the notebook with the table of contents open.
Use one H1 header for the title.
Include the button-bar immediately after the H1.
Headers that areH4 and below are not visible in the navigation
bar of tensorflow.org.
Include an overview section before any code.
Put all your installs and imports in a setup section.
Keep code and text cells as brief as possible.
Break text cells at headings
Break code cells between "building" and "running", and between "printing one result" and "printing another result".
Necessary but uninteresting code (like plotting logic) should be hidden in a toggleable code cell by putting #@title as the first line.
Code style
Notebooks are for people. Write code optimized for clarity.
Use the Google Python Style Guide, where applicable.
tensorflow.org doesn't support interactive plots.
Keep examples quick. Use small datasets, or small slices of datasets. Don't train to convergence, train until it's obvious it's making progress.
If you define a function, run it and show us what it does before using it in another function.
Demonstrate small parts before combining them into something more complex, like this
Step3:  Run the model on a single batch of data, and inspect the output
Step4:  Compile the model for training
<ASSISTANT_TASK:>
Python Code:
#@title Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
Explanation: Copyright 2020 The TensorFlow Authors.
End of explanation
import tensorflow as tf
import numpy as np
Explanation: Title
<table class="tfo-notebook-buttons" align="left">
  <td>
    <a target="_blank" href="https://www.tensorflow.org/not_a_real_link"><img src="https://www.tensorflow.org/images/tf_logo_32px.png" />View on TensorFlow.org</a>
  </td>
  <td>
    <a target="_blank" href="https://colab.research.google.com/github/tensorflow/docs/blob/master/tools/templates/notebook.ipynb"><img src="https://www.tensorflow.org/images/colab_logo_32px.png" />Run in Google Colab</a>
  </td>
  <td>
    <a target="_blank" href="https://github.com/tensorflow/docs/blob/master/tools/templates/notebook.ipynb"><img src="https://www.tensorflow.org/images/GitHub-Mark-32px.png" />View on GitHub</a>
  </td>
  <td>
    <a href="https://storage.googleapis.com/tensorflow_docs/docs/tools/templates/notebook.ipynb"><img src="https://www.tensorflow.org/images/download_logo_32px.png" />Download notebook</a>
  </td>
  <td>
    <a href="https://tfhub.dev/"><img src="https://www.tensorflow.org/images/hub_logo_32px.png" />See TF Hub model</a>
  </td>
</table>
[Update button links]
See model on TFHub is only required if the notebook uses a model from tfhub.dev
Overview
[Include a paragraph or two explaining what this example demonstrates, who should be interested in it, and what you need to know before you get started.]
Setup
[Put all your imports and installs up into a setup section.]
End of explanation
# Build the model
model = tf.keras.Sequential([
    tf.keras.layers.Dense(10, activation='relu', input_shape=(None, 5)),
    tf.keras.layers.Dense(3)
])
Explanation: Resources
TensorFlow documentation contributor guide
TensorFlow documentation style guide
Google developer documentation style guide
Notebook style
Include the collapsed license at the top (uses the Colab "Form" mode to hide the cells).
Save the notebook with the table of contents open.
Use one H1 header for the title.
Include the button-bar immediately after the H1.
Headers that areH4 and below are not visible in the navigation
bar of tensorflow.org.
Include an overview section before any code.
Put all your installs and imports in a setup section.
Keep code and text cells as brief as possible.
Break text cells at headings
Break code cells between "building" and "running", and between "printing one result" and "printing another result".
Necessary but uninteresting code (like plotting logic) should be hidden in a toggleable code cell by putting #@title as the first line.
Code style
Notebooks are for people. Write code optimized for clarity.
Use the Google Python Style Guide, where applicable.
tensorflow.org doesn't support interactive plots.
Keep examples quick. Use small datasets, or small slices of datasets. Don't train to convergence, train until it's obvious it's making progress.
If you define a function, run it and show us what it does before using it in another function.
Demonstrate small parts before combining them into something more complex, like this:
End of explanation
result = model(tf.constant(np.random.randn(10,5), dtype = tf.float32)).numpy()
print("min:", result.min())
print("max:", result.max())
print("mean:", result.mean())
print("shape:", result.shape)
Explanation: Run the model on a single batch of data, and inspect the output:
End of explanation
model.compile(optimizer=tf.keras.optimizers.Adam(),
              loss=tf.keras.losses.categorical_crossentropy)
Explanation: Compile the model for training:
End of explanation
<END_TASK>