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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
 Copyright 2021 Google LLC
Licensed under the Apache License, Version 2.0 (the "License")
Step1:  Compile a model for the Edge TPU
This notebook offers a convenient way to compile a TensorFlow Lite model for the Edge TPU, in case you don't have a system that's compatible with the Edge TPU Compiler (Debian Linux only).
Simply upload a compatible .tflite file to this Colab session, run the code below, and then download the compiled model.
For more details about how to create a model that's compatible with the Edge TPU, see the documentation at coral.ai.
<a href="https
Step2:  Now click Runtime > Run all in the Colab toolbar.
Get the Edge TPU Compiler
Step3:  Compile the model
Step4:  The compiled model uses the same filename but with "_edgetpu" appended at the end.
If the compilation failed, check the Files panel on the left for the .log file that contains more details. (You might need to click the Refresh button to see the new files.)
Download the model
You can download the converted model from Colab with this
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Python Code:
# 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 2021 Google LLC
Licensed under the Apache License, Version 2.0 (the "License")
End of explanation
%env TFLITE_FILE=example.tflite
Explanation: Compile a model for the Edge TPU
This notebook offers a convenient way to compile a TensorFlow Lite model for the Edge TPU, in case you don't have a system that's compatible with the Edge TPU Compiler (Debian Linux only).
Simply upload a compatible .tflite file to this Colab session, run the code below, and then download the compiled model.
For more details about how to create a model that's compatible with the Edge TPU, see the documentation at coral.ai.
<a href="https://colab.research.google.com/github/google-coral/tutorials/blob/master/compile_for_edgetpu.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a>
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<a href="https://github.com/google-coral/tutorials/blob/master/compile_for_edgetpu.ipynb" target="_parent"><img src="https://img.shields.io/static/v1?logo=GitHub&label=&color=333333&style=flat&message=View%20on%20GitHub" alt="View in GitHub"></a>
Upload a compatible TF Lite model
To use this script, you need to upload a TensorFlow Lite model that's fully quantized and meets all the Edge TPU model requirements.
With a compatible model in-hand, you can upload it as follows:
Click the Files tab (the folder icon) in the left panel. (Do not change directories.)
Click Upload to session storage (the file icon). 
Follow your system UI to select and open your .tflite file.
When it's uploaded, you should see the file appear in the left panel.
4.  Replace example.tflite with your uploaded model's filename:
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! curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | sudo apt-key add -
! echo "deb https://packages.cloud.google.com/apt coral-edgetpu-stable main" | sudo tee /etc/apt/sources.list.d/coral-edgetpu.list
! sudo apt-get update
! sudo apt-get install edgetpu-compiler	
Explanation: Now click Runtime > Run all in the Colab toolbar.
Get the Edge TPU Compiler
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! edgetpu_compiler $TFLITE_FILE
Explanation: Compile the model
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import os
from google.colab import files
name = os.path.splitext(os.environ['TFLITE_FILE'])[0]
files.download(str(name + '_edgetpu.tflite'))
Explanation: The compiled model uses the same filename but with "_edgetpu" appended at the end.
If the compilation failed, check the Files panel on the left for the .log file that contains more details. (You might need to click the Refresh button to see the new files.)
Download the model
You can download the converted model from Colab with this:
End of explanation
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