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| author | Alex Tawse <alex.tawse@arm.com> | 2023-09-29 15:55:38 +0100 |
|---|---|---|
| committer | Richard <richard.burton@arm.com> | 2023-10-26 12:35:48 +0000 |
| commit | daba3cf2e3633cbd0e4f8aabe7578b97e88deee1 (patch) | |
| tree | 51024b8025e28ecb2aecd67246e189e25f5a6e6c /model_conditioning_examples/training_utils.py | |
| parent | a11976fb866f77305708f832e603b963969e6a14 (diff) | |
| download | ml-embedded-evaluation-kit-daba3cf2e3633cbd0e4f8aabe7578b97e88deee1.tar.gz | |
MLECO-3995: Pylint + Shellcheck compatibility
* All Python scripts updated to abide by Pylint rules
* good-names updated to permit short variable names:
i, j, k, f, g, ex
* ignore-long-lines regex updated to allow long lines
for licence headers
* Shell scripts now compliant with Shellcheck
Signed-off-by: Alex Tawse <Alex.Tawse@arm.com>
Change-Id: I8d5af8279bc08bb8acfe8f6ee7df34965552bbe5
Diffstat (limited to 'model_conditioning_examples/training_utils.py')
| -rw-r--r-- | model_conditioning_examples/training_utils.py | 5 |
1 files changed, 3 insertions, 2 deletions
diff --git a/model_conditioning_examples/training_utils.py b/model_conditioning_examples/training_utils.py index a022bd1..2ce94b8 100644 --- a/model_conditioning_examples/training_utils.py +++ b/model_conditioning_examples/training_utils.py @@ -1,4 +1,4 @@ -# SPDX-FileCopyrightText: Copyright 2021 Arm Limited and/or its affiliates <open-source-office@arm.com> +# SPDX-FileCopyrightText: Copyright 2021, 2023 Arm Limited and/or its affiliates <open-source-office@arm.com> # SPDX-License-Identifier: Apache-2.0 # # Licensed under the Apache License, Version 2.0 (the "License"); @@ -49,7 +49,8 @@ def create_model(): """ keras_model = tf.keras.models.Sequential([ - tf.keras.layers.Conv2D(32, 3, padding='same', input_shape=(28, 28, 1), activation=tf.nn.relu), + tf.keras.layers.Conv2D(32, 3, padding='same', + input_shape=(28, 28, 1), activation=tf.nn.relu), tf.keras.layers.Conv2D(32, 3, padding='same', activation=tf.nn.relu), tf.keras.layers.MaxPool2D(), tf.keras.layers.Conv2D(32, 3, padding='same', activation=tf.nn.relu), |