Batching
Batching is a set of tools to format data for training sequence models.
Installation
$ pip install batching
Example usage
Example script exists in sample.py
# Metadata for batch info - including batch IDs and mappings to storage resouces like filenames
storage_meta = StorageMeta(validation_split=0.2)
# Storage for batch data - Memory, Files, S3
storage = BatchStorageMemory(storage_meta)
# Create batches - configuration contains feature names, windowing config, timeseries spacing
batch_generator = Builder(storage,
feature_set,
look_back,
look_forward,
batch_seconds,
batch_size=128)
batch_generator.generate_and_save_batches(list_of_dataframes)
# Generator for feeding batches to training - tf.keras.model.fit_generator
train_generator = BatchGenerator(storage)
validation_generator = BatchGenerator(storage, is_validation=True)
model = tf.keras.Sequential()
model.add(tf.keras.layers.Dense(1, activation='sigmoid')
model.compile(loss=tf.keras.losses.binary_crossentropy,
optimizer=tf.keras.optimizers.Adam(),
metrics=['accuracy'])
model.fit_generator(train_generator,
validation_data=validation_generator,
epochs=epochs)
License
- MIT license
- Copyright 2015 © FVCproductions.
1 maintainer
Metadata
1 maintainer
Release files for batching 1.2.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| batching-1.2.0.tar.gz | 9.9 kB | Details |
Release files / batching-1.2.0.tar.gz
| Download URL | batching-1.2.0.tar.gz |
|---|---|
| Size | 9.9 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
8ef11879c4edf320db72a1dd70203f23f28bd399a1eafaf76adc4779f80cda05
|
|
BLAKE2b-256 checksum How to use checksums |
45294525e96a0d128488e2572464839a85c8a124b697f6e64d089d625a6d07d5
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.0 CPython/3.8.12
|
