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Update example code in timeseries_dataset.py #14

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Update example code in timeseries_dataset.py #14

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84651ad
Update example code in timeseries_dataset.py
SuryanarayanaY Sep 20, 2023
e8da674
Update timeseries_dataset.py
SuryanarayanaY Sep 20, 2023
baa074b
Update formatting errors timeseries_dataset.py
SuryanarayanaY Nov 6, 2023
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17 changes: 12 additions & 5 deletions tf_keras/utils/timeseries_dataset.py
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Original file line number Diff line number Diff line change
Expand Up @@ -110,16 +110,23 @@ def timeseries_dataset_from_array(
timesteps to predict the next timestep, you would use:

```python
input_data = data[:-10]
targets = data[10:]
data = tf.range(15)
sequence_length =10
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Make sure to run the formatter (add a space before 10)

input_data = data[:]
targets = data[sequence_length:]
dataset = tf.keras.utils.timeseries_dataset_from_array(
input_data, targets, sequence_length=10)
input_data, targets, sequence_length=sequence_length)
for batch in dataset:
inputs, targets = batch
assert np.array_equal(inputs[0], data[:10]) # First sequence: steps [0-9]
# First sequence: steps [0-9]
assert np.array_equal(inputs[0], data[:sequence_length])
# Corresponding target: step 10
assert np.array_equal(targets[0], data[10])
assert np.array_equal(targets[0], data[sequence_length])
break
# To view the generated dataset
for batch in dataset.as_numpy_iterator():
input, label = batch
print(f"Input:{input}, target:{label}")
```

Example 3: Temporal regression for many-to-many architectures.
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