mirror of https://github.com/tqdm/tqdm.git
92 lines
2.5 KiB
Python
92 lines
2.5 KiB
Python
from .tests_tqdm import importorskip, mark
|
|
|
|
pytestmark = mark.slow
|
|
|
|
|
|
@mark.filterwarnings("ignore:.*:DeprecationWarning")
|
|
def test_keras(capsys):
|
|
"""Test tqdm.keras.TqdmCallback"""
|
|
TqdmCallback = importorskip('tqdm.keras').TqdmCallback
|
|
np = importorskip('numpy')
|
|
try:
|
|
import keras as K
|
|
except ImportError:
|
|
K = importorskip('tensorflow.keras')
|
|
|
|
# 1D autoencoder
|
|
dtype = np.float32
|
|
model = K.models.Sequential([
|
|
K.layers.InputLayer((1, 1), dtype=dtype), K.layers.Conv1D(1, 1)])
|
|
model.compile("adam", "mse")
|
|
x = np.random.rand(100, 1, 1).astype(dtype)
|
|
batch_size = 10
|
|
batches = len(x) / batch_size
|
|
epochs = 5
|
|
|
|
# just epoch (no batch) progress
|
|
model.fit(
|
|
x,
|
|
x,
|
|
epochs=epochs,
|
|
batch_size=batch_size,
|
|
verbose=False,
|
|
callbacks=[
|
|
TqdmCallback(
|
|
epochs,
|
|
desc="training",
|
|
data_size=len(x),
|
|
batch_size=batch_size,
|
|
verbose=0)])
|
|
_, res = capsys.readouterr()
|
|
assert "training: " in res
|
|
assert f"{epochs}/{epochs}" in res
|
|
assert f"{batches}/{batches}" not in res
|
|
|
|
# full (epoch and batch) progress
|
|
model.fit(
|
|
x,
|
|
x,
|
|
epochs=epochs,
|
|
batch_size=batch_size,
|
|
verbose=False,
|
|
callbacks=[
|
|
TqdmCallback(
|
|
epochs,
|
|
desc="training",
|
|
data_size=len(x),
|
|
batch_size=batch_size,
|
|
verbose=2)])
|
|
_, res = capsys.readouterr()
|
|
assert "training: " in res
|
|
assert f"{epochs}/{epochs}" in res
|
|
assert f"{batches}/{batches}" in res
|
|
|
|
# auto-detect epochs and batches
|
|
model.fit(
|
|
x,
|
|
x,
|
|
epochs=epochs,
|
|
batch_size=batch_size,
|
|
verbose=False,
|
|
callbacks=[TqdmCallback(desc="training", verbose=2)])
|
|
_, res = capsys.readouterr()
|
|
assert "training: " in res
|
|
assert f"{epochs}/{epochs}" in res
|
|
assert f"{batches}/{batches}" in res
|
|
|
|
# continue training (start from epoch != 0)
|
|
initial_epoch = 3
|
|
model.fit(
|
|
x,
|
|
x,
|
|
initial_epoch=initial_epoch,
|
|
epochs=epochs,
|
|
batch_size=batch_size,
|
|
verbose=False,
|
|
callbacks=[TqdmCallback(desc="training", verbose=0,
|
|
miniters=1, mininterval=0, maxinterval=0)])
|
|
_, res = capsys.readouterr()
|
|
assert "training: " in res
|
|
assert f"{initial_epoch - 1}/{initial_epoch - 1}" not in res
|
|
assert f"{epochs}/{epochs}" in res
|