mirror of https://github.com/tqdm/tqdm.git
95 lines
2.7 KiB
Python
95 lines
2.7 KiB
Python
from __future__ import division
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from tqdm import tqdm
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from .tests_tqdm import pretest_posttest # NOQA
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from .tests_tqdm import importorskip, StringIO, closing
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def test_keras():
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"""Test tqdm.keras.TqdmCallback"""
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TqdmCallback = importorskip("tqdm.keras").TqdmCallback
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np = importorskip("numpy")
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try:
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import keras as K
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except ImportError:
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K = importorskip("tensorflow.keras")
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# 1D autoencoder
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dtype = np.float32
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model = K.models.Sequential(
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[K.layers.InputLayer((1, 1), dtype=dtype), K.layers.Conv1D(1, 1)]
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)
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model.compile("adam", "mse")
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x = np.random.rand(100, 1, 1).astype(dtype)
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batch_size = 10
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batches = len(x) / batch_size
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epochs = 5
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with closing(StringIO()) as our_file:
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class Tqdm(tqdm):
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"""redirected I/O class"""
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def __init__(self, *a, **k):
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k.setdefault("file", our_file)
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super(Tqdm, self).__init__(*a, **k)
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# just epoch (no batch) progress
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model.fit(
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x,
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x,
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epochs=epochs,
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batch_size=batch_size,
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verbose=False,
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callbacks=[
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TqdmCallback(
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epochs,
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data_size=len(x),
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batch_size=batch_size,
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verbose=0,
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tqdm_class=Tqdm,
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)
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],
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)
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res = our_file.getvalue()
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assert "{epochs}/{epochs}".format(epochs=epochs) in res
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assert "{batches}/{batches}".format(batches=batches) not in res
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# full (epoch and batch) progress
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our_file.seek(0)
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our_file.truncate()
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model.fit(
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x,
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x,
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epochs=epochs,
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batch_size=batch_size,
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verbose=False,
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callbacks=[
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TqdmCallback(
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epochs,
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data_size=len(x),
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batch_size=batch_size,
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verbose=2,
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tqdm_class=Tqdm,
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)
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],
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)
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res = our_file.getvalue()
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assert "{epochs}/{epochs}".format(epochs=epochs) in res
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assert "{batches}/{batches}".format(batches=batches) in res
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# auto-detect epochs and batches
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our_file.seek(0)
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our_file.truncate()
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model.fit(
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x,
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x,
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epochs=epochs,
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batch_size=batch_size,
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verbose=False,
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callbacks=[TqdmCallback(verbose=2, tqdm_class=Tqdm)],
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)
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res = our_file.getvalue()
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assert "{epochs}/{epochs}".format(epochs=epochs) in res
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assert "{batches}/{batches}".format(batches=batches) in res
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