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From: Stephen Sinclair <radarsat1@gmail.com>
Date: Thu, 2 Jul 2020 22:01:48 +0000
Subject: Do not use is with literals
Fixes a SyntaxWarning introduced in Python 3.8.
---
keras/backend/numpy_backend.py | 2 +-
keras/backend/tensorflow_backend.py | 4 ++--
keras/backend/theano_backend.py | 4 ++--
keras/losses.py | 4 ++--
4 files changed, 7 insertions(+), 7 deletions(-)
diff --git a/keras/backend/numpy_backend.py b/keras/backend/numpy_backend.py
index e334a7b..42fe6d8 100644
--- a/keras/backend/numpy_backend.py
+++ b/keras/backend/numpy_backend.py
@@ -249,7 +249,7 @@ def in_train_phase(x, alt, training=None):
if training is None:
training = learning_phase()
- if training is 1 or training is True:
+ if training == 1 or training is True:
if callable(x):
return x()
else:
diff --git a/keras/backend/tensorflow_backend.py b/keras/backend/tensorflow_backend.py
index 5df41eb..99564c3 100644
--- a/keras/backend/tensorflow_backend.py
+++ b/keras/backend/tensorflow_backend.py
@@ -3198,13 +3198,13 @@ def in_train_phase(x, alt, training=None):
else:
uses_learning_phase = False
- if training is 1 or training is True:
+ if training == 1 or training is True:
if callable(x):
return x()
else:
return x
- elif training is 0 or training is False:
+ elif training == 0 or training is False:
if callable(alt):
return alt()
else:
diff --git a/keras/backend/theano_backend.py b/keras/backend/theano_backend.py
index 837ebe9..f271694 100644
--- a/keras/backend/theano_backend.py
+++ b/keras/backend/theano_backend.py
@@ -1731,13 +1731,13 @@ def in_train_phase(x, alt, training=None):
else:
uses_learning_phase = False
- if training is 1 or training is True:
+ if training == 1 or training is True:
if callable(x):
return x()
else:
return x
- elif training is 0 or training is False:
+ elif training == 0 or training is False:
if callable(alt):
return alt()
else:
diff --git a/keras/losses.py b/keras/losses.py
index 11eeb04..e537c8d 100644
--- a/keras/losses.py
+++ b/keras/losses.py
@@ -680,7 +680,7 @@ def categorical_crossentropy(y_true, y_pred, from_logits=False, label_smoothing=
y_pred = K.constant(y_pred) if not K.is_tensor(y_pred) else y_pred
y_true = K.cast(y_true, y_pred.dtype)
- if label_smoothing is not 0:
+ if label_smoothing != 0:
smoothing = K.cast_to_floatx(label_smoothing)
def _smooth_labels():
@@ -699,7 +699,7 @@ def sparse_categorical_crossentropy(y_true, y_pred, from_logits=False, axis=-1):
def binary_crossentropy(y_true, y_pred, from_logits=False, label_smoothing=0):
y_pred = K.constant(y_pred) if not K.is_tensor(y_pred) else y_pred
y_true = K.cast(y_true, y_pred.dtype)
- if label_smoothing is not 0:
+ if label_smoothing != 0:
smoothing = K.cast_to_floatx(label_smoothing)
y_true = K.switch(K.greater(smoothing, 0),
lambda: y_true * (1.0 - smoothing) + 0.5 * smoothing,
|
