Discard some unneccessary logging commands.
PiperOrigin-RevId: 168500721
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@ -27,7 +27,6 @@ from tensorflow.python.ops import nn
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from tensorflow.python.ops import nn_ops
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from tensorflow.python.ops import nn_ops
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from tensorflow.python.ops import weights_broadcast_ops
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from tensorflow.python.ops import weights_broadcast_ops
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from tensorflow.python.ops.losses import util
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from tensorflow.python.ops.losses import util
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from tensorflow.python.platform import tf_logging as logging
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class Reduction(object):
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class Reduction(object):
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@ -614,9 +613,7 @@ def sigmoid_cross_entropy(
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with ops.name_scope(scope, "sigmoid_cross_entropy_loss",
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with ops.name_scope(scope, "sigmoid_cross_entropy_loss",
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(logits, multi_class_labels, weights)) as scope:
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(logits, multi_class_labels, weights)) as scope:
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logits = ops.convert_to_tensor(logits)
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logits = ops.convert_to_tensor(logits)
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logging.info("logits.dtype=%s.", logits.dtype)
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multi_class_labels = math_ops.cast(multi_class_labels, logits.dtype)
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multi_class_labels = math_ops.cast(multi_class_labels, logits.dtype)
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logging.info("multi_class_labels.dtype=%s.", multi_class_labels.dtype)
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logits.get_shape().assert_is_compatible_with(multi_class_labels.get_shape())
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logits.get_shape().assert_is_compatible_with(multi_class_labels.get_shape())
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if label_smoothing > 0:
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if label_smoothing > 0:
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@ -626,7 +623,6 @@ def sigmoid_cross_entropy(
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losses = nn.sigmoid_cross_entropy_with_logits(labels=multi_class_labels,
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losses = nn.sigmoid_cross_entropy_with_logits(labels=multi_class_labels,
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logits=logits,
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logits=logits,
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name="xentropy")
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name="xentropy")
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logging.info("losses.dtype=%s.", losses.dtype)
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return compute_weighted_loss(
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return compute_weighted_loss(
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losses, weights, scope, loss_collection, reduction=reduction)
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losses, weights, scope, loss_collection, reduction=reduction)
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