experiments/STT-tensorflow
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Deprecate random_binomial in favor of random_bernoulli.

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PiperOrigin-RevId: 299205387
Change-Id: Id347f893f8e8fd6bf573c62827e96ec4d1de3343
This commit is contained in:
Zhenyu Tan 2020-03-05 15:11:54 -08:00 committed by TensorFlower Gardener
parent a1d2f94d2e
commit 4ab3153140
3 changed files with 28 additions and 0 deletions
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20
tensorflow/python/keras/backend.py
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@ -79,6 +79,7 @@ from tensorflow.python.util import nest
from tensorflow.python.util import object_identity from tensorflow.python.util import object_identity
from tensorflow.python.util import tf_contextlib from tensorflow.python.util import tf_contextlib
from tensorflow.python.util import tf_inspect from tensorflow.python.util import tf_inspect
from tensorflow.python.util.deprecation import deprecated
from tensorflow.python.util.tf_export import keras_export from tensorflow.python.util.tf_export import keras_export
py_all = all py_all = all
@ -5703,10 +5704,13 @@ def random_uniform(shape, minval=0.0, maxval=1.0, dtype=None, seed=None):
shape, minval=minval, maxval=maxval, dtype=dtype, seed=seed) shape, minval=minval, maxval=maxval, dtype=dtype, seed=seed)
@deprecated(None, 'Use `tf.keras.backend.random_bernoulli` instead.')
@keras_export('keras.backend.random_binomial') @keras_export('keras.backend.random_binomial')
def random_binomial(shape, p=0.0, dtype=None, seed=None): def random_binomial(shape, p=0.0, dtype=None, seed=None):
"""Returns a tensor with random binomial distribution of values. """Returns a tensor with random binomial distribution of values.
DEPRECATED, use `tf.keras.backend.random_bernoulli` instead.
The binomial distribution with parameters `n` and `p` is the probability The binomial distribution with parameters `n` and `p` is the probability
distribution of the number of successful Bernoulli process. Only supports distribution of the number of successful Bernoulli process. Only supports
`n` = 1 for now. `n` = 1 for now.
@ -5729,6 +5733,22 @@ def random_binomial(shape, p=0.0, dtype=None, seed=None):
array_ops.ones(shape, dtype=dtype), array_ops.zeros(shape, dtype=dtype)) array_ops.ones(shape, dtype=dtype), array_ops.zeros(shape, dtype=dtype))
@keras_export('keras.backend.random_bernoulli')
def random_bernoulli(shape, p=0.0, dtype=None, seed=None):
"""Returns a tensor with random bernoulli distribution of values.
Arguments:
shape: A tuple of integers, the shape of tensor to create.
p: A float, `0. <= p <= 1`, probability of bernoulli distribution.
dtype: String, dtype of returned tensor.
seed: Integer, random seed.
Returns:
A tensor.
"""
return random_binomial(shape, p, dtype, seed)
@keras_export('keras.backend.truncated_normal') @keras_export('keras.backend.truncated_normal')
def truncated_normal(shape, mean=0.0, stddev=1.0, dtype=None, seed=None): def truncated_normal(shape, mean=0.0, stddev=1.0, dtype=None, seed=None):
"""Returns a tensor with truncated random normal distribution of values. """Returns a tensor with truncated random normal distribution of values.

4
tensorflow/tools/api/golden/v1/tensorflow.keras.backend.pbtxt
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@ -372,6 +372,10 @@ tf_module {
name: "prod" name: "prod"
argspec: "args=[\'x\', \'axis\', \'keepdims\'], varargs=None, keywords=None, defaults=[\'None\', \'False\'], " argspec: "args=[\'x\', \'axis\', \'keepdims\'], varargs=None, keywords=None, defaults=[\'None\', \'False\'], "
} }
member_method {
name: "random_bernoulli"
argspec: "args=[\'shape\', \'p\', \'dtype\', \'seed\'], varargs=None, keywords=None, defaults=[\'0.0\', \'None\', \'None\'], "
}
member_method { member_method {
name: "random_binomial" name: "random_binomial"
argspec: "args=[\'shape\', \'p\', \'dtype\', \'seed\'], varargs=None, keywords=None, defaults=[\'0.0\', \'None\', \'None\'], " argspec: "args=[\'shape\', \'p\', \'dtype\', \'seed\'], varargs=None, keywords=None, defaults=[\'0.0\', \'None\', \'None\'], "

4
tensorflow/tools/api/golden/v2/tensorflow.keras.backend.pbtxt
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@ -368,6 +368,10 @@ tf_module {
name: "prod" name: "prod"
argspec: "args=[\'x\', \'axis\', \'keepdims\'], varargs=None, keywords=None, defaults=[\'None\', \'False\'], " argspec: "args=[\'x\', \'axis\', \'keepdims\'], varargs=None, keywords=None, defaults=[\'None\', \'False\'], "
} }
member_method {
name: "random_bernoulli"
argspec: "args=[\'shape\', \'p\', \'dtype\', \'seed\'], varargs=None, keywords=None, defaults=[\'0.0\', \'None\', \'None\'], "
}
member_method { member_method {
name: "random_binomial" name: "random_binomial"
argspec: "args=[\'shape\', \'p\', \'dtype\', \'seed\'], varargs=None, keywords=None, defaults=[\'0.0\', \'None\', \'None\'], " argspec: "args=[\'shape\', \'p\', \'dtype\', \'seed\'], varargs=None, keywords=None, defaults=[\'0.0\', \'None\', \'None\'], "