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Change so that tf.random_poisson is renamed to the v2 API instead of to compat

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PiperOrigin-RevId: 229150058
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Tamara Norman 2019-01-14 02:42:51 -08:00 committed by TensorFlower Gardener
parent 4ac9bda9d0
commit 267263629f
3 changed files with 11 additions and 1 deletions
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1
tensorflow/tools/compatibility/renames_v2.py
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@ -478,7 +478,6 @@ renames = {
'tf.random_crop': 'tf.image.random_crop', 'tf.random_crop': 'tf.image.random_crop',
'tf.random_gamma': 'tf.random.gamma', 'tf.random_gamma': 'tf.random.gamma',
'tf.random_normal': 'tf.random.normal', 'tf.random_normal': 'tf.random.normal',
'tf.random_poisson': 'tf.compat.v1.random_poisson',
'tf.random_shuffle': 'tf.random.shuffle', 'tf.random_shuffle': 'tf.random.shuffle',
'tf.random_uniform': 'tf.random.uniform', 'tf.random_uniform': 'tf.random.uniform',
'tf.read_file': 'tf.io.read_file', 'tf.read_file': 'tf.io.read_file',

2
tensorflow/tools/compatibility/tf_upgrade_v2.py
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@ -601,6 +601,8 @@ class TFAPIChangeSpec(ast_edits.APIChangeSpec):
"tf.compat.v1.initializers.truncated_normal", "tf.compat.v1.initializers.truncated_normal",
"tf.image.resize_images": "tf.image.resize_images":
"tf.image.resize", "tf.image.resize",
"tf.random_poisson":
"tf.random.poisson",
} }
# pylint: enable=line-too-long # pylint: enable=line-too-long

9
tensorflow/tools/compatibility/tf_upgrade_v2_test.py
View File

@ -539,6 +539,15 @@ bazel-bin/tensorflow/tools/compatibility/update/generate_v2_reorders_map
) )
self.assertEqual(new_text, expected_text) self.assertEqual(new_text, expected_text)
def testRandomPoissonConversion(self):
text1 = "tf.random_poisson(lam, shape, dtype)"
text2 = "tf.random.poisson(lam, shape, dtype)"
expected_text = "tf.random.poisson(lam=lam, shape=shape, dtype=dtype)"
_, unused_report, unused_errors, new_text1 = self._upgrade(text1)
self.assertEqual(new_text1, expected_text)
_, unused_report, unused_errors, new_text2 = self._upgrade(text2)
self.assertEqual(new_text2, expected_text)
def testConvolutionOpUpdate(self): def testConvolutionOpUpdate(self):
text = ( text = (
"tf.nn.convolution(input, filter, padding, strides, dilation_rate, " "tf.nn.convolution(input, filter, padding, strides, dilation_rate, "