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Deprecate arg_min and arg_max in the TF 2.0 API.

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PiperOrigin-RevId: 222125023
This commit is contained in:
Mihai Maruseac 2018-11-19 13:05:58 -08:00 committed by TensorFlower Gardener
parent c5695df38c
commit ea3ee9804d
4 changed files with 7 additions and 11 deletions
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4
tensorflow/python/ops/math_ops.py
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@ -51,8 +51,8 @@ linspace = gen_math_ops.lin_space
arg_max = deprecation.deprecated(None, "Use `tf.math.argmax` instead")(arg_max) # pylint: disable=used-before-assignment arg_max = deprecation.deprecated(None, "Use `tf.math.argmax` instead")(arg_max) # pylint: disable=used-before-assignment
arg_min = deprecation.deprecated(None, "Use `tf.math.argmin` instead")(arg_min) # pylint: disable=used-before-assignment arg_min = deprecation.deprecated(None, "Use `tf.math.argmin` instead")(arg_min) # pylint: disable=used-before-assignment
tf_export("arg_max")(arg_max) tf_export(v1=["arg_max"])(arg_max)
tf_export("arg_min")(arg_min) tf_export(v1=["arg_min"])(arg_min)
# This is set by resource_variable_ops.py. It is included in this way since # This is set by resource_variable_ops.py. It is included in this way since
# there is a circular dependency between math_ops and resource_variable_ops # there is a circular dependency between math_ops and resource_variable_ops

8
tensorflow/tools/api/golden/v2/tensorflow.pbtxt
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@ -444,14 +444,6 @@ tf_module {
name: "add_n" name: "add_n"
argspec: "args=[\'inputs\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], " argspec: "args=[\'inputs\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
} }
member_method {
name: "arg_max"
argspec: "args=[\'input\', \'dimension\', \'output_type\', \'name\'], varargs=None, keywords=None, defaults=[\"<dtype: \'int64\'>\", \'None\'], "
}
member_method {
name: "arg_min"
argspec: "args=[\'input\', \'dimension\', \'output_type\', \'name\'], varargs=None, keywords=None, defaults=[\"<dtype: \'int64\'>\", \'None\'], "
}
member_method { member_method {
name: "argmax" name: "argmax"
argspec: "args=[\'input\', \'axis\', \'output_type\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \"<dtype: \'int64\'>\", \'None\'], " argspec: "args=[\'input\', \'axis\', \'output_type\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \"<dtype: \'int64\'>\", \'None\'], "

4
tensorflow/tools/compatibility/renames_v2.py
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@ -70,6 +70,8 @@ renames = {
'tf.all_variables': 'tf.compat.v1.all_variables', 'tf.all_variables': 'tf.compat.v1.all_variables',
'tf.angle': 'tf.math.angle', 'tf.angle': 'tf.math.angle',
'tf.app.run': 'tf.compat.v1.app.run', 'tf.app.run': 'tf.compat.v1.app.run',
'tf.arg_max': 'tf.compat.v1.arg_max',
'tf.arg_min': 'tf.compat.v1.arg_min',
'tf.assert_greater_equal': 'tf.compat.v1.assert_greater_equal', 'tf.assert_greater_equal': 'tf.compat.v1.assert_greater_equal',
'tf.assert_integer': 'tf.compat.v1.assert_integer', 'tf.assert_integer': 'tf.compat.v1.assert_integer',
'tf.assert_less_equal': 'tf.compat.v1.assert_less_equal', 'tf.assert_less_equal': 'tf.compat.v1.assert_less_equal',
@ -562,7 +564,7 @@ renames = {
'tf.variable_scope': 'tf.compat.v1.variable_scope', 'tf.variable_scope': 'tf.compat.v1.variable_scope',
'tf.variables_initializer': 'tf.compat.v1.variables_initializer', 'tf.variables_initializer': 'tf.compat.v1.variables_initializer',
'tf.variance_scaling_initializer': 'tf.keras.initializers.VarianceScaling', 'tf.variance_scaling_initializer': 'tf.keras.initializers.VarianceScaling',
'tf.verify_tensor_all_finite': 'tf.debugging.assert_all_finite', 'tf.verify_tensor_all_finite': 'tf.compat.v1.verify_tensor_all_finite',
'tf.wrap_function': 'tf.compat.v1.wrap_function', 'tf.wrap_function': 'tf.compat.v1.wrap_function',
'tf.write_file': 'tf.io.write_file', 'tf.write_file': 'tf.io.write_file',
'tf.zeta': 'tf.math.zeta' 'tf.zeta': 'tf.math.zeta'

2
tensorflow/tools/compatibility/tf_upgrade_v2.py
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@ -145,6 +145,8 @@ class TFAPIChangeSpec(ast_edits.APIChangeSpec):
"tf.multinomial": "tf.random.categorical", "tf.multinomial": "tf.random.categorical",
"tf.random.multinomial": "tf.random.categorical", "tf.random.multinomial": "tf.random.categorical",
"tf.load_file_system_library": "tf.load_library", "tf.load_file_system_library": "tf.load_library",
"tf.arg_max": "tf.argmax",
"tf.arg_min": "tf.argmin",
}) })
# pylint: enable=line-too-long # pylint: enable=line-too-long