Deprecate `tf.train.input_producer()` and related APIs.

These APIs are based on queue runners, which have been deprecated and will be removed in TensorFlow 2.0. They have been replaced with `tf.data.Dataset`, which provides a more efficient version of the same functionality.

PiperOrigin-RevId: 211727844

1 files changed, 27 insertions, 5 deletions

diff --git a/tensorflow/python/training/input.py b/tensorflow/python/training/input.py
index 94c6b47027..9d9db70890 100644
--- a/tensorflow/python/training/input.py
+++ b/tensorflow/python/training/input.py
@@ -76,7 +76,10 @@ def match_filenames_once(pattern, name=None):
         collections=[ops.GraphKeys.LOCAL_VARIABLES])
 
 
-@tf_export("train.limit_epochs")
+@tf_export(v1=["train.limit_epochs"])
+@deprecation.deprecated(
+    None, "Queue-based input pipelines have been replaced by `tf.data`. Use "
+    "`tf.data.Dataset.from_tensors(tensor).repeat(num_epochs)`.")
 def limit_epochs(tensor, num_epochs=None, name=None):
   """Returns tensor `num_epochs` times and then raises an `OutOfRange` error.
 
@@ -109,7 +112,12 @@ def limit_epochs(tensor, num_epochs=None, name=None):
       return array_ops.identity(tensor, name=name)
 
 
-@tf_export("train.input_producer")
+@tf_export(v1=["train.input_producer"])
+@deprecation.deprecated(
+    None, "Queue-based input pipelines have been replaced by `tf.data`. Use "
+    "`tf.data.Dataset.from_tensor_slices(input_tensor).shuffle"
+    "(tf.shape(input_tensor, out_type=tf.int64)[0]).repeat(num_epochs)`. If "
+    "`shuffle=False`, omit the `.shuffle(...)`.")
 def input_producer(input_tensor,
                    element_shape=None,
                    num_epochs=None,
@@ -192,7 +200,12 @@ def input_producer(input_tensor,
     return q
 
 
-@tf_export("train.string_input_producer")
+@tf_export(v1=["train.string_input_producer"])
+@deprecation.deprecated(
+    None, "Queue-based input pipelines have been replaced by `tf.data`. Use "
+    "`tf.data.Dataset.from_tensor_slices(string_tensor).shuffle"
+    "(tf.shape(input_tensor, out_type=tf.int64)[0]).repeat(num_epochs)`. If "
+    "`shuffle=False`, omit the `.shuffle(...)`.")
 def string_input_producer(string_tensor,
                           num_epochs=None,
                           shuffle=True,
@@ -262,7 +275,11 @@ def string_input_producer(string_tensor,
         cancel_op=cancel_op)
 
 
-@tf_export("train.range_input_producer")
+@tf_export(v1=["train.range_input_producer"])
+@deprecation.deprecated(
+    None, "Queue-based input pipelines have been replaced by `tf.data`. Use "
+    "`tf.data.Dataset.range(limit).shuffle(limit).repeat(num_epochs)`. If "
+    "`shuffle=False`, omit the `.shuffle(...)`.")
 def range_input_producer(limit, num_epochs=None, shuffle=True, seed=None,
                          capacity=32, shared_name=None, name=None):
   """Produces the integers from 0 to limit-1 in a queue.
@@ -300,7 +317,12 @@ def range_input_producer(limit, num_epochs=None, shuffle=True, seed=None,
         shared_name, "fraction_of_%d_full" % capacity, name)
 
 
-@tf_export("train.slice_input_producer")
+@tf_export(v1=["train.slice_input_producer"])
+@deprecation.deprecated(
+    None, "Queue-based input pipelines have been replaced by `tf.data`. Use "
+    "`tf.data.Dataset.from_tensor_slices(tuple(tensor_list)).shuffle"
+    "(tf.shape(input_tensor, out_type=tf.int64)[0]).repeat(num_epochs)`. If "
+    "`shuffle=False`, omit the `.shuffle(...)`.")
 def slice_input_producer(tensor_list, num_epochs=None, shuffle=True, seed=None,
                          capacity=32, shared_name=None, name=None):
   """Produces a slice of each `Tensor` in `tensor_list`.