Add deprecation notice for BasicRNNCell, which will be replaced by keras.SimpleRNNCell.

PiperOrigin-RevId: 215249611

4 files changed, 42 insertions, 207 deletions

diff --git a/tensorflow/python/kernel_tests/rnn_test.py b/tensorflow/python/kernel_tests/rnn_test.py
index 05ad9f6336..2f6963f6b8 100644
--- a/tensorflow/python/kernel_tests/rnn_test.py
+++ b/tensorflow/python/kernel_tests/rnn_test.py
@@ -535,6 +535,45 @@ class RNNTest(test.TestCase):
     self.assertAllClose(tf_out, k_out)
     self.assertAllClose(tf_state, k_state)
 
+  def testSimpleRNNCellAndBasicRNNCellComparison(self):
+    input_shape = 10
+    output_shape = 5
+    timestep = 4
+    batch = 20
+    (x_train, _), _ = testing_utils.get_test_data(
+        train_samples=batch,
+        test_samples=0,
+        input_shape=(timestep, input_shape),
+        num_classes=output_shape)
+    fix_weights_generator = keras.layers.SimpleRNNCell(output_shape)
+    fix_weights_generator.build((None, input_shape))
+    # The SimpleRNNCell contains 3 weights: kernel, recurrent_kernel, and bias
+    # The BasicRNNCell contains 2 weight: kernel and bias, where kernel is
+    # zipped [kernel, recurrent_kernel] in SimpleRNNCell.
+    keras_weights = fix_weights_generator.get_weights()
+    kernel, recurrent_kernel, bias = keras_weights
+    tf_weights = [np.concatenate((kernel, recurrent_kernel)), bias]
+
+    with self.test_session(graph=ops_lib.Graph()) as sess:
+      inputs = array_ops.placeholder(
+          dtypes.float32, shape=(None, timestep, input_shape))
+      cell = keras.layers.SimpleRNNCell(output_shape)
+      k_out, k_state = rnn.dynamic_rnn(
+          cell, inputs, dtype=dtypes.float32)
+      cell.set_weights(keras_weights)
+      [k_out, k_state] = sess.run([k_out, k_state], {inputs: x_train})
+    with self.test_session(graph=ops_lib.Graph()) as sess:
+      inputs = array_ops.placeholder(
+          dtypes.float32, shape=(None, timestep, input_shape))
+      cell = rnn_cell_impl.BasicRNNCell(output_shape)
+      tf_out, tf_state = rnn.dynamic_rnn(
+          cell, inputs, dtype=dtypes.float32)
+      cell.set_weights(tf_weights)
+      [tf_out, tf_state] = sess.run([tf_out, tf_state], {inputs: x_train})
+
+    self.assertAllClose(tf_out, k_out)
+    self.assertAllClose(tf_state, k_state)
+
   def testBasicLSTMCellInterchangeWithLSTMCell(self):
     with self.session(graph=ops_lib.Graph()) as sess:
       basic_cell = rnn_cell_impl.BasicLSTMCell(1)
diff --git a/tensorflow/python/ops/rnn_cell_impl.py b/tensorflow/python/ops/rnn_cell_impl.py
index c2751e529a..dd4f3d7a99 100644
--- a/tensorflow/python/ops/rnn_cell_impl.py
+++ b/tensorflow/python/ops/rnn_cell_impl.py
@@ -370,7 +370,7 @@ class LayerRNNCell(RNNCell):
                                      *args, **kwargs)
 
 
-@tf_export("nn.rnn_cell.BasicRNNCell")
+@tf_export(v1=["nn.rnn_cell.BasicRNNCell"])
 class BasicRNNCell(LayerRNNCell):
   """The most basic RNN cell.
 
@@ -393,6 +393,8 @@ class BasicRNNCell(LayerRNNCell):
       `trainable` etc when constructing the cell from configs of get_config().
   """
 
+  @deprecated(None, "This class is equivalent as tf.keras.layers.SimpleRNNCell,"
+                    " and will be replaced by that in Tensorflow 2.0.")
   def __init__(self,
                num_units,
                activation=None,
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.nn.rnn_cell.-basic-r-n-n-cell.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.nn.rnn_cell.-basic-r-n-n-cell.pbtxt
deleted file mode 100644
index a4483fefa2..0000000000
--- a/tensorflow/tools/api/golden/v2/tensorflow.nn.rnn_cell.-basic-r-n-n-cell.pbtxt
+++ /dev/null
@@ -1,202 +0,0 @@
-path: "tensorflow.nn.rnn_cell.BasicRNNCell"
-tf_class {
-  is_instance: "<class \'tensorflow.python.ops.rnn_cell_impl.BasicRNNCell\'>"
-  is_instance: "<class \'tensorflow.python.ops.rnn_cell_impl.LayerRNNCell\'>"
-  is_instance: "<class \'tensorflow.python.ops.rnn_cell_impl.RNNCell\'>"
-  is_instance: "<class \'tensorflow.python.layers.base.Layer\'>"
-  is_instance: "<class \'tensorflow.python.keras.engine.base_layer.Layer\'>"
-  is_instance: "<class \'tensorflow.python.training.checkpointable.base.CheckpointableBase\'>"
-  is_instance: "<type \'object\'>"
-  member {
-    name: "activity_regularizer"
-    mtype: "<type \'property\'>"
-  }
-  member {
-    name: "dtype"
-    mtype: "<type \'property\'>"
-  }
-  member {
-    name: "graph"
-    mtype: "<type \'property\'>"
-  }
-  member {
-    name: "inbound_nodes"
-    mtype: "<type \'property\'>"
-  }
-  member {
-    name: "input"
-    mtype: "<type \'property\'>"
-  }
-  member {
-    name: "input_mask"
-    mtype: "<type \'property\'>"
-  }
-  member {
-    name: "input_shape"
-    mtype: "<type \'property\'>"
-  }
-  member {
-    name: "losses"
-    mtype: "<type \'property\'>"
-  }
-  member {
-    name: "name"
-    mtype: "<type \'property\'>"
-  }
-  member {
-    name: "non_trainable_variables"
-    mtype: "<type \'property\'>"
-  }
-  member {
-    name: "non_trainable_weights"
-    mtype: "<type \'property\'>"
-  }
-  member {
-    name: "outbound_nodes"
-    mtype: "<type \'property\'>"
-  }
-  member {
-    name: "output"
-    mtype: "<type \'property\'>"
-  }
-  member {
-    name: "output_mask"
-    mtype: "<type \'property\'>"
-  }
-  member {
-    name: "output_shape"
-    mtype: "<type \'property\'>"
-  }
-  member {
-    name: "output_size"
-    mtype: "<type \'property\'>"
-  }
-  member {
-    name: "scope_name"
-    mtype: "<type \'property\'>"
-  }
-  member {
-    name: "state_size"
-    mtype: "<type \'property\'>"
-  }
-  member {
-    name: "trainable_variables"
-    mtype: "<type \'property\'>"
-  }
-  member {
-    name: "trainable_weights"
-    mtype: "<type \'property\'>"
-  }
-  member {
-    name: "updates"
-    mtype: "<type \'property\'>"
-  }
-  member {
-    name: "variables"
-    mtype: "<type \'property\'>"
-  }
-  member {
-    name: "weights"
-    mtype: "<type \'property\'>"
-  }
-  member_method {
-    name: "__init__"
-    argspec: "args=[\'self\', \'num_units\', \'activation\', \'reuse\', \'name\', \'dtype\'], varargs=None, keywords=kwargs, defaults=[\'None\', \'None\', \'None\', \'None\'], "
-  }
-  member_method {
-    name: "add_loss"
-    argspec: "args=[\'self\', \'losses\', \'inputs\'], varargs=None, keywords=None, defaults=[\'None\'], "
-  }
-  member_method {
-    name: "add_update"
-    argspec: "args=[\'self\', \'updates\', \'inputs\'], varargs=None, keywords=None, defaults=[\'None\'], "
-  }
-  member_method {
-    name: "add_variable"
-    argspec: "args=[\'self\'], varargs=args, keywords=kwargs, defaults=None"
-  }
-  member_method {
-    name: "add_weight"
-    argspec: "args=[\'self\', \'name\', \'shape\', \'dtype\', \'initializer\', \'regularizer\', \'trainable\', \'constraint\', \'use_resource\', \'synchronization\', \'aggregation\', \'partitioner\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\', \'None\', \'None\', \'VariableSynchronization.AUTO\', \'VariableAggregation.NONE\', \'None\'], "
-  }
-  member_method {
-    name: "apply"
-    argspec: "args=[\'self\', \'inputs\'], varargs=args, keywords=kwargs, defaults=None"
-  }
-  member_method {
-    name: "build"
-    argspec: "args=[\'instance\', \'input_shape\'], varargs=None, keywords=None, defaults=None"
-  }
-  member_method {
-    name: "call"
-    argspec: "args=[\'self\', \'inputs\', \'state\'], varargs=None, keywords=None, defaults=None"
-  }
-  member_method {
-    name: "compute_mask"
-    argspec: "args=[\'self\', \'inputs\', \'mask\'], varargs=None, keywords=None, defaults=[\'None\'], "
-  }
-  member_method {
-    name: "compute_output_shape"
-    argspec: "args=[\'self\', \'input_shape\'], varargs=None, keywords=None, defaults=None"
-  }
-  member_method {
-    name: "count_params"
-    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
-  }
-  member_method {
-    name: "from_config"
-    argspec: "args=[\'cls\', \'config\'], varargs=None, keywords=None, defaults=None"
-  }
-  member_method {
-    name: "get_config"
-    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
-  }
-  member_method {
-    name: "get_initial_state"
-    argspec: "args=[\'self\', \'inputs\', \'batch_size\', \'dtype\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\'], "
-  }
-  member_method {
-    name: "get_input_at"
-    argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
-  }
-  member_method {
-    name: "get_input_mask_at"
-    argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
-  }
-  member_method {
-    name: "get_input_shape_at"
-    argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
-  }
-  member_method {
-    name: "get_losses_for"
-    argspec: "args=[\'self\', \'inputs\'], varargs=None, keywords=None, defaults=None"
-  }
-  member_method {
-    name: "get_output_at"
-    argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
-  }
-  member_method {
-    name: "get_output_mask_at"
-    argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
-  }
-  member_method {
-    name: "get_output_shape_at"
-    argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
-  }
-  member_method {
-    name: "get_updates_for"
-    argspec: "args=[\'self\', \'inputs\'], varargs=None, keywords=None, defaults=None"
-  }
-  member_method {
-    name: "get_weights"
-    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
-  }
-  member_method {
-    name: "set_weights"
-    argspec: "args=[\'self\', \'weights\'], varargs=None, keywords=None, defaults=None"
-  }
-  member_method {
-    name: "zero_state"
-    argspec: "args=[\'self\', \'batch_size\', \'dtype\'], varargs=None, keywords=None, defaults=None"
-  }
-}
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.nn.rnn_cell.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.nn.rnn_cell.pbtxt
index 64697e8a02..24767e250f 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.nn.rnn_cell.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.nn.rnn_cell.pbtxt
@@ -5,10 +5,6 @@ tf_module {
     mtype: "<type \'type\'>"
   }
   member {
-    name: "BasicRNNCell"
-    mtype: "<type \'type\'>"
-  }
-  member {
     name: "DeviceWrapper"
     mtype: "<type \'type\'>"
   }