Remove ">>> _ =" These are unnecessary.

The doctest system no longer checks outputs if the author doesn't supply one.

PiperOrigin-RevId: 305055550
Change-Id: I424110500a15a8c79bf0082318c0a7d9af7fe608

tensorflow/python/framework/ops.py

@@ -620,14 +620,14 @@ class Tensor(tensor_like.TensorLike):
 
     The shape inference functions propagate shapes to the extent possible:
 
-    >>> _ = my_matmul.get_concrete_function(
+    >>> f = my_matmul.get_concrete_function(
     ...   tf.TensorSpec([None,3]),
     ...   tf.TensorSpec([3,5]))
     Result shape: (None, 5)
 
     Tracing may fail if a shape missmatch can be detected:
 
-    >>> _ = my_matmul.get_concrete_function(
+    >>> cf = my_matmul.get_concrete_function(
     ...   tf.TensorSpec([None,3]),
     ...   tf.TensorSpec([4,5]))
     Traceback (most recent call last):
@@ -647,7 +647,7 @@ class Tensor(tensor_like.TensorLike):
     ...   print("Result shape: ", a.shape)
     ...   return a
 
-    >>> _ = my_fun.get_concrete_function(
+    >>> cf = my_fun.get_concrete_function(
     ...   tf.TensorSpec([None, None]))
     Result shape: (5, 5)
 
@@ -712,7 +712,7 @@ class Tensor(tensor_like.TensorLike):
     Trace the function, see the [Concrete Functions
     Guide](https://www.tensorflow.org/guide/concrete_function) for details.
 
-    >>> _ = load_image.get_concrete_function(
+    >>> cf = load_image.get_concrete_function(
     ...     tf.TensorSpec([], dtype=tf.string))
     Initial shape:  (None, None, 3)
     Final shape: (28, 28, 3)

tensorflow/python/keras/backend.py

@@ -3296,11 +3296,11 @@ _VALUE_SET_CODE_STRING = """
 
   >>> v = tf.Variable(1.)
 
-  >>> _ = v.assign(2.)
+  >>> v.assign(2.)
   >>> print(v.numpy())
   2.0
 
-  >>> _ = v.assign_add(1.)
+  >>> v.assign_add(1.)
   >>> print(v.numpy())
   3.0"""[3:]  # Prune first newline and indent to match the docstring template.
 

tensorflow/python/keras/engine/training.py

@@ -416,7 +416,7 @@ class Model(network.Network, version_utils.ModelVersionSelector):
 
     >>> x = np.random.random((2, 3))
     >>> y = np.random.randint(0, 2, (2, 2))
-    >>> _ = model.fit(x, y, verbose=0)
+    >>> model.fit(x, y, verbose=0)
     >>> [m.name for m in model.metrics]
     ['loss', 'mae']
 
@@ -429,7 +429,7 @@ class Model(network.Network, version_utils.ModelVersionSelector):
     >>> model.add_metric(
     ...    tf.reduce_sum(output_2), name='mean', aggregation='mean')
     >>> model.compile(optimizer="Adam", loss="mse", metrics=["mae", "acc"])
-    >>> _ = model.fit(x, (y, y), verbose=0)
+    >>> model.fit(x, (y, y), verbose=0)
     >>> [m.name for m in model.metrics]
     ['loss', 'out_loss', 'out_1_loss', 'out_mae', 'out_acc', 'out_1_mae',
     'out_1_acc', 'mean']