Add a human-readable Tensor.__repr__(), and improve TensorShape.__str__().

The repr replaces the default Python representation for an object with
information about the Tensor's name, shape and dtype. TensorShape's
new str() is a more compact representation that makes it easier to
tell, at a glance, what the shape represents.

For example:

    print repr(tf.placeholder(tf.qint32, shape=(32, None, 2), name="c"))
    # ==> <tf.Tensor 'c:0' shape=(32, ?, 2) dtype=qint32>

Fixes #460.
Change: 110268564

6 files changed, 43 insertions, 3 deletions

diff --git a/tensorflow/python/client/session.py b/tensorflow/python/client/session.py
index 4cc1b9809b..74358349b7 100644
--- a/tensorflow/python/client/session.py
+++ b/tensorflow/python/client/session.py
@@ -360,8 +360,7 @@ class BaseSession(SessionInterface):
               raise ValueError(
                   'Cannot feed value of shape %r for Tensor %r, '
                   'which has shape %r'
-                  % (np_val.shape, subfeed_t.name,
-                     tuple(subfeed_t.get_shape().dims)))
+                  % (np_val.shape, subfeed_t.name, str(subfeed_t.get_shape())))
           feed_dict_string[compat.as_bytes(subfeed_t.name)] = np_val
 
     # Run request and get response.
diff --git a/tensorflow/python/framework/ops.py b/tensorflow/python/framework/ops.py
index 00051b4a7f..d73cf47b71 100644
--- a/tensorflow/python/framework/ops.py
+++ b/tensorflow/python/framework/ops.py
@@ -383,6 +383,10 @@ class Tensor(object):
         (", dtype=%s" % self._dtype.name) if self._dtype else "",
         (", device=%s" % self.device) if self.device else "")
 
+  def __repr__(self):
+    return "<tf.Tensor '%s' shape=%s dtype=%s>" % (
+        self.name, self.get_shape(), self._dtype.name)
+
   def __hash__(self):
     # Necessary to support Python's collection membership operators
     return id(self)
diff --git a/tensorflow/python/framework/tensor_shape.py b/tensorflow/python/framework/tensor_shape.py
index d1fb6ddc06..c692e66577 100644
--- a/tensorflow/python/framework/tensor_shape.py
+++ b/tensorflow/python/framework/tensor_shape.py
@@ -424,6 +424,16 @@ class TensorShape(object):
   def __repr__(self):
     return "TensorShape(%s)" % self._dims
 
+  def __str__(self):
+    if self.ndims is None:
+      return "<unknown>"
+    elif self.ndims == 1:
+      length = self._dims[0].value
+      return "(%s,)" % (str(length) if length is not None else "?")
+    else:
+      return "(%s)" % ", ".join(str(d.value) if d.value is not None else "?"
+                                for d in self._dims)
+
   @property
   def dims(self):
     """Returns a list of Dimensions, or None if the shape is unspecified."""
diff --git a/tensorflow/python/framework/tensor_shape_test.py b/tensorflow/python/framework/tensor_shape_test.py
index ca5da2ba72..9efafb1f68 100644
--- a/tensorflow/python/framework/tensor_shape_test.py
+++ b/tensorflow/python/framework/tensor_shape_test.py
@@ -268,6 +268,20 @@ class ShapeTest(test_util.TensorFlowTestCase):
     self.assertEqual(tensor_shape.TensorShape([1, 37, 42]),
                      tensor_shape.as_shape(proto))
 
+  def testStr(self):
+    self.assertEqual("<unknown>", str(tensor_shape.unknown_shape()))
+    self.assertEqual("(?,)", str(tensor_shape.unknown_shape(ndims=1)))
+    self.assertEqual("(?, ?)", str(tensor_shape.unknown_shape(ndims=2)))
+    self.assertEqual("(?, ?, ?)", str(tensor_shape.unknown_shape(ndims=3)))
+
+    self.assertEqual("()", str(tensor_shape.scalar()))
+    self.assertEqual("(7,)", str(tensor_shape.vector(7)))
+    self.assertEqual("(3, 8)", str(tensor_shape.matrix(3, 8)))
+    self.assertEqual("(4, 5, 2)", str(tensor_shape.TensorShape([4, 5, 2])))
+
+    self.assertEqual("(32, ?, 1, 9)",
+                     str(tensor_shape.TensorShape([32, None, 1, 9])))
+
 
 if __name__ == "__main__":
   googletest.main()
diff --git a/tensorflow/python/kernel_tests/constant_op_test.py b/tensorflow/python/kernel_tests/constant_op_test.py
index 44182683ca..5bc7f2b37d 100644
--- a/tensorflow/python/kernel_tests/constant_op_test.py
+++ b/tensorflow/python/kernel_tests/constant_op_test.py
@@ -545,6 +545,19 @@ class PlaceholderTest(tf.test.TestCase):
       with self.assertRaisesOpError(r"Shape \[-1,10\] has negative dimensions"):
         s.eval()
 
+  def testTensorStr(self):
+    a = tf.placeholder(tf.float32, name="a")
+    self.assertEqual("<tf.Tensor 'a:0' shape=<unknown> dtype=float32>", repr(a))
+
+    b = tf.placeholder(tf.int32, shape=(32, 40), name="b")
+    self.assertEqual(
+        "<tf.Tensor 'b:0' shape=(32, 40) dtype=int32>",
+        repr(b))
+
+    c = tf.placeholder(tf.qint32, shape=(32, None, 2), name="c")
+    self.assertEqual(
+        "<tf.Tensor 'c:0' shape=(32, ?, 2) dtype=qint32>",
+        repr(c))
 
 if __name__ == "__main__":
   tf.test.main()
diff --git a/tensorflow/python/kernel_tests/unpack_op_test.py b/tensorflow/python/kernel_tests/unpack_op_test.py
index 47ed9e617c..621c717617 100644
--- a/tensorflow/python/kernel_tests/unpack_op_test.py
+++ b/tensorflow/python/kernel_tests/unpack_op_test.py
@@ -65,7 +65,7 @@ class UnpackOpTest(tf.test.TestCase):
   def testCannotInferNum(self):
     x = tf.placeholder(np.float32)
     with self.assertRaisesRegexp(
-        ValueError, r'Cannot infer num from shape TensorShape\(None\)'):
+        ValueError, r'Cannot infer num from shape <unknown>'):
       tf.unpack(x)