Point links at stable version of NumPy docs

Author: Molkree

site/en/guide/tf_numpy.ipynb

@@ -70,7 +70,7 @@
       "source": [
         "## Overview\n",
         "\n",
-        "TensorFlow implements a subset of the [NumPy API](https://numpy.org/doc/1.16), available as `tf.experimental.numpy`. This allows running NumPy code, accelerated by TensorFlow, while also allowing access to all of TensorFlow's APIs."
+        "TensorFlow implements a subset of the [NumPy API](https://numpy.org/doc/stable), available as `tf.experimental.numpy`. This allows running NumPy code, accelerated by TensorFlow, while also allowing access to all of TensorFlow's APIs."
       ]
     },
     {
@@ -155,7 +155,7 @@
       "source": [
         "### Type promotion\n",
         "\n",
-        "TensorFlow NumPy APIs have well-defined semantics for converting literals to ND array, as well as for performing type promotion on ND array inputs. Please see [`np.result_type`](https://numpy.org/doc/1.16/reference/generated/numpy.result_type.html) for more details. When converting literals to ND array, NumPy prefers wide types like `tnp.int64` and `tnp.float64`.\n",
+        "TensorFlow NumPy APIs have well-defined semantics for converting literals to ND array, as well as for performing type promotion on ND array inputs. Please see [`np.result_type`](https://numpy.org/doc/stable/reference/generated/numpy.result_type.html) for more details. When converting literals to ND array, NumPy prefers wide types like `tnp.int64` and `tnp.float64`.\n",
         "\n",
         "In contrast, `tf.convert_to_tensor` prefers `tf.int32` and `tf.float32` types for converting constants to `tf.Tensor`. TensorFlow APIs leave `tf.Tensor` inputs unchanged and do not perform type promotion on them.\n",
         "\n",
@@ -192,7 +192,7 @@
         "### Broadcasting\n",
         "\n",
         "Similar to TensorFlow, NumPy defines rich semantics for \"broadcasting\" values.\n",
-        "You can check out the [NumPy broadcasting guide](https://numpy.org/doc/1.16/user/basics.broadcasting.html) for more information and compare this with [TensorFlow broadcasting semantics](https://www.tensorflow.org/guide/tensor#broadcasting)."
+        "You can check out the [NumPy broadcasting guide](https://numpy.org/doc/stable/user/basics.broadcasting.html) for more information and compare this with [TensorFlow broadcasting semantics](https://www.tensorflow.org/guide/tensor#broadcasting)."
       ]
     },
     {
@@ -218,7 +218,7 @@
       "source": [
         "### Indexing\n",
         "\n",
-        "NumPy defines very sophisticated indexing rules. See the [NumPy Indexing guide](https://numpy.org/doc/1.16/reference/arrays.indexing.html). Note the use of ND arrays as indices below."
+        "NumPy defines very sophisticated indexing rules. See the [NumPy Indexing guide](https://numpy.org/doc/stable/reference/arrays.indexing.html). Note the use of ND arrays as indices below."
       ]
     },
     {