fix: Nx.LinAlg.norm axes support

nx/lib/nx/lin_alg.ex

@@ -388,6 +388,10 @@ defmodule Nx.LinAlg do
     # The idea is that by dividing the tensor by it, large values of
     # tensor entries and large values of p are reduced, which in turn
     # avoids numerical overflow.
+
+    keep_axes = opts[:keep_axes]
+
+    opts = Keyword.put(opts, :keep_axes, true)
     numerical_stability_coefficient = Nx.reduce_max(abs_t, opts)
 
     # This code prevents from division by zero.
@@ -398,12 +402,19 @@ defmodule Nx.LinAlg do
         1
       )
 
-    abs_t
-    |> Nx.divide(numerical_stability_coefficient)
-    |> Nx.pow(ord)
-    |> Nx.sum(opts)
-    |> Nx.pow(inv_ord)
-    |> Nx.multiply(numerical_stability_coefficient)
+    result =
+      abs_t
+      |> Nx.divide(numerical_stability_coefficient)
+      |> Nx.pow(ord)
+      |> Nx.sum(opts)
+      |> Nx.pow(inv_ord)
+      |> Nx.multiply(numerical_stability_coefficient)
+
+    if keep_axes do
+      result
+    else
+      Nx.squeeze(result, Keyword.take(opts, [:axes]))
+    end
   end
 
   @doc """

nx/test/nx/lin_alg_test.exs

@@ -276,6 +276,19 @@ defmodule Nx.LinAlgTest do
         Nx.LinAlg.norm(t, ord: -3)
       end)
     end
+
+    test "correctly support axes option" do
+      t =
+        Nx.tensor([
+          [-1.0, -1.0],
+          [0.0, 0.0],
+          [1.0, 1.0]
+        ])
+
+      result = Nx.tensor([1.4142135381698608, 0.0, 1.4142135381698608])
+      assert Nx.LinAlg.norm(t, axes: [1]) == result
+      assert Nx.LinAlg.norm(t, axes: [1], keep_axes: true) == Nx.reshape(result, {3, 1})
+    end
   end
 
   describe "matrix_power" do