Fix deprecation warnings

Author: josevalim

nx/lib/nx.ex

@@ -1305,7 +1305,7 @@ defmodule Nx do
       out =
         case shape do
           {n} ->
-            intermediate_shape = Tuple.duplicate(1, tuple_size(out_shape) - 1) |> Tuple.append(n)
+            intermediate_shape = Tuple.duplicate(1, tuple_size(out_shape) - 1) |> tuple_append(n)
 
             backend.eye(
               %T{type: type, shape: intermediate_shape, names: names},
@@ -1609,7 +1609,7 @@ defmodule Nx do
       t
     else
       diag_length = div(Nx.size(t), Tuple.product(batch_shape))
-      Nx.reshape(t, Tuple.append(batch_shape, diag_length))
+      Nx.reshape(t, tuple_append(batch_shape, diag_length))
     end
   end
 
@@ -10365,9 +10365,9 @@ defmodule Nx do
               if opts[:keep_axis] do
                 new_shape
                 |> Tuple.delete_at(tuple_size(new_shape) - 1)
-                |> Tuple.append(:auto)
+                |> tuple_append(:auto)
               else
-                Tuple.append(new_shape, :auto)
+                tuple_append(new_shape, :auto)
               end
 
             reshaped_tensor = reshape(tensor, flattened_shape)
@@ -13554,7 +13554,7 @@ defmodule Nx do
         end)
         |> Nx.stack()
         |> Nx.revectorize(vectorized_axes,
-          target_shape: Tuple.append(List.to_tuple(lengths), :auto)
+          target_shape: tuple_append(List.to_tuple(lengths), :auto)
         )
 
       Nx.gather(tensor, idx)
@@ -14288,7 +14288,7 @@ defmodule Nx do
       Nx.Shared.optional(:take_along_axis, [tensor, indices, [axis: axis]], out, fn
         tensor, indices, _opts ->
           axes_range = axes(indices)
-          new_axis_shape = Tuple.append(shape(indices), 1)
+          new_axis_shape = tuple_append(shape(indices), 1)
 
           full_indices =
             axes_range
@@ -14471,7 +14471,7 @@ defmodule Nx do
         indices = devectorize(indices, keep_names: false)
 
         iota_shape =
-          indices.shape |> Tuple.delete_at(tuple_size(indices.shape) - 1) |> Tuple.append(1)
+          indices.shape |> Tuple.delete_at(tuple_size(indices.shape) - 1) |> tuple_append(1)
 
         offset_axes = (offset - 1)..0//-1
 

nx/lib/nx/binary_backend.ex

@@ -1492,7 +1492,7 @@ defmodule Nx.BinaryBackend do
     dilations = opts[:window_dilations]
 
     %T{shape: padded_shape, type: {_, size} = type} =
-      tensor = Nx.pad(tensor, acc, Enum.map(padding_config, &Tuple.append(&1, 0)))
+      tensor = Nx.pad(tensor, acc, Enum.map(padding_config, &tuple_append(&1, 0)))
 
     acc = scalar_to_number(acc)
 
@@ -1608,7 +1608,7 @@ defmodule Nx.BinaryBackend do
     init_value = scalar_to_number(init_value)
 
     %T{shape: padded_shape, type: {_, size} = type} =
-      tensor = Nx.pad(t, init_value, Enum.map(padding, &Tuple.append(&1, 0)))
+      tensor = Nx.pad(t, init_value, Enum.map(padding, &tuple_append(&1, 0)))
 
     input_data = to_binary(tensor)
     input_weighted_shape = weighted_shape(padded_shape, size, window_dimensions)
@@ -2262,7 +2262,7 @@ defmodule Nx.BinaryBackend do
         <<write_complex(re, im, div(output_size, 2))::binary>>
       end
 
-    intermediate_shape = out.shape |> Tuple.delete_at(axis) |> Tuple.append(n)
+    intermediate_shape = out.shape |> Tuple.delete_at(axis) |> tuple_append(n)
 
     permuted_output = from_binary(%{out | shape: intermediate_shape}, output_data)
 

nx/lib/nx/defn/grad.ex

@@ -1157,7 +1157,7 @@ defmodule Nx.Defn.Grad do
 
     num_axes = tuple_size(window_dimensions)
 
-    indices = Nx.reshape(indices_to_flatten, Tuple.append(source.shape, num_axes))
+    indices = Nx.reshape(indices_to_flatten, Nx.Shared.tuple_append(source.shape, num_axes))
 
     dsource = Nx.gather(g, indices)
     dtensor = Nx.broadcast(0, tensor)
@@ -1490,7 +1490,7 @@ defmodule Nx.Defn.Grad do
   end
 
   defp grad_scatter_window__gather_windows(tensor, window_dimensions, strides, padding) do
-    tensor = Nx.pad(tensor, 0, Enum.map(padding, &Tuple.append(&1, 0)))
+    tensor = Nx.pad(tensor, 0, Enum.map(padding, &Nx.Shared.tuple_append(&1, 0)))
 
     shape_l = Tuple.to_list(tensor.shape)
     window_dims_l = Tuple.to_list(window_dimensions)

nx/lib/nx/lin_alg/svd.ex

@@ -59,9 +59,9 @@ defmodule Nx.LinAlg.SVD do
 
     collapsed_axes = shape |> Tuple.delete_at(rank - 2) |> Tuple.delete_at(rank - 2)
 
-    u_shape = collapsed_axes |> Tuple.append(m) |> Tuple.append(:auto)
-    s_shape = Tuple.append(collapsed_axes, :auto)
-    vt_shape = Tuple.append(s_shape, n)
+    u_shape = collapsed_axes |> Nx.Shared.tuple_append(m) |> Nx.Shared.tuple_append(:auto)
+    s_shape = Nx.Shared.tuple_append(collapsed_axes, :auto)
+    vt_shape = Nx.Shared.tuple_append(s_shape, n)
 
     {{m, n}, u_shape, s_shape, vt_shape}
   end

nx/lib/nx/random.ex

@@ -746,7 +746,7 @@ defmodule Nx.Random do
           {dim}
 
         dims when is_tuple(dims) ->
-          Tuple.append(dims, dim)
+          Nx.Shared.tuple_append(dims, dim)
 
         _ ->
           raise ArgumentError,
@@ -1126,7 +1126,7 @@ defmodule Nx.Random do
     case type do
       {:c, _} ->
         type = Nx.Type.to_real(type)
-        data = fun.(key, type, Tuple.append(shape, 2))
+        data = fun.(key, type, Nx.Shared.tuple_append(shape, 2))
         to_complex = Nx.stack([1, Nx.Constants.i()])
         Nx.dot(data, to_complex)
 

nx/lib/nx/shared.ex

@@ -445,6 +445,13 @@ defmodule Nx.Shared do
 
   ## Helpers
 
+  @doc """
+  Appends an element to a tuple.
+  """
+  def tuple_append(tuple, elem) do
+    Tuple.insert_at(tuple, tuple_size(tuple), elem)
+  end
+
   @doc """
   Extracts the backend from the given options.
   """