fix shape error in combine-getitem

paddle/fluid/pybind/eager_method.cc

@@ -1404,14 +1404,14 @@ static PyObject* tensor__getitem_dygraph(TensorObject* self,
 
   if (pos_of_new_dim != 0) {
     std::vector<int> perm(out.shape().size(), 0);
-    int tmp1 = pos_of_new_dim, tmp2 = 0,
+    int tmp1 = rank_of_new_dim, tmp2 = 0,
         tmp3 = pos_of_new_dim + rank_of_new_dim;
     for (int i = 0; i < static_cast<int>(out.shape().size()); ++i) {
-      if (i < rank_of_new_dim) {
+      if (i < pos_of_new_dim) {
         perm[i] =
-            tmp1++;  // range(pos_of_new_dim, pos_of_new_dim + rank_of_new_dim)
-      } else if (i >= rank_of_new_dim && i < pos_of_new_dim + rank_of_new_dim) {
-        perm[i] = tmp2++;  // range(0, pos_of_new_dim)
+            tmp1++;  // range(rank_of_new_dim, pos_of_new_dim + rank_of_new_dim)
+      } else if (i >= pos_of_new_dim && i < pos_of_new_dim + rank_of_new_dim) {
+        perm[i] = tmp2++;  // range(0, rank_of_new_dim)
       } else {
         perm[i] = tmp3++;  // range(pos_of_new_dim + rank_of_new_dim, out.ndim)
       }

python/paddle/base/variable_index.py

@@ -908,8 +908,8 @@ def _getitem_static(x, indices):
 
         if pos_of_new_dim != 0:
             perm = (
-                list(range(pos_of_new_dim, pos_of_new_dim + rank_of_new_dim))
-                + list(range(0, pos_of_new_dim))
+                list(range(rank_of_new_dim, pos_of_new_dim + rank_of_new_dim))
+                + list(range(0, rank_of_new_dim))
                 + list(range(pos_of_new_dim + rank_of_new_dim, out.ndim))
             )
             out = out.transpose(perm)

test/indexing/test_getitem.py

@@ -234,6 +234,26 @@ def test_combined_index_11(self):
 
         np.testing.assert_allclose(y.numpy(), np_res)
 
+    def test_combined_index_12(self):
+        np_data = (
+            np.arange(3 * 4 * 5 * 6).reshape((3, 4, 5, 6)).astype(self.ndtype)
+        )
+
+        if self.dtype == 'bfloat16':
+            np_data = convert_uint16_to_float(convert_float_to_uint16(np_data))
+        if self.dtype == 'complex64' or self.dtype == 'complex128':
+            np_data = np_data + 1j * np_data
+
+        np_res = np_data[:, :, [2, 4], :]
+
+        x = paddle.to_tensor(np_data, dtype=self.dtype)
+        y = x[:, :, [2, 4], :]
+
+        if self.dtype == 'bfloat16':
+            y = paddle.cast(y, dtype='float32')
+
+        np.testing.assert_allclose(y.numpy(), np_res)
+
     def test_index_has_range(self):
         np_data = (
             np.arange(3 * 4 * 5 * 6).reshape((3, 4, 5, 6)).astype(self.ndtype)
@@ -982,6 +1002,21 @@ def test_combined_index_11(self):
 
         np.testing.assert_allclose(res[0], np_res)
 
+    @test_with_pir_api
+    def test_combined_index_12(self):
+        np_data = np.arange(3 * 4 * 5 * 6).reshape((3, 4, 5, 6))
+        np_res = np_data[:, :, [2, 4], :]
+        with paddle.static.program_guard(
+            paddle.static.Program(), paddle.static.Program()
+        ):
+            x = paddle.to_tensor(np_data)
+            y = _getitem_static(
+                x, (slice(None), slice(None), [2, 4], slice(None))
+            )
+            res = self.exe.run(fetch_list=[y])
+
+        np.testing.assert_allclose(res[0], np_res)
+
     @test_with_pir_api
     def test_index_has_range(self):
         # only one bool tensor with all False