Fix SwinLayer / DonutSwinLayer / ClapAudioLayer attention mask device (…

…huggingface#31295)

Fix DonutSwinLayer attention mask device

src/transformers/models/clap/modeling_clap.py

@@ -593,10 +593,10 @@ def set_shift_and_window_size(self, input_resolution):
             self.shift_size = 0
             self.window_size = min(input_resolution)
 
-    def get_attn_mask(self, height, width, dtype):
+    def get_attn_mask(self, height, width, dtype, device):
         if self.shift_size > 0:
             # calculate attention mask for SW-MSA
-            img_mask = torch.zeros((1, height, width, 1), dtype=dtype)
+            img_mask = torch.zeros((1, height, width, 1), dtype=dtype, device=device)
             height_slices = (
                 slice(0, -self.window_size),
                 slice(-self.window_size, -self.shift_size),
@@ -661,9 +661,9 @@ def forward(
         # partition windows
         hidden_states_windows = window_partition(shifted_hidden_states, self.window_size)
         hidden_states_windows = hidden_states_windows.view(-1, self.window_size * self.window_size, channels)
-        attn_mask = self.get_attn_mask(height_pad, width_pad, dtype=hidden_states.dtype)
-        if attn_mask is not None:
-            attn_mask = attn_mask.to(hidden_states_windows.device)
+        attn_mask = self.get_attn_mask(
+            height_pad, width_pad, dtype=hidden_states.dtype, device=hidden_states_windows.device
+        )
 
         attention_outputs = self.attention(
             hidden_states_windows, attn_mask, head_mask, output_attentions=output_attentions

src/transformers/models/donut/modeling_donut_swin.py

@@ -565,10 +565,10 @@ def set_shift_and_window_size(self, input_resolution):
             self.shift_size = 0
             self.window_size = min(input_resolution)
 
-    def get_attn_mask(self, height, width, dtype):
+    def get_attn_mask(self, height, width, dtype, device):
         if self.shift_size > 0:
             # calculate attention mask for SW-MSA
-            img_mask = torch.zeros((1, height, width, 1), dtype=dtype)
+            img_mask = torch.zeros((1, height, width, 1), dtype=dtype, device=device)
             height_slices = (
                 slice(0, -self.window_size),
                 slice(-self.window_size, -self.shift_size),
@@ -633,9 +633,9 @@ def forward(
         # partition windows
         hidden_states_windows = window_partition(shifted_hidden_states, self.window_size)
         hidden_states_windows = hidden_states_windows.view(-1, self.window_size * self.window_size, channels)
-        attn_mask = self.get_attn_mask(height_pad, width_pad, dtype=hidden_states.dtype)
-        if attn_mask is not None:
-            attn_mask = attn_mask.to(hidden_states_windows.device)
+        attn_mask = self.get_attn_mask(
+            height_pad, width_pad, dtype=hidden_states.dtype, device=hidden_states_windows.device
+        )
 
         attention_outputs = self.attention(
             hidden_states_windows, attn_mask, head_mask, output_attentions=output_attentions

src/transformers/models/swin/modeling_swin.py

@@ -642,10 +642,10 @@ def set_shift_and_window_size(self, input_resolution):
             self.shift_size = 0
             self.window_size = min(input_resolution)
 
-    def get_attn_mask(self, height, width, dtype):
+    def get_attn_mask(self, height, width, dtype, device):
         if self.shift_size > 0:
             # calculate attention mask for SW-MSA
-            img_mask = torch.zeros((1, height, width, 1), dtype=dtype)
+            img_mask = torch.zeros((1, height, width, 1), dtype=dtype, device=device)
             height_slices = (
                 slice(0, -self.window_size),
                 slice(-self.window_size, -self.shift_size),
@@ -710,9 +710,9 @@ def forward(
         # partition windows
         hidden_states_windows = window_partition(shifted_hidden_states, self.window_size)
         hidden_states_windows = hidden_states_windows.view(-1, self.window_size * self.window_size, channels)
-        attn_mask = self.get_attn_mask(height_pad, width_pad, dtype=hidden_states.dtype)
-        if attn_mask is not None:
-            attn_mask = attn_mask.to(hidden_states_windows.device)
+        attn_mask = self.get_attn_mask(
+            height_pad, width_pad, dtype=hidden_states.dtype, device=hidden_states_windows.device
+        )
 
         attention_outputs = self.attention(
             hidden_states_windows, attn_mask, head_mask, output_attentions=output_attentions