[Whisper] patch float type on mps (#35295)

* fix float type on mps

* make

Author: eustlb

src/transformers/models/whisper/generation_whisper.py

@@ -632,7 +632,9 @@ def generate(
                 cur_bsz=cur_bsz,
                 batch_idx_map=batch_idx_map,
             )
-            time_offset = seek.to(torch.float64) * time_precision / input_stride
+            time_offset = (
+                seek.to(torch.float32 if device.type == "mps" else torch.float64) * time_precision / input_stride
+            )
             seek_num_frames = (max_frames - seek).clamp(max=num_segment_frames)
 
             # 6.2 cut out next 30s segment from input features
@@ -1805,6 +1807,7 @@ def _retrieve_segment(
         timestamp_segment_indices = torch.where(timestamp_tokens[:-1] & timestamp_tokens[1:])[0]
         timestamp_segment_indices.add_(1)
         token_timestamps = seek_outputs[idx]["token_timestamps"] if return_token_timestamps else []
+        device = seek_sequence.device
 
         # If whisper predicted a "end of segment" via a timestep token, let's go ever each
         # "end of segment" prediction and slice the decoding into segments accordingly
@@ -1828,8 +1831,12 @@ def _retrieve_segment(
                 end_timestamp_pos = sliced_tokens[idx_sliced_tokens] - timestamp_begin
                 segments.append(
                     {
-                        "start": time_offset[prev_idx] + start_timestamp_pos.to(torch.float64) * time_precision,
-                        "end": time_offset[prev_idx] + end_timestamp_pos.to(torch.float64) * time_precision,
+                        "start": time_offset[prev_idx]
+                        + start_timestamp_pos.to(torch.float32 if device.type == "mps" else torch.float64)
+                        * time_precision,
+                        "end": time_offset[prev_idx]
+                        + end_timestamp_pos.to(torch.float32 if device.type == "mps" else torch.float64)
+                        * time_precision,
                         "tokens": sliced_tokens,
                         "result": seek_outputs[idx],
                     }
@@ -1856,7 +1863,9 @@ def _retrieve_segment(
             last_timestamp_pos = int(seek_num_frames[prev_idx] * time_precision_features / time_precision)
             if timestamps.numel() > 0 and timestamps[-1] != timestamp_begin:
                 # no consecutive timestamps but it has a timestamp; use the last one.
-                last_timestamp_pos = (timestamps[-1] - timestamp_begin).to(torch.float64)
+                last_timestamp_pos = (timestamps[-1] - timestamp_begin).to(
+                    torch.float32 if device.type == "mps" else torch.float64
+                )
             segments = [
                 {
                     "start": time_offset[prev_idx],