[torch_int_div] Correct true division in generation (#15498)

* [torch_int_div] Correct true division in generation

* up

* up

src/transformers/__init__.py

@@ -1561,6 +1561,7 @@ if is_torch_available():
         "get_polynomial_decay_schedule_with_warmup",
         "get_scheduler",
     ]
+    _import_structure["pytorch_utils"] = []
     _import_structure["sagemaker"] = []
     _import_structure["trainer"] = ["Trainer"]
     _import_structure["trainer_pt_utils"] = ["torch_distributed_zero_first"]

src/transformers/generation_utils.py

@@ -48,6 +48,7 @@ from .generation_stopping_criteria import (
     StoppingCriteriaList,
     validate_stopping_criteria,
 )
+from .pytorch_utils import torch_int_div
 from .utils import logging
 
 
@@ -2024,7 +2025,7 @@ class GenerationMixin:
                 next_token_scores, 2 * num_beams, dim=1, largest=True, sorted=True
             )
 
-            next_indices = (next_tokens / vocab_size).long()
+            next_indices = torch_int_div(next_tokens, vocab_size)
             next_tokens = next_tokens % vocab_size
 
             # stateless
@@ -2345,7 +2346,7 @@ class GenerationMixin:
             next_token_scores, _indices = torch.sort(next_token_scores, descending=True, dim=1)
             next_tokens = torch.gather(next_tokens, -1, _indices)
 
-            next_indices = next_tokens // vocab_size
+            next_indices = torch_int_div(next_tokens, vocab_size)
             next_tokens = next_tokens % vocab_size
 
             # stateless
@@ -2678,7 +2679,7 @@ class GenerationMixin:
                     next_token_scores, 2 * group_size, dim=1, largest=True, sorted=True
                 )
 
-                next_indices = next_tokens // vocab_size
+                next_indices = torch_int_div(next_tokens, vocab_size)
                 next_tokens = next_tokens % vocab_size
 
                 # stateless
@@ -2706,7 +2707,7 @@ class GenerationMixin:
                 # (beam_idx // group_size) -> batch_idx
                 # (beam_idx % group_size) -> offset of idx inside the group
                 reordering_indices[batch_group_indices] = (
-                    num_beams * (beam_idx // group_size) + group_start_idx + (beam_idx % group_size)
+                    num_beams * torch_int_div(beam_idx, group_size) + group_start_idx + (beam_idx % group_size)
                 )
 
             # Store scores, attentions and hidden_states when required

src/transformers/modeling_utils.py

@@ -23,7 +23,6 @@ from functools import partial
 from typing import Any, Callable, Dict, List, Optional, Set, Tuple, Union
 
 import torch
-from packaging import version
 from torch import Tensor, device, nn
 from torch.nn import CrossEntropyLoss
 
@@ -2463,13 +2462,3 @@ def apply_chunking_to_forward(
         return torch.cat(output_chunks, dim=chunk_dim)
 
     return forward_fn(*input_tensors)
-
-
-def torch_int_div(tensor1, tensor2):
-    """
-    A function that performs integer division across different versions of PyTorch.
-    """
-    if version.parse(torch.__version__) < version.parse("1.8.0"):
-        return tensor1 // tensor2
-    else:
-        return torch.div(tensor1, tensor2, rounding_mode="floor")

src/transformers/models/hubert/modeling_hubert.py

@@ -33,7 +33,8 @@ from ...file_utils import (
     replace_return_docstrings,
 )
 from ...modeling_outputs import BaseModelOutput, CausalLMOutput, SequenceClassifierOutput
-from ...modeling_utils import PreTrainedModel, torch_int_div
+from ...modeling_utils import PreTrainedModel
+from ...pytorch_utils import torch_int_div
 from ...utils import logging
 from .configuration_hubert import HubertConfig
 

src/transformers/models/sew/modeling_sew.py

@@ -29,7 +29,8 @@ from transformers.deepspeed import is_deepspeed_zero3_enabled
 from ...activations import ACT2FN
 from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
 from ...modeling_outputs import BaseModelOutput, CausalLMOutput, SequenceClassifierOutput
-from ...modeling_utils import PreTrainedModel, torch_int_div
+from ...modeling_utils import PreTrainedModel
+from ...pytorch_utils import torch_int_div
 from ...utils import logging
 from .configuration_sew import SEWConfig
 

src/transformers/models/sew_d/modeling_sew_d.py

@@ -30,7 +30,8 @@ from transformers.deepspeed import is_deepspeed_zero3_enabled
 from ...activations import ACT2FN
 from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
 from ...modeling_outputs import BaseModelOutput, CausalLMOutput, SequenceClassifierOutput
-from ...modeling_utils import PreTrainedModel, torch_int_div
+from ...modeling_utils import PreTrainedModel
+from ...pytorch_utils import torch_int_div
 from ...utils import logging
 from .configuration_sew_d import SEWDConfig
 

src/transformers/models/unispeech/modeling_unispeech.py

@@ -35,7 +35,8 @@ from ...file_utils import (
     replace_return_docstrings,
 )
 from ...modeling_outputs import BaseModelOutput, CausalLMOutput, SequenceClassifierOutput
-from ...modeling_utils import PreTrainedModel, torch_int_div
+from ...modeling_utils import PreTrainedModel
+from ...pytorch_utils import torch_int_div
 from ...utils import logging
 from .configuration_unispeech import UniSpeechConfig
 

src/transformers/models/unispeech_sat/modeling_unispeech_sat.py

@@ -35,7 +35,8 @@ from ...file_utils import (
     replace_return_docstrings,
 )
 from ...modeling_outputs import BaseModelOutput, CausalLMOutput, SequenceClassifierOutput, TokenClassifierOutput
-from ...modeling_utils import PreTrainedModel, torch_int_div
+from ...modeling_utils import PreTrainedModel
+from ...pytorch_utils import torch_int_div
 from ...utils import logging
 from .configuration_unispeech_sat import UniSpeechSatConfig
 

src/transformers/models/wav2vec2/modeling_wav2vec2.py

@@ -41,7 +41,8 @@ from ...modeling_outputs import (
     SequenceClassifierOutput,
     TokenClassifierOutput,
 )
-from ...modeling_utils import PreTrainedModel, torch_int_div
+from ...modeling_utils import PreTrainedModel
+from ...pytorch_utils import torch_int_div
 from ...utils import logging
 from .configuration_wav2vec2 import Wav2Vec2Config
 

src/transformers/models/wavlm/modeling_wavlm.py

@@ -35,7 +35,8 @@ from ...file_utils import (
     add_start_docstrings_to_model_forward,
 )
 from ...modeling_outputs import BaseModelOutput, CausalLMOutput, SequenceClassifierOutput, TokenClassifierOutput
-from ...modeling_utils import PreTrainedModel, torch_int_div
+from ...modeling_utils import PreTrainedModel
+from ...pytorch_utils import torch_int_div
 from ...utils import logging
 from .configuration_wavlm import WavLMConfig
 

src/transformers/pytorch_utils.py

+# Copyright 2022 The HuggingFace Team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import torch
+from packaging import version
+
+from .utils import logging
+
+
+logger = logging.get_logger(__name__)
+
+
+def torch_int_div(tensor1, tensor2):
+    """
+    A function that performs integer division across different versions of PyTorch.
+    """
+    if version.parse(torch.__version__) < version.parse("1.8.0"):
+        return tensor1 // tensor2
+    else:
+        return torch.div(tensor1, tensor2, rounding_mode="floor")