style

stable_speech/configuration_stable_speech.py

@@ -14,8 +14,8 @@
 # limitations under the License.
 """ Stable Speech model configuration"""
 
-from transformers.configuration_utils import PretrainedConfig
 from transformers import AutoConfig, logging
+from transformers.configuration_utils import PretrainedConfig
 
 
 logger = logging.get_logger(__name__)

stable_speech/modeling_stable_speech.py

@@ -23,7 +23,7 @@ from typing import TYPE_CHECKING, Any, Dict, Optional, Tuple, Union
 import torch
 import torch.nn as nn
 from torch.nn import CrossEntropyLoss
-
+from transformers import AutoConfig, AutoModel
 from transformers.activations import ACT2FN
 from transformers.generation.configuration_utils import GenerationConfig
 from transformers.generation.logits_process import ClassifierFreeGuidanceLogitsProcessor, LogitsProcessorList
@@ -43,7 +43,7 @@ from transformers.utils import (
     logging,
     replace_return_docstrings,
 )
-from transformers import AutoConfig, AutoModel
+
 from .configuration_stable_speech import StableSpeechConfig, StableSpeechDecoderConfig
 
 
@@ -1091,7 +1091,7 @@ class StableSpeechForCausalLM(StableSpeechPreTrainedModel):
         # fill the shifted ids with the prompt entries, offset by the codebook idx
         for codebook in range(num_codebooks):
             # mono channel - loop over the codebooks one-by-one
-            input_ids_shifted[:, codebook, codebook: seq_len + codebook] = input_ids[:, codebook]
+            input_ids_shifted[:, codebook, codebook : seq_len + codebook] = input_ids[:, codebook]
 
         # construct a pattern mask that indicates the positions of padding tokens for each codebook
         # first fill the upper triangular part (the EOS padding)
@@ -1419,7 +1419,9 @@ class StableSpeechForConditionalGeneration(PreTrainedModel):
                 "Either a configuration has to be provided, or all three of text encoder, audio encoder and Stable Speech decoder."
             )
         if config is None:
-            config = StableSpeechConfig.from_sub_models_config(text_encoder.config, audio_encoder.config, decoder.config)
+            config = StableSpeechConfig.from_sub_models_config(
+                text_encoder.config, audio_encoder.config, decoder.config
+            )
         else:
             if not isinstance(config, self.config_class):
                 raise ValueError(f"Config: {config} has to be of type {self.config_class}")