fixed calculation of ctc loss in TFWav2Vec2ForCTC (#18014)

Co-authored-by: Sreyan-G@NVIDIA <sreyang@nvidia.com>

src/transformers/models/wav2vec2/modeling_tf_wav2vec2.py

@@ -25,7 +25,13 @@
 
 from ...activations_tf import get_tf_activation
 from ...modeling_tf_outputs import TFBaseModelOutput, TFCausalLMOutput
-from ...modeling_tf_utils import TFPreTrainedModel, booleans_processing, get_initializer, keras_serializable
+from ...modeling_tf_utils import (
+    TFPreTrainedModel,
+    booleans_processing,
+    get_initializer,
+    keras_serializable,
+    unpack_inputs,
+)
 from ...tf_utils import shape_list, stable_softmax
 from ...utils import (
     ModelOutput,
@@ -1580,6 +1586,7 @@ def freeze_feature_encoder(self):
         """
         self.wav2vec2.feature_extractor.trainable = False
 
+    @unpack_inputs
     @add_start_docstrings_to_model_forward(WAV_2_VEC_2_INPUTS_DOCSTRING)
     @replace_return_docstrings(output_type=TFCausalLMOutput, config_class=_CONFIG_FOR_DOC)
     def call(
@@ -1702,6 +1709,8 @@ def call(
                 loss = tf.reduce_sum(loss)
             if self.config.ctc_loss_reduction == "mean":
                 loss = tf.reduce_mean(loss)
+
+            loss = tf.reshape(loss, (1,))
         else:
             loss = None