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Add TFSpeech2Text (#15113)

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* Add wrapper classes

* convert inner layers to tf

* Add TF Encoder and Decoder layers

* TFSpeech2Text models

* Loadable model

* TF model with same outputs as PT model

* test skeleton

* correct tests and run the fixup

* correct attention expansion

* TFSpeech2Text pask_key_values with TF format
This commit is contained in:
Joao Gante
2022-02-08 16:27:23 +00:00
committed by GitHub
parent 6a5472a8e1
commit 8406fa6dd5
23 changed files with 2499 additions and 96 deletions
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4
tests/test_modeling_common.py
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@@ -1478,6 +1478,8 @@ class ModelTesterMixin:
tf_inputs_dict[key] = tf.convert_to_tensor(tensor.numpy(), dtype=tf.float32)
elif key == "pixel_values":
tf_inputs_dict[key] = tf.convert_to_tensor(tensor.numpy(), dtype=tf.float32)
elif key == "input_features":
tf_inputs_dict[key] = tf.convert_to_tensor(tensor.numpy(), dtype=tf.float32)
else:
tf_inputs_dict[key] = tf.convert_to_tensor(tensor.numpy(), dtype=tf.int32)
@@ -1529,6 +1531,8 @@ class ModelTesterMixin:
tf_inputs_dict[key] = tf.convert_to_tensor(tensor.numpy(), dtype=tf.float32)
elif key == "pixel_values":
tf_inputs_dict[key] = tf.convert_to_tensor(tensor.numpy(), dtype=tf.float32)
elif key == "input_features":
tf_inputs_dict[key] = tf.convert_to_tensor(tensor.numpy(), dtype=tf.float32)
else:
tf_inputs_dict[key] = tf.convert_to_tensor(tensor.numpy(), dtype=tf.int32)