diff --git a/tests/data2vec/test_modeling_data2vec_audio.py b/tests/data2vec/test_modeling_data2vec_audio.py index ecadcb5903..cec29518b2 100644 --- a/tests/data2vec/test_modeling_data2vec_audio.py +++ b/tests/data2vec/test_modeling_data2vec_audio.py @@ -116,7 +116,7 @@ class Data2VecAudioModelTester: self.adapter_output_seq_length = (self.output_seq_length - 1) // adapter_stride + 1 def prepare_config_and_inputs(self): - input_values = floats_tensor([self.batch_size, self.seq_length], self.vocab_size) + input_values = floats_tensor([self.batch_size, self.seq_length], scale=1.0) attention_mask = random_attention_mask([self.batch_size, self.seq_length]) config = self.get_config() diff --git a/tests/hubert/test_modeling_hubert.py b/tests/hubert/test_modeling_hubert.py index 0bc854114d..878fedb6e6 100644 --- a/tests/hubert/test_modeling_hubert.py +++ b/tests/hubert/test_modeling_hubert.py @@ -106,7 +106,7 @@ class HubertModelTester: self.encoder_seq_length = self.output_seq_length def prepare_config_and_inputs(self): - input_values = floats_tensor([self.batch_size, self.seq_length], self.vocab_size) + input_values = floats_tensor([self.batch_size, self.seq_length], scale=1.0) attention_mask = random_attention_mask([self.batch_size, self.seq_length]) config = self.get_config() diff --git a/tests/perceiver/test_modeling_perceiver.py b/tests/perceiver/test_modeling_perceiver.py index a394b00852..3f138373ca 100644 --- a/tests/perceiver/test_modeling_perceiver.py +++ b/tests/perceiver/test_modeling_perceiver.py @@ -143,7 +143,7 @@ class PerceiverModelTester: token_labels = ids_tensor([self.batch_size, self.seq_length], self.num_labels) if model_class is None or model_class.__name__ == "PerceiverModel": - inputs = floats_tensor([self.batch_size, self.seq_length, config.d_model], self.vocab_size) + inputs = floats_tensor([self.batch_size, self.seq_length, config.d_model], scale=1.0) return config, inputs, input_mask, sequence_labels, token_labels elif model_class.__name__ in ["PerceiverForMaskedLM", "PerceiverForSequenceClassification"]: inputs = ids_tensor([self.batch_size, self.seq_length], self.vocab_size) diff --git a/tests/sew/test_modeling_sew.py b/tests/sew/test_modeling_sew.py index e8b06610df..9881f5166d 100644 --- a/tests/sew/test_modeling_sew.py +++ b/tests/sew/test_modeling_sew.py @@ -108,7 +108,7 @@ class SEWModelTester: self.encoder_seq_length = self.output_seq_length // self.squeeze_factor def prepare_config_and_inputs(self): - input_values = floats_tensor([self.batch_size, self.seq_length], self.vocab_size) + input_values = floats_tensor([self.batch_size, self.seq_length], scale=1.0) attention_mask = random_attention_mask([self.batch_size, self.seq_length]) config = self.get_config() diff --git a/tests/sew_d/test_modeling_sew_d.py b/tests/sew_d/test_modeling_sew_d.py index 796bd8805e..7c65909c9f 100644 --- a/tests/sew_d/test_modeling_sew_d.py +++ b/tests/sew_d/test_modeling_sew_d.py @@ -122,7 +122,7 @@ class SEWDModelTester: self.encoder_seq_length = self.output_seq_length // self.squeeze_factor def prepare_config_and_inputs(self): - input_values = floats_tensor([self.batch_size, self.seq_length], self.vocab_size) + input_values = floats_tensor([self.batch_size, self.seq_length], scale=1.0) attention_mask = random_attention_mask([self.batch_size, self.seq_length]) config = self.get_config() diff --git a/tests/speech_encoder_decoder/test_modeling_flax_speech_encoder_decoder.py b/tests/speech_encoder_decoder/test_modeling_flax_speech_encoder_decoder.py index 0549e65064..3f982837ca 100644 --- a/tests/speech_encoder_decoder/test_modeling_flax_speech_encoder_decoder.py +++ b/tests/speech_encoder_decoder/test_modeling_flax_speech_encoder_decoder.py @@ -582,7 +582,7 @@ class FlaxWav2Vec2GPT2ModelTest(FlaxEncoderDecoderMixin, unittest.TestCase): "facebook/wav2vec2-large-lv60", "gpt2-medium" ) batch_size = 13 - input_values = floats_tensor([batch_size, 512], model.config.encoder.vocab_size) + input_values = floats_tensor([batch_size, 512], scale=1.0) attention_mask = random_attention_mask([batch_size, 512]) decoder_input_ids = ids_tensor([batch_size, 4], model.config.decoder.vocab_size) decoder_attention_mask = random_attention_mask([batch_size, 4]) @@ -638,7 +638,7 @@ class FlaxWav2Vec2GPT2ModelTest(FlaxEncoderDecoderMixin, unittest.TestCase): # prepare inputs batch_size = 13 - input_values = floats_tensor([batch_size, 512], fx_model.config.encoder.vocab_size) + input_values = floats_tensor([batch_size, 512], scale=1.0) attention_mask = random_attention_mask([batch_size, 512]) decoder_input_ids = ids_tensor([batch_size, 4], fx_model.config.decoder.vocab_size) decoder_attention_mask = random_attention_mask([batch_size, 4]) @@ -699,7 +699,7 @@ class FlaxWav2Vec2BartModelTest(FlaxEncoderDecoderMixin, unittest.TestCase): "facebook/wav2vec2-large-lv60", "bart-large" ) batch_size = 13 - input_values = floats_tensor([batch_size, 512], model.config.encoder.vocab_size) + input_values = floats_tensor([batch_size, 512], scale=1.0) attention_mask = random_attention_mask([batch_size, 512]) decoder_input_ids = ids_tensor([batch_size, 4], model.config.decoder.vocab_size) decoder_attention_mask = random_attention_mask([batch_size, 4]) @@ -755,7 +755,7 @@ class FlaxWav2Vec2BartModelTest(FlaxEncoderDecoderMixin, unittest.TestCase): # prepare inputs batch_size = 13 - input_values = floats_tensor([batch_size, 512], fx_model.config.encoder.vocab_size) + input_values = floats_tensor([batch_size, 512], scale=1.0) attention_mask = random_attention_mask([batch_size, 512]) decoder_input_ids = ids_tensor([batch_size, 4], fx_model.config.decoder.vocab_size) decoder_attention_mask = random_attention_mask([batch_size, 4]) diff --git a/tests/speech_encoder_decoder/test_modeling_speech_encoder_decoder.py b/tests/speech_encoder_decoder/test_modeling_speech_encoder_decoder.py index c17792084d..bf7428d716 100644 --- a/tests/speech_encoder_decoder/test_modeling_speech_encoder_decoder.py +++ b/tests/speech_encoder_decoder/test_modeling_speech_encoder_decoder.py @@ -425,7 +425,7 @@ class Wav2Vec2BertModelTest(EncoderDecoderMixin, unittest.TestCase): "facebook/wav2vec2-base-960h", "bert-base-cased" ) batch_size = 13 - input_values = floats_tensor([batch_size, 512], model.encoder.config.vocab_size) + input_values = floats_tensor([batch_size, 512], scale=1.0) attention_mask = random_attention_mask([batch_size, 512]) decoder_input_ids = ids_tensor([batch_size, 4], model.decoder.config.vocab_size) decoder_attention_mask = random_attention_mask([batch_size, 4]) @@ -489,7 +489,7 @@ class Speech2TextBertModelTest(EncoderDecoderMixin, unittest.TestCase): "facebook/s2t-small-librispeech-asr", "bert-base-cased" ) batch_size = 13 - input_features = floats_tensor([batch_size, 7, 80], model.encoder.config.vocab_size) + input_features = floats_tensor([batch_size, 7, 80], scale=1.0) attention_mask = random_attention_mask([batch_size, 7]) decoder_input_ids = ids_tensor([batch_size, 4], model.decoder.config.vocab_size) decoder_attention_mask = random_attention_mask([batch_size, 4]) diff --git a/tests/unispeech/test_modeling_unispeech.py b/tests/unispeech/test_modeling_unispeech.py index 9a25237bf3..3654f28a8f 100644 --- a/tests/unispeech/test_modeling_unispeech.py +++ b/tests/unispeech/test_modeling_unispeech.py @@ -107,7 +107,7 @@ class UniSpeechModelTester: self.encoder_seq_length = self.output_seq_length def prepare_config_and_inputs(self): - input_values = floats_tensor([self.batch_size, self.seq_length], self.vocab_size) + input_values = floats_tensor([self.batch_size, self.seq_length], scale=1.0) attention_mask = random_attention_mask([self.batch_size, self.seq_length]) config = self.get_config() diff --git a/tests/unispeech_sat/test_modeling_unispeech_sat.py b/tests/unispeech_sat/test_modeling_unispeech_sat.py index da4359659a..537892b5bf 100644 --- a/tests/unispeech_sat/test_modeling_unispeech_sat.py +++ b/tests/unispeech_sat/test_modeling_unispeech_sat.py @@ -121,7 +121,7 @@ class UniSpeechSatModelTester: self.encoder_seq_length = self.output_seq_length def prepare_config_and_inputs(self): - input_values = floats_tensor([self.batch_size, self.seq_length], self.vocab_size) + input_values = floats_tensor([self.batch_size, self.seq_length], scale=1.0) attention_mask = random_attention_mask([self.batch_size, self.seq_length]) config = self.get_config() @@ -306,7 +306,7 @@ class UniSpeechSatModelTester: model.freeze_base_model() # use a longer sequence length to account for TDNN temporal downsampling - input_values = floats_tensor([self.batch_size, self.seq_length * 2], self.vocab_size) + input_values = floats_tensor([self.batch_size, self.seq_length * 2], scale=1.0) input_lengths = [input_values.shape[-1] // i for i in [4, 2, 1]] labels = ids_tensor((input_values.shape[0], 1), len(model.config.id2label)) diff --git a/tests/wav2vec2/test_modeling_flax_wav2vec2.py b/tests/wav2vec2/test_modeling_flax_wav2vec2.py index f70bb319fc..da03c95c06 100644 --- a/tests/wav2vec2/test_modeling_flax_wav2vec2.py +++ b/tests/wav2vec2/test_modeling_flax_wav2vec2.py @@ -117,7 +117,7 @@ class FlaxWav2Vec2ModelTester: self.encoder_seq_length = self.output_seq_length def prepare_config_and_inputs(self): - input_values = floats_tensor([self.batch_size, self.seq_length], self.vocab_size) + input_values = floats_tensor([self.batch_size, self.seq_length], scale=1.0) attention_mask = random_attention_mask([self.batch_size, self.seq_length]) config = Wav2Vec2Config( diff --git a/tests/wav2vec2/test_modeling_wav2vec2.py b/tests/wav2vec2/test_modeling_wav2vec2.py index c1978a45b7..c64b0201ee 100644 --- a/tests/wav2vec2/test_modeling_wav2vec2.py +++ b/tests/wav2vec2/test_modeling_wav2vec2.py @@ -150,7 +150,7 @@ class Wav2Vec2ModelTester: self.adapter_output_seq_length = (self.output_seq_length - 1) // adapter_stride + 1 def prepare_config_and_inputs(self): - input_values = floats_tensor([self.batch_size, self.seq_length], self.vocab_size) + input_values = floats_tensor([self.batch_size, self.seq_length], scale=1.0) attention_mask = random_attention_mask([self.batch_size, self.seq_length]) config = self.get_config() diff --git a/tests/wavlm/test_modeling_wavlm.py b/tests/wavlm/test_modeling_wavlm.py index 937325e721..0bc40ed5f7 100644 --- a/tests/wavlm/test_modeling_wavlm.py +++ b/tests/wavlm/test_modeling_wavlm.py @@ -114,7 +114,7 @@ class WavLMModelTester: self.encoder_seq_length = self.output_seq_length def prepare_config_and_inputs(self): - input_values = floats_tensor([self.batch_size, self.seq_length], self.vocab_size) + input_values = floats_tensor([self.batch_size, self.seq_length], scale=1.0) attention_mask = random_attention_mask([self.batch_size, self.seq_length]) config = self.get_config()