Generation tests: update imagegpt input name, remove unused functions (…

…huggingface#33663)
BernardZach · Dec 5, 2024 · f02923a · f02923a
1 parent 5b1a672
commit f02923a
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Showing 18 changed files with 23 additions and 656 deletions.
diff --git a/src/transformers/models/imagegpt/modeling_imagegpt.py b/src/transformers/models/imagegpt/modeling_imagegpt.py
@@ -690,8 +690,7 @@ def forward(
 
         if "pixel_values" in kwargs:
             warnings.warn(
-                "The `pixel_values` argument is deprecated and will be removed in a future version, use `input_ids`"
-                " instead.",
+                "The `pixel_values` argument is deprecated and will be removed in v4.47, use `input_ids` instead.",
                 FutureWarning,
             )
 
@@ -1004,8 +1003,7 @@ def forward(
 
         if "pixel_values" in kwargs:
             warnings.warn(
-                "The `pixel_values` argument is deprecated and will be removed in a future version, use `input_ids`"
-                " instead.",
+                "The `pixel_values` argument is deprecated and will be removed in v4.47, use `input_ids` instead.",
                 FutureWarning,
             )
 
@@ -1137,8 +1135,7 @@ def forward(
 
         if "pixel_values" in kwargs:
             warnings.warn(
-                "The `pixel_values` argument is deprecated and will be removed in a future version, use `input_ids`"
-                " instead.",
+                "The `pixel_values` argument is deprecated and will be removed in v4.47, use `input_ids` instead.",
                 FutureWarning,
             )
 

diff --git a/tests/generation/test_utils.py b/tests/generation/test_utils.py
@@ -190,26 +190,6 @@ def _get_constrained_beam_kwargs(self, num_return_sequences=1):
         }
         return beam_kwargs
 
-    @staticmethod
-    def _get_encoder_outputs(
-        model, input_ids, attention_mask, output_attentions=None, output_hidden_states=None, num_interleave=1
-    ):
-        encoder = model.get_encoder()
-        encoder_outputs = encoder(
-            input_ids,
-            attention_mask=attention_mask,
-            output_attentions=output_attentions,
-            output_hidden_states=output_hidden_states,
-        )
-        encoder_outputs["last_hidden_state"] = encoder_outputs.last_hidden_state.repeat_interleave(
-            num_interleave, dim=0
-        )
-        generation_config = copy.deepcopy(model.generation_config)
-        model._prepare_special_tokens(generation_config)
-        input_ids = torch.zeros_like(input_ids[:, :1]) + generation_config.decoder_start_token_id
-        attention_mask = None
-        return encoder_outputs, input_ids, attention_mask
-
     def _greedy_generate(
         self,
         model,

diff --git a/tests/models/codegen/test_modeling_codegen.py b/tests/models/codegen/test_modeling_codegen.py
@@ -23,7 +23,7 @@
 
 from ...generation.test_utils import GenerationTesterMixin
 from ...test_configuration_common import ConfigTester
-from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
+from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
 from ...test_pipeline_mixin import PipelineTesterMixin
 
 
@@ -150,35 +150,6 @@ def get_config(self):
             rotary_dim=self.rotary_dim,
         )
 
-    def prepare_config_and_inputs_for_decoder(self):
-        (
-            config,
-            input_ids,
-            input_mask,
-            head_mask,
-            token_type_ids,
-            mc_token_ids,
-            sequence_labels,
-            token_labels,
-            choice_labels,
-        ) = self.prepare_config_and_inputs()
-
-        encoder_hidden_states = floats_tensor([self.batch_size, self.seq_length, self.hidden_size])
-        encoder_attention_mask = ids_tensor([self.batch_size, self.seq_length], vocab_size=2)
-
-        return (
-            config,
-            input_ids,
-            input_mask,
-            head_mask,
-            token_type_ids,
-            sequence_labels,
-            token_labels,
-            choice_labels,
-            encoder_hidden_states,
-            encoder_attention_mask,
-        )
-
     def create_and_check_codegen_model(self, config, input_ids, input_mask, head_mask, token_type_ids, *args):
         model = CodeGenModel(config=config)
         model.to(torch_device)

diff --git a/tests/models/falcon_mamba/test_modeling_falcon_mamba.py b/tests/models/falcon_mamba/test_modeling_falcon_mamba.py
@@ -150,25 +150,6 @@ def get_pipeline_config(self):
         config.vocab_size = 300
         return config
 
-    def prepare_config_and_inputs_for_decoder(self):
-        (
-            config,
-            input_ids,
-            attention_mask,
-            sequence_labels,
-            token_labels,
-            choice_labels,
-        ) = self.prepare_config_and_inputs()
-
-        return (
-            config,
-            input_ids,
-            attention_mask,
-            sequence_labels,
-            token_labels,
-            choice_labels,
-        )
-
     def create_and_check_falcon_mamba_model(self, config, input_ids, *args):
         config.output_hidden_states = True
         model = FalconMambaModel(config=config)

diff --git a/tests/models/gpt_bigcode/test_modeling_gpt_bigcode.py b/tests/models/gpt_bigcode/test_modeling_gpt_bigcode.py
@@ -22,7 +22,7 @@
 
 from ...generation.test_utils import GenerationTesterMixin
 from ...test_configuration_common import ConfigTester
-from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
+from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
 from ...test_pipeline_mixin import PipelineTesterMixin
 
 
@@ -178,35 +178,6 @@ def get_pipeline_config(self):
         config.vocab_size = 300
         return config
 
-    def prepare_config_and_inputs_for_decoder(self):
-        (
-            config,
-            input_ids,
-            input_mask,
-            head_mask,
-            token_type_ids,
-            mc_token_ids,
-            sequence_labels,
-            token_labels,
-            choice_labels,
-        ) = self.prepare_config_and_inputs()
-
-        encoder_hidden_states = floats_tensor([self.batch_size, self.seq_length, self.hidden_size])
-        encoder_attention_mask = ids_tensor([self.batch_size, self.seq_length], vocab_size=2)
-
-        return (
-            config,
-            input_ids,
-            input_mask,
-            head_mask,
-            token_type_ids,
-            sequence_labels,
-            token_labels,
-            choice_labels,
-            encoder_hidden_states,
-            encoder_attention_mask,
-        )
-
     def create_and_check_gpt_bigcode_model(self, config, input_ids, input_mask, head_mask, token_type_ids, *args):
         model = GPTBigCodeModel(config=config)
         model.to(torch_device)

diff --git a/tests/models/gpt_neo/test_modeling_gpt_neo.py b/tests/models/gpt_neo/test_modeling_gpt_neo.py
@@ -22,7 +22,7 @@
 
 from ...generation.test_utils import GenerationTesterMixin
 from ...test_configuration_common import ConfigTester
-from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
+from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
 from ...test_pipeline_mixin import PipelineTesterMixin
 
 
@@ -157,35 +157,6 @@ def get_pipeline_config(self):
         config.vocab_size = 300
         return config
 
-    def prepare_config_and_inputs_for_decoder(self):
-        (
-            config,
-            input_ids,
-            input_mask,
-            head_mask,
-            token_type_ids,
-            mc_token_ids,
-            sequence_labels,
-            token_labels,
-            choice_labels,
-        ) = self.prepare_config_and_inputs()
-
-        encoder_hidden_states = floats_tensor([self.batch_size, self.seq_length, self.hidden_size])
-        encoder_attention_mask = ids_tensor([self.batch_size, self.seq_length], vocab_size=2)
-
-        return (
-            config,
-            input_ids,
-            input_mask,
-            head_mask,
-            token_type_ids,
-            sequence_labels,
-            token_labels,
-            choice_labels,
-            encoder_hidden_states,
-            encoder_attention_mask,
-        )
-
     def create_and_check_gpt_neo_model(self, config, input_ids, input_mask, head_mask, token_type_ids, *args):
         model = GPTNeoModel(config=config)
         model.to(torch_device)

diff --git a/tests/models/gptj/test_modeling_gptj.py b/tests/models/gptj/test_modeling_gptj.py
@@ -32,7 +32,7 @@
 
 from ...generation.test_utils import GenerationTesterMixin
 from ...test_configuration_common import ConfigTester
-from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
+from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
 from ...test_pipeline_mixin import PipelineTesterMixin
 
 
@@ -173,35 +173,6 @@ def get_pipeline_config(self):
         config.vocab_size = 300
         return config
 
-    def prepare_config_and_inputs_for_decoder(self):
-        (
-            config,
-            input_ids,
-            input_mask,
-            head_mask,
-            token_type_ids,
-            mc_token_ids,
-            sequence_labels,
-            token_labels,
-            choice_labels,
-        ) = self.prepare_config_and_inputs()
-
-        encoder_hidden_states = floats_tensor([self.batch_size, self.seq_length, self.hidden_size])
-        encoder_attention_mask = ids_tensor([self.batch_size, self.seq_length], vocab_size=2)
-
-        return (
-            config,
-            input_ids,
-            input_mask,
-            head_mask,
-            token_type_ids,
-            sequence_labels,
-            token_labels,
-            choice_labels,
-            encoder_hidden_states,
-            encoder_attention_mask,
-        )
-
     def create_and_check_gptj_model(self, config, input_ids, input_mask, head_mask, token_type_ids, *args):
         model = GPTJModel(config=config)
         model.to(torch_device)