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Update tiny models for pipeline testing. (#24364)

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* fix

---------

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
This commit is contained in:
Yih-Dar
2023-06-20 14:43:10 +02:00
committed by GitHub
parent 56efbf4301
commit c23d131eab
15 changed files with 110 additions and 29 deletions
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4
tests/models/autoformer/test_modeling_autoformer.py
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@@ -25,6 +25,7 @@ from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor
from ...test_pipeline_mixin import PipelineTesterMixin
TOLERANCE = 1e-4
@@ -201,9 +202,10 @@ class AutoformerModelTester:
@require_torch
class AutoformerModelTest(ModelTesterMixin, unittest.TestCase):
class AutoformerModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
all_model_classes = (AutoformerModel, AutoformerForPrediction) if is_torch_available() else ()
all_generative_model_classes = (AutoformerForPrediction,) if is_torch_available() else ()
pipeline_model_mapping = {"feature-extraction": AutoformerModel} if is_torch_available() else {}
test_pruning = False
test_head_masking = False
test_missing_keys = False

2
tests/models/encodec/test_modeling_encodec.py
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@@ -117,7 +117,7 @@ class EncodecModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase)
test_pruning = False
test_headmasking = False
test_resize_embeddings = False
pipeline_model_mapping = {}
pipeline_model_mapping = {"feature-extraction": EncodecModel} if is_torch_available() else {}
input_name = "input_values"
def _prepare_for_class(self, inputs_dict, model_class, return_labels=False):

13
tests/models/git/test_modeling_git.py
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@@ -383,11 +383,22 @@ class GitModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixin,
all_model_classes = (GitModel, GitForCausalLM) if is_torch_available() else ()
all_generative_model_classes = (GitForCausalLM,) if is_torch_available() else ()
pipeline_model_mapping = (
{"feature-extraction": GitModel, "text-generation": GitForCausalLM} if is_torch_available() else {}
{"feature-extraction": GitModel, "image-to-text": GitForCausalLM, "text-generation": GitForCausalLM}
if is_torch_available()
else {}
)
fx_compatible = False
test_torchscript = False
# `GitForCausalLM` doesn't fit into image-to-text pipeline. We might need to overwrite its `generate` function.
def is_pipeline_test_to_skip(
self, pipeline_test_casse_name, config_class, model_architecture, tokenizer_name, processor_name
):
if pipeline_test_casse_name == "ImageToTextPipelineTests":
return True
return False
# special case for GitForCausalLM model
def _prepare_for_class(self, inputs_dict, model_class, return_labels=False):
inputs_dict = super()._prepare_for_class(inputs_dict, model_class, return_labels=return_labels)

5
tests/models/layoutlmv2/test_modeling_layoutlmv2.py
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@@ -270,10 +270,7 @@ class LayoutLMv2ModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCa
else ()
)
pipeline_model_mapping = (
{
"document-question-answering": LayoutLMv2ForQuestionAnswering,
"feature-extraction": LayoutLMv2Model,
}
{"document-question-answering": LayoutLMv2ForQuestionAnswering, "feature-extraction": LayoutLMv2Model}
if is_torch_available()
else {}
)

5
tests/models/layoutlmv3/test_modeling_layoutlmv3.py
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@@ -286,10 +286,7 @@ class LayoutLMv3ModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCa
else ()
)
pipeline_model_mapping = (
{
"document-question-answering": LayoutLMv3ForQuestionAnswering,
"feature-extraction": LayoutLMv3Model,
}
{"document-question-answering": LayoutLMv3ForQuestionAnswering, "feature-extraction": LayoutLMv3Model}
if is_torch_available()
else {}
)

8
tests/models/layoutlmv3/test_modeling_tf_layoutlmv3.py
View File

@@ -278,13 +278,7 @@ class TFLayoutLMv3ModelTest(TFModelTesterMixin, PipelineTesterMixin, unittest.Te
else ()
)
pipeline_model_mapping = (
{
"feature-extraction": TFLayoutLMv3Model,
"question-answering": TFLayoutLMv3ForQuestionAnswering,
"text-classification": TFLayoutLMv3ForSequenceClassification,
"token-classification": TFLayoutLMv3ForTokenClassification,
"zero-shot": TFLayoutLMv3ForSequenceClassification,
}
{"document-question-answering": TFLayoutLMv3ForQuestionAnswering, "feature-extraction": TFLayoutLMv3Model}
if is_tf_available()
else {}
)

5
tests/models/timm_backbone/test_modeling_timm_backbone.py
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@@ -32,6 +32,8 @@ if is_torch_available():
from transformers import TimmBackbone, TimmBackboneConfig
from ...test_pipeline_mixin import PipelineTesterMixin
class TimmBackboneModelTester:
def __init__(
@@ -95,8 +97,9 @@ class TimmBackboneModelTester:
@require_torch
@require_timm
class TimmBackboneModelTest(ModelTesterMixin, BackboneTesterMixin, unittest.TestCase):
class TimmBackboneModelTest(ModelTesterMixin, BackboneTesterMixin, PipelineTesterMixin, unittest.TestCase):
all_model_classes = (TimmBackbone,) if is_torch_available() else ()
pipeline_model_mapping = {"feature-extraction": TimmBackbone} if is_torch_available() else {}
test_resize_embeddings = False
test_head_masking = False
test_pruning = False

2
tests/models/wav2vec2/test_modeling_tf_wav2vec2.py
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@@ -322,7 +322,7 @@ class TFWav2Vec2ModelTest(TFModelTesterMixin, PipelineTesterMixin, unittest.Test
(TFWav2Vec2Model, TFWav2Vec2ForCTC, TFWav2Vec2ForSequenceClassification) if is_tf_available() else ()
)
pipeline_model_mapping = (
{"feature-extraction": TFWav2Vec2Model, "audio-classification": TFWav2Vec2ForSequenceClassification}
{"audio-classification": TFWav2Vec2ForSequenceClassification, "feature-extraction": TFWav2Vec2Model}
if is_tf_available()
else {}
)