Add BLIP (#20716)
* add new model like * add v1 * v1 * v1 * vision encoder logits match * v2 * fix * add docstring * CI tests pass * fix tests * make fixup * add to `toctree` * fix processors * fix processors * fix doc * fill title * add content doc * remove from tokenization auto * fix config * change order * add `# Copied from` * few fixes - add correct license on modeling text - remove dummy argument * Apply suggestions from code review Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * replace name * refactor a bit * more refactor * remove unused arg * make fixup + remove some `# Adapted from ...` * Apply suggestions from code review Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * more `# Copied from` * Apply suggestions from code review Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * now `generate` supports no prefix * remove `FeatureExtractor` * fix path * correct dependency * fix tests * few fixes * add integration tests * add correct conversion script * Apply suggestions from code review Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * add `blip` to tokenization auto * fix docstrings * fix test + add image * remove processor from uncorrect place * Apply suggestions from code review Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * clean up a bit * Apply suggestions from code review Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * clean pixel mask * clean pixel mask * fix `F` * Update src/transformers/models/blip/modeling_blip.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Apply suggestions from code review Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * fix output * Apply suggestions from code review Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * fix pad token id * remove `token_type_ids` * make fixup * Apply suggestions from code review Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * make fixup * Apply suggestions from code review Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * add comments * Update src/transformers/models/blip/modeling_blip.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * remove `token_type_ids` * make fixup * better name * replace with `image_attention_mask` * refactor * make fixup * better docstring * replace `answer_xx` * remove ununsed args * add `labels` * add `labels` * fix processing tests * make fixup * make fixup * put correct repo * remove `pad` * remove `crop` and `center_crop` * Update src/transformers/models/blip/image_processing_blip.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * fix * remove `size_divisor` * fix weights `init` * remove unneeded functions * add suggestions * minor changes - change slow test output for PT 1.13 - docstring order * replace `feature_extractor` by `image_processor` * fix doctests * fix weight init order + add fp16 slow test * add `blip` to doctest * add correct repo name and fix test * Update src/transformers/models/blip/processing_blip.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * fix tests * use `convert_to_rgb` from `image_transforms` * make fixup * fix large loading issue Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
This commit is contained in:
Younes Belkada
167
tests/models/blip/test_modeling_blip_text.py
Normal file
167
tests/models/blip/test_modeling_blip_text.py
Normal file
@@ -0,0 +1,167 @@
|
||||
# coding=utf-8
|
||||
# Copyright 2022 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
""" Testing suite for the PyTorch Blip model. """
|
||||
import unittest
|
||||
|
||||
import numpy as np
|
||||
|
||||
from transformers import BlipTextConfig
|
||||
from transformers.testing_utils import require_torch, slow, torch_device
|
||||
from transformers.utils import is_torch_available
|
||||
|
||||
from ...test_configuration_common import ConfigTester
|
||||
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
|
||||
|
||||
|
||||
if is_torch_available():
|
||||
import torch
|
||||
|
||||
from transformers import BlipTextModel
|
||||
from transformers.models.blip.modeling_blip import BLIP_PRETRAINED_MODEL_ARCHIVE_LIST
|
||||
|
||||
|
||||
class BlipTextModelTester:
|
||||
def __init__(
|
||||
self,
|
||||
parent,
|
||||
batch_size=12,
|
||||
seq_length=7,
|
||||
is_training=True,
|
||||
use_input_mask=True,
|
||||
use_labels=True,
|
||||
vocab_size=99,
|
||||
hidden_size=32,
|
||||
projection_dim=32,
|
||||
num_hidden_layers=5,
|
||||
num_attention_heads=4,
|
||||
intermediate_size=37,
|
||||
dropout=0.1,
|
||||
attention_dropout=0.1,
|
||||
max_position_embeddings=512,
|
||||
initializer_range=0.02,
|
||||
bos_token_id=0,
|
||||
scope=None,
|
||||
):
|
||||
self.parent = parent
|
||||
self.batch_size = batch_size
|
||||
self.seq_length = seq_length
|
||||
self.is_training = is_training
|
||||
self.use_input_mask = use_input_mask
|
||||
self.use_labels = use_labels
|
||||
self.vocab_size = vocab_size
|
||||
self.hidden_size = hidden_size
|
||||
self.projection_dim = projection_dim
|
||||
self.num_hidden_layers = num_hidden_layers
|
||||
self.num_attention_heads = num_attention_heads
|
||||
self.intermediate_size = intermediate_size
|
||||
self.dropout = dropout
|
||||
self.attention_dropout = attention_dropout
|
||||
self.max_position_embeddings = max_position_embeddings
|
||||
self.initializer_range = initializer_range
|
||||
self.scope = scope
|
||||
self.bos_token_id = bos_token_id
|
||||
|
||||
def prepare_config_and_inputs(self):
|
||||
input_ids = ids_tensor([self.batch_size, self.seq_length], self.vocab_size)
|
||||
|
||||
input_mask = None
|
||||
if self.use_input_mask:
|
||||
input_mask = random_attention_mask([self.batch_size, self.seq_length])
|
||||
|
||||
if input_mask is not None:
|
||||
batch_size, seq_length = input_mask.shape
|
||||
rnd_start_indices = np.random.randint(1, seq_length - 1, size=(batch_size,))
|
||||
for batch_idx, start_index in enumerate(rnd_start_indices):
|
||||
input_mask[batch_idx, :start_index] = 1
|
||||
input_mask[batch_idx, start_index:] = 0
|
||||
|
||||
config = self.get_config()
|
||||
|
||||
return config, input_ids, input_mask
|
||||
|
||||
def get_config(self):
|
||||
return BlipTextConfig(
|
||||
vocab_size=self.vocab_size,
|
||||
hidden_size=self.hidden_size,
|
||||
projection_dim=self.projection_dim,
|
||||
num_hidden_layers=self.num_hidden_layers,
|
||||
num_attention_heads=self.num_attention_heads,
|
||||
intermediate_size=self.intermediate_size,
|
||||
dropout=self.dropout,
|
||||
attention_dropout=self.attention_dropout,
|
||||
max_position_embeddings=self.max_position_embeddings,
|
||||
initializer_range=self.initializer_range,
|
||||
bos_token_id=self.bos_token_id,
|
||||
)
|
||||
|
||||
def create_and_check_model(self, config, input_ids, input_mask):
|
||||
model = BlipTextModel(config=config)
|
||||
model.to(torch_device)
|
||||
model.eval()
|
||||
with torch.no_grad():
|
||||
result = model(input_ids, attention_mask=input_mask)
|
||||
result = model(input_ids)
|
||||
self.parent.assertEqual(result.last_hidden_state.shape, (self.batch_size, self.seq_length, self.hidden_size))
|
||||
self.parent.assertEqual(result.pooler_output.shape, (self.batch_size, self.hidden_size))
|
||||
|
||||
def prepare_config_and_inputs_for_common(self):
|
||||
config_and_inputs = self.prepare_config_and_inputs()
|
||||
config, input_ids, input_mask = config_and_inputs
|
||||
inputs_dict = {"input_ids": input_ids, "attention_mask": input_mask}
|
||||
return config, inputs_dict
|
||||
|
||||
|
||||
@require_torch
|
||||
class BlipTextModelTest(ModelTesterMixin, unittest.TestCase):
|
||||
|
||||
all_model_classes = (BlipTextModel,) if is_torch_available() else ()
|
||||
fx_compatible = False
|
||||
test_pruning = False
|
||||
test_head_masking = False
|
||||
|
||||
def setUp(self):
|
||||
self.model_tester = BlipTextModelTester(self)
|
||||
self.config_tester = ConfigTester(self, config_class=BlipTextConfig, hidden_size=37)
|
||||
|
||||
def test_config(self):
|
||||
self.config_tester.run_common_tests()
|
||||
|
||||
def test_model(self):
|
||||
config_and_inputs = self.model_tester.prepare_config_and_inputs()
|
||||
self.model_tester.create_and_check_model(*config_and_inputs)
|
||||
|
||||
def test_training(self):
|
||||
pass
|
||||
|
||||
def test_training_gradient_checkpointing(self):
|
||||
pass
|
||||
|
||||
@unittest.skip(reason="Blip does not use inputs_embeds")
|
||||
def test_inputs_embeds(self):
|
||||
pass
|
||||
|
||||
@unittest.skip(reason="BlipTextModel has no base class and is not available in MODEL_MAPPING")
|
||||
def test_save_load_fast_init_from_base(self):
|
||||
pass
|
||||
|
||||
@unittest.skip(reason="BlipTextModel has no base class and is not available in MODEL_MAPPING")
|
||||
def test_save_load_fast_init_to_base(self):
|
||||
pass
|
||||
|
||||
@slow
|
||||
def test_model_from_pretrained(self):
|
||||
for model_name in BLIP_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
|
||||
model = BlipTextModel.from_pretrained(model_name)
|
||||
self.assertIsNotNone(model)
|
||||
Reference in New Issue
Block a user