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# Copyright 2024 Big Vision Authors.
#
# 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.
# pylint: disable=line-too-long,missing-function-docstring
r"""A config to run timing for FlexiViT (only inference, no I/O etc.).
big_vision.tools.eval_only \
--config big_vision/configs/proj/flexivit/timing.py \
--workdir gs://[your_bucket]/big_vision/`date '+%m-%d_%H%M'` \
--config.total_epochs 90
"""
from ml_collections import ConfigDict
def get_config():
c = ConfigDict()
shape = (240, 240, 3)
c.batch_size = 8 # swept
c.init_shapes = [(1, *shape)]
c.representation_layer = 'pre_logits'
# Creating complete model using all params, the sweep will go over variants.
c.model_name = 'xp.flexivit.vit'
c.model = dict(
variant='B',
pool_type='tok',
patch_size=(10, 10), # Like deit@384
seqhw=(24, 24),
)
c.num_classes = 0
c.evals = {}
c.evals.timing = dict(
type='timing',
input_shapes=[shape],
timing=True,
pred_kw=dict(outputs=('pre_logits',)),
)
return c |