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* remove validation args from textual onverson tests * reduce number of train steps in textual inversion tests * fix: directories. * debig * fix: directories. * remove validation tests from textual onversion * try reducing the time of test_text_to_image_checkpointing_use_ema * fix: directories * speed up test_text_to_image_checkpointing * speed up test_text_to_image_checkpointing_checkpoints_total_limit_removes_multiple_checkpoints * fix * speed up test_instruct_pix2pix_checkpointing_checkpoints_total_limit_removes_multiple_checkpoints * set checkpoints_total_limit to 2. * test_text_to_image_lora_checkpointing_checkpoints_total_limit_removes_multiple_checkpoints speed up * speed up test_unconditional_checkpointing_checkpoints_total_limit_removes_multiple_checkpoints * debug * fix: directories. * speed up test_instruct_pix2pix_checkpointing_checkpoints_total_limit * speed up: test_controlnet_checkpointing_checkpoints_total_limit_removes_multiple_checkpoints * speed up test_controlnet_sdxl * speed up dreambooth tests * speed up test_dreambooth_lora_checkpointing_checkpoints_total_limit_removes_multiple_checkpoints * speed up test_custom_diffusion_checkpointing_checkpoints_total_limit_removes_multiple_checkpoints * speed up test_text_to_image_lora_sdxl_text_encoder_checkpointing_checkpoints_total_limit * speed up # checkpoint-2 should have been deleted * speed up examples/text_to_image/test_text_to_image.py::TextToImage::test_text_to_image_checkpointing_checkpoints_total_limit * additional speed ups * style
125 lines
4.7 KiB
Python
125 lines
4.7 KiB
Python
# coding=utf-8
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# Copyright 2023 HuggingFace Inc.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import logging
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import os
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import sys
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import tempfile
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sys.path.append("..")
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from test_examples_utils import ExamplesTestsAccelerate, run_command # noqa: E402
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logging.basicConfig(level=logging.DEBUG)
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logger = logging.getLogger()
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stream_handler = logging.StreamHandler(sys.stdout)
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logger.addHandler(stream_handler)
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class CustomDiffusion(ExamplesTestsAccelerate):
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def test_custom_diffusion(self):
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with tempfile.TemporaryDirectory() as tmpdir:
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test_args = f"""
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examples/custom_diffusion/train_custom_diffusion.py
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--pretrained_model_name_or_path hf-internal-testing/tiny-stable-diffusion-pipe
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--instance_data_dir docs/source/en/imgs
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--instance_prompt <new1>
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--resolution 64
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--train_batch_size 1
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--gradient_accumulation_steps 1
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--max_train_steps 2
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--learning_rate 1.0e-05
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--scale_lr
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--lr_scheduler constant
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--lr_warmup_steps 0
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--modifier_token <new1>
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--no_safe_serialization
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--output_dir {tmpdir}
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""".split()
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run_command(self._launch_args + test_args)
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# save_pretrained smoke test
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self.assertTrue(os.path.isfile(os.path.join(tmpdir, "pytorch_custom_diffusion_weights.bin")))
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self.assertTrue(os.path.isfile(os.path.join(tmpdir, "<new1>.bin")))
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def test_custom_diffusion_checkpointing_checkpoints_total_limit(self):
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with tempfile.TemporaryDirectory() as tmpdir:
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test_args = f"""
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examples/custom_diffusion/train_custom_diffusion.py
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--pretrained_model_name_or_path=hf-internal-testing/tiny-stable-diffusion-pipe
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--instance_data_dir=docs/source/en/imgs
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--output_dir={tmpdir}
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--instance_prompt=<new1>
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--resolution=64
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--train_batch_size=1
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--modifier_token=<new1>
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--dataloader_num_workers=0
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--max_train_steps=6
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--checkpoints_total_limit=2
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--checkpointing_steps=2
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--no_safe_serialization
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""".split()
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run_command(self._launch_args + test_args)
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self.assertEqual({x for x in os.listdir(tmpdir) if "checkpoint" in x}, {"checkpoint-4", "checkpoint-6"})
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def test_custom_diffusion_checkpointing_checkpoints_total_limit_removes_multiple_checkpoints(self):
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with tempfile.TemporaryDirectory() as tmpdir:
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test_args = f"""
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examples/custom_diffusion/train_custom_diffusion.py
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--pretrained_model_name_or_path=hf-internal-testing/tiny-stable-diffusion-pipe
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--instance_data_dir=docs/source/en/imgs
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--output_dir={tmpdir}
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--instance_prompt=<new1>
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--resolution=64
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--train_batch_size=1
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--modifier_token=<new1>
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--dataloader_num_workers=0
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--max_train_steps=4
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--checkpointing_steps=2
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--no_safe_serialization
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""".split()
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run_command(self._launch_args + test_args)
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self.assertEqual(
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{x for x in os.listdir(tmpdir) if "checkpoint" in x},
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{"checkpoint-2", "checkpoint-4"},
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)
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resume_run_args = f"""
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examples/custom_diffusion/train_custom_diffusion.py
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--pretrained_model_name_or_path=hf-internal-testing/tiny-stable-diffusion-pipe
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--instance_data_dir=docs/source/en/imgs
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--output_dir={tmpdir}
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--instance_prompt=<new1>
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--resolution=64
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--train_batch_size=1
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--modifier_token=<new1>
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--dataloader_num_workers=0
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--max_train_steps=8
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--checkpointing_steps=2
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--resume_from_checkpoint=checkpoint-4
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--checkpoints_total_limit=2
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--no_safe_serialization
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""".split()
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run_command(self._launch_args + resume_run_args)
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self.assertEqual({x for x in os.listdir(tmpdir) if "checkpoint" in x}, {"checkpoint-6", "checkpoint-8"})
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