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[misc] update pre-commit and run all files (#4752)

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* [misc] update pre-commit

* [misc] run pre-commit

* [misc] remove useless configuration files

* [misc] ignore cuda for clang-format
This commit is contained in:
Hongxin Liu
2023-09-19 14:20:26 +08:00
committed by GitHub
parent 3c6b831c26
commit 079bf3cb26
1268 changed files with 50037 additions and 38444 deletions
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25
tests/test_fx/test_pipeline/test_hf_model/hf_utils.py
View File

@@ -1,11 +1,12 @@
import torch
from torch.fx import symbolic_trace
from torch.fx import GraphModule
from colossalai.fx.passes.adding_split_node_pass import split_with_split_nodes_pass, balanced_split_pass
from colossalai.fx import ColoTracer
import inspect
import random
import numpy as np
import torch
from torch.fx import GraphModule
from colossalai.fx import ColoTracer
from colossalai.fx.passes.adding_split_node_pass import balanced_split_pass, split_with_split_nodes_pass
MANUAL_SEED = 0
random.seed(MANUAL_SEED)
@@ -26,7 +27,7 @@ def split_model_and_compare_output(model, data_gen):
# tracing model
tracer = ColoTracer()
try:
meta_args = {k: v.to('meta') for k, v in kwargs.items()}
meta_args = {k: v.to("meta") for k, v in kwargs.items()}
graph = tracer.trace(root=model, meta_args=meta_args)
except Exception as e:
raise RuntimeError(f"Failed to trace {model.__class__.__name__}, error: {e}")
@@ -49,16 +50,16 @@ def split_model_and_compare_output(model, data_gen):
output_part1 = model_part1(output_part0)
else:
if len(output_part0) > len(sig.parameters):
output_part0 = output_part0[:len(sig.parameters)]
output_part0 = output_part0[: len(sig.parameters)]
output_part1 = model_part1(*output_part0)
# get output tensor from HFOutput datastructure
if 'logits' in output:
output_to_compare = output['logits']
elif 'prediction_logits' in output:
output_to_compare = output['prediction_logits']
if "logits" in output:
output_to_compare = output["logits"]
elif "prediction_logits" in output:
output_to_compare = output["prediction_logits"]
else:
output_to_compare = output['last_hidden_state']
output_to_compare = output["last_hidden_state"]
# compare output
if isinstance(output_part1, torch.Tensor):

18
tests/test_fx/test_pipeline/test_hf_model/test_albert.py
View File

@@ -7,7 +7,7 @@ BATCH_SIZE = 2
SEQ_LENGHT = 16
@pytest.mark.skip('balance split v2 is not ready')
@pytest.mark.skip("balance split v2 is not ready")
def test_single_sentence_albert():
MODEL_LIST = [
transformers.AlbertModel,
@@ -17,12 +17,14 @@ def test_single_sentence_albert():
transformers.AlbertForTokenClassification,
]
config = transformers.AlbertConfig(vocab_size=100,
embedding_size=128,
hidden_size=128,
num_hidden_layers=2,
num_attention_heads=4,
intermediate_size=256)
config = transformers.AlbertConfig(
vocab_size=100,
embedding_size=128,
hidden_size=128,
num_hidden_layers=2,
num_attention_heads=4,
intermediate_size=256,
)
def data_gen():
input_ids = torch.zeros((BATCH_SIZE, SEQ_LENGHT), dtype=torch.int64)
@@ -36,5 +38,5 @@ def test_single_sentence_albert():
split_model_and_compare_output(model, data_gen)
if __name__ == '__main__':
if __name__ == "__main__":
test_single_sentence_albert()

12
tests/test_fx/test_pipeline/test_hf_model/test_bert.py
View File

@@ -7,7 +7,7 @@ BATCH_SIZE = 2
SEQ_LENGHT = 16
@pytest.mark.skip('balance split v2 is not ready')
@pytest.mark.skip("balance split v2 is not ready")
def test_single_sentence_bert():
MODEL_LIST = [
transformers.BertModel,
@@ -18,11 +18,9 @@ def test_single_sentence_bert():
transformers.BertForTokenClassification,
]
config = transformers.BertConfig(vocab_size=100,
hidden_size=128,
num_hidden_layers=4,
num_attention_heads=4,
intermediate_size=256)
config = transformers.BertConfig(
vocab_size=100, hidden_size=128, num_hidden_layers=4, num_attention_heads=4, intermediate_size=256
)
def data_gen():
input_ids = torch.zeros((BATCH_SIZE, SEQ_LENGHT), dtype=torch.int64)
@@ -36,5 +34,5 @@ def test_single_sentence_bert():
split_model_and_compare_output(model, data_gen)
if __name__ == '__main__':
if __name__ == "__main__":
test_single_sentence_bert()

6
tests/test_fx/test_pipeline/test_hf_model/test_gpt.py
View File

@@ -9,14 +9,14 @@ NUM_EPOCHS = 2
NUM_CHUNKS = 1
@pytest.mark.skip('balance split v2 is not ready')
@pytest.mark.skip("balance split v2 is not ready")
def test_gpt():
MODEL_LIST = [
transformers.GPT2Model,
transformers.GPT2LMHeadModel,
transformers.GPT2DoubleHeadsModel,
transformers.GPT2ForTokenClassification,
# transformers.GPT2ForSequenceClassification, # not supported yet
# transformers.GPT2ForSequenceClassification, # not supported yet
]
config = transformers.GPT2Config(n_position=64, n_layer=4, n_head=8)
@@ -32,5 +32,5 @@ def test_gpt():
split_model_and_compare_output(model, data_gen)
if __name__ == '__main__':
if __name__ == "__main__":
test_gpt()

4
tests/test_fx/test_pipeline/test_hf_model/test_opt.py
View File

@@ -7,7 +7,7 @@ BATCH_SIZE = 1
SEQ_LENGHT = 16
@pytest.mark.skip('balance split v2 is not ready')
@pytest.mark.skip("balance split v2 is not ready")
def test_opt():
MODEL_LIST = [
transformers.OPTModel,
@@ -27,5 +27,5 @@ def test_opt():
split_model_and_compare_output(model, data_gen)
if __name__ == '__main__':
if __name__ == "__main__":
test_opt()

4
tests/test_fx/test_pipeline/test_hf_model/test_t5.py
View File

@@ -7,7 +7,7 @@ BATCH_SIZE = 1
SEQ_LENGHT = 16
@pytest.mark.skip('balance split v2 is not ready')
@pytest.mark.skip("balance split v2 is not ready")
def test_t5():
MODEL_LIST = [
transformers.T5Model,
@@ -39,5 +39,5 @@ def test_t5():
split_model_and_compare_output(model, data_gen_func)
if __name__ == '__main__':
if __name__ == "__main__":
test_t5()