Another attempt at getting Ubuntu test runner to work

pull/154/head
Ross Wightman 5 years ago
parent 20329f2630
commit 4212cd3b9f

@ -1,15 +1,24 @@
import pytest import pytest
import torch import torch
import platform
import os
import fnmatch
from timm import list_models, create_model from timm import list_models, create_model
MAX_FWD_SIZE = 320
if 'GITHUB_ACTIONS' in os.environ and 'Linux' in platform.system():
# GitHub Linux runner is slower and hits memory limits sooner than MacOS, exclude bigger models
EXCLUDE_FILTERS = ['*efficientnet_l2*']
else:
EXCLUDE_FILTERS = []
MAX_FWD_SIZE = 384
MAX_BWD_SIZE = 128 MAX_BWD_SIZE = 128
MAX_FWD_FEAT_SIZE = 448 MAX_FWD_FEAT_SIZE = 448
@pytest.mark.timeout(120) @pytest.mark.timeout(120)
@pytest.mark.parametrize('model_name', list_models()) @pytest.mark.parametrize('model_name', list_models(exclude_filters=EXCLUDE_FILTERS))
@pytest.mark.parametrize('batch_size', [1]) @pytest.mark.parametrize('batch_size', [1])
def test_model_forward(model_name, batch_size): def test_model_forward(model_name, batch_size):
"""Run a single forward pass with each model""" """Run a single forward pass with each model"""
@ -28,7 +37,8 @@ def test_model_forward(model_name, batch_size):
@pytest.mark.timeout(120) @pytest.mark.timeout(120)
@pytest.mark.parametrize('model_name', list_models(exclude_filters='dla*')) # DLA models have an issue TBD # DLA models have an issue TBD, add them to exclusions
@pytest.mark.parametrize('model_name', list_models(exclude_filters=EXCLUDE_FILTERS + ['dla*']))
@pytest.mark.parametrize('batch_size', [2]) @pytest.mark.parametrize('batch_size', [2])
def test_model_backward(model_name, batch_size): def test_model_backward(model_name, batch_size):
"""Run a single forward pass with each model""" """Run a single forward pass with each model"""
@ -65,7 +75,8 @@ def test_model_default_cfgs(model_name, batch_size):
pool_size = cfg['pool_size'] pool_size = cfg['pool_size']
input_size = model.default_cfg['input_size'] input_size = model.default_cfg['input_size']
if all([x <= MAX_FWD_FEAT_SIZE for x in input_size]) and 'efficientnet_l2' not in model_name: if all([x <= MAX_FWD_FEAT_SIZE for x in input_size]) and \
not any([fnmatch.fnmatch(model_name, x) for x in EXCLUDE_FILTERS]):
# pool size only checked if default res <= 448 * 448 to keep resource down # pool size only checked if default res <= 448 * 448 to keep resource down
input_size = tuple([min(x, MAX_FWD_FEAT_SIZE) for x in input_size]) input_size = tuple([min(x, MAX_FWD_FEAT_SIZE) for x in input_size])
outputs = model.forward_features(torch.randn((batch_size, *input_size))) outputs = model.forward_features(torch.randn((batch_size, *input_size)))

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