diff --git a/.azure-pipelines/scripts/ut/run_basic_others.sh b/.azure-pipelines/scripts/ut/run_basic_others.sh index 4781eb89468..60ae3f09bf6 100644 --- a/.azure-pipelines/scripts/ut/run_basic_others.sh +++ b/.azure-pipelines/scripts/ut/run_basic_others.sh @@ -22,6 +22,10 @@ sed -i '/ neural_coder\//d' run.sh sed -i '/ ipex\//d' run.sh sed -i '/ itex\//d' run.sh +echo "copy model for dynas..." +mkdir -p .torch/ofa_nets || true +cp -r /tf_dataset/ut-localfile/ofa_mbv3_d234_e346_k357_w1.2 .torch/ofa_nets || true + LOG_DIR=/neural-compressor/log_dir mkdir -p ${LOG_DIR} ut_log_name=${LOG_DIR}/ut_tf_${tensorflow_version}_pt_${pytorch_version}.log diff --git a/.azure-pipelines/ut-basic.yml b/.azure-pipelines/ut-basic.yml index 05417fae4e0..b57b97b8b62 100644 --- a/.azure-pipelines/ut-basic.yml +++ b/.azure-pipelines/ut-basic.yml @@ -11,6 +11,7 @@ pr: - neural_compressor - test - setup.py + - .azure-pipelines/scripts/ut exclude: - neural_compressor/ux - test/ux diff --git a/.azure-pipelines/ut-ncoder.yml b/.azure-pipelines/ut-ncoder.yml index 14ce726c626..9663aeae21d 100644 --- a/.azure-pipelines/ut-ncoder.yml +++ b/.azure-pipelines/ut-ncoder.yml @@ -11,6 +11,7 @@ pr: - neural_coder - test/neural_coder - setup.py + - .azure-pipelines/scripts/ut pool: ICX-16C diff --git a/.azure-pipelines/ut-ux.yml b/.azure-pipelines/ut-ux.yml index 2b79fb4b9b4..25b5e5a94c0 100644 --- a/.azure-pipelines/ut-ux.yml +++ b/.azure-pipelines/ut-ux.yml @@ -11,6 +11,7 @@ pr: - neural_compressor/ux - test/ux - setup.py + - .azure-pipelines/scripts/ut pool: ICX-16C diff --git a/test/itex/test_tensorflow_itex_basic.py b/test/itex/test_tensorflow_itex_basic.py index 491b97ed973..407a47e6a6e 100644 --- a/test/itex/test_tensorflow_itex_basic.py +++ b/test/itex/test_tensorflow_itex_basic.py @@ -22,6 +22,7 @@ def build_fake_yaml(fake_yaml, save_path, **kwargs): class TestItexEnabling(unittest.TestCase): @classmethod def setUpClass(self): + os.system("rm *.log") fake_yaml_1 = ''' model: name: fake_model_cpu @@ -238,8 +239,6 @@ def test_itex_benchmark_gpu(self): relu = tf.nn.relu(add) relu6 = tf.nn.relu6(relu, name='op_to_store') out_name = relu6.name.split(':')[0] - num_of_instance = 1 - cores_per_instance = 1 with tf.compat.v1.Session() as sess: sess.run(tf.compat.v1.global_variables_initializer()) output_graph_def = graph_util.convert_variables_to_constants(