def test_mnist_tp_to_estimator() -> None:
config = conf.load_config(
conf.experimental_path("mnist_tp_to_estimator/const.yaml"))
config = conf.set_max_steps(config, 2)
exp.run_basic_test_with_temp_config(
config, conf.experimental_path("mnist_tp_to_estimator"), 1)
def test_resnet50() -> None:
config = conf.load_config(
conf.experimental_path("resnet50_tf_keras/const.yaml"))
config = conf.set_max_steps(config, 2)
exp.run_basic_test_with_temp_config(
config, conf.experimental_path("resnet50_tf_keras"), 1)
def test_efficientdet_coco_pytorch_const() -> None:
config = conf.load_config(
conf.cv_examples_path("efficientdet_pytorch/const_fake.yaml"))
config = conf.set_max_length(config, {"batches": 200})
exp.run_basic_test_with_temp_config(
config, conf.cv_examples_path("efficientdet_pytorch"), 1)
def test_bert_glue() -> None:
config = conf.load_config(
conf.experimental_path("bert_glue_pytorch/const.yaml"))
config = conf.set_max_steps(config, 2)
exp.run_basic_test_with_temp_config(
config, conf.experimental_path("bert_glue_pytorch/"), 1)
def test_tf_keras_const_warm_start(tf2: bool) -> None:
config = conf.load_config(conf.official_examples_path("cifar10_cnn_tf_keras/const.yaml"))
config = conf.set_max_steps(config, 2)
config = conf.set_tf2_image(config) if tf2 else conf.set_tf1_image(config)
experiment_id1 = exp.run_basic_test_with_temp_config(
config, conf.official_examples_path("cifar10_cnn_tf_keras"), 1
)
trials = exp.experiment_trials(experiment_id1)
assert len(trials) == 1
first_trial = trials[0]
first_trial_id = first_trial["id"]
assert len(first_trial["steps"]) == 2
first_checkpoint_id = first_trial["steps"][1]["checkpoint"]["id"]
# Add a source trial ID to warm start from.
config["searcher"]["source_trial_id"] = first_trial_id
experiment_id2 = exp.run_basic_test_with_temp_config(
config, conf.official_examples_path("cifar10_cnn_tf_keras"), 1
)
# The new trials should have a warm start checkpoint ID.
trials = exp.experiment_trials(experiment_id2)
assert len(trials) == 1
for trial in trials:
assert trial["warm_start_checkpoint_id"] == first_checkpoint_id
def test_mmdetection_pytorch_const() -> None:
config = conf.load_config(
conf.cv_examples_path("mmdetection_pytorch/const_fake_data.yaml"))
config = conf.set_max_length(config, {"batches": 200})
exp.run_basic_test_with_temp_config(
config, conf.cv_examples_path("mmdetection_pytorch"), 1)
def test_mnist_estimator_warm_start(tf2: bool) -> None:
config = conf.load_config(conf.fixtures_path("mnist_estimator/single.yaml"))
config = conf.set_tf2_image(config) if tf2 else conf.set_tf1_image(config)
experiment_id1 = exp.run_basic_test_with_temp_config(
config, conf.official_examples_path("trial/mnist_estimator"), 1
)
trials = exp.experiment_trials(experiment_id1)
assert len(trials) == 1
first_trial = trials[0]
first_trial_id = first_trial["id"]
assert len(first_trial["steps"]) == 1
first_checkpoint_id = first_trial["steps"][0]["checkpoint"]["id"]
config_obj = conf.load_config(conf.fixtures_path("mnist_estimator/single.yaml"))
config_obj["searcher"]["source_trial_id"] = first_trial_id
config_obj = conf.set_tf2_image(config_obj) if tf2 else conf.set_tf1_image(config_obj)
experiment_id2 = exp.run_basic_test_with_temp_config(
config_obj, conf.official_examples_path("trial/mnist_estimator"), 1
)
trials = exp.experiment_trials(experiment_id2)
assert len(trials) == 1
assert trials[0]["warm_start_checkpoint_id"] == first_checkpoint_id
def test_pytorch_11_const(aggregation_frequency: int, using_k8s: bool) -> None:
config = conf.load_config(
conf.fixtures_path("mnist_pytorch/const-pytorch11.yaml"))
config = conf.set_aggregation_frequency(config, aggregation_frequency)
if using_k8s:
pod_spec = {
"metadata": {
"labels": {
"ci": "testing"
}
},
"spec": {
"containers": [{
"name":
"determined-container",
"volumeMounts": [{
"name": "temp1",
"mountPath": "/random"
}],
}],
"volumes": [{
"name": "temp1",
"emptyDir": {}
}],
},
}
config = conf.set_pod_spec(config, pod_spec)
exp.run_basic_test_with_temp_config(config,
conf.tutorials_path("mnist_pytorch"),
1)
def test_gbt_estimator() -> None:
config = conf.load_config(
conf.experimental_path("trial/gbt_estimator/const.yaml"))
config = conf.set_max_length(config, {"batches": 200})
exp.run_basic_test_with_temp_config(
config, conf.experimental_path("trial/gbt_estimator"), 1)
def test_nas_search() -> None:
config = conf.load_config(
conf.experimental_path("trial/rsws_nas/train_one_arch.yaml"))
config = conf.set_max_length(config, {"batches": 200})
exp.run_basic_test_with_temp_config(
config, conf.experimental_path("trial/rsws_nas"), 1)
def test_imagenet_nas() -> None:
config = conf.load_config(
conf.experimental_path("trial/gaea_nas/eval/const.yaml"))
config = conf.set_max_length(config, {"batches": 200})
exp.run_basic_test_with_temp_config(
config, conf.experimental_path("trial/gaea_nas/eval"), 1)
def test_mnist_pytorch_multi_output() -> None:
config = conf.load_config(
conf.experimental_path("trial/mnist_pytorch_multi_output/const.yaml"))
config = conf.set_max_length(config, {"batches": 200})
exp.run_basic_test_with_temp_config(
config, conf.experimental_path("trial/mnist_pytorch_multi_output"), 1)
def test_resnet50() -> None:
config = conf.load_config(
conf.experimental_path("trial/resnet50_tf_keras/const.yaml"))
config = conf.set_max_length(config, {"batches": 200})
exp.run_basic_test_with_temp_config(
config, conf.experimental_path("trial/resnet50_tf_keras"), 1)
def test_bert_glue() -> None:
config = conf.load_config(
conf.experimental_path("trial/bert_glue_pytorch/const.yaml"))
config = conf.set_max_length(config, {"batches": 200})
exp.run_basic_test_with_temp_config(
config, conf.experimental_path("trial/bert_glue_pytorch/"), 1)
def test_fashion_mnist_tf_keras_distributed() -> None:
config = conf.load_config(
conf.tutorials_path("fashion_mnist_tf_keras/distributed.yaml"))
config = conf.set_max_length(config, {"batches": 200})
exp.run_basic_test_with_temp_config(
config, conf.tutorials_path("fashion_mnist_tf_keras"), 1)
def test_pytorch_const_with_amp(api_style: str) -> None:
config = conf.load_config(
conf.fixtures_path("pytorch_amp/" + api_style + "_amp.yaml"))
config = conf.set_max_length(config, {"batches": 200})
exp.run_basic_test_with_temp_config(config,
conf.fixtures_path("pytorch_amp"), 1)
def test_mnist_estimator_distributed() -> None:
config = conf.load_config(
conf.cv_examples_path("mnist_estimator/distributed.yaml"))
config = conf.set_max_length(config, {"batches": 200})
exp.run_basic_test_with_temp_config(
config, conf.cv_examples_path("mnist_estimator"), 1)
def test_protein_pytorch_geometric() -> None:
config = conf.load_config(
conf.graphs_examples_path("proteins_pytorch_geometric"))
config = conf.set_max_length(config, {"epochs": 50})
exp.run_basic_test_with_temp_config(
config, conf.graphs_examples_path("proteins_pytorch_geometric"), 1)
def test_unets_tf_keras_distributed() -> None:
config = conf.load_config(
conf.cv_examples_path("unets_tf_keras/distributed.yaml"))
config = conf.set_max_length(config, {"batches": 200})
exp.run_basic_test_with_temp_config(
config, conf.cv_examples_path("unets_tf_keras"), 1)
def test_pix2pix_facades_const() -> None:
config = conf.load_config(
conf.gan_examples_path("pix2pix_tf_keras/const.yaml"))
config = conf.set_max_length(config, {"batches": 200})
exp.run_basic_test_with_temp_config(
config, conf.gan_examples_path("pix2pix_tf_keras"), 1)
def test_bert_glue_pytorch_distributed() -> None:
config = conf.load_config(
conf.nlp_examples_path("bert_glue_pytorch/distributed.yaml"))
config = conf.set_max_length(config, {"batches": 200})
exp.run_basic_test_with_temp_config(
config, conf.nlp_examples_path("bert_glue_pytorch"), 1)
def test_gan_mnist_pytorch_const() -> None:
config = conf.load_config(
conf.gan_examples_path("gan_mnist_pytorch/const.yaml"))
config = conf.set_max_length(config, {"batches": 200})
exp.run_basic_test_with_temp_config(
config, conf.gan_examples_path("gan_mnist_pytorch"), 1)
def test_mnist_pytorch_multi_output() -> None:
config = conf.load_config(
conf.experimental_path("mnist_pytorch_multi_output/const.yaml"))
config = conf.set_max_steps(config, 2)
exp.run_basic_test_with_temp_config(
config, conf.experimental_path("mnist_pytorch_multi_output"), 1)
def test_maskrcnn_distributed_fake() -> None:
example_path = conf.fixtures_path("mmdetection")
config = conf.load_config(os.path.join(example_path, "distributed_fake_data.yaml"))
config = conf.set_max_length(config, {"batches": 200})
config = set_docker_image(config)
exp.run_basic_test_with_temp_config(config, example_path, 1)
def test_mnist_estimator_adaptive_with_data_layer() -> None:
config = conf.load_config(
conf.fixtures_path("mnist_estimator/adaptive.yaml"))
config = conf.set_tf2_image(config)
config = conf.set_shared_fs_data_layer(config)
exp.run_basic_test_with_temp_config(
config, conf.experimental_path("data_layer_mnist_estimator"), None)
def test_gaea_pytorch_const() -> None:
config = conf.load_config(
conf.nas_examples_path("gaea_pytorch/eval/const.yaml"))
config = conf.set_global_batch_size(config, 32)
config = conf.set_max_length(config, {"batches": 200})
exp.run_basic_test_with_temp_config(
config, conf.nas_examples_path("gaea_pytorch/eval"), 1)
def test_deepspeed_pipeline_parallel() -> None:
config = conf.load_config(conf.deepspeed_examples_path("pipeline_parallelism/distributed.yaml"))
config = conf.set_max_length(config, {"batches": 200})
config = conf.set_min_validation_period(config, {"batches": 100})
exp.run_basic_test_with_temp_config(
config, conf.deepspeed_examples_path("pipeline_parallelism"), 1
)
def test_word_language_lstm_const() -> None:
config = conf.load_config(conf.nlp_examples_path("word_language_model/distributed.yaml"))
config = conf.set_max_length(config, {"batches": 200})
config = config.copy()
config["hyperparameters"]["model_cls"] = "LSTM"
config["hyperparameters"]["tied"] = False
exp.run_basic_test_with_temp_config(config, conf.nlp_examples_path("word_language_model"), 1)
def test_gaea_pytorch_distributed() -> None:
config = conf.load_config(
conf.nas_examples_path("gaea_pytorch/eval/distributed_no_data_download.yaml")
)
config = conf.set_global_batch_size(config, 256)
config = conf.set_max_length(config, {"batches": 200})
exp.run_basic_test_with_temp_config(config, conf.nas_examples_path("gaea_pytorch/eval"), 1)
def test_mnist_pytorch_distributed() -> None:
config = conf.load_config(
conf.tutorials_path("mnist_pytorch/distributed.yaml"))
config = conf.set_max_length(config, {"batches": 200})
exp.run_basic_test_with_temp_config(config,
conf.tutorials_path("mnist_pytorch"),
1)
