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working subgraphs in workflow (#1842)
* working subgraphs in workflow * add in subgraph transform to compare * change to subworkflows in workflow instead of subgraph4 * remove reset_index calls in asserts of test
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# | ||
# Copyright (c) 2023, NVIDIA CORPORATION. | ||
# | ||
# Licensed under the Apache License, Version 2.0 (the "License"); | ||
# you may not use this file except in compliance with the License. | ||
# You may obtain a copy of the License at | ||
# | ||
# http://www.apache.org/licenses/LICENSE-2.0 | ||
# | ||
# Unless required by applicable law or agreed to in writing, software | ||
# distributed under the License is distributed on an "AS IS" BASIS, | ||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
# See the License for the specific language governing permissions and | ||
# limitations under the License. | ||
# | ||
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import os | ||
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import numpy as np | ||
import pytest | ||
from pandas.api.types import is_integer_dtype | ||
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from merlin.core.utils import set_dask_client | ||
from merlin.dag.ops.subgraph import Subgraph | ||
from nvtabular import Workflow, ops | ||
from tests.conftest import assert_eq | ||
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@pytest.mark.parametrize("gpu_memory_frac", [0.01, 0.1]) | ||
@pytest.mark.parametrize("engine", ["parquet", "csv", "csv-no-header"]) | ||
@pytest.mark.parametrize("dump", [True, False]) | ||
@pytest.mark.parametrize("replace", [True, False]) | ||
def test_workflow_subgraphs(tmpdir, client, df, dataset, gpu_memory_frac, engine, dump, replace): | ||
cat_names = ["name-cat", "name-string"] if engine == "parquet" else ["name-string"] | ||
cont_names = ["x", "y", "id"] | ||
label_name = ["label"] | ||
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norms = ops.Normalize() | ||
cat_features = cat_names >> ops.Categorify() | ||
if replace: | ||
cont_features = cont_names >> ops.FillMissing() >> ops.LogOp >> norms | ||
else: | ||
fillmissing_logop = ( | ||
cont_names | ||
>> ops.FillMissing() | ||
>> ops.LogOp | ||
>> ops.Rename(postfix="_FillMissing_1_LogOp_1") | ||
) | ||
cont_features = cont_names + fillmissing_logop >> norms | ||
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set_dask_client(client=client) | ||
wkflow_ops = Subgraph("cat_graph", cat_features) + Subgraph("cont_graph", cont_features) | ||
workflow = Workflow(wkflow_ops + label_name) | ||
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workflow.fit(dataset) | ||
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if dump: | ||
workflow_dir = os.path.join(tmpdir, "workflow") | ||
workflow.save(workflow_dir) | ||
workflow = None | ||
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workflow = Workflow.load(workflow_dir) | ||
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def get_norms(tar): | ||
ser_median = tar.dropna().quantile(0.5, interpolation="linear") | ||
gdf = tar.fillna(ser_median) | ||
gdf = np.log(gdf + 1) | ||
return gdf | ||
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concat_ops = "_FillMissing_1_LogOp_1" | ||
if replace: | ||
concat_ops = "" | ||
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df_pp = workflow.transform(dataset).to_ddf().compute() | ||
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if engine == "parquet": | ||
assert is_integer_dtype(df_pp["name-cat"].dtype) | ||
assert is_integer_dtype(df_pp["name-string"].dtype) | ||
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subgraph_cat = workflow.get_subworkflow("cat_graph") | ||
subgraph_cont = workflow.get_subworkflow("cont_graph") | ||
assert isinstance(subgraph_cat, Workflow) | ||
assert isinstance(subgraph_cont, Workflow) | ||
# will not be the same nodes of saved out and loaded back | ||
if not dump: | ||
assert subgraph_cat.output_node == cat_features | ||
assert subgraph_cont.output_node == cont_features | ||
# check failure path works as expected | ||
with pytest.raises(ValueError) as exc: | ||
workflow.get_subworkflow("not_exist") | ||
assert "No subgraph named" in str(exc.value) | ||
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# test transform results from subgraph | ||
sub_cat_df = subgraph_cat.transform(dataset).to_ddf().compute() | ||
assert_eq(sub_cat_df, df_pp[cat_names]) | ||
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cont_names = [name + concat_ops for name in cont_names] | ||
sub_cont_df = subgraph_cont.transform(dataset).to_ddf().compute() | ||
assert_eq(sub_cont_df[cont_names], df_pp[cont_names]) |