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Fix Categorify inference and testing #1874

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merged 8 commits into from
Apr 29, 2024
Merged

Fix Categorify inference and testing #1874

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337e904
improve Categorify inference testing
rjzamora Apr 10, 2024
a92f0b9
fix module name
rjzamora Apr 11, 2024
f091625
avoid TENSOR_TABLE
rjzamora Apr 11, 2024
f4c9de3
fix previous commit
rjzamora Apr 11, 2024
700b196
opt out of tensor-table support by default
rjzamora Apr 17, 2024
e22a836
simplify sort_values call
rjzamora Apr 17, 2024
c83d679
avoid using p2p shuffle - sorting used to be unstable
rjzamora Apr 17, 2024
f568565
Merge branch 'main' into test-categorify-inference
rnyak Apr 29, 2024
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4 changes: 2 additions & 2 deletions cpp/nvtabular/inference/categorify.cc
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Expand Up @@ -337,12 +337,12 @@ namespace nvtabular
// this operator currently only supports CPU arrays
.def_property_readonly("supports", [](py::object self)
{
py::object supports = py::module_::import("nvtabular").attr("graph").attr("base_operator").attr("Supports");
py::object supports = py::module_::import("nvtabular").attr("graph").attr("operator").attr("Supports");
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The base_operator.py file was renamed to operator.py in NVIDIA-Merlin/core#359. Therefore, this fix should be valid for >=23.08

return supports.attr("CPU_DICT_ARRAY");
})
.def_property_readonly("supported_formats", [](py::object self)
{
py::object supported = py::module_::import("nvtabular").attr("graph").attr("base_operator").attr("DataFormats");
py::object supported = py::module_::import("nvtabular").attr("graph").attr("operator").attr("DataFormats");
return supported.attr("NUMPY_DICT_ARRAY");
});
}
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13 changes: 11 additions & 2 deletions nvtabular/ops/operator.py
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Expand Up @@ -13,6 +13,15 @@
# See the License for the specific language governing permissions and
# limitations under the License.
#
from merlin.dag import BaseOperator, ColumnSelector # noqa pylint: disable=unused-import
from merlin.dag import ( # noqa pylint: disable=unused-import
BaseOperator,
ColumnSelector,
DataFormats,
)

Operator = BaseOperator

# Avoid TENSOR_TABLE by default (for now)
class Operator(BaseOperator):
@property
def supported_formats(self):
return DataFormats.PANDAS_DATAFRAME | DataFormats.CUDF_DATAFRAME
Comment on lines +26 to +27
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With NVIDIA-Merlin/systems#389 applied to systems, I was seeing inference errors in Groupby. This is because the Groupby operator calls sort_values, and sorting is not supported for merlins TensorTable abstraction.

Since I am not entirely sure which NVTabular operations are supported with TensorTable, I figured the safest fix was to assume none of the operations are supported for now. (Any thoughts on this @jperez999 ?)

In a follow-up to this PR, it probably makes sense to add GeneralOperator = BaseOperator above this. That way, any operator with known support for TensorTable could inherit from GeneralOperator instead.

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@oliverholworthy and @jperez999 do you have a chance to look at Rick's comments above? thanks.

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This should be alright. All of the operators in nvtabular were created with data frames in mind. If we ever decide to add in tensor table, we can make the change then. If this speeds up the runs I say we should do it and solves breaking issues we should execute.

5 changes: 5 additions & 0 deletions tests/unit/ops/test_categorify.py
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Expand Up @@ -734,3 +734,8 @@ def test_categorify_inference():
output_tensors = inference_op.transform(cats.input_columns, input_tensors)
for key in input_tensors:
assert output_tensors[key].dtype == np.dtype("int64")

# Check results are consistent with python code path
expect = workflow.transform(df)
got = pd.DataFrame(output_tensors)
assert_eq(expect, got)
Comment on lines +738 to +741
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This test was only.checking the data type of the result. Now it also checks if the result is correct.

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