Update test config to get postmerge tests running correctly (#359)

* Add OPAL_PREFIX to passenv in test-gpu-postmerge

This is required for horovod init to work correctly

* Move merlin-models dependency to test.txt

* Trigger postmerge on pull_request to check they run sucessfully

* Skip test_transformer_model if tritonserver not found

* Use match_representations for example input matching input schema

* Update formatting of conversions.py

* Add noqa to match_representations import

* Try setting LD_LIBRARY_PATH for pytorch tests

* Move LD_LIBRARY_PATH config to setenv

* Add OPAL_PREFIX passenv to test-gpu tox environment

* Restore tensorflow constraint on test-cpu.txt

* Remove pull_request trigger from postmerge workflows

Author: oliverholworthy

merlin/systems/triton/conversions.py

@@ -25,6 +25,7 @@
 # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
 import itertools
+from functools import singledispatch
 from typing import Any, Dict, List
 
 import numpy as np
@@ -33,6 +34,7 @@
 import merlin.dtypes as md
 from merlin.core.compat import cudf
 from merlin.core.compat import cupy as cp
+from merlin.core.compat.torch import torch
 from merlin.core.dispatch import build_cudf_list_column, is_list_dtype
 from merlin.dag import Supports
 from merlin.schema import Schema
@@ -135,19 +137,24 @@ def _from_values_offsets(values, offsets, shape):
     return values.reshape(new_shape)
 
 
-def _to_values_offsets(array):
+@singledispatch
+def _to_values_offsets(values):
     """Convert array to values/offsets representation
 
     Parameters
     ----------
-    array : numpy.ndarray or cupy.ndarray
-        Array to convert
+    values : array or tensor
+        Array or tensor to convert
 
     Returns
     -------
     values, offsets
         Tuple of values and offsets
     """
+    raise NotImplementedError(f"_to_values_offsets not implemented for {type(values)}")
+
+
+def _to_values_offsets_array(array):
     num_rows = array.shape[0]
     row_lengths = [array.shape[1]] * num_rows
     offsets = [0] + list(itertools.accumulate(row_lengths))
@@ -157,6 +164,30 @@ def _to_values_offsets(array):
     return values, offsets
 
 
+@_to_values_offsets.register(np.ndarray)
+def _(array):
+    return _to_values_offsets_array(array)
+
+
+if cp:
+
+    @_to_values_offsets.register(cp.ndarray)
+    def _(array):
+        return _to_values_offsets_array(array)
+
+
+if torch:
+
+    @_to_values_offsets.register(torch.Tensor)
+    def _(tensor):
+        num_rows = tensor.shape[0]
+        row_lengths = [tensor.shape[1]] * num_rows
+        offsets = [0] + list(itertools.accumulate(row_lengths))
+        offsets = torch.tensor(offsets, dtype=torch.int32, device=tensor.device)
+        values = tensor.reshape(-1, *tensor.shape[2:])
+        return values, offsets
+
+
 def triton_request_to_tensor_table(request, schema):
     """
     Turns a Triton request into a TensorTable by extracting individual tensors

requirements/test-cpu.txt

@@ -1,6 +1,5 @@
 -r test.txt
 
-merlin-models>=0.6.0
 faiss-cpu==1.7.2
 tensorflow<=2.9.0
 treelite==2.4.0

requirements/test-gpu.txt

@@ -1,4 +1,3 @@
 -r test.txt
 
-tensorflow
 faiss-gpu==1.7.2

requirements/test.txt

@@ -18,5 +18,7 @@ feast==0.31
 xgboost==1.6.2
 implicit==0.6.0
 
+merlin-models[tensorflow,pytorch,transformers]@git+https://github.com/NVIDIA-Merlin/models.git
+
 # TODO: do we need more of these?
 # https://github.com/NVIDIA-Merlin/Merlin/blob/a1cc48fe23c4dfc627423168436f26ef7e028204/ci/dockerfile.ci#L13-L18

tests/integration/t4r/test_pytorch_backend.py

@@ -14,6 +14,8 @@
 # limitations under the License.
 #
 
+import shutil
+
 import pytest
 
 np = pytest.importorskip("numpy")
@@ -30,9 +32,13 @@
 from merlin.core.dispatch import make_df  # noqa
 from merlin.systems.dag import Ensemble  # noqa
 from merlin.systems.dag.ops.pytorch import PredictPyTorch  # noqa
+from merlin.systems.triton.conversions import match_representations  # noqa
 from merlin.systems.triton.utils import run_ensemble_on_tritonserver  # noqa
 
+TRITON_SERVER_PATH = shutil.which("tritonserver")
+
 
+@pytest.mark.skipif(not TRITON_SERVER_PATH, reason="triton server not found")
 def test_serve_t4r_with_torchscript(tmpdir):
     # ===========================================
     # Generate training data
@@ -69,11 +75,12 @@ def test_serve_t4r_with_torchscript(tmpdir):
 
     model.eval()
 
-    traced_model = torch.jit.trace(model, torch_yoochoose_like, strict=True)
+    example_inputs = match_representations(model.input_schema, torch_yoochoose_like)
+    traced_model = torch.jit.trace(model, example_inputs, strict=True)
     assert isinstance(traced_model, torch.jit.TopLevelTracedModule)
     assert torch.allclose(
-        model(torch_yoochoose_like),
-        traced_model(torch_yoochoose_like),
+        model(example_inputs),
+        traced_model(example_inputs),
     )
 
     # ===========================================

tests/integration/tf/test_transformer_model.py

@@ -14,6 +14,8 @@
 # limitations under the License.
 #
 
+import shutil
+
 import pytest
 
 tf = pytest.importorskip("tensorflow")
@@ -31,7 +33,10 @@
 from merlin.systems.dag.ops.tensorflow import PredictTensorflow  # noqa
 from merlin.systems.triton.utils import run_ensemble_on_tritonserver  # noqa
 
+TRITON_SERVER_PATH = shutil.which("tritonserver")
+
 
+@pytest.mark.skipif(not TRITON_SERVER_PATH, reason="triton server not found")
 def test_serve_tf_session_based_with_libtensorflow(tmpdir):
 
     # ===========================================

tox.ini

@@ -47,6 +47,8 @@ sitepackages=true
 ; need to add some back.
 setenv = 
     TF_GPU_ALLOCATOR=cuda_malloc_async
+passenv =
+    OPAL_PREFIX
 deps =
     -rrequirements/test-gpu.txt
     pytest
@@ -71,6 +73,9 @@ sitepackages=true
 ; need to add some back.
 setenv = 
     TF_GPU_ALLOCATOR=cuda_malloc_async
+    LD_LIBRARY_PATH=/opt/tritonserver/backends/pytorch
+passenv =
+    OPAL_PREFIX
 deps =
     pytest
     pytest-cov