[executorch][nvidia][tensorrt][20/n] Add bmm converter

backends/nvidia/tensorrt/converters/__init__.py

@@ -1,3 +1,3 @@
 # Copyright (c) Meta Platforms, Inc. and affiliates.
 # All rights reserved.
 #
@@ -11,6 +11,7 @@
 from executorch.backends.nvidia.tensorrt.converters import add  # noqa: F401
 from executorch.backends.nvidia.tensorrt.converters import addmm  # noqa: F401
 from executorch.backends.nvidia.tensorrt.converters import batch_norm  # noqa: F401
+from executorch.backends.nvidia.tensorrt.converters import bmm  # noqa: F401
 from executorch.backends.nvidia.tensorrt.converters import clamp  # noqa: F401
 from executorch.backends.nvidia.tensorrt.converters import concat  # noqa: F401
 from executorch.backends.nvidia.tensorrt.converters import conv2d  # noqa: F401

backends/nvidia/tensorrt/converters/bmm.py

@@ -0,0 +1,45 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+
+"""Converter for batch matrix multiplication operations."""
+
+from typing import Any, Dict, Optional
+
+import tensorrt as trt
+import torch
+from executorch.backends.nvidia.tensorrt.converter_registry import converter
+from executorch.backends.nvidia.tensorrt.converter_utils import set_layer_name
+
+
+@converter("aten.bmm.default")
+def convert_bmm(
+    node: torch.fx.Node,
+    network: trt.INetworkDefinition,
+    input_map: Dict[torch.fx.Node, Any],
+    edge_program: Optional[Any] = None,
+) -> trt.ITensor:
+    """Convert aten.bmm.default to TensorRT MatrixMultiply.
+
+    Performs batch matrix multiplication of two 3D tensors (B, M, K) @ (B, K, N) -> (B, M, N).
+    TensorRT's IMatrixMultiplyLayer supports batch matrix multiplication natively.
+    """
+    lhs_arg = node.args[0]
+    rhs_arg = node.args[1]
+
+    if lhs_arg not in input_map:
+        raise ValueError(f"Input node '{lhs_arg.name}' not found in input_map for bmm")
+    if rhs_arg not in input_map:
+        raise ValueError(f"Input node '{rhs_arg.name}' not found in input_map for bmm")
+
+    lhs = input_map[lhs_arg]
+    rhs = input_map[rhs_arg]
+
+    layer = network.add_matrix_multiply(
+        lhs, trt.MatrixOperation.NONE, rhs, trt.MatrixOperation.NONE
+    )
+    set_layer_name(layer, node, "bmm")
+
+    return layer.get_output(0)

backends/nvidia/tensorrt/converters/targets.bzl

@@ -15,6 +15,7 @@ def define_common_targets():
             "add.py",
             "addmm.py",
             "batch_norm.py",
+            "bmm.py",
             "clamp.py",
             "concat.py",
             "conv2d.py",

examples/nvidia/tensorrt/export.py

@@ -1,3 +1,3 @@
 # Copyright (c) Meta Platforms, Inc. and affiliates.
 # All rights reserved.
 #
@@ -38,6 +38,10 @@
     "conv1d",
     "dl3",
     "edsr",
+    # "efficient_sam",  # TODO: diff ~41 — likely bicubic interpolation decomposition or ConvTranspose2d issue
+    "emformer_join",
+    # "emformer_predict",  # TODO: passes 1/3 seeds — precision sensitive with randomized inputs
+    "emformer_transcribe",
     "ic3",
     "linear",
     "mul",
@@ -126,6 +130,7 @@
 
     et_module = _load_for_executorch_from_buffer(pte_bytes)
 
+
     for seed in _TEST_SEEDS:
         inputs = _randomise_inputs(example_inputs, seed)
 

examples/nvidia/tensorrt/tests/test_export.py

@@ -1,3 +1,3 @@
 # Copyright (c) Meta Platforms, Inc. and affiliates.
 # All rights reserved.
 #
@@ -16,7 +16,7 @@
 import shutil
 import unittest
 
 import torch
 
 logger = logging.getLogger(__name__)
 logging.basicConfig(level=logging.INFO)
@@ -40,11 +40,7 @@
     for env_var, filename in _WEIGHT_ENV_VARS.items():
         src = os.environ.get(env_var)
         if src and os.path.isfile(src):
-            # dog.jpg goes to CWD (mv2 model downloads it there)
-            if filename == "dog.jpg":
-                dst = os.path.join(os.getcwd(), filename)
-            else:
-                dst = os.path.join(cache_dir, filename)
+            dst = os.path.join(cache_dir, filename)
             if not os.path.exists(dst):
                 shutil.copy2(src, dst)
                 logger.info(f"Cached {filename} from {src}")
@@ -87,7 +83,7 @@
         from executorch.examples.models import MODEL_NAME_TO_MODEL
         from executorch.examples.models.model_factory import EagerModelFactory
         from executorch.exir import to_edge_transform_and_lower
         import torch
         from torch.export import export
         model, example_inputs, _, _ = EagerModelFactory.create_model(*MODEL_NAME_TO_MODEL["add"])
         model = model.eval()
@@ -121,3 +117,15 @@
 
     def test_sdpa(self) -> None:
         _export_and_verify("sdpa")
+
+    def test_emformer_join(self) -> None:
+        _export_and_verify("emformer_join")
+
+    def test_softmax(self) -> None:
+        _export_and_verify("softmax")
+
+    def test_mv3(self) -> None:
+        _export_and_verify("mv3")
+
+    def test_ic3(self) -> None:
+        _export_and_verify("ic3")