Convert ONNX models during import and run import in parallel.

iree_tests/.gitignore

@@ -1,3 +1,7 @@
+# TODO(scotttodd): compile into a build/temp dir instead of the source dir
 *.vmfb
-# TODO(scotttodd): compile into a build dir instead of the source dir
+# TODO(scotttodd): convert into a build/temp dir instead of the source dir
+*.onnx
+
+# Leftovers from an older iteration of compile/run test scripts.
 config_*.txt

iree_tests/configs/config_cpu_llvm_sync.json

@@ -11,8 +11,7 @@
     "test_dequantizelinear",
     "test_slice_default_axes",
   ],
-  "skip_run_tests": [
-  ],
+  "skip_run_tests": [],
   "expected_compile_failures": [
     "test_acos_example",
     "test_acos",
@@ -134,7 +133,6 @@
     "test_castlike_FLOAT8E5M2FNUZ_to_FLOAT",
     "test_castlike_STRING_to_FLOAT_expanded",
     "test_castlike_STRING_to_FLOAT",
-    "test_celu_expanded",
     "test_celu",
     "test_center_crop_pad_crop_and_pad_expanded",
     "test_center_crop_pad_crop_and_pad",
@@ -148,9 +146,7 @@
     "test_center_crop_pad_crop",
     "test_center_crop_pad_pad_expanded",
     "test_center_crop_pad_pad",
-    "test_clip_default_inbounds_expanded",
     "test_clip_default_inbounds",
-    "test_clip_default_int8_inbounds_expanded",
     "test_clip_default_int8_inbounds",
     "test_clip_default_int8_max",
     "test_clip_default_max",
@@ -231,8 +227,6 @@
     "test_gemm_default_no_bias",
     "test_globalmaxpool_precomputed",
     "test_globalmaxpool",
-    "test_greater_bcast",
-    "test_greater",
     "test_gridsample_aligncorners_true",
     "test_gridsample_bicubic_align_corners_0_additional_1",
     "test_gridsample_bicubic_align_corners_1_additional_1",
@@ -371,7 +365,6 @@
     "test_mod_uint8",
     "test_momentum_multiple",
     "test_momentum",
-    "test_mvn_expanded",
     "test_mvn",
     "test_nesterov_momentum",
     "test_nllloss_NC",
@@ -711,13 +704,6 @@
     "test_slice_negative_axes",
     "test_slice_start_out_of_bounds",
     "test_slice",
-    "test_softmax_axis_0_expanded",
-    "test_softmax_axis_1_expanded",
-    "test_softmax_axis_2_expanded",
-    "test_softmax_default_axis_expanded",
-    "test_softmax_example_expanded",
-    "test_softmax_large_number_expanded",
-    "test_softmax_negative_axis_expanded",
     "test_softplus_example",
     "test_softplus",
     "test_softsign_example",

iree_tests/configs/config_gpu_vulkan.json

@@ -10,7 +10,6 @@
     // Timeouts?
     "test_dequantizelinear",
     "test_slice_default_axes",
-    "test_sum_example",
   ],
   "skip_run_tests": [],
   "expected_compile_failures": [
@@ -134,7 +133,6 @@
     "test_castlike_FLOAT8E5M2FNUZ_to_FLOAT",
     "test_castlike_STRING_to_FLOAT_expanded",
     "test_castlike_STRING_to_FLOAT",
-    "test_celu_expanded",
     "test_celu",
     "test_center_crop_pad_crop_and_pad_expanded",
     "test_center_crop_pad_crop_and_pad",
@@ -148,9 +146,7 @@
     "test_center_crop_pad_crop",
     "test_center_crop_pad_pad_expanded",
     "test_center_crop_pad_pad",
-    "test_clip_default_inbounds_expanded",
     "test_clip_default_inbounds",
-    "test_clip_default_int8_inbounds_expanded",
     "test_clip_default_int8_inbounds",
     "test_clip_default_int8_max",
     "test_clip_default_max",
@@ -231,8 +227,6 @@
     "test_gemm_default_no_bias",
     "test_globalmaxpool_precomputed",
     "test_globalmaxpool",
-    "test_greater_bcast",
-    "test_greater",
     "test_gridsample_aligncorners_true",
     "test_gridsample_bicubic_align_corners_0_additional_1",
     "test_gridsample_bicubic_align_corners_1_additional_1",
@@ -371,7 +365,6 @@
     "test_mod_uint8",
     "test_momentum_multiple",
     "test_momentum",
-    "test_mvn_expanded",
     "test_mvn",
     "test_nesterov_momentum",
     "test_nllloss_NC",
@@ -711,13 +704,6 @@
     "test_slice_negative_axes",
     "test_slice_start_out_of_bounds",
     "test_slice",
-    "test_softmax_axis_0_expanded",
-    "test_softmax_axis_1_expanded",
-    "test_softmax_axis_2_expanded",
-    "test_softmax_default_axis_expanded",
-    "test_softmax_example_expanded",
-    "test_softmax_large_number_expanded",
-    "test_softmax_negative_axis_expanded",
     "test_softplus_example",
     "test_softplus",
     "test_softsign_example",
@@ -941,6 +927,7 @@
     "test_castlike_FLOAT_to_FLOAT16",
     "test_castlike_FLOAT16_to_FLOAT_expanded",
     "test_castlike_FLOAT16_to_FLOAT",
+    "test_clip_default_int8_inbounds_expanded",
     "test_isinf_float16",
     "test_isnan_float16",
     "test_max_float16",

iree_tests/onnx/import_tests.py

@@ -4,9 +4,11 @@
 # See https://llvm.org/LICENSE.txt for license information.
 # SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
 
+import argparse
 import onnx
+from multiprocessing import Pool
 from pathlib import Path
-from onnx import numpy_helper
+from onnx import numpy_helper, version_converter
 import shutil
 import subprocess
 import numpy as np
@@ -20,6 +22,9 @@
 ONNX_REPO_GENERATED_TESTS_ROOT = ONNX_REPO_ROOT / "onnx/backend/test/data"
 NODE_TESTS_ROOT = ONNX_REPO_GENERATED_TESTS_ROOT / "node"
 
+# Convert test cases to at least this version using The ONNX Version Converter.
+ONNX_CONVERTER_OUTPUT_MIN_VERSION = 17
+
 # Write imported files to our own 'generated' folder.
 GENERATED_FILES_OUTPUT_ROOT = REPO_ROOT / "iree_tests/onnx/node/generated"
 
@@ -48,6 +53,16 @@ def convert_io_proto(proto_filename, type_proto):
             return None
 
 
+def import_onnx_files_with_cleanup(test_dir_path):
+    test_name = test_dir_path.name
+    imported_dir_path = Path(GENERATED_FILES_OUTPUT_ROOT) / test_name
+    result = import_onnx_files(test_dir_path, imported_dir_path)
+    if not result:
+        # Note: could comment this out to keep partially imported directories.
+        shutil.rmtree(imported_dir_path)
+    return (test_name, result)
+
+
 def import_onnx_files(test_dir_path, imported_dir_path):
     # This imports one 'test_[name]' subfolder from this:
     #
@@ -71,15 +86,32 @@ def import_onnx_files(test_dir_path, imported_dir_path):
     test_data_flagfile_path = imported_dir_path / "test_data_flags.txt"
     test_data_flagfile_lines = []
 
-    # Import model.onnx to model.mlir.
-    # TODO(scotttodd): copy the .onnx file into the generated folder? Useful for reproducing
-    #                  could also add a symlink or other files with info
-    #                  e.g. importer tool / version / flags used, reproducer command
-    onnx_model_path = test_dir_path / "model.onnx"
+    # Convert model.onnx up to ONNX_CONVERTER_OUTPUT_MIN_VERSION if needed.
+    # TODO(scotttodd): stamp some info e.g. importer tool / version / flags used
+    original_model_path = test_dir_path / "model.onnx"
+    converted_model_path = imported_dir_path / "model.onnx"
+
+    original_model = onnx.load_model(original_model_path)
+    original_version = original_model.opset_import[0].version
+    if original_version < ONNX_CONVERTER_OUTPUT_MIN_VERSION:
+        try:
+            converted_model = version_converter.convert_version(
+                original_model, ONNX_CONVERTER_OUTPUT_MIN_VERSION
+            )
+            onnx.save(converted_model, converted_model_path)
+        except:
+            # Conversion failed. Do our best with the original file.
+            # print(f"WARNING: ONNX conversion failed for {test_dir_path.name}")
+            shutil.copy(original_model_path, converted_model_path)
+    else:
+        # No conversion needed.
+        shutil.copy(original_model_path, converted_model_path)
+
+    # Import converted model.onnx to model.mlir.
     imported_model_path = imported_dir_path / "model.mlir"
     exec_args = [
         "iree-import-onnx",
-        str(onnx_model_path),
+        str(converted_model_path),
         "-o",
         str(imported_model_path),
     ]
@@ -101,7 +133,7 @@ def import_onnx_files(test_dir_path, imported_dir_path):
     test_data_dir = test_data_dirs[0]
     test_inputs = list(test_data_dir.glob("input_*.pb"))
     test_outputs = list(test_data_dir.glob("output_*.pb"))
-    model = onnx.load(onnx_model_path)
+    model = onnx.load(converted_model_path)
     for i in range(len(test_inputs)):
         test_input = test_inputs[i]
         t = convert_io_proto(test_input, model.graph.input[i].type)
@@ -126,6 +158,16 @@ def import_onnx_files(test_dir_path, imported_dir_path):
 
 
 if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="ONNX test case importer.")
+    parser.add_argument(
+        "-j",
+        "--jobs",
+        type=int,
+        default=8,
+        help="Number of parallel processes to use when importing test cases",
+    )
+    args = parser.parse_args()
+
     test_dir_paths = find_onnx_tests(NODE_TESTS_ROOT)
 
     # TODO(scotttodd): add flag to not clear output dir?
@@ -134,27 +176,16 @@ def import_onnx_files(test_dir_path, imported_dir_path):
     GENERATED_FILES_OUTPUT_ROOT.mkdir(parents=True)
 
     print(f"Importing tests in '{NODE_TESTS_ROOT}'")
-
     print("******************************************************************")
     passed_imports = []
     failed_imports = []
-    # TODO(scotttodd): parallelize this (or move into a test runner like pytest)
-    for i in range(len(test_dir_paths)):
-        test_dir_path = test_dir_paths[i]
-        test_name = test_dir_path.name
-
-        current_number = str(i).rjust(4, "0")
-        progress_str = f"[{current_number}/{len(test_dir_paths)}]"
-        print(f"{progress_str}: Importing {test_name}")
-
-        imported_dir_path = Path(GENERATED_FILES_OUTPUT_ROOT) / test_name
-        result = import_onnx_files(test_dir_path, imported_dir_path)
-        if result:
-            passed_imports.append(test_name)
-        else:
-            failed_imports.append(test_name)
-            # Note: could comment this out to keep partially imported directories.
-            shutil.rmtree(imported_dir_path)
+    with Pool(args.jobs) as pool:
+        results = pool.imap_unordered(import_onnx_files_with_cleanup, test_dir_paths)
+        for result in results:
+            if result[1]:
+                passed_imports.append(result[0])
+            else:
+                failed_imports.append(result[0])
     print("******************************************************************")
 
     passed_imports.sort()

iree_tests/onnx/node/generated/test_abs/model.mlir

@@ -1,5 +1,5 @@
 module {
-  func.func @test_abs(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  func.func @test_abs(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
     %none = torch.constant.none
     %0 = torch.operator "onnx.Abs"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> 
     return %0 : !torch.vtensor<[3,4,5],f32>

iree_tests/onnx/node/generated/test_acos/model.mlir

@@ -1,5 +1,5 @@
 module {
-  func.func @test_acos(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  func.func @test_acos(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
     %none = torch.constant.none
     %0 = torch.operator "onnx.Acos"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> 
     return %0 : !torch.vtensor<[3,4,5],f32>

iree_tests/onnx/node/generated/test_acos_example/model.mlir

@@ -1,5 +1,5 @@
 module {
-  func.func @test_acos_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  func.func @test_acos_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
     %none = torch.constant.none
     %0 = torch.operator "onnx.Acos"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> 
     return %0 : !torch.vtensor<[3],f32>

iree_tests/onnx/node/generated/test_acosh/model.mlir

@@ -1,5 +1,5 @@
 module {
-  func.func @test_acosh(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 4 : si64, torch.onnx_meta.opset_version = 9 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  func.func @test_acosh(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 4 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
     %none = torch.constant.none
     %0 = torch.operator "onnx.Acosh"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> 
     return %0 : !torch.vtensor<[3,4,5],f32>

iree_tests/onnx/node/generated/test_acosh_example/model.mlir

@@ -1,5 +1,5 @@
 module {
-  func.func @test_acosh_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 4 : si64, torch.onnx_meta.opset_version = 9 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  func.func @test_acosh_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 4 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
     %none = torch.constant.none
     %0 = torch.operator "onnx.Acosh"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> 
     return %0 : !torch.vtensor<[3],f32>

iree_tests/onnx/node/generated/test_add/model.mlir

@@ -1,5 +1,5 @@
 module {
-  func.func @test_add(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  func.func @test_add(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
     %none = torch.constant.none
     %0 = torch.operator "onnx.Add"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> 
     return %0 : !torch.vtensor<[3,4,5],f32>

iree_tests/onnx/node/generated/test_add_bcast/model.mlir

@@ -1,5 +1,5 @@
 module {
-  func.func @test_add_bcast(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  func.func @test_add_bcast(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
     %none = torch.constant.none
     %0 = torch.operator "onnx.Add"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],f32> 
     return %0 : !torch.vtensor<[3,4,5],f32>

iree_tests/onnx/node/generated/test_add_uint8/model.mlir

@@ -1,5 +1,5 @@
 module {
-  func.func @test_add_uint8(%arg0: !torch.vtensor<[3,4,5],ui8>, %arg1: !torch.vtensor<[3,4,5],ui8>) -> !torch.vtensor<[3,4,5],ui8> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  func.func @test_add_uint8(%arg0: !torch.vtensor<[3,4,5],ui8>, %arg1: !torch.vtensor<[3,4,5],ui8>) -> !torch.vtensor<[3,4,5],ui8> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
     %none = torch.constant.none
     %0 = torch.operator "onnx.Add"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],ui8>, !torch.vtensor<[3,4,5],ui8>) -> !torch.vtensor<[3,4,5],ui8> 
     return %0 : !torch.vtensor<[3,4,5],ui8>

iree_tests/onnx/node/generated/test_and2d/model.mlir

@@ -1,5 +1,5 @@
 module {
-  func.func @test_and2d(%arg0: !torch.vtensor<[3,4],i1>, %arg1: !torch.vtensor<[3,4],i1>) -> !torch.vtensor<[3,4],i1> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  func.func @test_and2d(%arg0: !torch.vtensor<[3,4],i1>, %arg1: !torch.vtensor<[3,4],i1>) -> !torch.vtensor<[3,4],i1> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
     %none = torch.constant.none
     %0 = torch.operator "onnx.And"(%arg0, %arg1) : (!torch.vtensor<[3,4],i1>, !torch.vtensor<[3,4],i1>) -> !torch.vtensor<[3,4],i1> 
     return %0 : !torch.vtensor<[3,4],i1>

iree_tests/onnx/node/generated/test_and3d/model.mlir

@@ -1,5 +1,5 @@
 module {
-  func.func @test_and3d(%arg0: !torch.vtensor<[3,4,5],i1>, %arg1: !torch.vtensor<[3,4,5],i1>) -> !torch.vtensor<[3,4,5],i1> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  func.func @test_and3d(%arg0: !torch.vtensor<[3,4,5],i1>, %arg1: !torch.vtensor<[3,4,5],i1>) -> !torch.vtensor<[3,4,5],i1> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
     %none = torch.constant.none
     %0 = torch.operator "onnx.And"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],i1>) -> !torch.vtensor<[3,4,5],i1> 
     return %0 : !torch.vtensor<[3,4,5],i1>

iree_tests/onnx/node/generated/test_and4d/model.mlir

@@ -1,5 +1,5 @@
 module {
-  func.func @test_and4d(%arg0: !torch.vtensor<[3,4,5,6],i1>, %arg1: !torch.vtensor<[3,4,5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  func.func @test_and4d(%arg0: !torch.vtensor<[3,4,5,6],i1>, %arg1: !torch.vtensor<[3,4,5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
     %none = torch.constant.none
     %0 = torch.operator "onnx.And"(%arg0, %arg1) : (!torch.vtensor<[3,4,5,6],i1>, !torch.vtensor<[3,4,5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> 
     return %0 : !torch.vtensor<[3,4,5,6],i1>

iree_tests/onnx/node/generated/test_and_bcast3v1d/model.mlir

@@ -1,5 +1,5 @@
 module {
-  func.func @test_and_bcast3v1d(%arg0: !torch.vtensor<[3,4,5],i1>, %arg1: !torch.vtensor<[5],i1>) -> !torch.vtensor<[3,4,5],i1> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  func.func @test_and_bcast3v1d(%arg0: !torch.vtensor<[3,4,5],i1>, %arg1: !torch.vtensor<[5],i1>) -> !torch.vtensor<[3,4,5],i1> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
     %none = torch.constant.none
     %0 = torch.operator "onnx.And"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[5],i1>) -> !torch.vtensor<[3,4,5],i1> 
     return %0 : !torch.vtensor<[3,4,5],i1>