llvm
/
torch-mlir
mirror of https://github.com/llvm/torch-mlir
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

Bump Onnx Version to 1.16.1 (#3515) 

This commit adds the support for new data types: uint4, and int4 and
uint8 tensor protos. Also, it moves some tests from failing to crashing.

Fixes https://github.com/llvm/torch-mlir/issues/3507

Signed-Off By: Vivek Khandelwal <vivekkhandelwal1424@gmail.com>
pull/3517/head
Vivek Khandelwal 2024-07-01 22:15:45 +05:30 committed by GitHub
parent 0e71a192d8
commit 2f231f394e
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
4 changed files with 11 additions and 6 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

8
projects/pt1/e2e_testing/xfail_sets.py
View File

@ -2572,8 +2572,6 @@ ONNX_XFAIL_SET = {
"SplitDimStaticModule_basic", "SplitDimStaticModule_basic",
"SqrtIntConstantModule_basic", "SqrtIntConstantModule_basic",
"SqrtIntModule_basic", "SqrtIntModule_basic",
"StdCorrectionEmptyDimModule_basic",
"StdDimEmptyDimModule_basic",
"SubFloatModule_basic", "SubFloatModule_basic",
"SubIntModule_basic", "SubIntModule_basic",
"TanhBackward_basic", "TanhBackward_basic",
@ -2627,8 +2625,6 @@ ONNX_XFAIL_SET = {
"UpSampleNearest2dDynamicFactor_basic", "UpSampleNearest2dDynamicFactor_basic",
"UpSampleNearest2dStaticFactor_basic", "UpSampleNearest2dStaticFactor_basic",
"UpSampleNearest2d_basic", "UpSampleNearest2d_basic",
"VarCorrectionEmptyDimModule_basic",
"VarDimEmptyDimModule_basic",
"ViewCollapseDynamicWithAtenSizeIntModule_basic", "ViewCollapseDynamicWithAtenSizeIntModule_basic",
"ViewCollapseModule_basic", "ViewCollapseModule_basic",
"ViewDynamicExpandCollapseModule_basic", "ViewDynamicExpandCollapseModule_basic",
@ -2797,6 +2793,10 @@ ONNX_CRASHING_SET = {
# Runtime crash: mismatched size for broadcast # Runtime crash: mismatched size for broadcast
"MaxPool2dWithIndicesAllNegativeValuesModule_basic", "MaxPool2dWithIndicesAllNegativeValuesModule_basic",
"MaxPool2dWithIndicesNonDefaultPaddingModule_basic", "MaxPool2dWithIndicesNonDefaultPaddingModule_basic",
"StdDimEmptyDimModule_basic",
"StdCorrectionEmptyDimModule_basic",
"VarCorrectionEmptyDimModule_basic",
"VarDimEmptyDimModule_basic",
} }
FX_IMPORTER_TOSA_XFAIL_SET = { FX_IMPORTER_TOSA_XFAIL_SET = {

5
python/torch_mlir/extras/onnx_importer.py
View File

@ -1098,6 +1098,8 @@ ELEM_TYPE_TO_IR_TYPE_CB = {
onnx.TensorProto.DataType.FLOAT8E5M2: lambda: Float8E5M2Type.get(), onnx.TensorProto.DataType.FLOAT8E5M2: lambda: Float8E5M2Type.get(),
onnx.TensorProto.DataType.FLOAT8E5M2FNUZ: lambda: Float8E5M2FNUZType.get(), onnx.TensorProto.DataType.FLOAT8E5M2FNUZ: lambda: Float8E5M2FNUZType.get(),
onnx.TensorProto.DataType.STRING: lambda: "!torch.str", onnx.TensorProto.DataType.STRING: lambda: "!torch.str",
onnx.TensorProto.DataType.UINT4: lambda: IntegerType.get_unsigned(4),
onnx.TensorProto.DataType.INT4: lambda: IntegerType.get_signed(4),
# Ommitted: STRING, # Ommitted: STRING,
} }
@ -1134,6 +1136,9 @@ ELEM_TYPE_INLINE_TENSOR_PROTO_CB = {
), ),
signless=False, signless=False,
), ),
onnx.TensorProto.DataType.UINT8: lambda tp: DenseElementsAttr.get(
np.asarray(tp.int32_data, dtype=np.uint8).reshape(tp.dims), signless=False
),
onnx.TensorProto.DataType.INT8: lambda tp: DenseElementsAttr.get( onnx.TensorProto.DataType.INT8: lambda tp: DenseElementsAttr.get(
np.asarray(tp.int32_data, dtype=np.int8).reshape(tp.dims), signless=False np.asarray(tp.int32_data, dtype=np.int8).reshape(tp.dims), signless=False
), ),

2
python/torch_mlir/tools/import_onnx/__main__.py
View File

@ -84,7 +84,7 @@ def load_onnx_model(args: argparse.Namespace) -> onnx.ModelProto:
raw_model = onnx.load(args.input_file) raw_model = onnx.load(args.input_file)
else: else:
raw_model = onnx.load(args.input_file, load_external_data=False) raw_model = onnx.load(args.input_file, load_external_data=False)
onnx.load_external_data_for_model(raw_model, args.data_dir) onnx.load_external_data_for_model(raw_model, str(args.data_dir))
if args.opset_version: if args.opset_version:
raw_model = onnx.version_converter.convert_version( raw_model = onnx.version_converter.convert_version(

2
test-requirements.txt
View File

@ -1,5 +1,5 @@
pillow pillow
dill dill
multiprocess multiprocess
onnx==1.15.0 onnx==1.16.1
mpmath==1.3.0 mpmath==1.3.0