add dilations field to onnx importer

blacking files

black file

python/tvm/relay/frontend/onnx.py

@@ -19,6 +19,7 @@
 """ONNX: Open Neural Network Exchange frontend for Relay."""
 import copy
 import warnings
+
 import numpy as np
 import tvm
 from tvm.ir import IRModule
@@ -28,16 +29,23 @@
 from .. import analysis
 from .. import expr as _expr
 from .. import function as _function
+from .. import loops as _loops
 from .. import op as _op
 from .. import qnn as _qnn
-from .. import vision as _vision
-from .. import loops as _loops
 from .. import ty as _ty
-
-from .common import AttrCvt, Renamer
-from .common import get_relay_op, new_var, infer_shape, infer_channels, infer_value, fold_constant
-from .common import infer_type, get_name
-
+from .. import vision as _vision
+from .common import (
+    AttrCvt,
+    Renamer,
+    fold_constant,
+    get_name,
+    get_relay_op,
+    infer_channels,
+    infer_shape,
+    infer_type,
+    infer_value,
+    new_var,
+)
 
 __all__ = ["from_onnx"]
 
@@ -312,8 +320,12 @@ def _impl_v1(cls, inputs, attr, params):
 
         return AttrCvt(
             op_name=dimension_picker(cls.name),
-            transforms={"kernel_shape": "pool_size", "pads": ("padding", 0)},
-            ignores=["dilations", "storage_order"],
+            transforms={
+                "kernel_shape": "pool_size",
+                "pads": ("padding", 0),
+                "dilations": ("dilation", 1),
+            },
+            ignores=["storage_order"],
             custom_check=dimension_constraint(),
         )([data], attr, params)
 

tests/python/frontend/onnx/test_forward.py

@@ -15,17 +15,18 @@
 # specific language governing permissions and limitations
 # under the License.
 import numpy as np
-import onnx
-from onnx import helper, TensorProto, mapping, numpy_helper
+import pytest
+import scipy
 import torch
 import torchvision
-import pytest
-import tvm.topi.testing
 import tvm
+import tvm.testing
+import tvm.topi.testing
 from tvm import relay
 from tvm.contrib import graph_executor
-import scipy
-import tvm.testing
+
+import onnx
+from onnx import TensorProto, helper, mapping, numpy_helper
 
 
 def get_input_data_shape_dict(graph_def, input_data):
@@ -2696,7 +2697,7 @@ def repeat(N, D):
 
 @tvm.testing.uses_gpu
 def test_unsqueeze_constant():
-    from torch.nn import Linear, Sequential, Module
+    from torch.nn import Linear, Module, Sequential
 
     class Flatten(Module):
         def forward(self, input):
@@ -4212,7 +4213,6 @@ def verify_cumsum(indata, axis, exclusive=0, reverse=0, type="float32"):
     "test_isinf_negative/",
     "test_isinf_positive/",
     "test_matmulinteger/",
-    "test_maxpool_2d_dilations/",
     "test_maxpool_2d_same_lower/",
     "test_maxpool_2d_same_upper/",
     "test_maxpool_with_argmax_2d_precomputed_pads/",