icemelon9 commented on a change in pull request #5955:
URL: https://github.com/apache/incubator-tvm/pull/5955#discussion_r457731237
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File path: python/tvm/relay/op/image/_image.py
##########
@@ -64,6 +67,22 @@ def compute_crop_and_resize(attrs, inputs, out_type):
reg.register_injective_schedule("image.crop_and_resize")
+@script
+def _crop_and_resize_func(image_shape, boxes_shape, crop_size):
+ out = output_tensor((4,), "int64")
+ out[0] = boxes_shape[0]
+ out[1] = int64(crop_size[0])
+ out[2] = int64(crop_size[1])
+ out[3] = image_shape[3]
+
+ return out
+
[email protected]_shape_func("image.crop_and_resize", False)
+def crop_and_resize_func(attrs, inputs, _):
+ crop_size = get_const_tuple(attrs.crop_size)
Review comment:
I see. Sorry for missing the details here.
##########
File path: tests/python/relay/test_any.py
##########
@@ -816,6 +816,55 @@ def test_mixed_input_type():
assert result.asnumpy().shape == ref_out_shape, \
"Shape mismatch: expect %s but got %s." % (str(ref_out_shape),
str(result.asnumpy().shape))
+def verify_any_crop_and_resize(data_shape, boxes_shape, box_indices_shape,
crop_size,
+ static_boxes, static_box_indices_shape,
ref_out_shape):
+ mod = tvm.IRModule()
+ dtype = "float32"
+ indices_dtype = "int32"
+ data = relay.var('data', shape=data_shape, dtype=dtype)
+ boxes = relay.var('boxes', shape=boxes_shape, dtype=dtype)
+ box_indices = relay.var('box_indices', shape=box_indices_shape,
dtype=indices_dtype)
+ y = relay.image.crop_and_resize(data, boxes, box_indices, crop_size,
'NHWC')
Review comment:
Could you add test case for "NCHW" as well?
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