icemelon9 commented on a change in pull request #5955:
URL: https://github.com/apache/incubator-tvm/pull/5955#discussion_r459019580
##########
File path: tests/python/relay/test_any.py
##########
@@ -816,6 +816,66 @@ 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,
+ layout, 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,
layout)
+ mod["main"] = relay.Function([data, boxes, box_indices], y)
+ data_np = np.random.uniform(size=data_shape).astype(dtype)
+ boxes_np = np.random.uniform(size=static_boxes).astype(dtype)
+ box_indices_np =
np.random.uniform(size=static_box_indices_shape).astype(indices_dtype)
+ for kind in ["debug", "vm"]:
+ ex = relay.create_executor(kind, mod=mod, ctx=tvm.cpu(), target="llvm")
+ result = ex.evaluate()(data_np, boxes_np, box_indices_np)
+ assert result.asnumpy().shape == ref_out_shape, \
+ "Shape mismatch: expect %s but got %s." % (str(ref_out_shape),
str(result.asnumpy().shape))
+
+def test_any_crop_and_resize():
+ verify_any_crop_and_resize(
+ data_shape=(1, 234, 234, 256),
+ boxes_shape=(relay.Any(), 4),
+ box_indices_shape=(relay.Any(),),
+ crop_size=(14, 14),
+ layout='NHWC',
+ static_boxes=(128, 4),
+ static_box_indices_shape=(128,),
+ ref_out_shape=(128, 14, 14, 256))
+ verify_any_crop_and_resize(
+ data_shape=(1, 256, 234, 234),
+ boxes_shape=(relay.Any(), 4),
+ box_indices_shape=(relay.Any(),),
+ crop_size=(14, 14),
+ layout='NCHW',
+ static_boxes=(128, 4),
+ static_box_indices_shape=(128,),
+ ref_out_shape=(128, 256, 14, 14)
+ )
+
+def verify_any_mirror_pad(data_shape, pad_width, static_data_shape,
ref_out_shape):
+ mod = tvm.IRModule()
+ dtype = "float32"
+ data = relay.var('data', shape=data_shape, dtype=dtype)
+ y = relay.nn.mirror_pad(data, pad_width)
+ mod["main"] = relay.Function([data], y)
+ data_np = np.random.uniform(size=static_data_shape).astype(dtype)
+ for kind in ["debug", "vm"]:
+ ex = relay.create_executor(kind, mod=mod, ctx=tvm.cpu(), target="llvm")
+ result = ex.evaluate()(data_np)
+ assert result.asnumpy().shape == ref_out_shape, \
Review comment:
use `tvm.testing.assert_allclose`.
##########
File path: tests/python/relay/test_any.py
##########
@@ -816,6 +816,66 @@ 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,
+ layout, 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,
layout)
+ mod["main"] = relay.Function([data, boxes, box_indices], y)
+ data_np = np.random.uniform(size=data_shape).astype(dtype)
+ boxes_np = np.random.uniform(size=static_boxes).astype(dtype)
+ box_indices_np =
np.random.uniform(size=static_box_indices_shape).astype(indices_dtype)
+ for kind in ["debug", "vm"]:
+ ex = relay.create_executor(kind, mod=mod, ctx=tvm.cpu(), target="llvm")
+ result = ex.evaluate()(data_np, boxes_np, box_indices_np)
+ assert result.asnumpy().shape == ref_out_shape, \
Review comment:
use `tvm.testing.assert_allclose`. it will check both the shape and value
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