ymwangg commented on a change in pull request #7441:
URL: https://github.com/apache/tvm/pull/7441#discussion_r579580281
##########
File path: tests/python/relay/test_op_level3.py
##########
@@ -1453,5 +1453,53 @@ def verify_scatter_nd_with_stack(data_np, indices_np,
shape, ref_res, rtol=1e-5,
verify_scatter_nd_with_stack(data, indices, shape, out)
[email protected]_gpu
+def test_unique():
+ def calc_numpy_unique(data, is_sorted=False):
+ uniq, index, inverse, counts = np.unique(
+ data, return_index=True, return_inverse=True, return_counts=True
+ )
+ num_uniq = np.array([len(uniq)]).astype("int32")
+ if not is_sorted:
+ order = np.argsort(index)
+ reverse_order = np.argsort(order)
+ uniq = uniq[order].astype(data.dtype)
+ inverse = np.array([reverse_order[i] for i in
inverse]).astype("int32")
+ counts = counts[order].astype("int32")
+ return [uniq.astype(data.dtype), inverse.astype("int32"), counts,
num_uniq]
+
+ def verify_unique(n, dtype, is_dyn=False, is_sorted=False):
+ if is_dyn:
+ x = relay.var("x", relay.TensorType([relay.Any()], dtype))
+ else:
+ x = relay.var("x", relay.TensorType([n], dtype))
+ outs = relay.unique(x, is_sorted)
+ outs = outs.astuple()
+ func = relay.Function([x], outs)
+ x_data = np.random.randint(50, size=n).astype(dtype)
+
+ if is_dyn:
+ backends = ["vm", "debug"]
+ else:
+ backends = ["graph", "debug"]
+ for target, ctx in tvm.testing.enabled_targets():
Review comment:
thanks, will fix it.
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