[Bugfix] Repeat and tile bug fixed, relay tests added (#2804)

src/relay/op/tensor/transform.cc

@@ -363,7 +363,7 @@ RELAY_REGISTER_OP("stack")
 .set_attrs_type_key("relay.attrs.StackAttrs")
 .set_num_inputs(1)
 .add_argument("data", "Tensor", "The input list of tensors.")
-.set_support_level(1)
+.set_support_level(3)
 .add_type_rel("Stack", StackRel)
 .set_attr<FTVMCompute>("FTVMCompute", StackCompute)
 .set_attr<TOpPattern>("TOpPattern", kInjective);
@@ -1109,7 +1109,7 @@ RELAY_REGISTER_OP("repeat")
 .set_num_inputs(1)
 .set_attrs_type_key("relay.attrs.Repeat")
 .add_argument("data", "Tensor", "The input tensor.")
-.set_support_level(1)
+.set_support_level(3)
 .add_type_rel("Repeat", RepeatRel)
 .set_attr<FTVMCompute>("FTVMCompute", RepeatCompute)
 .set_attr<TOpPattern>("TOpPattern", kBroadcast);
@@ -1134,9 +1134,15 @@ bool TileRel(const Array<Type>& types,
   const size_t ndim = data->shape.size();
   const Array<Integer>& reps = param->reps;
   // check dimension match
-  CHECK(!reps.defined())
+  CHECK(reps.defined())
     << "repetition array is not defined. data.ndim = " << ndim;
   const size_t rndim = reps.size();
+  for (size_t i = 0; i < rndim; ++i) {
+    if (const tvm::ir::IntImm* val = reps[i].as<tvm::ir::IntImm>()) {
+      CHECK_GT(val->value, 0)
+          << "Tile reps value should always be larger than 0, but get: " << val->value;
+    }
+  }
   size_t tndim = (ndim > rndim) ? ndim : rndim;
   // re-construct data shape or reps shape
   std::vector<IndexExpr> data_shape;
@@ -1158,6 +1164,10 @@ bool TileRel(const Array<Type>& types,
   } else {
     for (size_t i = 0; i < rndim; ++i)
         reps_shape.emplace_back(reps[i]);
+    for (size_t i = 0; i < (rndim - ndim); ++i)
+        data_shape.emplace_back(1);
+    for (size_t i = 0; i < ndim; ++i)
+        data_shape.emplace_back(data->shape[i]);
   }
   std::vector<IndexExpr> oshape;
   oshape.reserve(tndim);
@@ -1199,7 +1209,7 @@ RELAY_REGISTER_OP("tile")
 .set_num_inputs(1)
 .set_attrs_type_key("relay.attrs.Tile")
 .add_argument("data", "Tensor", "The input tensor.")
-.set_support_level(1)
+.set_support_level(3)
 .add_type_rel("Tile", TileRel)
 .set_attr<FTVMCompute>("FTVMCompute", TileCompute)
 .set_attr<TOpPattern>("TOpPattern", kBroadcast);

tests/python/relay/test_op_level3.py

@@ -491,6 +491,62 @@ def test_arange():
     verify_arange(20, 1, -1)
     verify_arange(20, 1, -1.5)
 
+def test_tile():
+    def verify_tile(dshape, reps):
+        x = relay.var("x", relay.TensorType(dshape, "float32"))
+        z = relay.tile(x, reps=reps)
+
+        func = relay.Function([x], z)
+        x_data = np.random.uniform(low=-1, high=1, size=dshape).astype("float32")
+        ref_res = np.tile(x_data, reps=reps)
+
+        for target, ctx in ctx_list():
+            for kind in ["graph", "debug"]:
+                intrp = relay.create_executor(kind, ctx=ctx, target=target)
+                op_res = intrp.evaluate(func)(x_data)
+                tvm.testing.assert_allclose(op_res.asnumpy(), ref_res, rtol=1e-5)
+    verify_tile((2, 3, 4), (3, 2, 1))
+    verify_tile((2, 3, 4), (1, 2))
+    verify_tile((2, 3), (3, 2, 1))
+
+def test_repeat():
+    def verify_repeat(dshape, repeats, axis):
+        x = relay.Var("x", relay.TensorType(dshape, "float32"))
+        func = relay.Function([x], relay.repeat(x, repeats, axis))
+        data = np.random.uniform(size=dshape).astype("float32")
+        ref_res = np.repeat(data, repeats, axis)
+        for target, ctx in ctx_list():
+            for kind in ["graph", "debug"]:
+                intrp = relay.create_executor(kind, ctx=ctx, target=target)
+                op_res = intrp.evaluate(func)(data)
+                tvm.testing.assert_allclose(op_res.asnumpy(), ref_res, rtol=1e-5)
+    verify_repeat((3,), 2, 0)
+    verify_repeat((3, 10), 2, -1)
+    verify_repeat((3, 2, 4), 3, 1)
+
+def test_stack():
+    def verify_stack(dshapes, axis):
+        y = []
+        for shape in dshapes:
+            y.append(relay.var("input", relay.TensorType(shape, "float32")))
+        x = relay.Tuple(y)
+        z = relay.stack(x, axis=axis)
+
+        func = relay.Function(y, z)
+        x_data = [np.random.normal(size=shape).astype("float32") for shape in dshapes]
+        ref_res = np.stack(x_data, axis=axis)
+
+        for target, ctx in ctx_list():
+            for kind in ["graph", "debug"]:
+                intrp = relay.create_executor(kind, ctx=ctx, target=target)
+                op_res = intrp.evaluate(func)(*x_data)
+                tvm.testing.assert_allclose(op_res.asnumpy(), ref_res, rtol=1e-5)
+    verify_stack([(2,), (2,), (2,)], -1)
+    verify_stack([(2,), (2,), (2,)], 0)
+    verify_stack([(2, 2, 4), (2, 2, 4), (2, 2, 4)], 1)
+    verify_stack([(2, 2, 3, 4), (2, 2, 3, 4), (2, 2, 3, 4), (2, 2, 3, 4)], -1)
+
+
 
 def test_reverse():
     def verify_reverse(dshape, axis):
@@ -536,3 +592,6 @@ if __name__ == "__main__":
     test_split_infer_type()
     test_arange()
     test_reverse()
+    test_stack()
+    test_tile()
+    test_repeat()

topi/tests/python/test_topi_transform.py

@@ -29,7 +29,7 @@ def verify_expand_dims(in_shape, out_shape, axis, num_newaxis):
         check_device(device)
 
 
-def verify_tranpose(in_shape, axes):
+def verify_transpose(in_shape, axes):
     A = tvm.placeholder(shape=in_shape, name="A")
     B = topi.transpose(A, axes)
     def check_device(device):
@@ -40,7 +40,7 @@ def verify_tranpose(in_shape, axes):
         print("Running on target: %s" % device)
         with tvm.target.create(device):
             s = topi.generic.schedule_injective(B)
-        foo = tvm.build(s, [A, B], device, name="tranpose")
+        foo = tvm.build(s, [A, B], device, name="transpose")
         data_npy = np.arange(np.prod(in_shape)).reshape(in_shape).astype(A.dtype)
         out_npy = data_npy.transpose(axes)
         data_nd = tvm.nd.array(data_npy, ctx)
@@ -416,10 +416,10 @@ def test_expand_dims():
     verify_expand_dims((3, 10), (1, 3, 10), -3, 1)
 
 
-def test_tranpose():
-    verify_tranpose((3, 10, 2), (1, 0, 2))
-    verify_tranpose((3, 10, 5), (2, 0, 1))
-    verify_tranpose((3, 10), None)
+def test_transpose():
+    verify_transpose((3, 10, 2), (1, 0, 2))
+    verify_transpose((3, 10, 5), (2, 0, 1))
+    verify_transpose((3, 10), None)
 
 
 def test_reshape():
@@ -595,7 +595,7 @@ if __name__ == "__main__":
     test_strided_slice()
     test_concatenate()
     test_stack()
-    test_tranpose()
+    test_transpose()
     test_expand_dims()
     test_reshape()
     test_squeeze()