[Relay] Minor fix for some TF OD models

include/tvm/topi/transform.h

@@ -897,8 +897,14 @@ inline Tensor where(const Tensor& condition, const Tensor& x, const Tensor& y,
     return compute(
         condition->shape,
         [&](const Array<Var>& indices) {
-          Array<PrimExpr> condition_idx{indices[0]};
-          return tvm::tir::Select(condition(condition_idx) != 0, x(), y());
+          PrimExpr cond;
+          if (condition->shape.size() == 0) {
+            cond = condition();
+          } else {
+            Array<PrimExpr> condition_idx{indices[0]};
+            cond = condition(condition_idx);
+          }
+          return tvm::tir::Select(cond != 0, x(), y());
         },
         name, tag);
   } else if (condition->shape.size() != 1) {
@@ -913,9 +919,13 @@ inline Tensor where(const Tensor& condition, const Tensor& x, const Tensor& y,
         },
         name, tag);
   } else {
-    CHECK_EQ(topi::GetConstInt(condition->shape[0]), topi::GetConstInt(x->shape[0]))
-        << "If condition is 1-D, the first dimension must be the same as x: " << condition->shape[0]
-        << " vs " << x->shape[0];
+    int64_t cond_first_dim = topi::GetConstInt(condition->shape[0]);
+    int64_t x_first_dim = topi::GetConstInt(x->shape[0]);
+    if (cond_first_dim > 0 && x_first_dim > 0) {
+      CHECK_EQ(cond_first_dim, x_first_dim)
+          << "If condition is 1-D, the first dimension must be the same as x: " << cond_first_dim
+          << " vs " << x_first_dim;
+    }
     return compute(
         x->shape,
         [&](const Array<Var>& indices) {

python/tvm/relay/frontend/tensorflow.py

@@ -1549,7 +1549,7 @@ def _impl(inputs, attr, params, mod):
                 idx += st
 
             # Only return when in_shape is fully static in the range from begin to end.
-            if idx >= st:
+            if idx >= ed:
                 ret = _expr.const(out_data, dtype)
                 if shrink_axis_mask:
                     ret = _op.squeeze(ret)
@@ -1659,14 +1659,26 @@ def _transform_mask(stride_dim, ellipsis_mask):
 
 def _pad(name):
     def _impl(inputs, attr, params, mod):
-        padlist = _get_param(params, inputs[1])
-        paddings = tuple(tuple(l) for l in padlist)
+        try:
+            padlist = _get_param(params, inputs[1])
+        except (IndexError, KeyError, AttributeError):
+            try:
+                padlist = _infer_value(inputs[1], params, mod).asnumpy().tolist()
+            except Exception:
+                padlist = inputs[1]
+
+        if isinstance(padlist, _expr.Expr):
+            paddings = padlist
+        else:
+            paddings = tuple(tuple(l) for l in padlist)
         attr["pad_width"] = paddings
         attr["pad_value"] = 0
         new_inputs = [inputs[0]]
         if name == "PadV2":
-            constant_values = _get_num_param(params, inputs[2])
-            attr["pad_value"] = constant_values
+            try:
+                attr["pad_value"] = _get_num_param(params, inputs[2])
+            except (IndexError, KeyError, AttributeError):
+                attr["pad_value"] = inputs[2]
         return AttrCvt(
             op_name="pad",
             ignores=["Tpaddings"],

python/tvm/relay/op/_transform.py

@@ -778,6 +778,9 @@ def repeat_shape_func(attrs, inputs, _):
 
 @_reg.register_shape_func("broadcast_to_like", False)
 def broadcast_to_like_shape_func(attrs, inputs, _):
+    """
+    Shape func for broadcast_to_like.
+    """
     return [topi.math.identity(inputs[1])]
 
 
@@ -798,7 +801,22 @@ def _stack_shape_func(data_shape, axis, num_inputs):
 
 @_reg.register_shape_func("stack", False)
 def stack_shape_func(attrs, inputs, _):
+    """
+    Shape func for stack.
+    """
     axis = get_const_int(attrs.axis)
     if axis < 0:
         axis += inputs[0].shape[0] + 1
     return [_stack_shape_func(inputs[0], convert(axis), convert(len(inputs)))]
+
+
+@_reg.register_shape_func("where", False)
+def where_shape_func(attrs, inputs, _):
+    """
+    Shape func for where.
+    """
+    cond_shape = inputs[0]
+    x_shape = inputs[1]
+    out_shape = x_shape if x_shape.shape else cond_shape
+
+    return [topi.math.identity(out_shape)]

tests/python/topi/python/test_topi_transform.py

@@ -839,6 +839,7 @@ def test_reshape():
 
 @tvm.testing.uses_gpu
 def test_where():
+    verify_where(())
     verify_where((1, 2, 3, 4))