b&c start ops | add dim order sanity check

Differential Revision: D59824515

Author: Songhao Jia

kernels/portable/cpu/op_bitwise_and.cpp

@@ -32,6 +32,9 @@ Tensor& bitwise_and_Tensor_out(
       InvalidArgument,
       out);
 
+  ET_KERNEL_CHECK(
+      ctx, tensors_have_same_dim_order(a, b, out), InvalidArgument, out);
+
   ScalarType a_type = a.scalar_type();
   ScalarType b_type = b.scalar_type();
   ScalarType common_type = promoteTypes(a_type, b_type);
@@ -82,6 +85,9 @@ Tensor& bitwise_and_Scalar_out(
       out,
       "Failed to resize output tensor.");
 
+  ET_KERNEL_CHECK(
+      ctx, tensors_have_same_dim_order(a, out), InvalidArgument, out);
+
   ScalarType a_type = a.scalar_type();
   ScalarType b_type = utils::get_scalar_dtype(b);
   ScalarType common_type = utils::promote_type_with_scalar(a_type, b);

kernels/portable/cpu/op_bitwise_not.cpp

@@ -33,6 +33,8 @@ Tensor& bitwise_not_out(RuntimeContext& ctx, const Tensor& in, Tensor& out) {
       "Failed to resize output tensor.");
 
   ET_KERNEL_CHECK(ctx, tensors_have_same_dtype(in, out), InvalidArgument, out);
+  ET_KERNEL_CHECK(
+      ctx, tensors_have_same_dim_order(in, out), InvalidArgument, out);
 
   if (in.scalar_type() == exec_aten::ScalarType::Bool) {
     apply_unary_map_fn(

kernels/portable/cpu/op_bitwise_or.cpp

@@ -32,6 +32,9 @@ Tensor& bitwise_or_Tensor_out(
       InvalidArgument,
       out);
 
+  ET_KERNEL_CHECK(
+      ctx, tensors_have_same_dim_order(a, b, out), InvalidArgument, out);
+
   ScalarType a_type = a.scalar_type();
   ScalarType b_type = b.scalar_type();
   ScalarType common_type = promoteTypes(a_type, b_type);
@@ -74,6 +77,9 @@ Tensor& bitwise_or_Scalar_out(
     Tensor& out) {
   (void)ctx;
 
+  ET_KERNEL_CHECK(
+      ctx, tensors_have_same_dim_order(a, out), InvalidArgument, out);
+
   // Resize for dynamic shape
   ET_KERNEL_CHECK_MSG(
       ctx,

kernels/portable/cpu/op_bitwise_xor.cpp

@@ -32,6 +32,9 @@ Tensor& bitwise_xor_Tensor_out(
       InvalidArgument,
       out);
 
+  ET_KERNEL_CHECK(
+      ctx, tensors_have_same_dim_order(a, b, out), InvalidArgument, out);
+
   ScalarType a_type = a.scalar_type();
   ScalarType b_type = b.scalar_type();
   ScalarType common_type = promoteTypes(a_type, b_type);
@@ -82,6 +85,9 @@ Tensor& bitwise_xor_Scalar_out(
       out,
       "Failed to resize output tensor.");
 
+  ET_KERNEL_CHECK(
+      ctx, tensors_have_same_dim_order(a, out), InvalidArgument, out);
+
   ScalarType a_type = a.scalar_type();
   ScalarType b_type = utils::get_scalar_dtype(b);
   ScalarType common_type = utils::promote_type_with_scalar(a_type, b);

kernels/portable/cpu/op_bmm.cpp

@@ -23,6 +23,11 @@ Tensor& bmm_out(
     Tensor& out) {
   ET_KERNEL_CHECK(ctx, check_bmm_args(in, mat2, out), InvalidArgument, out);
 
+  ET_KERNEL_CHECK(
+      ctx, tensors_have_same_dim_order(in, mat2, out), InvalidArgument, out);
+
+  ET_KERNEL_CHECK(ctx, tensor_is_default_dim_order(in), InvalidArgument, out);
+
   size_t output_ndim = 0;
   exec_aten::SizesType output_sizes[kTensorDimensionLimit];
   get_bmm_out_target_size(in, mat2, output_sizes, &output_ndim);

kernels/portable/cpu/op_cdist_forward.cpp

@@ -124,6 +124,11 @@ Tensor& _cdist_forward_out(
     Tensor& out) {
   (void)ctx;
 
+  ET_KERNEL_CHECK(
+      ctx, tensors_have_same_dim_order(x1, x2, out), InvalidArgument, out);
+
+  ET_KERNEL_CHECK(ctx, tensor_is_default_dim_order(x1), InvalidArgument, out);
+
   ET_KERNEL_CHECK(
       ctx,
       check_cdist_args(x1, x2, p, compute_mode, out),

kernels/portable/cpu/op_clamp.cpp

@@ -83,6 +83,9 @@ Tensor& clamp_out(
       out,
       "Failed to resize output tensor.");
 
+  ET_KERNEL_CHECK(
+      ctx, tensors_have_same_dim_order(in, out), InvalidArgument, out);
+
   ScalarType in_type = in.scalar_type();
   ScalarType min_type = in_type;
   ScalarType max_type = in_type;
@@ -182,6 +185,12 @@ Tensor& clamp_tensor_out(
   const Tensor& min = has_min ? min_opt.value() : in;
   const Tensor& max = has_max ? max_opt.value() : in;
 
+  ET_KERNEL_CHECK(
+      ctx,
+      tensors_have_same_dim_order(in, min, max, out),
+      InvalidArgument,
+      out);
+
   ET_KERNEL_CHECK(
       ctx,
       resize_to_broadcast_target_size(in, min, max, out) == Error::Ok,

kernels/portable/cpu/op_clone.cpp

@@ -38,6 +38,9 @@ Tensor& clone_out(
       InvalidArgument,
       out);
 
+  ET_KERNEL_CHECK(
+      context, tensors_have_same_dim_order(self, out), InvalidArgument, out);
+
   // Right now we only focus on contiguous memory, memory_format shall always
   // either a nullopt or exec::aten::MemoryFormat::Contiguous
   ET_KERNEL_CHECK(

kernels/portable/cpu/op_constant_pad_nd.cpp

@@ -170,6 +170,9 @@ Tensor& constant_pad_nd_out(
   ET_KERNEL_CHECK(
       ctx, check_constant_pad_args(in, pad, value, out), InvalidArgument, out);
 
+  ET_KERNEL_CHECK(
+      ctx, tensors_have_same_dim_order(in, out), InvalidArgument, out);
+
   // resize out tensor for dynamic shapes
   ET_KERNEL_CHECK_MSG(
       ctx,

kernels/portable/cpu/op_convolution.cpp

@@ -365,6 +365,9 @@ Tensor& convolution_out(
       InvalidArgument,
       out);
 
+  ET_KERNEL_CHECK(
+      ctx, tensors_have_same_dim_order(in, out), InvalidArgument, out);
+
   size_t output_ndim = 0;
   exec_aten::SizesType output_sizes[kTensorDimensionLimit];
   get_convolution_out_target_size(

kernels/portable/cpu/op_copy.cpp

@@ -39,6 +39,9 @@ Tensor& copy_out(
   ET_KERNEL_CHECK(
       ctx, resize_tensor(out, in.sizes()) == Error::Ok, InvalidArgument, out);
 
+  ET_KERNEL_CHECK(
+      ctx, tensors_have_same_dim_order(in, out), InvalidArgument, out);
+
   ScalarType in_type = in.scalar_type();
   ScalarType src_type = src.scalar_type();
 
@@ -66,6 +69,9 @@ copy_(RuntimeContext& ctx, Tensor& in, const Tensor& src, bool non_blocking) {
   ET_KERNEL_CHECK(
       ctx, tensor_is_broadcastable_to(src, in), InvalidArgument, in);
 
+  ET_KERNEL_CHECK(
+      ctx, tensors_have_same_dim_order(in, src), InvalidArgument, in);
+
   ScalarType in_type = in.scalar_type();
   ScalarType src_type = src.scalar_type();
 

kernels/portable/cpu/op_cumsum.cpp

@@ -93,6 +93,9 @@ Tensor& cumsum_out(
       InvalidArgument,
       out);
 
+  ET_KERNEL_CHECK(
+      ctx, tensors_have_same_dim_order(self, out), InvalidArgument, out);
+
   ET_KERNEL_CHECK(
       ctx, resize_tensor(out, self.sizes()) == Error::Ok, InvalidArgument, out);
 

kernels/portable/cpu/util/copy_ops_util.cpp

@@ -95,6 +95,8 @@ bool check_cat_args(
     ET_LOG_AND_RETURN_IF_FALSE(
         canCast(tensors[i].scalar_type(), out.scalar_type()));
 
+    ET_LOG_AND_RETURN_IF_FALSE(tensors_have_same_dim_order(tensors[i], out));
+
     // Empty tensors have no shape constraints.
     if (tensors[i].numel() == 0) {
       continue;