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[TF2XLA] Show stack traces of op definitions for some common tf2xla error messages

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Eventually it might make sense to always show this.

PiperOrigin-RevId: 348707164
Change-Id: Id05656460920763c3e3260695333c41f69386e45
This commit is contained in:
George Karpenkov 2020-12-22 15:57:19 -08:00 committed by TensorFlower Gardener
parent 5624ed9f01
commit e5d1243857
3 changed files with 36 additions and 9 deletions
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24
tensorflow/compiler/tf2xla/kernels/tensor_list_ops.cc
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@ -154,7 +154,8 @@ class TensorListReserveOp : public XlaOpKernel {
"XLA compilation requires a fixed tensor list size. Set the number "
"of elements. This could also happen if you're using a TensorArray "
"in a while loop that does not have its maximum_iteration set, you "
"can fix this by setting maximum_iteration to a suitable value."));
"can fix this by setting maximum_iteration to a suitable value.",
ctx->StackTrace()));
// If element shape is compile time constant and it's not "unknown rank"
// shape (-1), create an initialized TensorList. Otherwise create an
@ -224,7 +225,8 @@ class EmptyTensorListOp : public XlaOpKernel {
"the max number of elements. This could also happen if "
"you're using a TensorArray in a while loop that does not "
"have its maximum_iteration set, you can fix this by "
"setting maximum_iteration to a suitable value."));
"setting maximum_iteration to a suitable value.",
ctx->StackTrace()));
if (dtype_ != DT_VARIANT) {
// We are creating a non-nested TensorList.
@ -292,7 +294,8 @@ class TensorListElementShapeOp : public XlaOpKernel {
OP_REQUIRES_OK(ctx,
(IsTensorListInitialized(ctx->Input(0), &is_initialized)));
OP_REQUIRES(ctx, is_initialized,
errors::InvalidArgument("TensorList is not initialized"));
errors::InvalidArgument("TensorList is not initialized",
ctx->StackTrace()));
// Only non-nested TensorList is supported for now.
bool is_nested;
@ -348,7 +351,8 @@ class TensorListGetItemOp : public XlaOpKernel {
OP_REQUIRES_OK(ctx,
(IsTensorListInitialized(ctx->Input(0), &is_initialized)));
OP_REQUIRES(ctx, is_initialized,
errors::InvalidArgument("TensorList is not initialized"));
errors::InvalidArgument("TensorList is not initialized",
ctx->StackTrace()));
// Only non-nested TensorList is supported for now.
bool is_nested;
@ -386,7 +390,8 @@ class TensorListGatherOp : public XlaOpKernel {
OP_REQUIRES_OK(ctx,
(IsTensorListInitialized(ctx->Input(0), &is_initialized)));
OP_REQUIRES(ctx, is_initialized,
errors::InvalidArgument("TensorList is not initialized"));
errors::InvalidArgument("TensorList is not initialized",
ctx->StackTrace()));
// Only non-nested TensorList is supported for now.
bool is_nested;
@ -437,7 +442,8 @@ class TensorListStackOp : public XlaOpKernel {
OP_REQUIRES_OK(ctx,
(IsTensorListInitialized(ctx->Input(0), &is_initialized)));
OP_REQUIRES(ctx, is_initialized,
errors::InvalidArgument("TensorList is not initialized"));
errors::InvalidArgument("TensorList is not initialized",
ctx->StackTrace()));
// Only non-nested TensorList is supported for now.
bool is_nested;
@ -468,7 +474,8 @@ class TensorListConcatOp : public XlaOpKernel {
bool is_initialized;
OP_REQUIRES_OK(ctx, (IsTensorListInitialized(input, &is_initialized)));
OP_REQUIRES(ctx, is_initialized,
errors::InvalidArgument("TensorList is not initialized"));
errors::InvalidArgument("TensorList is not initialized",
ctx->StackTrace()));
// Only non-nested TensorList is supported for now.
bool is_nested;
@ -666,7 +673,8 @@ class TensorListPopBackOp : public XlaOpKernel {
OP_REQUIRES_OK(ctx,
(IsTensorListInitialized(ctx->Input(0), &is_initialized)));
OP_REQUIRES(ctx, is_initialized,
errors::InvalidArgument("TensorList is not initialized"));
errors::InvalidArgument("TensorList is not initialized",
ctx->StackTrace()));
xla::XlaOp list = ctx->Input(0);
xla::XlaOp list_result, element_result;

17
tensorflow/compiler/tf2xla/xla_op_kernel.cc
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@ -177,7 +177,8 @@ Status XlaOpKernelContext::ConstantInputReshaped(
"This error means that a shape or dimension argument could not be "
"evaluated at compile time, usually because the value of the argument "
"depends on a parameter to the computation, on a variable, or on a "
"stateful operation such as a random number generator.");
"stateful operation such as a random number generator.",
StackTrace());
}
Tensor temp(constant->dtype());
@ -705,4 +706,18 @@ void XlaOpKernel::Compute(OpKernelContext* context) {
Compile(&xla_context);
}
std::string XlaOpKernelContext::StackTrace() const {
if (const AbstractStackTrace* stack_trace =
xla_context()->StackTraceForNodeName(op_kernel().name())) {
AbstractStackTrace::TracePrintingOptions opts;
opts.show_line_contents = true;
opts.filter_common_prefix = true;
opts.drop_internal_frames = true;
return absl::StrCat("\nStack trace for op definition: \n",
stack_trace->ToString(opts), "\n");
} else {
return "";
}
}
} // namespace tensorflow

4
tensorflow/compiler/tf2xla/xla_op_kernel.h
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@ -290,6 +290,10 @@ class XlaOpKernelContext {
// separate specialization of the computation for each DataType.
const xla::XlaComputation* GetOrCreateMul(const DataType type);
// Returns stack trace encoded as a string at a given module, or an empty
// string if none found.
std::string StackTrace() const;
private:
// Returns the tensor of input `name`.
const Tensor& GetInputTensorByName(absl::string_view name);