LiangHao151941 commented on a change in pull request #4828: [QNN][TFLite]
TFLite rounding mode support
URL: https://github.com/apache/incubator-tvm/pull/4828#discussion_r376853818
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File path: src/relay/qnn/util.cc
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@@ -22,13 +22,47 @@
* \brief Utility functions for QNN.
*/
+#include <limits>
#include "util.h"
#include "../pass/pattern_util.h"
namespace tvm {
namespace relay {
namespace qnn {
+/* \brief This function implements the rounding part of ARMv7 NEON VQRDMULH
+ * instruction. For code reuse, the multiplied tensor is directly passed in
+ * as parameter.
+ */
+Expr SaturatingRoundingDoublingHigh32(const Expr& input_tensor,
+ const Expr& multiplier_expr,
+ const Expr& scaled_tensor,
+ const Array<IndexExpr>& input_shape) {
+ DataType hp_dtype = DataType::Int(64);
+ int32_t pos_nudge_value = (1ll << 30);
+ int32_t neg_nudge_value = 1 - (1ll << 30);
+ auto pos_nudge = MakeConstantScalar(hp_dtype, pos_nudge_value);
+ auto neg_nudge = MakeConstantScalar(hp_dtype, neg_nudge_value);
+ auto pos_nudge_t = Full(pos_nudge, input_shape, hp_dtype);
+ auto neg_nudge_t = Full(neg_nudge, input_shape, hp_dtype);
+
+ auto int32_min = MakeConstantScalar(
+ hp_dtype, std::numeric_limits<std::int32_t>::min());
+ auto int32_max = MakeConstantScalar(
+ hp_dtype, std::numeric_limits<std::int32_t>::max());
+ auto int32_min_t = Full(int32_min, input_shape, hp_dtype);
+ auto int32_max_t = Full(int32_max, input_shape, hp_dtype);
Review comment:
This patch is for a unique request that needs bit-exact execution compared
to tflite implementation(not only on arm targets). I believe moving this
generic implementation into relay help us to gain more control over compiler
behavior and reduce gaps between different targets and implementations.
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