shoubhik commented on a change in pull request #4629: [QNN] Channel wise
quantization - Quantize & Requantize
URL: https://github.com/apache/incubator-tvm/pull/4629#discussion_r363864178
##########
File path: src/relay/pass/pattern_util.h
##########
@@ -221,29 +222,69 @@ inline bool IsScalar(const Expr& expr) {
return true;
}
+/*!
+ * \brief Check if expr is a const scalar.
+ * \param expr The expr.
+ * \return True if const scalar.
+ */
+inline bool IsConstScalar(const Expr& expr) {
+ const auto* const_expr = expr.as<ConstantNode>();
+ if (const_expr) {
+ return const_expr->is_scalar();
+ }
+ return false;
+}
+
/*!
* \brief Create a Constant with a scalar
*
* \param dtype The data type.
* \param value The value of the scalar.
* \return A Constant.
*/
-template<typename T>
+template <typename T>
inline Constant MakeConstantScalar(DataType dtype, T value) {
runtime::NDArray arr = runtime::NDArray::Empty({}, dtype, {kDLCPU, 0});
TVM_DTYPE_DISPATCH(dtype, DType, {
if (dtype == DataType::Float(16)) {
// convert to float16
// storage is uint16_t
*static_cast<DType*>(arr->data) =
- __truncXfYf2__<float, uint32_t, 23, uint16_t, uint16_t,
10>(static_cast<float>(value));
+ __truncXfYf2__<float, uint32_t, 23, uint16_t, uint16_t,
10>(static_cast<float>(value));
} else {
*static_cast<DType*>(arr->data) = value;
}
})
return ConstantNode::make(arr);
}
+/*!
+ * \brief Create a Constant with a tensor.
+ *
+ * \param dtype The data type.
+ * \param value The vector of the tensor values.
+ * \return A Constant.
+ */
+template <typename T>
+static inline Constant MakeConstantTensor(DataType dtype, std::vector<int64_t>
shape,
+ std::vector<T> value) {
+ runtime::NDArray arr = runtime::NDArray::Empty(shape, dtype, {kDLCPU, 0});
Review comment:
can we also templatize of device type with default beding kDLCPU?
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