dhruvaray commented on a change in pull request #5447:
URL: https://github.com/apache/incubator-tvm/pull/5447#discussion_r430402869
##########
File path: topi/include/topi/transform.h
##########
@@ -1309,5 +1309,57 @@ inline Tensor one_hot(const Tensor& indices, const
PrimExpr on_value, const Prim
name, tag);
}
+/*!
+ * \brief Get a dense tensor.
+ * \param sparse_indices sparse_indices[i] contains the complete index where
sparse_values[i] will be placed.
+ * \param sparse_values is a 0-D or 1-D tensor. Values corresponding to each
row of sparse_indices
+ * \param default_value is a 0-D tensor. Defaults to zero.
+ * \param output_shape is the shape of the dense output tensor
+ * \param name output tensor name.
+ * \param tag output tensor tag.
+ * \return Tensor of output_shape.
+ */
+inline Tensor sparse_to_dense(const Tensor& sparse_indices,
+ const Tensor& sparse_values,
+ const Tensor& default_value,
+ const Array<Integer>& output_shape,
Review comment:
@siju-samuel : tf 2.0 introduces a top-level wrapper object
SparseTensor(
https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor) which
encapsulates this information (indices, values, dense_shape). The topi layer
takes all these pieces of information and hence should be compatible across all
frameworks
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