tkonolige commented on a change in pull request #7125:
URL: https://github.com/apache/tvm/pull/7125#discussion_r546831211
##########
File path: python/tvm/relay/op/_transform.py
##########
@@ -63,6 +63,8 @@
_reg.register_injective_schedule("sparse_to_dense")
_reg.register_injective_schedule("matrix_set_diag")
_reg.register_injective_schedule("adv_index")
+_reg.register_injective_schedule("sparsereshape")
Review comment:
I think `sparse_reshape` would be a more appropriate name given the
above naming conventions.
##########
File path: python/tvm/relay/op/transform.py
##########
@@ -1320,3 +1320,52 @@ def adv_index(inputs):
Output tensor.
"""
return _make.adv_index(Tuple(inputs))
+
+
+def sparsereshape(sparse_indices, sparse_values, prev_shape, new_shape):
+ """
+ Reshape a Sparse Tensor
Review comment:
Could you note that this function only support tensors in COO format,
not CSR. In other parts of the codebase, we tend to use CSR.
##########
File path: src/relay/op/tensor/transform.cc
##########
@@ -1553,6 +1553,52 @@ RELAY_REGISTER_OP("meshgrid")
.set_attr<FTVMCompute>("FTVMCompute", MeshgridCompute)
.set_attr<TOpPattern>("TOpPattern", kInjective);
+TVM_REGISTER_NODE_TYPE(SparseReshapeAttrs);
+
+bool SparseReshapeRel(const Array<Type>& types, int num_inputs, const Attrs&
attrs,
+ const TypeReporter& reporter) {
+ // types: [sparse_indices, sparse_values, result]
+ // ICHECK_EQ(types.size(), 3);
+ auto sparse_indices = types[0].as<TensorTypeNode>();
+ const auto* param = attrs.as<SparseReshapeAttrs>();
+ CHECK(param != nullptr);
+ Array<PrimExpr> new_sparse_indices_shape{sparse_indices->shape[0],
+
static_cast<int>((param->new_shape).size())};
+ reporter->Assign(types[2], TensorType(new_sparse_indices_shape,
sparse_indices->dtype));
+ return true;
+}
+
+Array<te::Tensor> SparseReshapeCompute(const Attrs& attrs, const
Array<te::Tensor>& inputs,
+ const Type& out_type) {
+ // ICHECK_EQ(inputs.size(), 2);
+ const auto* param = attrs.as<SparseReshapeAttrs>();
+ CHECK(param != nullptr);
+ return {topi::SparseReshape(inputs[0], inputs[1], param->prev_shape,
param->new_shape)};
+}
+
+Expr MakeSparseReshape(Expr sparse_indices, Expr sparse_values, Array<Integer>
prev_shape,
+ Array<Integer> new_shape) {
+ auto attrs = make_object<SparseReshapeAttrs>();
+ attrs->prev_shape = std::move(prev_shape);
+ attrs->new_shape = std::move(new_shape);
+ static const Op& op = Op::Get("sparsereshape");
+ return Call(op, {sparse_indices, sparse_values}, Attrs(attrs), {});
+}
+
+TVM_REGISTER_GLOBAL("relay.op._make.sparsereshape").set_body_typed(MakeSparseReshape);
+
+RELAY_REGISTER_OP("sparsereshape")
+ .describe(R"code(Return twice of normal addition of two tensors.
Review comment:
Update the description
##########
File path: src/relay/op/tensor/transform.cc
##########
@@ -1553,6 +1553,52 @@ RELAY_REGISTER_OP("meshgrid")
.set_attr<FTVMCompute>("FTVMCompute", MeshgridCompute)
.set_attr<TOpPattern>("TOpPattern", kInjective);
+TVM_REGISTER_NODE_TYPE(SparseReshapeAttrs);
+
+bool SparseReshapeRel(const Array<Type>& types, int num_inputs, const Attrs&
attrs,
+ const TypeReporter& reporter) {
+ // types: [sparse_indices, sparse_values, result]
+ // ICHECK_EQ(types.size(), 3);
Review comment:
uncomment or remove
##########
File path: src/relay/op/tensor/transform.cc
##########
@@ -1553,6 +1553,52 @@ RELAY_REGISTER_OP("meshgrid")
.set_attr<FTVMCompute>("FTVMCompute", MeshgridCompute)
.set_attr<TOpPattern>("TOpPattern", kInjective);
+TVM_REGISTER_NODE_TYPE(SparseReshapeAttrs);
+
+bool SparseReshapeRel(const Array<Type>& types, int num_inputs, const Attrs&
attrs,
+ const TypeReporter& reporter) {
+ // types: [sparse_indices, sparse_values, result]
+ // ICHECK_EQ(types.size(), 3);
+ auto sparse_indices = types[0].as<TensorTypeNode>();
+ const auto* param = attrs.as<SparseReshapeAttrs>();
+ CHECK(param != nullptr);
Review comment:
```suggestion
ICHECK(param != nullptr);
```
##########
File path: src/relay/op/tensor/transform.cc
##########
@@ -1553,6 +1553,52 @@ RELAY_REGISTER_OP("meshgrid")
.set_attr<FTVMCompute>("FTVMCompute", MeshgridCompute)
.set_attr<TOpPattern>("TOpPattern", kInjective);
+TVM_REGISTER_NODE_TYPE(SparseReshapeAttrs);
+
+bool SparseReshapeRel(const Array<Type>& types, int num_inputs, const Attrs&
attrs,
+ const TypeReporter& reporter) {
+ // types: [sparse_indices, sparse_values, result]
+ // ICHECK_EQ(types.size(), 3);
+ auto sparse_indices = types[0].as<TensorTypeNode>();
+ const auto* param = attrs.as<SparseReshapeAttrs>();
+ CHECK(param != nullptr);
+ Array<PrimExpr> new_sparse_indices_shape{sparse_indices->shape[0],
+
static_cast<int>((param->new_shape).size())};
+ reporter->Assign(types[2], TensorType(new_sparse_indices_shape,
sparse_indices->dtype));
+ return true;
+}
+
+Array<te::Tensor> SparseReshapeCompute(const Attrs& attrs, const
Array<te::Tensor>& inputs,
+ const Type& out_type) {
+ // ICHECK_EQ(inputs.size(), 2);
Review comment:
uncomment or remove. If you keep it, it would be great to have an error
message too.
##########
File path: src/relay/op/tensor/transform.cc
##########
@@ -1553,6 +1553,52 @@ RELAY_REGISTER_OP("meshgrid")
.set_attr<FTVMCompute>("FTVMCompute", MeshgridCompute)
.set_attr<TOpPattern>("TOpPattern", kInjective);
+TVM_REGISTER_NODE_TYPE(SparseReshapeAttrs);
+
+bool SparseReshapeRel(const Array<Type>& types, int num_inputs, const Attrs&
attrs,
+ const TypeReporter& reporter) {
+ // types: [sparse_indices, sparse_values, result]
+ // ICHECK_EQ(types.size(), 3);
+ auto sparse_indices = types[0].as<TensorTypeNode>();
+ const auto* param = attrs.as<SparseReshapeAttrs>();
+ CHECK(param != nullptr);
+ Array<PrimExpr> new_sparse_indices_shape{sparse_indices->shape[0],
+
static_cast<int>((param->new_shape).size())};
+ reporter->Assign(types[2], TensorType(new_sparse_indices_shape,
sparse_indices->dtype));
+ return true;
+}
+
+Array<te::Tensor> SparseReshapeCompute(const Attrs& attrs, const
Array<te::Tensor>& inputs,
+ const Type& out_type) {
+ // ICHECK_EQ(inputs.size(), 2);
+ const auto* param = attrs.as<SparseReshapeAttrs>();
+ CHECK(param != nullptr);
Review comment:
```suggestion
ICHECK(param != nullptr);
```
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