mbrookhart commented on a change in pull request #6007:
URL: https://github.com/apache/incubator-tvm/pull/6007#discussion_r451152469
##########
File path: src/relay/transforms/pattern_util.h
##########
@@ -330,6 +331,29 @@ static inline Constant CheckConstantShape(const
Array<IndexExpr>& shape) {
return Constant(shape_array);
}
+/*!
+ * \brief Check whether a shape is static and create corresponding
Array<Integer>. Will replace
+ * CheckConstantShape after dynamic refactorization is complete
+ *
+ * \param shape The Array of the shape values.
+ * \return A Constant.
+ */
+static inline Array<Integer> CheckConstantShapeArrayInteger(const
Array<IndexExpr>& shape) {
+ Array<Integer> constShape;
+ // auto shape_array =
+ // runtime::NDArray::Empty({int64_t(shape.size())}, DataType::Int(64),
{kDLCPU, 0});
+ // auto* shape_data = static_cast<int64_t*>(shape_array->data);
Review comment:
Remove commented code
##########
File path: src/relay/transforms/pattern_util.h
##########
@@ -330,6 +331,29 @@ static inline Constant CheckConstantShape(const
Array<IndexExpr>& shape) {
return Constant(shape_array);
}
+/*!
+ * \brief Check whether a shape is static and create corresponding
Array<Integer>. Will replace
+ * CheckConstantShape after dynamic refactorization is complete
+ *
+ * \param shape The Array of the shape values.
+ * \return A Constant.
+ */
+static inline Array<Integer> CheckConstantShapeArrayInteger(const
Array<IndexExpr>& shape) {
+ Array<Integer> constShape;
+ // auto shape_array =
+ // runtime::NDArray::Empty({int64_t(shape.size())}, DataType::Int(64),
{kDLCPU, 0});
+ // auto* shape_data = static_cast<int64_t*>(shape_array->data);
+ for (size_t i = 0; i < shape.size(); ++i) {
+ const auto& dim_val = shape[i].as<IntImmNode>();
+ CHECK(dim_val) << "Do not support symbolic shape for "
+ "Array format. Pass shape as Expr instead.";
+
+ // shape_data[i] = dim_val->value;
Review comment:
Remove Commented Code
##########
File path: src/relay/transforms/dynamic_to_static.cc
##########
@@ -56,6 +58,30 @@ class DynamicToStaticMutator : public MixedModeMutator {
return Call(op, {call_node->args[0]}, Attrs(attrs), {});
}
}
+ if (call_node->op == dyn_broadcast_to_op_) {
+ if (const ConstantNode* shape = call_node->args[1].as<ConstantNode>()) {
+ auto attrs = make_object<InitOpAttrs>();
+ CHECK_EQ(shape->data->ndim, 1);
+
+ // put shape in attrs
+ attrs->shape = ToVector(shape->data);
+ static const Op& broadcast_to = Op::Get("broadcast_to");
+ // pass in one arg to static broadcast to
+ return Call(broadcast_to, {call_node->args[0]}, Attrs(attrs), {});
+ }
+ }
+ if (call_node->op == dyn_broadcast_to_op_) {
+ if (const ConstantNode* shape = call_node->args[1].as<ConstantNode>()) {
+ auto attrs = make_object<InitOpAttrs>();
+ CHECK_EQ(shape->data->ndim, 1);
+
+ // put shape in attrs
+ attrs->shape = ToVector(shape->data);
+ static const Op& broadcast_to = Op::Get("broadcast_to");
+ // pass in one arg to static broadcast to
+ return Call(broadcast_to, {call_node->args[0]}, Attrs(attrs), {});
+ }
+ }
Review comment:
You have two copies of this code block, remove one.
##########
File path: src/relay/op/dyn/tensor/transform.cc
##########
@@ -36,6 +37,8 @@ namespace relay {
namespace dyn {
/* relay.dyn.reshape */
+// TVM_REGISTER_NODE_TYPE(ReshapeAttrs);
+
Review comment:
Remove
##########
File path: tests/python/relay/test_op_level10.py
##########
@@ -455,13 +457,13 @@ def _verify(indices_shape, depth, on_value, off_value,
axis, dtype):
func = relay.Function([indices], out)
indices_np = np.random.randint(0, depth,
size=indices_shape).astype("int32")
out_np = topi.testing.one_hot(indices_np, on_value, off_value, depth,
axis, dtype)
-
+
for target, ctx in ctx_list():
for kind in ["graph", "debug"]:
intrp = relay.create_executor(kind, ctx=ctx, target=target)
out_relay = intrp.evaluate(func)(indices_np)
tvm.testing.assert_allclose(out_relay.asnumpy(), out_np)
-
+
Review comment:
delete extra whitespace
##########
File path: tests/python/relay/test_op_level10.py
##########
@@ -455,13 +457,13 @@ def _verify(indices_shape, depth, on_value, off_value,
axis, dtype):
func = relay.Function([indices], out)
indices_np = np.random.randint(0, depth,
size=indices_shape).astype("int32")
out_np = topi.testing.one_hot(indices_np, on_value, off_value, depth,
axis, dtype)
-
+
Review comment:
delete extra whitespace
##########
File path: tests/python/relay/dyn/test_dynamic_op_level10.py
##########
@@ -0,0 +1,57 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements. See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership. The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied. See the License for the
+# specific language governing permissions and limitations
+# under the License.
+"""
+Support level10 operator test cases.
+
+"""
+
+
+import numpy as np
+import tvm
+from tvm import te
+import topi.testing
+from tvm import relay
+from tvm.relay import transform
+from tvm.relay.testing import ctx_list, run_infer_type
+import topi
+import topi.testing
+import random
Review comment:
You don't use some of these imports?
##########
File path: python/tvm/relay/op/dyn/transform.py
##########
@@ -0,0 +1,93 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements. See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership. The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied. See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+# pylint: disable=import-outside-toplevel
+"""Dynamic Transform operators."""
+
+from . import _make
+
+
+def reshape(data, newshape):
+ """Reshape the input array based on the values of the newshape tensor.
+
+ To give user more convenience in without doing manual shape inference,
+ some dimensions of the shape can take special values from the set {0, -1,
-3}.
+ The significance of each is explained below:
+
+ ``0`` copy this dimension from the input to the output shape.
+
+ .. code-block:: python
+
+ data.shape = (2,3,4), newshape = (4,0,2), result.shape = (4,3,2)
+ data.shape = (2,3,4), newshape = (2,0,0), result.shape = (2,3,4)
+
+ ``-1`` infers the dimension of the output shape by using the remainder of
+ the input dimensions keeping the size of the new array same as that of the
input array.
+ At most one dimension of shape can be -1.
+
+ .. code-block:: python
+
+ data.shape = (2,3,4), newshape = (6,1,-1), result.shape = (6,1,4)
+ data.shape = (2,3,4), newshape = (3,-1,8), result.shape = (3,1,8)
+ data.shape = (2,3,4), newshape = (-1,), result.shape = (24,)
+
+ ``-3`` use the product of two consecutive dimensions of the input shape
+ as the output dimension.
+
+ .. code-block:: python
+
+ data.shape = (2,3,4), newshape = (-3,4), result.shape = (6,4)
+ data.shape = (2,3,4,5), newshape = (-3,-3), result.shape = (6,20)
+ data.shape = (2,3,4), newshape = (0,-3), result.shape = (2,12)
+
+ Special values -2 and -4 from the standard reshape op would introduce
dynamic rank
+ in this op. Thus, they are not permitted.
+
+ Parameters
+ ----------
+ data : relay.Expr
+ The input data to the operator.
+
+ newshape : relay.Expr
+ The new shape. Should be compatible with the original shape.
+
+ Returns
+ -------
+ result : relay.Expr
+ The reshaped result.
+ """
+ return _make.reshape(data, newshape)
+
+def broadcast_to(data, shape):
+
+ """Return a scalar value array with the same type, broadcast to
+ the provided shape.
+
+ Parameters
+ ----------
+ data : relay.Expr
+ The input tensor.
+
+ shape : a relay.Expr, cannot be a tuple of consts
+ Provide the shape to broadcast to.
+
+ Returns
+ -------
+ result : relay.Expr
+ The resulting tensor.
+ """
+ return _make.broadcast_to(data, shape)
Review comment:
Remove this file, since you're providing access to the op via the
standard interface in python/tvm/relay/op/transform.py
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