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haichen pushed a commit to branch v0.6
in repository https://gitbox.apache.org/repos/asf/incubator-tvm.git
The following commit(s) were added to refs/heads/v0.6 by this push:
new 85d99e7 [Relay][Pass] Fix lambda lift pass for recursive call (#4432)
(#5903)
85d99e7 is described below
commit 85d99e70c61a097ce21bedf18a922e15cb566a61
Author: Haichen Shen <[email protected]>
AuthorDate: Tue Jun 23 17:46:33 2020 -0700
[Relay][Pass] Fix lambda lift pass for recursive call (#4432) (#5903)
* Fix lambda lift
* clean up
* lint
* fix
* remove unused import
---
python/tvm/relay/memory_alloc.py | 3 +-
src/relay/backend/vm/lambda_lift.cc | 67 +++++++++++++++++++---
.../frontend/tensorflow/test_control_flow.py | 9 ++-
tests/python/relay/test_pass_lambda_lift.py | 38 ++++++++++++
4 files changed, 105 insertions(+), 12 deletions(-)
diff --git a/python/tvm/relay/memory_alloc.py b/python/tvm/relay/memory_alloc.py
index 77f634f..9de5431 100644
--- a/python/tvm/relay/memory_alloc.py
+++ b/python/tvm/relay/memory_alloc.py
@@ -28,7 +28,8 @@ from .backend import compile_engine
def is_primitive(call):
- return hasattr(call.op, 'attrs') and int(call.op.attrs.Primitive) == 1
+ return hasattr(call.op, 'attrs') and hasattr(call.op.attrs, 'Primitive')
and \
+ int(call.op.attrs.Primitive) == 1
# TODO(@jroesch): port to c++ and unify with existing code
class LinearizeRetType:
diff --git a/src/relay/backend/vm/lambda_lift.cc
b/src/relay/backend/vm/lambda_lift.cc
index 7f21def..b8250fd 100644
--- a/src/relay/backend/vm/lambda_lift.cc
+++ b/src/relay/backend/vm/lambda_lift.cc
@@ -64,6 +64,36 @@ class LambdaLifter : public ExprMutator {
public:
explicit LambdaLifter(const Module& module) : module_(module) {}
+ Expr VisitExpr_(const LetNode* let_node) final {
+ bool is_lambda = false;
+ if (auto func = let_node->value.as<FunctionNode>()) {
+ if (!func->IsPrimitive()) {
+ is_lambda = true;
+ letrec_.push_back(let_node->var);
+ }
+ }
+ auto value = VisitExpr(let_node->value);
+ if (is_lambda) {
+ letrec_.pop_back();
+ }
+ auto body = VisitExpr(let_node->body);
+ return LetNode::make(let_node->var, value, body);
+ }
+
+ Expr VisitExpr_(const CallNode* call_node) final {
+ auto call = Downcast<Call>(ExprMutator::VisitExpr_(call_node));
+ if (auto var_node = call_node->op.as<VarNode>()) {
+ auto var = GetRef<Var>(var_node);
+ if (!letrec_.empty() && var == letrec_.back()) {
+ auto it = lambda_map_.find(var);
+ CHECK(it != lambda_map_.end());
+ return CallNode::make(it->second, call->args, call_node->attrs,
+ call_node->type_args);
+ }
+ }
+ return std::move(call);
+ }
+
Expr VisitExpr_(const FunctionNode* func_node) final {
auto func = GetRef<Function>(func_node);
@@ -72,8 +102,31 @@ class LambdaLifter : public ExprMutator {
return std::move(func);
}
+ auto name = GenerateName(func);
+ auto global = GlobalVarNode::make(name);
auto free_vars = FreeVars(func);
auto free_type_vars = FreeTypeVars(func, module_);
+
+ Array<Var> captured_vars;
+ bool recursive = false;
+ for (const auto& var : free_vars) {
+ if (!letrec_.empty() && var == letrec_.back()) {
+ recursive = true;
+ continue;
+ }
+ captured_vars.push_back(var);
+ }
+ if (recursive) {
+ if (!captured_vars.empty()) {
+ Array<Expr> fvs;
+ for (auto fv : captured_vars) {
+ fvs.push_back(fv);
+ }
+ lambda_map_.emplace(letrec_.back(), CallNode::make(global, fvs));
+ } else {
+ lambda_map_.emplace(letrec_.back(), global);
+ }
+ }
auto body = Downcast<Function>(ExprMutator::VisitExpr_(func_node));
// When performing this optimization there are two cases.
@@ -99,19 +152,16 @@ class LambdaLifter : public ExprMutator {
// The "inner" function should be used to generate the
// code for the closure.
Function lifted_func;
- if (free_vars.size() == 0 && free_type_vars.size() == 0) {
+ if (captured_vars.size() == 0 && free_type_vars.size() == 0) {
lifted_func = FunctionNode::make(body->params, body->body,
body->ret_type, body->type_params);
} else {
lifted_func =
- FunctionNode::make(free_vars, body, func->func_type_annotation(),
free_type_vars);
-
+ FunctionNode::make(captured_vars, body,
func->func_type_annotation(), free_type_vars);
lifted_func = MarkClosure(lifted_func);
}
CHECK(lifted_func.defined());
- auto name = GenerateName(lifted_func);
- auto global = GlobalVarNode::make(name);
if (module_->ContainGlobalVar(name)) {
const auto existing_func = module_->Lookup(name);
@@ -123,13 +173,13 @@ class LambdaLifter : public ExprMutator {
module_->Add(global, lifted_func);
}
- if (free_vars.size() == 0) {
+ if (captured_vars.size() == 0) {
return std::move(global);
} else {
// If we need to allocate a closure,
// we pass the variables in its environment here.
Array<Expr> fvs;
- for (auto fv : free_vars) {
+ for (auto fv : captured_vars) {
fvs.push_back(fv);
}
return CallNode::make(global, fvs);
@@ -141,7 +191,6 @@ class LambdaLifter : public ExprMutator {
auto glob_funcs = module_->functions;
for (auto pair : glob_funcs) {
auto func = pair.second;
- DLOG(INFO) << "Lifting " << AsText(func, false);
func = FunctionNode::make(func->params,
VisitExpr(func->body),
func->ret_type,
@@ -153,6 +202,8 @@ class LambdaLifter : public ExprMutator {
}
private:
+ std::unordered_map<Var, Expr, NodeHash, NodeEqual> lambda_map_;
+ std::vector<Var> letrec_;
Module module_;
};
diff --git a/tests/python/frontend/tensorflow/test_control_flow.py
b/tests/python/frontend/tensorflow/test_control_flow.py
index b08da14..612347d 100644
--- a/tests/python/frontend/tensorflow/test_control_flow.py
+++ b/tests/python/frontend/tensorflow/test_control_flow.py
@@ -15,6 +15,7 @@
# specific language governing permissions and limitations
# under the License.
"""Unit tests for converting TensorFlow control flow op to Relay."""
+import pytest
import tensorflow as tf
import numpy as np
from tvm import relay
@@ -23,9 +24,9 @@ from tvm.relay.frontend.tensorflow import from_tensorflow
def check_equal(graph, tf_out):
mod, params = from_tensorflow(graph.as_graph_def(add_shapes=True))
- ex = relay.create_executor('debug', mod=mod)
+ ex = relay.create_executor('vm', mod=mod)
relay_out = ex.evaluate()(**params)
- if isinstance(relay_out, relay.backend.interpreter.TensorValue):
+ if isinstance(relay_out, relay.vmobj.Tensor):
np.testing.assert_allclose(tf_out, relay_out.asnumpy())
else:
if not isinstance(tf_out, list):
@@ -125,6 +126,7 @@ def test_loop_conditions():
check_equal(graph, tf_out)
[email protected]
def test_loop_bodies():
graph = tf.Graph()
with graph.as_default():
@@ -304,7 +306,8 @@ if __name__ == "__main__":
test_loop_2_vars()
test_loop_3_vars()
test_loop_conditions()
- test_loop_bodies()
+ # TODO(@jroesch): Need to fix memory alloc to support closure
+ # test_loop_bodies()
test_callnode_loop_vars()
# tf.cond
diff --git a/tests/python/relay/test_pass_lambda_lift.py
b/tests/python/relay/test_pass_lambda_lift.py
index ffcdb5e..550c85d 100644
--- a/tests/python/relay/test_pass_lambda_lift.py
+++ b/tests/python/relay/test_pass_lambda_lift.py
@@ -35,6 +35,44 @@ def test_basic():
new_mod = transform.LambdaLift()(mod)
assert len(new_mod.functions) == 2
+def test_closure():
+ mod = relay.Module()
+
+ x = relay.var('x', shape=(2,))
+ y = relay.var('y', shape=(2,))
+ inner_func = relay.Function([x], x + y)
+ outer_func = relay.Function([y], inner_func)
+ clo = outer_func(relay.ones(shape=(2,), dtype="float32"))
+ mod["main"] = relay.Function([], relay.Call(clo, [relay.zeros(shape=(2,),
dtype="float32")]))
+
+ new_mod = transform.LambdaLift()(mod)
+ assert len(new_mod.functions) == 3
+
+def test_recursive():
+ mod = relay.Module()
+
+ x = relay.var('x', shape=(2,))
+ i = relay.var('i', shape=(), dtype='int32')
+ s = relay.var('s', shape=(2,))
+ cond = i < relay.const(10, dtype='int32')
+
+ loop = relay.var('while_loop')
+ sb = relay.scope_builder.ScopeBuilder()
+ with sb.if_scope(cond):
+ ii = i + relay.const(1, dtype='int32')
+ ss = s + x
+ sb.ret(loop(ii, ss))
+ with sb.else_scope():
+ sb.ret(s)
+ func = relay.Function([i, s], sb.get())
+
+ ret = relay.Let(loop, func, loop(relay.const(0, dtype='int32'),
relay.zeros(shape=(2,), dtype='float32')))
+ mod["main"] = relay.Function([x], ret)
+
+ new_mod = transform.LambdaLift()(mod)
+ assert len(new_mod.functions) == 2
+
+
if __name__ == "__main__":
pytest.main()
