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new ae0a062 [FIX] Verify that tensor reshape is valid. (#6215)
ae0a062 is described below
commit ae0a0627b644fc07247a82f432e939810c63b382
Author: Tristan Konolige <[email protected]>
AuthorDate: Sat Aug 8 18:26:36 2020 -0700
[FIX] Verify that tensor reshape is valid. (#6215)
---
src/relay/op/tensor/transform.cc | 31 ++++++++++++++++++++++
tests/python/relay/test_op_level3.py | 9 +++++++
.../relay/test_pass_combine_parallel_dense.py | 4 +--
3 files changed, 42 insertions(+), 2 deletions(-)
diff --git a/src/relay/op/tensor/transform.cc b/src/relay/op/tensor/transform.cc
index 9427ded..79a8da4 100644
--- a/src/relay/op/tensor/transform.cc
+++ b/src/relay/op/tensor/transform.cc
@@ -25,6 +25,7 @@
#include <tvm/ir/error.h>
#include <tvm/relay/attrs/transform.h>
+#include <tvm/relay/expr.h>
#include <tvm/relay/op.h>
#include <tvm/runtime/packed_func.h>
#include <tvm/tir/data_layout.h>
@@ -581,6 +582,36 @@ bool ReshapeRel(const Array<Type>& types, int num_inputs,
const Attrs& attrs,
oshape.Set(infer_idx, infer_dim);
}
+ // Verify that the sum of dimensions in the output shape is the sum of
+ // dimensions in the input shape
+ bool found_dynamic = false;
+ int64_t oshape_sum = 1;
+ for (auto& x : oshape) {
+ // Check if we have a dynamic shape. If we do, we can't verify if the
+ // reshape is valid. Dynamic shapes are marker by using Any, but can also
+ // occur from SizeVar's. In the case of SizeVar, the shape expression can
+ // be an AST. We can't easily check if we have an AST because of a ShapeVar
+ // or some other reason, so our check for dynamic shape is just if we can
+ // convert the shape to in integer or not.
+ if (!x->IsInstance<tvm::Integer::ContainerType>()) {
+ found_dynamic = true;
+ break;
+ }
+ oshape_sum *= Downcast<tvm::Integer>(x)->value;
+ }
+ int64_t data_shape_sum = 1;
+ for (auto& x : data_shape) {
+ if (!x->IsInstance<tvm::Integer::ContainerType>()) {
+ found_dynamic = true;
+ break;
+ }
+ data_shape_sum *= Downcast<tvm::Integer>(x)->value;
+ }
+ if (!found_dynamic) {
+ CHECK_EQ(oshape_sum, data_shape_sum)
+ << "Input tensor shape and reshaped shape are not compatible";
+ }
+
if (param->reverse) {
reporter->Assign(types[1],
TensorType(Array<IndexExpr>(oshape.rbegin(),
oshape.rend()), data->dtype));
diff --git a/tests/python/relay/test_op_level3.py
b/tests/python/relay/test_op_level3.py
index 76f10d6..db45fcb 100644
--- a/tests/python/relay/test_op_level3.py
+++ b/tests/python/relay/test_op_level3.py
@@ -21,6 +21,7 @@ import pytest
import tvm
from tvm import te
from tvm import relay
+from tvm.error import TVMError
from tvm.relay import create_executor, transform
from tvm.relay.testing import ctx_list, check_grad, run_infer_type
@@ -282,6 +283,13 @@ def test_reshape():
verify_reshape((2, 3, 4), (2, -4, -1, 3, -2), (2, 1, 3, 4))
+def test_reshape_fail():
+ with pytest.raises(TVMError) as reshape_err:
+ x = relay.var("x", relay.TensorType([2,3], "float32"))
+ z = relay.reshape(x, [7])
+ zz = run_infer_type(z)
+
+
def test_reshape_like_infer_type():
# concrete shape
x = relay.var("x", relay.TensorType((1, 2, 3), "float32"))
@@ -1070,6 +1078,7 @@ if __name__ == "__main__":
test_transpose()
test_reshape_infer_type()
test_reshape()
+ test_reshape_fail()
test_reshape_like_infer_type()
test_reshape_like()
test_take_infer_type()
diff --git a/tests/python/relay/test_pass_combine_parallel_dense.py
b/tests/python/relay/test_pass_combine_parallel_dense.py
index a8d7f11..535f97a 100644
--- a/tests/python/relay/test_pass_combine_parallel_dense.py
+++ b/tests/python/relay/test_pass_combine_parallel_dense.py
@@ -187,7 +187,7 @@ def test_combine_parallel_dense_biasadd_scale_reshape():
tvm.ir.assert_structural_equal(y, y_expected, map_free_vars=True)
check(3, 5, 4, 0.5, 0.25, (1, 1, 15))
- check(100, 200, 300, 0.5, 0.25, (1, 1, 200))
+ check(100, 200, 300, 0.5, 0.25, (1, 1, 20000))
def test_combine_parallel_dense_flat():
@@ -369,7 +369,7 @@ def
test_combine_parallel_dense_flat_biasadd_scale_reshape():
tvm.ir.assert_structural_equal(y, y_expected, map_free_vars=True)
check(3, 5, 4, 0.5, 0.25, (1, 1, 15), (1, 1, 30))
- check(100, 200, 300, 0.5, 0.25, (1, 1, 200), (1, 1, 400))
+ check(100, 200, 300, 0.5, 0.25, (1, 1, 20000), (1, 1, 40000))
if __name__ == "__main__":
