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Diffstat (limited to 'tensorflow/core/grappler/costs/graph_properties_test.cc')
-rw-r--r--tensorflow/core/grappler/costs/graph_properties_test.cc286
1 files changed, 283 insertions, 3 deletions
diff --git a/tensorflow/core/grappler/costs/graph_properties_test.cc b/tensorflow/core/grappler/costs/graph_properties_test.cc
index aa787ae620..5acfb56b05 100644
--- a/tensorflow/core/grappler/costs/graph_properties_test.cc
+++ b/tensorflow/core/grappler/costs/graph_properties_test.cc
@@ -783,7 +783,7 @@ TEST_F(GraphPropertiesTest, InferRestoreOpShape_WithTwoNodesShareSameOutput) {
EXPECT_EQ("float: [128,256]", PropToString(prop));
}
-TEST_F(GraphPropertiesTest, FunctionStaticShapeInference) {
+TEST_F(GraphPropertiesTest, SimpleFunctionStaticShapeInference) {
// Test graph produced in python using:
/*
@function.Defun(*[tf.float32] * 2, noinline=True)
@@ -796,7 +796,6 @@ TEST_F(GraphPropertiesTest, FunctionStaticShapeInference) {
z = MyAdd(x, y)
z = MyAdd(x, z)
*/
- // Check that the shape inference code infers what it can.
GrapplerItem item;
string filename = io::JoinPath(testing::TensorFlowSrcRoot(), kTestDataPath,
"simple_function.pbtxt");
@@ -806,15 +805,296 @@ TEST_F(GraphPropertiesTest, FunctionStaticShapeInference) {
const auto out_props = properties.GetOutputProperties("MyAdd_55e046a8");
const OpInfo::TensorProperties& out_prop = out_props[0];
EXPECT_EQ(DT_FLOAT, out_prop.dtype());
- EXPECT_TRUE(out_prop.shape().unknown_rank());
+ EXPECT_FALSE(out_prop.shape().unknown_rank());
+ EXPECT_EQ(2, out_prop.shape().dim_size());
+ EXPECT_EQ(1, out_prop.shape().dim(0).size());
+ EXPECT_EQ(2, out_prop.shape().dim(1).size());
const auto in_props = properties.GetInputProperties("MyAdd_55e046a8");
+ EXPECT_EQ(2, in_props.size());
+
+ const OpInfo::TensorProperties& in_prop = in_props[0];
+ EXPECT_EQ(DT_FLOAT, in_prop.dtype());
+ EXPECT_FALSE(in_prop.shape().unknown_rank());
+ EXPECT_EQ(2, in_prop.shape().dim_size());
+ EXPECT_EQ(1, in_prop.shape().dim(0).size());
+ EXPECT_EQ(2, in_prop.shape().dim(1).size());
+
+ const OpInfo::TensorProperties& in_prop1 = in_props[1];
+ EXPECT_EQ(DT_FLOAT, in_prop1.dtype());
+ EXPECT_FALSE(in_prop1.shape().unknown_rank());
+ EXPECT_EQ(2, in_prop1.shape().dim_size());
+ EXPECT_EQ(1, in_prop1.shape().dim(0).size());
+ EXPECT_EQ(2, in_prop1.shape().dim(1).size());
+}
+
+TEST_F(GraphPropertiesTest, LargeFunctionStaticShapeInference) {
+ GrapplerItem item;
+ string filename = io::JoinPath(testing::TensorFlowSrcRoot(), kTestDataPath,
+ "large_function_graph.pbtxt");
+ TF_CHECK_OK(ReadGraphDefFromFile(filename, &item.graph));
+ GraphProperties properties(item);
+ TF_CHECK_OK(properties.InferStatically(false));
+
+ const auto out_props = properties.GetOutputProperties("y0");
+ EXPECT_EQ(2, out_props.size());
+
+ const OpInfo::TensorProperties& out_prop0 = out_props[0];
+ EXPECT_EQ(DT_FLOAT, out_prop0.dtype());
+ EXPECT_EQ(4, out_prop0.shape().dim_size());
+ EXPECT_EQ(128, out_prop0.shape().dim(0).size());
+ EXPECT_EQ(112, out_prop0.shape().dim(1).size());
+ EXPECT_EQ(112, out_prop0.shape().dim(2).size());
+ EXPECT_EQ(64, out_prop0.shape().dim(3).size());
+
+ const OpInfo::TensorProperties& out_prop1 = out_props[1];
+ EXPECT_EQ(DT_FLOAT, out_prop1.dtype());
+ EXPECT_EQ(128, out_prop1.shape().dim(0).size());
+ EXPECT_EQ(112, out_prop1.shape().dim(1).size());
+ EXPECT_EQ(112, out_prop1.shape().dim(2).size());
+ EXPECT_EQ(24, out_prop1.shape().dim(3).size());
+
+ const auto in_props = properties.GetInputProperties("y0");
+ EXPECT_EQ(4, in_props.size());
+
+ const OpInfo::TensorProperties& in_prop0 = in_props[0];
+ EXPECT_EQ(DT_FLOAT, in_prop0.dtype());
+ EXPECT_EQ(1, in_prop0.shape().dim_size());
+ EXPECT_EQ(64, in_prop0.shape().dim(0).size());
+
+ const OpInfo::TensorProperties& in_prop1 = in_props[1];
+ EXPECT_EQ(DT_FLOAT, in_prop1.dtype());
+ EXPECT_EQ(4, in_prop1.shape().dim_size());
+ EXPECT_EQ(1, in_prop1.shape().dim(0).size());
+ EXPECT_EQ(1, in_prop1.shape().dim(1).size());
+ EXPECT_EQ(24, in_prop1.shape().dim(2).size());
+ EXPECT_EQ(64, in_prop1.shape().dim(3).size());
+
+ const OpInfo::TensorProperties& in_prop2 = in_props[2];
+ EXPECT_EQ(DT_FLOAT, in_prop2.dtype());
+ EXPECT_EQ(4, in_prop2.shape().dim_size());
+ EXPECT_EQ(128, in_prop2.shape().dim(0).size());
+ EXPECT_EQ(224, in_prop2.shape().dim(1).size());
+ EXPECT_EQ(224, in_prop2.shape().dim(2).size());
+ EXPECT_EQ(3, in_prop2.shape().dim(3).size());
+
+ const OpInfo::TensorProperties& in_prop3 = in_props[3];
+ EXPECT_EQ(DT_FLOAT, in_prop3.dtype());
+ EXPECT_EQ(4, in_prop3.shape().dim_size());
+ EXPECT_EQ(7, in_prop3.shape().dim(0).size());
+ EXPECT_EQ(7, in_prop3.shape().dim(1).size());
+ EXPECT_EQ(3, in_prop3.shape().dim(2).size());
+ EXPECT_EQ(8, in_prop3.shape().dim(3).size());
+}
+
+TEST_F(GraphPropertiesTest, LargeFunctionWithMultipleOutputs) {
+ // Test graph produced in python using:
+ /*
+ @function.Defun(noinline=True)
+ def MyFunc():
+ @function.Defun(*[tf.float32] * 2)
+ def Cond(n, unused_x):
+ return n > 0
+
+ @function.Defun(*[tf.float32] * 2)
+ def Body(n, x):
+ return n - 1, x + n
+
+ i = tf.constant(10)
+ return functional_ops.While([i, 0.], Cond, Body)
+
+ with tf.Graph().as_default():
+ z = MyFunc()
+ */
+ GrapplerItem item;
+ string filename = io::JoinPath(testing::TensorFlowSrcRoot(), kTestDataPath,
+ "function_functional_while.pbtxt");
+ TF_CHECK_OK(ReadGraphDefFromFile(filename, &item.graph));
+ GraphProperties properties(item);
+ TF_CHECK_OK(properties.InferStatically(false));
+
+ const auto out_props = properties.GetOutputProperties("MyFunc_AenMyWWx1Us");
+ EXPECT_EQ(2, out_props.size());
+
+ const OpInfo::TensorProperties& out_prop0 = out_props[0];
+ EXPECT_EQ(DT_INT32, out_prop0.dtype());
+ EXPECT_FALSE(out_prop0.shape().unknown_rank());
+
+ const OpInfo::TensorProperties& out_prop1 = out_props[1];
+ EXPECT_EQ(DT_FLOAT, out_prop1.dtype());
+ EXPECT_FALSE(out_prop1.shape().unknown_rank());
+}
+
+TEST_F(GraphPropertiesTest, FunctionWithErrorStaticShapeInference) {
+ GrapplerItem item;
+ string filename = io::JoinPath(testing::TensorFlowSrcRoot(), kTestDataPath,
+ "function_error.pbtxt");
+ TF_CHECK_OK(ReadGraphDefFromFile(filename, &item.graph));
+ GraphProperties properties(item);
+ TF_CHECK_OK(properties.InferStatically(false));
+
+ const auto out_props = properties.GetOutputProperties("MyAdd_yabA4wXEdM4");
+ EXPECT_EQ(1, out_props.size());
+
+ const OpInfo::TensorProperties& out_prop = out_props[0];
+ EXPECT_EQ(DT_FLOAT, out_prop.dtype());
+ EXPECT_TRUE(out_prop.shape().unknown_rank());
+
+ const auto in_props = properties.GetInputProperties("MyAdd_yabA4wXEdM4");
+ EXPECT_EQ(2, in_props.size());
+
+ const OpInfo::TensorProperties& in_prop = in_props[0];
+ EXPECT_EQ(DT_FLOAT, in_prop.dtype());
+ EXPECT_FALSE(in_prop.shape().unknown_rank());
+ EXPECT_EQ(2, in_prop.shape().dim_size());
+ EXPECT_EQ(1, in_prop.shape().dim(0).size());
+ EXPECT_EQ(2, in_prop.shape().dim(1).size());
+
+ const OpInfo::TensorProperties& in_prop1 = in_props[1];
+ EXPECT_EQ(DT_FLOAT, in_prop1.dtype());
+ EXPECT_FALSE(in_prop1.shape().unknown_rank());
+ EXPECT_EQ(2, in_prop1.shape().dim_size());
+ EXPECT_EQ(1, in_prop1.shape().dim(0).size());
+ EXPECT_EQ(2, in_prop1.shape().dim(1).size());
+}
+
+TEST_F(GraphPropertiesTest, FunctionSwitchStaticShapeInference) {
+ // Test graph produced in python using:
+ /*
+ @function.Defun(*[tf.float32] * 2, noinline=True)
+ def MyAdd(x, y):
+ return tf.add(x, y)
+
+ with tf.Graph().as_default():
+ x = lambda: tf.constant(2.0, shape=[1, 2], dtype=tf.float32)
+ y = lambda: tf.constant(2.0, shape=[1, 2], dtype=tf.float32)
+ z = tf.constant(2.0, shape=[1, 2], dtype=tf.float32)
+ z2 = MyAdd(tf.case([(tf.less(0, 1), x)], default=y), z)
+ */
+ GrapplerItem item;
+ string filename = io::JoinPath(testing::TensorFlowSrcRoot(), kTestDataPath,
+ "function_switch.pbtxt");
+ TF_CHECK_OK(ReadGraphDefFromFile(filename, &item.graph));
+ GraphProperties properties(item);
+ TF_CHECK_OK(properties.InferStatically(false));
+ const auto out_props = properties.GetOutputProperties("MyAdd_MPaeanipb7o");
+ const OpInfo::TensorProperties& out_prop = out_props[0];
+ EXPECT_EQ(DT_FLOAT, out_prop.dtype());
+ EXPECT_FALSE(out_prop.shape().unknown_rank());
+ EXPECT_EQ(2, out_prop.shape().dim_size());
+ EXPECT_EQ(1, out_prop.shape().dim(0).size());
+ EXPECT_EQ(2, out_prop.shape().dim(1).size());
+
+ const auto in_props = properties.GetInputProperties("MyAdd_MPaeanipb7o");
+ EXPECT_EQ(2, in_props.size());
+
+ const OpInfo::TensorProperties& in_prop = in_props[0];
+ EXPECT_EQ(DT_FLOAT, in_prop.dtype());
+ EXPECT_FALSE(in_prop.shape().unknown_rank());
+ EXPECT_EQ(2, in_prop.shape().dim_size());
+ EXPECT_EQ(1, in_prop.shape().dim(0).size());
+ EXPECT_EQ(2, in_prop.shape().dim(1).size());
+
+ const OpInfo::TensorProperties& in_prop1 = in_props[1];
+ EXPECT_EQ(DT_FLOAT, in_prop1.dtype());
+ EXPECT_FALSE(in_prop1.shape().unknown_rank());
+ EXPECT_EQ(2, in_prop1.shape().dim_size());
+ EXPECT_EQ(1, in_prop1.shape().dim(0).size());
+ EXPECT_EQ(2, in_prop1.shape().dim(1).size());
+}
+
+TEST_F(GraphPropertiesTest, FunctionSwitch2StaticShapeInference) {
+ // Test graph produced in python using:
+ /*
+ @function.Defun(*[tf.float32] * 2, noinline=True)
+ def MyAdd(x, y):
+ return tf.add(x, y)
+
+ with tf.Graph().as_default():
+ x = lambda: tf.constant(2.0, shape=[1, 2], dtype=tf.float32)
+ y = lambda: tf.constant(2.0, shape=[1, 2], dtype=tf.float32)
+ z = tf.constant(2.0, shape=[1, 2], dtype=tf.float32)
+ z2 = MyAdd(tf.case([(tf.less(1, 0), x)], default=y), z)
+ */
+ GrapplerItem item;
+ string filename = io::JoinPath(testing::TensorFlowSrcRoot(), kTestDataPath,
+ "function_switch_2.pbtxt");
+ TF_CHECK_OK(ReadGraphDefFromFile(filename, &item.graph));
+ GraphProperties properties(item);
+ TF_CHECK_OK(properties.InferStatically(false));
+ const auto out_props = properties.GetOutputProperties("MyAdd_MPaeanipb7o");
+ const OpInfo::TensorProperties& out_prop = out_props[0];
+ EXPECT_EQ(DT_FLOAT, out_prop.dtype());
+ EXPECT_FALSE(out_prop.shape().unknown_rank());
+ EXPECT_EQ(2, out_prop.shape().dim_size());
+ EXPECT_EQ(1, out_prop.shape().dim(0).size());
+ EXPECT_EQ(2, out_prop.shape().dim(1).size());
+
+ const auto in_props = properties.GetInputProperties("MyAdd_MPaeanipb7o");
+ EXPECT_EQ(2, in_props.size());
+
const OpInfo::TensorProperties& in_prop = in_props[0];
EXPECT_EQ(DT_FLOAT, in_prop.dtype());
EXPECT_FALSE(in_prop.shape().unknown_rank());
EXPECT_EQ(2, in_prop.shape().dim_size());
EXPECT_EQ(1, in_prop.shape().dim(0).size());
EXPECT_EQ(2, in_prop.shape().dim(1).size());
+
+ const OpInfo::TensorProperties& in_prop1 = in_props[1];
+ EXPECT_EQ(DT_FLOAT, in_prop1.dtype());
+ EXPECT_FALSE(in_prop1.shape().unknown_rank());
+ EXPECT_EQ(2, in_prop1.shape().dim_size());
+ EXPECT_EQ(1, in_prop1.shape().dim(0).size());
+ EXPECT_EQ(2, in_prop1.shape().dim(1).size());
+}
+
+TEST_F(GraphPropertiesTest, FunctionSwitchShapesStaticShapeInference) {
+ // Test graph produced in python using:
+ /*
+ @function.Defun(*[tf.float32] * 2, noinline=True)
+ def MyAdd(x, y):
+ a = tf.constant(2.0, shape=[1, 2], dtype=tf.float32)
+ b = tf.constant(2.0, shape=[1, 3], dtype=tf.float32)
+ c = tf.add(x, a)
+ d = tf.add(y, b)
+ return c
+
+ with tf.Graph().as_default():
+ x = lambda: tf.constant(2.0, shape=[1, 2], dtype=tf.float32)
+ y = lambda: tf.constant(2.0, shape=[1, 2], dtype=tf.float32)
+ z = tf.constant(2.0, shape=[1, 3], dtype=tf.float32)
+ z2 = MyAdd(tf.case([(tf.less(1, 0), x)], default=y), z)
+ */
+ GrapplerItem item;
+ string filename = io::JoinPath(testing::TensorFlowSrcRoot(), kTestDataPath,
+ "function_switch_shapes.pbtxt");
+ TF_CHECK_OK(ReadGraphDefFromFile(filename, &item.graph));
+ GraphProperties properties(item);
+ TF_CHECK_OK(properties.InferStatically(false));
+ const auto out_props = properties.GetOutputProperties("MyAdd_lEKAAnIwI5I");
+ const OpInfo::TensorProperties& out_prop = out_props[0];
+ EXPECT_EQ(DT_FLOAT, out_prop.dtype());
+ EXPECT_FALSE(out_prop.shape().unknown_rank());
+ EXPECT_EQ(2, out_prop.shape().dim_size());
+ EXPECT_EQ(1, out_prop.shape().dim(0).size());
+ EXPECT_EQ(2, out_prop.shape().dim(1).size());
+
+ const auto in_props = properties.GetInputProperties("MyAdd_lEKAAnIwI5I");
+ EXPECT_EQ(2, in_props.size());
+
+ const OpInfo::TensorProperties& in_prop = in_props[0];
+ EXPECT_EQ(DT_FLOAT, in_prop.dtype());
+ EXPECT_FALSE(in_prop.shape().unknown_rank());
+ EXPECT_EQ(2, in_prop.shape().dim_size());
+ EXPECT_EQ(1, in_prop.shape().dim(0).size());
+ EXPECT_EQ(2, in_prop.shape().dim(1).size());
+
+ const OpInfo::TensorProperties& in_prop1 = in_props[1];
+ EXPECT_EQ(DT_FLOAT, in_prop1.dtype());
+ EXPECT_FALSE(in_prop1.shape().unknown_rank());
+ EXPECT_EQ(2, in_prop1.shape().dim_size());
+ EXPECT_EQ(1, in_prop1.shape().dim(0).size());
+ EXPECT_EQ(3, in_prop1.shape().dim(1).size());
}
TEST_F(GraphPropertiesTest, SymbolicShapes) {
generated by cgit v1.2.3 (git 2.39.1) at 2024-05-29 09:48:41 +0000