Tensorflow to IREE test case for tf.Fill, which is failing because broadcast_in_dims can't infer its output shape based on its inputs with the new tf2xla path.  For now, only run the test on the 'tf' backend

PiperOrigin-RevId: 300585192

integrations/tensorflow/e2e/BUILD

diff --git a/integrations/tensorflow/e2e/BUILD b/integrations/tensorflow/e2e/BUILD
index f4ecdf3..b1fb681 100644
--- a/integrations/tensorflow/e2e/BUILD
+++ b/integrations/tensorflow/e2e/BUILD
@@ -37,6 +37,7 @@
     )
     for name in [
         "batch_norm_test",
+        "fill_test",
         "control_flow_test",
         "dynamic_mlp_test",
         "exported_names_test",

integrations/tensorflow/e2e/fill_test.py

diff --git a/integrations/tensorflow/e2e/fill_test.py b/integrations/tensorflow/e2e/fill_test.py
new file mode 100644
index 0000000..29e3ab7
--- /dev/null
+++ b/integrations/tensorflow/e2e/fill_test.py
@@ -0,0 +1,48 @@
+# Copyright 2020 Google LLC
+#
+# Licensed 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
+#
+#      https://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.
+
+import numpy as np
+from pyiree.tf.support import tf_test_utils
+import tensorflow.compat.v2 as tf
+
+
+class FillModule(tf.Module):
+
+  def __init__(self):
+    pass
+
+  @tf.function(input_signature=[
+      tf.TensorSpec([2], tf.int32),
+      tf.TensorSpec([], tf.float32)
+  ])
+  def fill(self, dims, value):
+    return tf.fill(dims, value)
+
+
+# TODO(jennik): Get this test working on IREE.
+@tf_test_utils.compile_modules(backends=["tf"], fill=FillModule)
+class FillTest(tf_test_utils.SavedModelTestCase):
+
+  def test_fill(self):
+    dims = np.array([2, 3], dtype=np.int32)
+    value = np.array(9., dtype=np.float32)
+
+    result = self.modules.fill.all.fill(dims, value)
+    result.assert_all_close()
+
+
+if __name__ == "__main__":
+  if hasattr(tf, "enable_v2_behavior"):
+    tf.enable_v2_behavior()
+  tf.test.main()