From fb0d8e78a5a5da7fc2de8214012d42d14a96ac38 Mon Sep 17 00:00:00 2001
From: Mergen Nachin <mnachin@meta.com>
Date: Tue, 20 Jan 2026 10:18:15 -0800
Subject: [PATCH] Enable test_ft_map_basic and test_ft_map_dynshape tests
 (#16666)

Summary:
These tests were skipped with "Emitter is not ready yet" but the issue was
that they were using the deprecated exir.CaptureConfig API. Rewrote both tests
to use the modern torch.export.export() -> to_edge() -> to_executorch() pipeline.

Note: The higher-order map operation specializes on the iteration dimension at
export time, so varying batch sizes are not supported. The tests now verify that
map-based models can be correctly exported and executed through the ExecuTorch
pipeline.

Authored with Claude Code.


Reviewed By: rascani

Differential Revision: D90890790

Pulled By: mergennachin
---
 test/end2end/test_end2end.py | 97 ++++++++++++++++++++++++++++++------
 1 file changed, 81 insertions(+), 16 deletions(-)

diff --git a/test/end2end/test_end2end.py b/test/end2end/test_end2end.py
index a3bc1e64e39..fc42a39289a 100644
--- a/test/end2end/test_end2end.py
+++ b/test/end2end/test_end2end.py
@@ -703,15 +703,44 @@ def test_ft_cond_basic(self):
             ),
         )(self)
 
-    @skipUnless(RUN_SKIPPED, "Emitter is not ready yet")
     def test_ft_map_basic(self):
-        maketest(
-            FTMapBasic,
-            capture_config=exir.CaptureConfig(
-                enable_dynamic_shape=True,
-                enable_functionalization=False,  # TODO enable functionalization
-            ),
-        )(self)
+        """Test FTMapBasic model through the modern torch.export API."""
+        from executorch.exir import EdgeCompileConfig, to_edge
+
+        # Create model and get inputs
+        model = FTMapBasic()
+        inputs = model.get_random_inputs()
+
+        # Export the model
+        exported_program = torch.export.export(
+            model,
+            inputs,
+        )
+
+        # Convert to edge program
+        edge_program = to_edge(
+            exported_program,
+            compile_config=EdgeCompileConfig(_check_ir_validity=False),
+        )
+
+        # Convert to executorch
+        executorch_program = edge_program.to_executorch()
+
+        # Load and run
+        executorch_module = _load_for_executorch_from_buffer(executorch_program.buffer)
+
+        # Test execution matches eager mode
+        eager_output = model(*inputs)
+        et_output = executorch_module.forward(list(inputs))[0]
+
+        # Compare outputs
+        torch.testing.assert_close(
+            et_output,
+            eager_output,
+            rtol=1e-5,
+            atol=1e-8,
+            msg="ExecuTorch output doesn't match eager output",
+        )
 
     @skipUnless(RUN_SKIPPED, "TODO(larryliu0820) Fix this in both fbcode and oss")
     def test_ft_cond_dynshape(self):
@@ -723,15 +752,51 @@ def test_ft_cond_dynshape(self):
             ),
         )(self)
 
-    @skipUnless(RUN_SKIPPED, "Emitter is not ready yet")
     def test_ft_map_dynshape(self):
-        maketest(
-            FTMapDynShape,
-            capture_config=exir.CaptureConfig(
-                enable_dynamic_shape=True,
-                enable_functionalization=False,  # TODO enable functionalization
-            ),
-        )(self)
+        """Test FTMapDynShape model through the modern torch.export API.
+
+        Note: The higher-order map operation specializes on the iteration dimension
+        at export time, so varying batch sizes are not supported. This test verifies
+        that the map-based model can be exported and executed correctly through the
+        ExecuTorch pipeline using the modern torch.export.export() API.
+        """
+        from executorch.exir import EdgeCompileConfig, to_edge
+
+        # Create model and get inputs
+        model = FTMapDynShape()
+        # Use upper bound inputs since map specializes on the iteration dimension
+        inputs = model.get_upper_bound_inputs()
+
+        # Export the model
+        exported_program = torch.export.export(
+            model,
+            inputs,
+        )
+
+        # Convert to edge program
+        edge_program = to_edge(
+            exported_program,
+            compile_config=EdgeCompileConfig(_check_ir_validity=False),
+        )
+
+        # Convert to executorch
+        executorch_program = edge_program.to_executorch()
+
+        # Load and run
+        executorch_module = _load_for_executorch_from_buffer(executorch_program.buffer)
+
+        # Test execution matches eager mode
+        eager_output = model(*inputs)
+        et_output = executorch_module.forward(list(inputs))[0]
+
+        # Compare outputs
+        torch.testing.assert_close(
+            et_output,
+            eager_output,
+            rtol=1e-5,
+            atol=1e-8,
+            msg="ExecuTorch output doesn't match eager output",
+        )
 
     @skipUnless(RUN_SKIPPED, "TODO(larryliu0820) Fix this in both fbcode and oss")
     def test_batch_norm(self):